Preços e cobertura consistentes de um livro de opções de fx

Entendendo as Negociações em Blocos.

O que são negócios de bloco?

Negociações em block são transações de futuros, opções ou combinações negociadas privadamente que podem ser executadas separadamente do CLOB (Central Limit Order Book) ou da Pit e posteriormente submetidas ao CME Clearing via CME ClearPort ou CME Direct. As negociações em bloco devem ser submetidas à CME Clearing para fins de relatório de preços dentro de um prazo determinado após a execução.

A regra 526 (“Block Trades”) regula a negociação em bloco nos produtos CME, CBOT, NYMEX e COMEX. Negociações em bloco são permitidas em produtos específicos e estão sujeitas a requisitos mínimos de tamanho de transação que variam de acordo com o produto, o tipo de transação e o tempo de execução. As negociações em bloco devem ser negociadas a preços que sejam “justos e razoáveis” em função do tamanho das transações, dos preços de mercado prevalecentes nos mercados futuros e outros relacionados e de outras circunstâncias relevantes.

Os negócios em bloco oferecem a grandes empresas comerciais e traders institucionais a conveniência de negociarem de forma privada uma transação de futuros ou opções com uma contraparte elegível selecionada. Em particular, as instituições muitas vezes procuram executar grandes transações a um único preço, enquanto desfrutam dos benefícios concedidos pelas garantias financeiras associadas ao sistema de compensação da contraparte centralizada (CCP) da CME.

Uma vez executado e compensado, o contrato de futuros / opções resultante é indistinguível de quaisquer outras transações de futuros / opções registradas nesse produto. Assim, essas transações podem ser subsequentemente liquidadas por uma transação de compensação executada através de meios mais convencionais, como o sistema de comércio eletrônico CME Globex ou em um pit via open-outcry.

O Exchange impõe certas restrições às transações em bloco. Somente “Participantes de Contrato Elegíveis” ou PCEs podem realizar blocos. As ECPs podem geralmente ser consideradas como membros da bolsa e firmas-membro registradas como corretores e corretores, corretores / corretores, entidades governamentais, fundos de pensão, grupos de commodities, corporações, companhias de investimento, seguradoras, instituições depositárias e indivíduos de alta renda. As qualificações são formalmente definidas na Seção 1a (18) da Commodity Exchange Act (CEA).

Block Trades para Produtos Agrícolas.

No passado, o CME Group permitia negociações em bloco para a maioria das classes de ativos. Produtos agrícolas, no entanto, eram uma exceção. Mais recentemente, os clientes solicitaram formas mais eficientes de negociar opções menos líquidas e futuros de mês posterior. Como resultado, o CME Group planeja oferecer operações em bloco para produtos agrícolas a partir de 8 de janeiro de 2018.

De um modo geral, os mercados com alta liquidez têm limites mínimos de bloqueio mais altos e tempos de relatório mais curtos. Por exemplo, os futuros de milho, o mercado de grãos mais líquidos, terão um limite de bloqueio de 300 contratos durante o horário normal de negociação e um limite de bloqueio de 150 contratos durante as horas de negociação na Europa e na Ásia. As negociações de futuros de milho devem ser submetidas à Bolsa dentro de cinco (5) minutos de execução. Em contraste, os futuros de Arroz Rude, um mercado não tão líquido quanto o milho, terão um limite de 10 contratos durante o horário regular de negociação e um limite de bloqueio de 5 contratos durante o horário comercial europeu e asiático. Os negócios de blocos futuros de Arroz Integral devem ser submetidos à Bolsa no prazo de quinze (15) minutos após a execução.

Como Transacionar?

Uma negociação em bloco pode ser negociada a qualquer momento e a qualquer preço justo e razoável acordado pelas duas contrapartes. Dois clientes que transacionam um bloco devem ter a (s) posição (ões) resultante (s) de futuros / opções subseqüentemente submetidos ao CME Clearing via CME ClearPort ou CME Direct.

Mais comumente, no entanto, um cliente estabelece um relacionamento com um corretor que é capaz de fazer um mercado, ou seja, mostra uma oferta e uma oferta, no instrumento específico em questão. Há uma variedade de firmas que podem fazer mercados em blocos, embora as Bolsas de Valores assumam uma postura neutra e não ofereçam recomendações a esse respeito. Após a negociação ser executada, a posição de futuros ou opções deve ser informada à CME Clearing através do CME ClearPort ou CME Direct. O acesso ao CME ClearPort e CME Direct requer registro. Informações adicionais sobre o acesso ao CME ClearPort e CME Direct estão disponíveis aqui: CME Direct / CME ClearPort.

O CME Group implementou um processo de registro para fornecer às empresas informações de contato do criador de mercado com o objetivo de participar de negociações de negociação em bloco.

Quem troca blocos e por quê?

Os negócios em bloco geralmente são executados por grandes firmas comerciais e por comerciantes institucionais com fins específicos em mente.

A negociação em bloco é frequentemente praticada por instituições com grandes lotes de tamanho para transacionar. Freqüentemente, esses comerciantes institucionais podem preferir negociação em bloco sobre a execução em um poço ou através do sistema de negociação eletrônica do CME Globex para garantir que a transação seja executada a um único preço. Em outras palavras, um participante pode estar preocupado com a perspectiva de que uma ordem de grande porte inserida no sistema de negociação eletrônica do CME Globex possa ser executada em incrementos menores a múltiplos preços. Assim, a decisão de negociar bloqueios é freqüentemente motivada por uma avaliação da liquidez do mercado em relação ao tamanho do pedido.

Existem muitas maneiras de medir a liquidez, incluindo a “profundidade do livro” e o tamanho da ordem. A liquidez normalmente diminui e flui em função da volatilidade do mercado. Mas os mercados do CME Group geralmente oferecem uma enorme profundidade. Como resultado, os métodos de execução convencionais são geralmente mais do que suficientes para atender à demanda normal de liquidez. Assim, para a maioria dos produtos elegíveis em bloco, tendemos a achar que o volume e o número de transações executadas através de negociações em bloco tendem a ser pequenas em relação ao volume total e ao número de transações. Além disso, o tamanho médio de uma transação de bloco é bastante alto em relação ao tamanho médio da transação para a maioria dos produtos elegíveis em bloco.

Valor do preço transparente.

Negociações em bloco são permitidas pelas Bolsas do CME Group como uma acomodação para negociadores que acham isso uma maneira conveniente e rápida de conduzir negócios. Eles não pretendem representar a maneira tradicional de negociação. Em vez disso, as Bolsas esperam que a pluralidade de negociações de produtos agrícolas seja conduzida nos espaços de negociação abertos e competitivos da Bolsa - via manifestações abertas ou na CME Globex. A descoberta de preços representa uma função primordial dos mercados futuros. Assim, é importante promover um local de negociação transparente como o principal local de negociação onde os valores podem ser facilmente referenciados. A liquidez sendo um pré-requisito necessário para a descoberta eficiente dos preços de equilíbrio dificilmente desviará qualquer volume significativo de comércio do principal mercado competitivo para produtos agrícolas. Na verdade, apenas uma pequena proporção do volume é transacionada como blocos na maioria das outras classes de ativos. Ainda assim, os bloqueios geralmente representam uma saída útil e conveniente para alguns traders e, portanto, permanecem consistentes com a missão da Exchange de fornecer aos clientes uma fonte eficiente de descoberta de preços, bem como a utilidade de hedge.

Sobre o CME Group.

Como o principal e mais diversificado mercado de derivativos do mundo, o CME Group é onde o mundo vem para gerenciar riscos. Composta por quatro bolsas - CME, CBOT, NYMEX e COMEX -, oferecemos a mais ampla gama de produtos benchmark globais em todas as principais classes de ativos, ajudando as empresas em todos os lugares a mitigar os inúmeros riscos que enfrentam na atual economia global incerta.

Siga-nos para notícias econômicas e financeiras globais.

Centro de Subscrição.

Envie-nos comentários.

Quem nós somos.

O CME Group é o maior e mais diversificado mercado de derivativos do mundo. A empresa é composta por quatro Mercados de Contratos Designados (DCMs). Mais informações sobre as regras e listagens de produtos de cada bolsa podem ser encontradas clicando nos links para CME, CBOT, NYMEX e COMEX.

Atividades offshore e financeira vs cobertura operacional ☆

Uma questão-chave é por que muitas empresas multinacionais abandonam a cobertura de derivativos cambiais (FX) e, em vez disso, usam hedge operacional. Propomos uma explicação baseada na iliquidez e nas vantagens exclusivas das coberturas operacionais. Usamos arquivamentos de 10-K para construir medidas baseadas em texto dinamicamente atualizadas da venda offshore de produção, compra de insumos e propriedade de ativos. Descobrimos que as empresas usam derivativos cambiais quando são líquidas e geralmente disponíveis. Caso contrário, eles geralmente favorecem a compra de insumos dos mesmos países para os quais vendem a produção, um hedge operacional. Experimentos quase naturais baseados em lançamentos de novos produtos derivados sugerem uma provável relação causal.

Classificação JEL.

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Agradecemos ao árbitro Erik Gilje, ao editor Toni Whited, Laurent Fresard, Rachita Gullapalli, Kristine Hankins, Yrjö Koskinen (debatedora do FIRS), John Matsusaka, Gordon Phillips, Martin Schmalz, James Weston (debatedor da WFA) e Vijay Yerramilli (debatedora da CFEA) ) para excelentes comentários e sugestões. Agradecemos também aos participantes da Conferência CFEA de 2014 da Georgia State University, da Conferência FIRS de 2015, da Conferência WFA de 2015 e dos participantes do seminário do Claremont Mckenna College, do Instituto de Tecnologia da Geórgia, da Universidade de Santa Clara, da Comissão de Valores Mobiliários e da Universidade de California Riverside, Universidade do Colorado Boulder, Universidade de Houston, Universidade de Illinois, Chicago, Universidade de Massachusetts, Boston, Universidade de Nevada, Las Vegas, Universidade do Sul da Califórnia e Washington State University. Agradecemos a Yue Wu pela excelente assistência de pesquisa e Christopher Ball especialmente pelo uso do software metaHeuristica. Quaisquer erros restantes são exclusivamente nossos.

A escolha das técnicas de cobertura e as características das empresas industriais do Reino Unido.

Este estudo apresenta os resultados empíricos para a relação entre o uso de técnicas de hedge e as características de empresas multinacionais do Reino Unido (MNEs). Todas as empresas da amostra cobrem a exposição cambial (FX). Os resultados indicam que as empresas do Reino Unido se concentram em um conjunto muito restrito de técnicas de hedge. Eles fazem um uso muito maior de derivativos do que as técnicas internas de hedge. O grau de utilização de técnicas internas e externas depende do tipo de exposição que é protegida. Além disso, as características das empresas parecem explicar a escolha da técnica de hedge, mas o uso de certas técnicas de hedge parece estar associado a aumentos na variabilidade de algumas medidas contábeis. Este impacto adverso do hedging não foi enfatizado na literatura financeira. Os resultados implicam que as empresas precisam garantir que as técnicas apropriadas sejam usadas para proteger as exposições.

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riskderivatives.

17 de abril de 2016.

Abordagem Padronizada do FRTB e Modelada Internamente.

Introdução.

O Comitê da Basileia publicou em maio de 2012 um documento de consulta que propõe um limite mais robusto entre os livros Trading e Banking para evitar a arbitragem regulatória, capturar a iliquidez do mercado de forma mais eficaz, fortalecer os requisitos de mensuração e avaliação de risco sob abordagens baseadas em modelos padronizados e internos e fortalecer o relação entre as duas abordagens.

Fundo.

A crise de 2008 destacou a grave subcapitalização das exposições da carteira de negociação. Essa característica foi, em grande medida, o resultado das metodologias de mensuração e avaliação de risco utilizadas pelos bancos.

A crise expôs uma série de fraquezas fundamentais do desenho geral do regime de carteiras que contribuíram ou amplificaram o impacto da crise.

O Basel 2.5 introduziu algumas mudanças, mas elas foram reconhecidas como insuficientes.

Cronologia das Mudanças de RM.

Modelo Interno Abordagem Baseada em MR.

CRM (Comprehensive Risk Measure)

Risco não no VaR e no RNiV estressado.

Coerência e coerência: não há uma visão consistente da categorização e capitalização do risco.

Risco da cauda: Não consistentemente ou totalmente capturado.

Risco de Liquidez do Mercado: Não consistentemente ou totalmente capturado.

Variabilidade específica do banco: multiplicador de supervisão, comprimento histórico da janela, esquema de ponderação, dimensionamento, agregação.

Pró-ciclicidade: medidas de risco e aumento de capital à medida que as condições econômicas pioram.

Overalapping de modelos: dupla contagem VaR, SVaR, IRC.

Cobertura e diversificação: os benefícios da utilização destas técnicas são exagerados.

Uma nova distinção mais clara.

O BIS propôs reconsiderar o que constitui um ativo na TB e no BB.

A distinção inicial foi ditada pela intenção do banco de manter um ativo para fins de negociação ou para proteger uma posição detida para fins de negociação. Antes do FRTB, a fronteira entre a TB e o BB estava sujeita a arbitragem regulatória dando origem a carteiras de negociação com pouco capital.

O BIS propôs duas definições alternativas:

Um limite baseado em evidência de negociação Um limite baseado em avaliação.

O limite baseado em evidências de negociação.

Ao contrário do limite existente, o limite baseado em evidência de negociação é projetado para ser objetivo. A evidência comercial é baseada na intenção de negociação, portanto, a inclusão de negociações na TB requer prova de tal intenção.

Essa prova pode ser o produto de estatísticas sobre o giro da posição, frequência de rebalanceamento de suas coberturas e sua idade média. Os bancos seriam obrigados a apresentar provas da viabilidade de negociar um instrumento. Isso agora inclui provas de acesso a mercados relevantes para negociação e hedge, possuir dados históricos e dados de mercado para o subjacente e um plano plausível para justificar por que e como o banco negociaria em um mercado em que tinha experiência limitada.

Os bancos também seriam obrigados a demonstrar a gestão ativa de posições de negociação e, para isso, talvez precisassem estabelecer e aplicar limites tanto em um instrumento quanto em uma base de posição de risco. Outro novo requisito seria que os bancos monitorassem ativamente os níveis de liquidez de mercado (incluindo registros de dados de mercado) e especificassem um período de detenção máximo esperado para um instrumento com penalidades se esse período fosse excedido.

O limite baseado na avaliação.

Essa abordagem dispensaria totalmente a intenção de negociação e, em vez disso, aplicaria exigências de capital de risco de mercado a todos os instrumentos financeiros de valor justo para os quais as mudanças de avaliação poderiam levar a uma redução nos recursos de capital de um banco.

Isso aumentaria significativamente o tamanho da TB dos bancos e aumentaria o número de bancos sujeitos a exigências de capital de risco de mercado. Em termos contábeis, a nova TB incluiria instrumentos financeiros, instrumentos financeiros disponíveis para venda e outros instrumentos financeiros para os quais o valor justo é aplicado como opção ou como um requerimento.

Mudanças Comuns.

Independentemente de qual dessas fronteiras é finalmente adotada, a proposta inclui algumas mudanças comuns:

Os bancos estarão sujeitos a exigências de divulgação pública mais rigorosas em relação às suas posições de negociação. Os bancos não poderão alterar o destino do livro. Essa limitação é imposta pelo limite baseado em evidência de negociação ou pelos requisitos contábeis do valor justo na abordagem de avaliação. Todos os instrumentos financeiros de valor justo na TB ou no BB estarão sujeitos a exigências de avaliação prudente mais rigorosas.

Nova abordagem para avaliação de riscos.

Além dos novos limites, o comitê propôs uma série de mudanças destinadas a tornar o cálculo do risco de mercado mais sensível ao risco.

O BIS propôs substituir a métrica de risco VaR por um novo método ES (Expected Shortfall). ES considera uma gama mais ampla de resultados potenciais do que o VaR e mede o risco considerando tanto o tamanho quanto a probabilidade de perdas acima de um certo nível de confiança. Espera-se que o ES capte o risco de cauda (o risco de imprevistos não incluídos no modelo de VaR do banco) O BIS propõe-se a recalibrar a estrutura de TB de modo que os encargos de capital de risco de mercado sejam suficientes apenas em condições benignas de mercado, mas também períodos de estresse.

Freqüência de cálculo.

O capital de risco de mercado deverá ser calculado diariamente no nível da mesa de negociação. A aprovação para usar modelos internos deve ser avaliada diariamente no mesmo nível usando dois novos testes:

Como já mencionado, o ES substituirá o VaR enquanto o Incremental Default Risk substituirá o Incremental Risk Charge. Os dados das séries temporais também estarão sujeitos a avaliação de qualidade.

Principais ingredientes FRTB.

Requisitos de dados mais rigorosos.

TB vs limite BB.

Foco de nível de mesa de negociação granular.

Modelo Interno (ES)

Tratamento conservador da cobertura e diversificação.

Cenários de Estresse Não Modeláveis.

Captura de risco de cauda.

Requisitos de divulgação granular aumentados.

Elegibilidade de dados de mercado.

Risco Incremental Padrão.

Tratamento consistente do risco de crédito.

Abordagem Baseada em Modelo Interno: Elegibilidade.

Método do modelo interno: elegibilidade de dados de mercado.

Elegibilidade para fator de risco modulável.

Preço Real: é o preço pelo qual a instituição efetuou transações com base no critério de mercado, ou entre dois ou outros terceiros independentes. Este preço é retirado de uma cotação firme.

Frequência aceitável: com um mínimo de 24 observações por ano e um período máximo de um mês entre duas transações consecutivas.

Outros dados de mercado podem não satisfazer a elegibilidade. Estes incluem IPOs, títulos emitidos pela primeira vez para os quais não existem dados históricos para essa emissão específica. A análise por pares ou a média do setor pode ser um bom começo como proxy. Da mesma forma, um modelo de fator de risco pode ser calibrado, enriquecendo-o com dados por um período suficientemente longo até que o modelo substitua o conjunto de dados por dados reais no futuro.

As alternativas propostas pela indústria incluem proxies razoáveis ​​com bons dados, modelos estatísticos que podem alavancar o relacionamento com outras variáveis ​​com bons dados históricos. As proxies para volatilidades são razoáveis ​​se forem baseadas em raciocínio econômico / financeiro ou parametrização de fatores de risco com características similares e suportarem evidências empíricas. Os acréscimos de estilo RNIV (Risco não no Var) capturam os riscos ausentes.

Expectativa de escassez (modelo interno)

Em suma.

FRTB diz respeito a novas regras para determinar o alcance dos instrumentos elegíveis para inclusão na TB.

Existem agora requisitos mais rigorosos que regem a transferência de risco interno entre o BB e a TB.

A introdução dos horizontes de liquidez no cálculo do ES é refletir o período de tempo necessário para vender ou cobrir uma determinada posição durante um período de estresse.

A substituição do VaR e do VaR estressado por uma única medida de risco de queda esperada visa capitalizar o evento de perda na cauda da distribuição P & amp; L.

Voltar requisitos de teste de modelos internos no nível da mesa de negociações determinará a validação dos modelos em uso. Se o backtesting falhar, a mesa de operações terá que aplicar a abordagem padronizada.

A substituição do IRC por um Modelo de Risco Padrão, visa capturar o risco de inadimplência na estrutura de risco de mercado.

A abordagem padronizada revisada para risco de mercado é agora baseada em sensibilidade de preço, portanto, mais sensível ao risco. A intenção do BIS de estabelecer a nova abordagem de DST foi reduzir a lacuna com os resultados dos Modelos Internos.

Divulgação pública sobre os encargos de capital de risco de mercado sob STD e modelos internos é agora reforçada.

Abordagem Padronizada.

Sob a estrutura existente, há diferenças materiais entre as metodologias baseadas em modelos padronizados e internos. As regras padrão atuais baseiam-se em uma abordagem simples ponderada por risco e nocional ou baseada em mercado.

Os bancos no passado foram criticados por usar excessivamente os modelos internos para obter menores exigências de capital. A metodologia padrão atual não permitia ampla diversificação e benefícios de hedge. A nova estrutura forneceria um método para calcular as exigências de capital para bancos sem um modelo de mensuração sofisticado e garantiria uma calculadora alternativa mais apropriada caso a Mesa de Operações falhe no teste de elegibilidade do modelo interno.

Alinhamento ao método de modelos internos.

As novas Regras Padrão estão mais alinhadas ao Método de Modelos Internos em termos de requisitos de capital. Os instrumentos agora são preenchidos de acordo com suas características de risco. Os Pesos de Risco de cada balde são prescritos e eles foram calibrados com os modelos internos de Falhas Esperadas. Atualmente, há mais reconhecimento dos benefícios de hedging e diversificação por meio do uso de uma fórmula de agregação usando os parâmetros de correlação prescritos pela regulamentação.

Fluxo Padronizado do Processo de Cálculo de Capital.

O requisito de capital de DST é a soma de:

Encargo de Capital de Risco Delta Melhorado + Encargo de Capital de Risco Padrão + Adição de Risco Residual.

Os bancos são obrigados a calcular o & # 8216; delta otimizado mais o risco & # 8217; e & # 8216; Risco padrão & # 8217; encargo de capital nos seguintes níveis de carteira:

Mesas de negociação completas Abordagem de Modelo Não Interno (Mesas que falharam nos testes de elegibilidade do modelo) Cada mesa como uma carteira por conta própria: sem diversificação ou benefícios de cobertura nas mesas.

Delta, Vega e Curvatura.

O Comitê de Basileia decidiu implementar o “método delta plus aprimorado”, que é baseado em sensibilidade, diferenciando três componentes de risco diferentes: risco delta como base para capturar riscos lineares e risco de vega e curvatura como dois componentes adicionais que se aplicam aos produtos com opcionalidade.

O risco da Vega avalia o risco de mudanças de preço com base na expectativa do mercado sobre a volatilidade futura. Em outras palavras, a sensibilidade à volatilidade.

O risco de curvatura captura o risco não linear, que não é contabilizado pelo risco delta.

Definições de classes de risco de STD.

As sensibilidades são calculadas para 7 classes de risco na abordagem de DST:

GIRR Equity Credit Spread Securitizações Credit Spread Não Securitizações Credit Spread Securitizações Não Correlação Carteiras de Negociação Commodity FX.

O encargo de capital de DST também é calculado sobre as classes de risco acima, de acordo com as sensibilidades relevantes: Delta, Vega, Curvatura e Risco de Default.

Os encargos de capital lineares e não lineares são calculados separadamente, sem benefício de diversificação reconhecido entre eles.

As opções estão sujeitas aos riscos de Vega e Curvatura.

Mais especificamente para cada classe de risco:

Risco geral de RI.

Definido ao longo de duas dimensões:

1) Uma curva de rendimento livre de risco para cada mercado no qual os instrumentos sensíveis à IR são denominados.

2) Vértices (pontos de maturidade): 0,25, 0,5, 1, 2, 3, 5, 10, 15, 20, 30.

Inclui também os fatores de risco de inflação e base cambial.

(Delta é a taxa de mudança do valor da opção teórica em relação às mudanças no subjacente).

Vega Rf são as volatilidades implícitas de opções que referenciam subjacentes sensíveis GIRR definidos ao longo de duas dimensões. (a sensibilidade à volatilidade)

1) Maturidade se a opção estiver mapeada nos vértices: 0,5, 1, 3, 5, 10 anos.

Definido ao longo de apenas uma dimensão: a curva de rendimento livre de risco construída por moeda.

Risco de Spread de Crédito Não Sec.

Definido ao longo de 2 dimensões.

1) as curvas relevantes de spread de crédito do emissor (Bond e CDS)

2) Vértices: 0,5, 1, 3, 5, 10 anos.

O Vega Rf são volatilidades implícitas de opções que referenciam os nomes dos emissores de crédito como subjacentes (títulos e CDS). Além disso, definido ao longo da maturidade da opção mapeada para os vértices: 0,5, 1, 3, 5, 10 anos.

As curvas relevantes de spread de crédito do emissor (Bond an CDS)

Segmento de risco de spread de crédito

Rf são definidos ao longo de 2 dimensões:

1) as curvas de spread de crédito da tranche relevante.

2) Vértices: 0,5, 1, 3, 5, 10.

Os fatores de risco de Vega são as volatilidades implícitas de opções que referenciam spreads de credores não CTP como subjacentes (bond e CDS) definidos ao longo do vencimento da opção mapeada nos vértices: 0,5, 1, 3, 5, 10.

Curvas de spread de crédito da tranche relevante (Bond e CDS)

Spread de Crédito Sec (Carteira de Negociação de Correlação)

Fatores de risco são definidos em duas dimensões:

1) Curvas de spread de crédito da tranche relevante.

2) Vértices: 0,5, 1, 3, 5, 10.

Vega rf são as volatilidades implícitas de opções que fazem referência a spreads de crédito não CTP como subjacentes.

Curvas de spread de crédito da tranche relevante (títulos e CDS)

Securitisaitons de risco de spread de crédito (carteira de negociação de correlação)

Definido ao longo de duas dimensões:

1) as curvas relevantes de spread de crédito subjacente (obrigações e CDS)

2) Vértices: 0,5, 1, 3, 5, 10.

Vega rf são as volatilidades implícitas das opções que fazem referência aos spreads de crédito da CTP como subjacentes (Bonds e CDS) definidos ao longo da maturidade e a opção mapeada aos vértices: 0,5, 1, 3, 5, 10.

As curvas relevantes de spread de crédito subjacente (bond e CDS)

1) Preços de Equity Spot.

2) taxas de acordo de recompra de ações.

As volatilidades implícitas das opções que referenciam os preços à vista da equidade como subjacentes ao longo do vencimento da dimensão da opção nos 0,5, 1, 3, 5, 10 anos.

Preços de Equity Spot.

Preços à vista de commodities, dependendo do grau de contrato da commodity física e do prazo até o vencimento do instrumento negociado.

As volatilidades implícitas das opções que referenciam os preços à vista de commodities como subjacentes ao longo do vencimento da dimensão opção nos 0,5, 1, 3, 5, 10 anos.

Preços spot de commodities.

Todas as taxas de câmbio entre a moeda na qual um instrumento é denominado e a moeda do relatório.

As volatilidades implícitas das opções que referenciam as taxas de câmbio entre pares de moedas com vencimento da opção definida nos vértices 0,5, 1, 3, 5, 10.

Todas as taxas de câmbio entre a moeda na qual um instrumento é denominado e a moeda do relatório.

Sensibilidades Definição para abordagem de DST.

Cálculo de Carga de Capital Linear sob a abordagem de DST: DELTA.

A Comissão de Capital Linear é calculada para cada classe de risco separadamente. A sensibilidade Delta é 1pb absoluta nos fatores de risco GIRR e CSR, ou 1% de movimento relativo nos fatores de risco EQ, FX e Comm.

As posições em uma classe de risco são colocadas em depósitos definidos por classe de risco. Cada bucket tem um RW predefinido. Por exemplo, os buckets Equity são definidos em três dimensões: região, capitalização de mercado e setor.

Net a sensibilidade Sk através de instrumentos para cada fator de risco k pertencentes ao mesmo balde. As sensibilidades não podem ser feitas através de baldes.

Cálculo da sensibilidade líquida ponderada pelo risco segue: WSk = RWksk.

Em cada um dos grupos, agregue as sensibilidades ponderadas entre os fatores de risco usando o seguinte:

O parâmetro de correlação pkl entre os fatores de risco foi prescrito pelo BIS. Para obter uma taxa de capital delta para uma classe de risco, o capital de nível de bucket Kb é agregado da seguinte forma:

O Comitê de Basileia prescreveu semelhanças para a agregação de intervalos, o parâmetro de correlação Ybc, entre os intervalos para cada classe de risco.

Cálculo de Carga de Capital Linear sob a abordagem de DST: VEGA.

O cálculo do encargo de capital da Vega permanece o mesmo, exceto pelos cálculos de RW, correlações e sensibilidade. O RW usado em Vega é calibrado para cada horizonte de liquidez da classe de risco e não depende da estrutura do grupo como era o encargo de capital da Delta.

Vega é definido ao longo da maturidade da opção em 5 pontos de tenor. Portanto, Vega de uma posição com um determinado vencimento deve ser alocado para um ou dois dos 5 pontos de tenor.

Suponha uma posição de opção de compra de ações com Vega de 100 e prazo de 4,5 anos.

Vértices ou pontos de maturidade são 0,5, 1. 3. 5. 10 anos.

A posição é alocada linearmente entre 3 e 5 anos.

No ano 3, alocar 100 *

A sensibilidade Vega é calculada como um produto da opção Vega como alocado acima e sua volatilidade implícita no prazo de vencimento relevante.

O BIS prescreveu o método para calcular o parâmetro de correlação: um para o GIRR e outro para as outras classes de ativos.

Cálculo de Carga de Capital Não-Linear sob a abordagem de DST: Curvatura.

O cálculo do encargo de capital de curvatura segue os mesmos depósitos e fundamentos de classe de risco de encargo de capital linear, com a única diferença de que essa sensibilidade é calculada aplicando um movimento de estresse ao fator de risco.

da equação acima:

em 1. o fator de risco é chocado de forma equivalente ao RW do balde no qual a posição é colocada. Em 2. tiramos o delta da sensibilidade de curvatura para evitar a contagem dupla.

Os parâmetros de correlação nas fórmulas de agregação de buckets intra e bucket bucket são os mesmos que os usados ​​no cálculo de encargos de capital delta.

Suponha que tenhamos uma opção no estoque da IBM. (Grande capitalização de mercado, Economia avançada, Tecnologia, Balde 8, RW 50%). O preço atual é de USD 151,31.

O preço das ações subiu para USD 227,01 (151,34 1,5) e USD 75,67 (151,34 0,50). A posição é reavaliada ao nível do preço do mercado de ações acima, mantendo outros fatores de risco constantes.

A curvatura é calculada como:

O sistema FO terá a capacidade de fornecer a avaliação para uma posição nos dois cenários e preço atual. A curvatura é então calculada para o encargo de capital.

Taxa de risco padrão.

Antes do FRTB, os bancos capturam o risco de inadimplência e migração usando os modelos para portfólios securitizados e não securitizados.

Nomeadamente: IRC para Carteiras não Securitizadas e Todos os Riscos de Preços (APR) ou Medida de Risco Abrangente (CRM) para Carteiras Securitizadas (carteiras de negociação de correlação).

As abordagens acima são baseadas em modelos, portanto, não existe cálculo de risco de default padrão, exceto para operações de securitização. O risco de inadimplência também não se aplica às carteiras de ações.

A cobrança padrão de risco padrão será calculada para todas as mesas de negociação no escopo.

A exigência de capital para o risco de inadimplência é a soma do risco de inadimplência de:

não titularizações (incluindo capital próprio), titularizações (carteira de negociação sem correlação) e titularizações (carteiras de negociação de correlação).

O DRC captura o risco de Jump-To-Default no horizonte de 1 ano e é calibrado com base no tratamento de risco de crédito da carteira bancária, a fim de reduzir a discrepância potencial nas exigências de capital para exposições semelhantes no Livro Bancário.

Semelhante ao delta aprimorado mais o componente da abordagem de DST, permite algum reconhecimento de hedge em um nível de bucket.

As etapas de cálculo são:

Categorizar posições como longas ou curtas (uma posição longa implica a inadimplência do devedor subjacente resulta em uma perda) As posições recebem uma antiguidade com base na LGD alocada A JTD bruta é calculada por posição. Este valor é uma função da LGD, valor nocional (valor nominal) e P & amp; L acumulado já realizado na posição. Escala e compensação são realizadas no JTD bruto para chegar à JTD líquida. Os ratings de devedores subjacentes são atribuídos em cada JTD líquido. posicione e coloque nos buckets definidos Calcule o rácio do benefício de cobertura para cada bucket Calcule o DRC para cada bucket Calcule o capital total para o DRC pela soma dos encargos de capital ao nível do bucket. Nenhum hedge ou diversificação é reconhecido nos buckets em qualquer escopo determinado.

Adicionar Risco Residual.

O objetivo desse encargo é capturar o risco que não é coberto pelo Risco de risco e de inadimplência do Enhanced Delta Plus.

O escopo deste complemento é qualquer instrumento satisfazendo ambas as condições abaixo:

Está sujeito ao encargo de capital de Vega Sensibilidade e Curvatura na Carteira de Negociação. Seu pagamento não pode ser escrito como uma combinação linear de opções de baunilha.

Um exemplo de instrumentos afetados pela adição de risco residual são as opções dependentes do caminho.

O cálculo Add On é direto:

N = número total de posições em escopo.

x = o multiplicador adicional (1% é o valor prescrito)

Gross nocional é a quantia nocional do instrumento i.

Caso o montante nocional esteja indisponível, a perda potencial máxima deve ser usada.

Caçambas de Classe de Risco de Taxa de Juros Gerais e respectivos Pesos de Risco.

Risco de Spread de Crédito Risco de Crédito Não Securitizado / Securitizado Carteiras Negociadas Baldes de Classe de Risco e respectivos Pesos de Risco.

Risco de Spread de Crédito Securitizado Carteiras Negociadas Não Correlacionadas Caixas de Classe de Risco e respectivos Pesos de Risco.

Baldes de Classe de Risco Patrimonial e respectivos Pesos de Risco.

CAN, EUA, MEX, € zona, não € zona, JAP, AUS, NZL, SIN, HK, SAR.

Caixas de Classe de Risco de Commodities e respectivos Pesos de Risco.

Baldes de Classe de Risco FX e respectivos Pesos de Risco.

A estrutura do bucket é definida por cada par de moedas. (um balde = um par de moedas)

O peso cambial é fixado em 15% e aplicado a todas as sensibilidades ou exposições de risco. However for the following currency pairs, the 15% RW is divided by the SQRT of 2.

USD/EUR, USD/JPY, USD/GBP, USD/AUD, USD/CAD, USD/CHF, USD/MXN, USD/CNY, USD/NZD, USD/RB, USD/HKD, USD/SGD, USD/TRY, USD/KRW, USD/SEK, USD/ZAR, USD/INR, USD/NOK, USD/BRL, EUR/JPY, EUR/GBP, EUR/CHF, JPY/AUD.

April 13, 2016.

Backtesting guidelines for US, UK and Swiss Regulators.

Summary Banks have the obligation to deliver back-testing results of Counterparty Credit Risk (CCR) exposure models to the regulators on a quartely basis. Back Testing Platforms have been designed…

March 29, 2016.

About RiskDerivatives.

This webpage will guide you through the world of Credit Derivatives to gain a better understanding of Credit, Counterparty and Market Risk Management. It will provide you with three different level…

riskderivatives.

The Standardised FRTB (Fundamental Review of Trading Book)

Índice.

Alignment to Internal Model Methods.

Introdução.

The Basel Committee published in May 2012 a consultation paper proposing a more robust boundary between Trading and Banking books to avoid regulatory arbitrage, capture market illiquidity more effectively, strengthen the risk measurement and valuation requirements under both standardised and internal model based approaches along with strengthening the relationship between the two approaches.

Fundo.

The 2008 crisis highlighted the severe undercapitalisation of the trading book exposures. This characteristic was to a large extent the result of the risk measurement and valuation methodologies used by banks.

The crisis exposed a series of fundamental weaknesses of the overall design of the trading book regime which contributed or amplified the impact of the crisis.

Basel 2.5 introduced some changes but they were recognised to be insufficient.

Chronology of the MR Changes.

Internal Model Based approach to MR.

CRM (Comprehensive Risk Measure)

Risk not in VaR and Stressed RNiV.

Shortcomings:

Consistency and Coherence : there is no consistent view of risk categorisation and capitalisation.

Tail Risk: Not consistently or fully captured.

Market Liquidity Risk: Not consistently or fully captured.

Bank-Specific variability: Supervisory multiplier, historical window length, weighting scheme, scaling, aggregation.

Pro-cyclicality: risk measures and capital increase as economic conditions worsen.

Overalapping of models: double counting VaR, SVaR, IRC.

Hedging and diversification : Benefits from using these techniques are overstated.

A clearer distinction.

The BIS proposed to reconsider what constitutes an asset in the TB and BB.

The initial distinction was dictated by the bank’s intent to hold an asset for trading purpose or to hedge a position held for trading purposes. Prior to FRTB, the boundary between TB and BB was subject to regulatory arbitrage giving rise to lightly capital charged trading books.

The BIS proposed two alternative definitions:

A trading evidence based boundary A valuation based boundary.

The trading evidence based boundary.

Unlike the existing boundary the trading evidence based boundary is designed to be objective. The trading evidence is based on the trading intent, hence inclusion of trades in the TB requires proof of such intent.

Such proof may be the product of statistics on the position turnover, rebalancing frequency for their hedges and their average age. Banks would be required to produce evidence of the feasibility of trading an instrument. This now includes proofs of access to relevant markets for trading and hedging, owning historical data and market data for the underlying and a plausible plan to justify why and how the bank would trade on a market in which it had limited experience.

Banks would also be required to demonstrate active management of trading positions ad to do so they may need to set and enforce limits both on an instrument and on a risk position basis. Another new requirement would be for banks to actively monitor market liquidity levels (including market data records) and to specify an expected maximum holding period for an instrument with penalties if that period is exceeded.

The Valuation Based Boundary.

This approach would dispense altogether with trading intent and instead apply market risk capital requirements to all fair valued financial instruments for which valuation changes could lead to a reduction in a bank’s capital resources.

This would significantly increase the size of bank’s TB and increase the number of banks subject to market risk capital requirements. In accounting terms the new TB would include held for financial instruments, available for sale financial instruments and other financial instruments to which fair value is applied either as an option or a requirement.

Common Changes.

Regardless of which of these boundaries is finally adopted, the proposal includes some common changes:

Banks will be subject to more stringent public disclosure requirements regarding their trading positions Banks will be restricted from changing the book destination. This limitation is imposed by the trading evidence based boundary or through the fair value accounting requirements in the valuation approach All fair valued financial instruments either in the TB or BB will be subject to more specific stringent prudent valuation requirements.

New Approach to Risk Assessment.

In addition to the new boundaries the committee has proposed a series of changes designed to make the market risk calculation more risk sensitive.

BIS proposed to replace the VaR risk metric with a new ES method (Expected Shortfall). ES considers a broader range of potential outcomes than VaR and measures risk by considering both size and likelihood of losses above a certain confidence level. ES is expected to capture the tail risk (the risk of unforeseen events not factored into a bank’s VaR model) BIS proposes to recalibrate the TB framework such that market risk capital charges are sufficient not only in benign market conditions but also in periods of stress.

Calculation frequency.

Market Risk capital will be required to be calculated daily at trading desk level. Approval to use internal models is to be assessed daily at same level using two new tests:

The trading desks that fail any of the above tests will need to be capitalised under the Standardised method , also known as Sensitivity Based Approach. Trading desks that pass both tests will be capitalised using the firm’s Internal Models.

As already mentioned, ES will replace the VaR whilst Incremental Default Risk will replace the Incremental Risk Charge. Time series data will also be subject to quality assessment.

Key FRTB elements.

Stricter Data Requirements.

TB vs BB Boundary.

Granular Trading Desk level focus.

Internal Model (ES)

Conservative treatment of hedging and diversification.

Non Modellable Stress Scenarios.

Tail risk capture.

Increased granular disclosure requirements.

Market Data Eligibility.

Incremental Default Risk.

Consistent treatment of credit risk.

Internal Model Based Approach Eligibility.

Banks will be allowed to use one of the two available methodologies to calculate capital under the new rules: Standardised or Internal Model.

Em suma.

FRTB concerns with new rules to determine the scope of the instruments eligible for inclusion in the TB.

There are now more stringent requirements governing internal risk transfer between the BB and the TB.

The introduction of the Liquidity Horizons in the 97.5% ES calculation is to reflect the period of time required to sell or hedge a given position during a period of stress.

The replacement of VaR and Stressed VaR with a single expected shortfall risk measure aims at capitalising for the loss event in the tail of the P&L distribution.

Back testing requirements of internal models at trading desk level will determine the validation of the models in use. Should backtesting fail, the trading desk will have to apply the standardised approach.

The replacement of the IRC with a Default Risk Model, aims at capturing the default risk in the market risk framework.

The revised Standardised Approach for market risk is now based on price sensitivities, therefore more risk sensitive. BIS intention to set up the new STD approach was to reduce the gap with the Internal Models results.

Public disclosure on market risk capital charges under STD and Internal Models is now enhanced.

Standardised Approach.

Under the existing framework, there are material differences between the Standardised and Internal Models based methodologies. The current standard rules are based on a simple Risk Weighted and Notionals or Mark to Market based Approach.

Banks in the past have been criticised for overusing the internal models in order to achieve lower capital requirements. The current Standard methodology did not allow for wide diversification and hedging benefits. The new framework would provide a method for calculating capital requirements for banks without sophisticated measuring model in place and would ensure a more appropriate fall back calculator should the Trading Desk fail the internal model eligibility test.

Alignment to Internal Models Method.

The new Standard Rules are more aligned to the Internal Models Method in terms of capital requirements. Instruments are now bucketed as per their risk characteristics. The Risk Weights of each bucket are prescribed and they have been calibrated with the internal models for Expected Shortfall. There is now more recognition of hedging and diversification benefits through the use of an aggregation formula using the regulatory prescribed correlation parameters.

Standardised Capital Charge Calculation Process Flow.

The STD capital requirement is the sum of:

Enhanced Delta Risk Capital Charge + Default Risk Capital Charge + Residual Risk Add On.

Banks are required to calculate the ‘Enhanced delta plus Risk’ and ‘Default Risk’ capital charge at the following portfolios levels:

Complete trading desks Non Internal Model Approach (Desks which failed the model eligibility tests) Each desk as a portfolio on its own: no diversification or hedging benefits across desks.

Delta, Vega and Curvature.

The Basel Committee decided to implement the “enhanced delta plus method”, which is sensitivity-based, differentiating between three different risk components: delta risk as a foundation for capturing linear risks, and vega and curvature risk as two additional components which apply to products with optionality.

Vega risk assesses the risk of price changes based on market expectation on future volatility. In other words the sensitivity to the volatility.

Curvature risk captures the non-linear risk, which is not accounted for by delta risk.

STD Risk Class Definitions.

Sensitivities are calculated for 7 Risk Classes in STD approach:

GIRR Equity Credit Spread Securitisations Credit Spread Non Securitisations Credit Spread Securitisations Non Correlation Trading Portfolios Commodity FX.

The STD capital charge is also calculated on the above risk classes according to the relevant sensitivities: Delta, Vega, Curvature and Default Risk.

The linear and non linear capital charges are calculated separately with no diversifation benefit recognised between them.

Options are subject to Vega and Curvature risks.

More specifically for each Risk Class:

General IR risk.

Defined along two dimensions:

1) A risk-free yield curve for each ccy in which IR sensitive instruments are denominated.

2) Vertices (maturity points): 0.25, 0.5, 1, 2, 3, 5, 10, 15, 20, 30.

Also includes inflation and cross currency basis risk factors.

(Delta is the rate of change of the theoretical option value with respect to changes in the underlying).

Vega Rf are the implied volatilities of options that reference GIRR sensitive underlyings defined along two dimensions. (the Sensitivity to Volatility)

1) Maturity if the option mapped to the vertices :0.5, 1, 3, 5, 10 yrs.

Defined along only one dimension: the constructed risk free yield curve per currency.

Credit Spread Risk Non Sec.

Defined along 2 dimensions.

1) the relevant issuer credit spread curves (Bond and CDS)

2) Vertices: 0.5, 1, 3, 5, 10 yrs.

The Vega Rf are implied volatilities of options that reference credit issuer names as underlyings (bonds and CDS). Further defined along maturity of the option mapped to the vertices: 0.5, 1, 3, 5, 10 yrs.

The relevant issuer credit spread curves (Bond an CDS)

Credit Spread Risk Sec.

Rf are defined along 2 dimensions:

1) the relevant tranche credit spread curves.

2) Vertices: 0.5, 1, 3, 5, 10.

Vega risk factors are the implied volatilities of options that reference non CTP credt spreads as underlying (bond and CDS) defined along maturity of the option mapped to the vertices: 0.5, 1, 3, 5, 10.

The relevant tranche credit spread curves (Bond and CDS)

Credit Spread Sec (Correlation Trading Portfolio)

Risk factors are defined along two dimensions:

1) The relevant tranche credit spread curves.

2) Vertices: 0.5, 1, 3, 5, 10.

Vega rf are the implied volatilities of options that reference non CTP credit spreads as underlyings.

The relevant tranche credit spread curves (bonds and CDS)

Credit Spread Risk Securitisaitons (correlation trading portfolio)

Defined along two dimensions:

1) the relevant underlying credit spread curves (bonds and CDS)

2) Vertices: 0.5, 1, 3, 5, 10.

Vega rf are the implied volatilities of the options that reference CTP credit spreads as underlyings (Bonds and CDS) defined along maturity and the option mapped to the vertices: 0.5, 1, 3, 5, 10.

The relevant underlying credit spread curves (bond and CDS)

1) Equity Spot prices.

2) equity repo agreement rates.

The implied volatilities of the options that reference the equity spot prices as underlyings along maturity of the option dimension at the 0.5, 1, 3, 5, 10 yrs.

Equity Spot prices.

Commodity spot prices depending on the contract grade of the physical commodity and time to maturity of the traded instrument.

The implied volatilities of the options that reference commodity spot prices as underlyings along maturity of the option dimension at the 0.5, 1, 3, 5, 10 years.

Commodity spot prices.

All the exchange rates between the currency in which an instrument is denominated and the reporting currency.

The implied volatilities of the options that reference exchange rates between currency pairs with maturity of the option defined at the vertices 0.5, 1, 3, 5, 10.

All the exchange rates between the currency in which an instrument is denominated and the reporting currency.

Sensitivities Definition for STD approach.

Linear Capital Charge Calculation under the STD approach: DELTA.

Linear Capital Charge is calculated for each risk class separately. The Delta sensitivity is 1bp absolute in GIRR and CSR risk factors, or 1% relative move in EQ, FX and Comm Risk Factors.

The positions in a risk class are placed in buckets defined per risk class. Each bucket has a predefined RW. For example, Equity buckets are defined along 3 dimensions: region, market capitalisation and industry.

Net the sensitivity Sk across instruments to each risk factor k belonging to the same bucket. The Sensitivities cannot be netter across buckets.

Calculation of the Risk Weighted net sensitivities follows: WSk=RWksk.

In each of the buckets ‘b’, aggregate the weighted sensitivities across risk factors using the following:

The correlation parameter pkl between risk factors have been prescribed by the BIS. TO come up with delta capital charge for a risk class, bucket level capital Kb is aggregated as follows:

The Basel Committee prescribed similarities for across buckets aggregation, correlation parameter Ybc, between buckets for each risk class.

Linear Capital Charge Calculation under the STD approach: VEGA.

Calculation of Vega capital charge remains the same except for RW, correlations and sensitivity calculations. The RW used in Vega is calibrated to each risk class liquidity horizon and is not dependent on the bucket structure as Delta capital charge was.

Vega is defined along the option maturity at 5 tenor points. Hence, Vega of a position with a given maturity has to be allocated to one or two of the 5 tenor points.

Suppose an equity call option position with Vega of 100 and maturity of 4.5 years.

Vertices or maturity points are 0.5, 1. 3. 5. 10 years.

The position is linearly allocated between 3 and 5 years.

At yr 3 vertice, allocate 100*

Vega sensitivity is calculated as a product of the option Vega as allocated above and its implied volatility at the relevant maturity tenor.

The BIS has prescribed the method to calculate the correlation parameter: one for the GIRR and another for the other asset classes.

Non-Linear Capital Charge Calculation under the STD approach: Curvature.

Curvature capital charge calculation follows the same buckets and risk class foundations of linear capital charge with the only difference that this sensitivity is calculated by applying a stress move to the risk factor.

from the above equation:

in 1. the risk factor is shocked equivalently to the RW of the bucket in which the position is placed. In 2. we strip the delta from the curvature sensitivity to avoid double counting.

The correlation parameters in the intra bucket and across bucket aggregation formulas are the same as those used in the delta capital charge calculation.

Suppose we have an option on IBM stock. (Large market capitalisation, Advanced economy, Technology, Bucket 8, RW 50%). Current Stock Price is USD 151.31.

The stock price is bumped to USD 227.01 (151.34 1.5) and USD 75.67 (151.34 0.50). The position are revalued at the above stock market price level holding other risk factors constant.

The Curvature is calculated as:

The FO system will ahve to provide the valuation for a position in the 2 scenarios and current price. Curvature is then calculated for the capital charge.

Default Risk Charge.

Prior to FRTB, banks capture default and migration risk using the models for securitised and non securitised portfolios.

Namely: IRC for non Securitised Portfolios and All Price Risk (APR) or Comprehensive Risk Measure (CRM) for Securitised Portfolios (correlation trading portfolios).

The above are model based approaches, therefore no Standard default risk calculation exists except for securitisations trades. Default risk does not apply to equity portfolios either.

Going forward the standardised default risk charge will be calcualated for all trading desks in scope.

The capital requirement for default risk is the sum of the default risk of:

non-securitisations (including equity), Securitisations (non correlation trading portfolio) and Securitisations (correlation trading portfolios).

The DRC captures the Jump-To-Default risk at 1 year horizon and it’s calibrated on the basis of the banking book credit risk treatment in order to reduce the potential discrepancy in capital requirements for similar exposures in the Banking Book.

Similar to the enhanced delta plus component of the STD approach, it allows some hedging recognition at a bucket level.

The calculation steps are:

Categorise positions as long or short (a long position implies the default of the underlying obligor results in a loss) Positions are assigned a seniority on the basis of the allocated LGD Gross JTD is calculated per position. This value is a function of the LGD, notional amount (face value) and the cumulative P&L already realised on the position Scaling and offsetting is performed on gross JTD to arrive at net JTD Underlying obligors ratings are assigned in each of the net JTD position and placed in the defined buckets Calculate hedge benefit ratio for each bucket Calculate DRC for each bucket Calculate total capital charge for DRC by sum of bucket level capital charges No hedging or diversification is recognised across buckets in any given scope.

Residual Risk Add On.

The objective of this charge is to capture the risk which is not covered by the Enhanced Delta Plus Risk and Default Risk.

The scope of this add on is any instrument satisfying both conditions below:

It is subject to Vega Sensitivity and Curvature capital charge in the Trading Book Its pay off cannot be written as a linear combination of vanilla options.

An example of instruments affected by residual risk add on are path dependent options.

The Add On calculation is straightforward:

N= total number of positions under scope.

x = the add on multiplier (1% is the prescribed value)

Gross Notional is the notional amount of the instrument i.

In case the Notional amount is unavailable, then the maximum potential loss should be used.

General Interest Rate Risk Class Buckets and respective Risk Weights.

Credit Spread Risk Non-Securitised/Securitised Correlation Traded Portfolios Risk Class Buckets and respective Risk Weights.

Credit Spread Risk Securitised Non-Correlation Traded Portfolios Risk Class Buckets and respective Risk Weights.

Equity Risk Class Buckets and respective Risk Weights.

CAN, USA, MEX, €zone, non €zone, JAP, AUS, NZL, SIN, HK, SAR.

Commodity Risk Class Buckets ad respective Risk Weights.

FX Risk Class Buckets ad respective Risk Weights.

The Bucket structure is defined by each currency pair. (one bucket = one currency pair)

The FX weight is fixed at 15% and applied to all sensitivies or risk exposures. However for the following currency pairs, the 15% RW is divided by the SQRT of 2.

USD/EUR, USD/JPY, USD/GBP, USD/AUD, USD/CAD, USD/CHF, USD/MXN, USD/CNY, USD/NZD, USD/RB, USD/HKD, USD/SGD, USD/TRY, USD/KRW, USD/SEK, USD/ZAR, USD/INR, USD/NOK, USD/BRL, EUR/JPY, EUR/GBP, EUR/CHF, JPY/AUD.

The Internal Model Approach (IMA)

Current VaR.

To calculate portfolio VaR, Portfolio mean & Portfolio standard deviation (which includes effect of correlation between each individual security in the portfolio) is used, thus when Portfolio VaR is calculated, it would always be equal or less than the aggregate VaR of each individual security in the portfolio, which satisfies the subadditivity criteria.

Expected Shortfall.

The Expected Shortfall behaves differently. ES is sub-additive giving more diversification benefits. Under ES estimation the tail region is assigned a distribution(e. g. extreme value) now this distribution is divided into equal probability slices weighted by the more general risk aversion (weighting) function. The focus is on tail region only the difference is that the tail region itself follows a distribution which is then treated as said above to estimate the ES. It is generally assumed to be difficult to backtest and implement for the lack of peers and simulate through Montecarlo. ES is calculated using the instantaneous shocks equivalent to the movement of the relevant Risk Factors during the time span associated to the liquidity horizon. The risk factor move is taken from the 12 more stressful months since 2005.

Affected calculators.

The key changes affects the calculations of the following:

a) Internal Models (non modellable component), b) Standard Rules, c) Incremental Default Risk, d) Default Risk Charge and e) Capital Aggregation.

Methodology inputs are common to all of asset classes.

Internal Model Approach: Liquidity Horizons.

Liquidity Horizon is the time required to execute a transaction and liquidate the position in stressed market periods The increase in Liquidity Horizons from the previous 10 days to the the actual 250 is also another major change.

Before the increase of the Liquidity Horizon values, the market believed that trading book positions could be easily sold or hedged in the in the market over 10 day holding period. This was not what really happened. BIS proposed to incorporate the liquidity horizons into the market risk metrics similarly to the IRC and CRM (comprhensive risk measure)

Banks risk factors are now assigned 5 LH categories (IR, Equities, FX, Credit Spreads and Commodities):

Credit Spreads: capital requirements increase disproportionately to to other asset classes. Some Liquidity Horizons categories seem arbitrary: US treasury and USD/EUR FX have double the liquidity horizon compared to Large Cap Equity (10 days). It’s difficult to interpret and analyse the results. In addition, operational challenges are substantial.

ES is calculated using instantaneous shocks equivalent to the movement of the risk factors during the time span of the associated liquidity horizon. ES ignores dynamic re-balancing and trades maturity and the path dependency. In fact it’s risk factor dependent not product dependent. In addition, ES is independent of the position size.

A LH class is assigned to each sensitivity position and passed on to the P&L component (P&L Strips). This attribute is used for bucketing and aggregation of P&L Strips for the purpose of calculating the cascading expected shortfall and to calibrate the stressed scenario shocks for non modellable components.

Liquidity Horizons Implementation Approach.

There are two versions of Liquidity Horizons methodologies:

Full LH implementation Approach Scaling LH approach.

Full LH implementation.

The Full LH implementation approach requires the following:

Calculation of the moves/shocks in the time series over various LH depending on the risk factor (10, 20…250 days) Calculation of the corresponding P&Ls Aggregation of the PL st;rips aligned by start date.

The Pros of this approach are:

Actual underlying market moves More accurate for long horizons (not exceeding theoretical limits) Recognition of barrier effects (knock in, knock out) in partial/full reval models.

The Cons of this approach are:

Difficult to implement May violate non-arbitrage conditions causing pricing models to fail Large overlapping periods Distorts correlations b/ween asset classe Does not recognise hedging/re-hedging benefits as different risk factors are shocked by different LHs.

Scaling LH Approach.

The scaling approach is deterministic and driven by a formula.

ESt is the Expected Shortfall at horizon T (days)

Qj is the subset of risk fators whose liquidity horizons are at least as long as LHj.

The Pros of this approach are:

Easy to implement based on existing 10 days P&L strips Retains correlation structures.

The Cons of this approach are:

Scaling P&L rather than market moves introduces additional errors, ignoring non linearity Squareroot time scaling assumes IID returns, not always valid May break theoretical parameters limit Does not recognise hedges/re-hedging as different risk factors are shocked by differnet LHs Does not recognise barrier effects.

Constraints on diversification benefits.

FRTB ES Aggregation.

Two approaches are possible:

Unconstrained: It calculates ES allowing diversification effects between risk factor classes (full correlation benefit) Constrained: It calculates ES without diversification effects between risk factor classes (correlation benefit only within asset classes)

Capital_modellable= p Unconstrained + (1-p) Constrained.

where p is determined by the regulators post QIS.

Expected Shortfall – Capital Uplift Drivers.

Non Modellable – Stress Scenarios.

Punitive capital charges, more conservative than other approaches, including:

Current RNIV approach (PRA) where diversification within risk types is recognised Standard rules framework where diversification between offsetting trades in neighbouring buckets are allowed.

IR Volatility Skew.

RNIV is to be included in VaR soon via timeseries simulation Risk is captured via sensitivities and timeseries to the SABR volatility model parameters (ALpha, Beta, Rho) Parameters are not very frequently marked but data is filled using stochastic bridges Using historical simulation, there is a great deal of offsetting betwenn the P&L strips for each risk factor.

The actual marks do not satisy the FRTB requirements criteria Bridged data points are not real prices and cannot count as observations THe IR Vega Skew will be considered as non-modellable (>96&) and will be capitalised via stress scenarios.

Breakdown P/L strips into 5832 stress scenrios (18 tenors*18 expiries*3SABR parameters*6 currencies) LH driven by largest gaps/flat periods in data (IR Vega LH floor) Stressed period specific to each risk factors Overall RWA uplift factors > 20 X current RNIV VaR.

Reducing grnularity of grids to 10X10 (STD Granularity) results in.

25% RWA reduction Allow aggregation across expiries and only consider tenors as risk factors.

60% reduction Allow diversification benefits via IR Vega STD Approach correlations.

Regulatory feedback and consultation Ensure SABR parameters are marked at least 24 times a year with no gaps longer than a month.

Regression Models (RNIV)

Regression models capture market risk via a weighted average (index) timeseries (XBeta) Specific risk is captured via extreme moves (regression residual) 10 Day moves/shocks are used Specific risk components are aggregated using zero correlation.

FRTB treatment if non-modellable:

Every issuer/single name is shocked by Expected Shortfall shock corresponding to its own worst year Conservative aggregation by absolute sum Zero correlation to absolute sum (SQRT (N) uplift factor where N is the number of single names/issuers (N.

1000s) LH driven shocks is the largest gap in own data, prescribed asset class LH floor.

Improve data and include in modellable where possible RNIV examples: Borrow cost (single names), ETF NAV vs Listed Basis, EQ VEga Skew Convexity.

Non Modellable – Specification of market risk factors.

Risk factors Vs Pricing Inputs definition: Factors that are deemed relevant for pricing should be included as risk factors in the bank’s internal models. Where a risk factor is incorporated in a pricing model but not in the risk capital model, the bank must justify this omission to the satisfaction of its supervisor.

Additional risk will be in scope (basis risk) to ensure model performance with regards to:

Backtesting (capital multiplier impact) P&L attribution.

Scope: inclusion in line with the current trends imposed by the regulators Check if the model dependent parameters are real prices Minimum data requirements are 24 observation with maximum 1 month gap and check if observation gaps and flat periods differ Offset with valuation reserves Granularity of parameters (IR Skew and Correlation risks) currency, tenor, maturity attributes grids, marked at the same value, existing offsetting RNIV will not be realised.

Possible unforeseen consequences.

Dis-incentivise hedging of illiquid risks (trade and hedge offset is not recognised Dis-incentivise the development of more complex and more flexible risk models where dta fails the frequency and real price test Incentivise retrenchment of efforts to increase risk factor granularity over the past 5 years (move from 20 to the minimum of 6 tenor buckets (min imposed) to avoid significantly larger capital charges.

Modellable/NonModellable vs RNIV.

Review of the common Risk Models in Investment Banking.

Incremental Default Risk.

The potential MtM loss from shocks to credit spreads (including Migration risk) will be captured by the ES models of price risks.

IDR models where the loss is incremental to the risk already captured in the ES price risk model.

A 1 yr time horizon calibrated to a 99.9th percentile confidence level correlaiton parameters must be estimated based on listed equity prices and use a one year observation period based on a period of stress PD floor is 0.03% two factor simulation model Joint approval process with credit spread risk.

Tag: Retail FX System.

Understanding Global OTC Foreign Exchange (FX) Market.

Understanding Global OTC Foreign Exchange (FX) Market.

OTC FX Market is biggest market in the world. About 5.1 trillion USD are traded in this market every day.

Originally all FX transactions were for cross border trades in goods and services, but later on developments led to speculative investments activities in foreign currencies.

OTC FX Market is decentralized. It means there is no exchange on which currencies are traded. Interbank market in FX is among dealer banks. Dealer Banks are the biggest global banks. Top 10 banks who trade in FX have total trade volume of 67%.

USD is the dominant currency in global FX market. UK is the biggest location for FX trading followed by USA and Singapore. Hong Kong SAR and Japan are other important FX trading centers.

Markets operate 24/7 unlike other financial markets which open and close at certain times.

Bank of International Settlement publishes its triennial survey of global FX markets. 2016 survey showed 5.1 trillion USD/day FX turnover down from 5.3 T/Day back in 2013 survey. Markets peaked in September of 2014 at 6.5 Trillion USD/day. Since then the trend is declining. De-risking by global banks, decline in global trade are cited as main reasons for decline. Will attempt to understand this issue at a later date.

Following Issues emerge from this post but are not discussed here in detail.

Retail FX Market Algorithmic Trading Non Bank High Frequency Liquidity Providers FX Prime Brokerage Financial Stability in OTC Market – Case for CCP China RMB Internationalization Clearing and Settlement in FX Markets – CLS Bank and CLSNet Liquidity for FX trades – Funding and Market Liquidity.

Highlights from the 2016 Triennial Survey of turnover in OTC foreign exchange markets:

 Trading in foreign exchange markets averaged $5.1 trillion per day in April 2016. This is down from $5.4 trillion in April 2013, a month which had seen heightened activity in Japanese yen against the background of monetary policy developments at that time.  For first time since 2001, spot turnover declined. Spot transactions fell to $1.7 trillion per day in April 2016 from $2.0 trillion in 2013. In contrast, the turnover of FX swaps rose further, reaching $2.4 trillion per day in April 2016. This rise was driven in large part by increased trading of FX swaps involving yen.  The US dollar remained the dominant vehicle currency, being on one side of 88% of all trades in April 2016. The euro, yen and Australian dollar all lost market share. In contrast, many emerging market currencies increased their share. The renminbi doubled its share, to 4%, to become the world’s eighth most actively traded currency and the most actively traded emerging market currency, overtaking the Mexican peso. The rise in the share of renminbi was primarily due to the increase in trading against the US dollar. In April 2016, as much as 95% of renminbi trading volume was against the US dollar.  The share of trading between reporting dealers grew over the three-year period, accounting for 42% of turnover in April 2016, compared with 39% in April 2013. Banks other than reporting dealers accounted for a further 22% of turnover. Institutional investors were the third largest group of counterparties in FX markets, at 16%.  In April 2016, sales desks in five countries – the United Kingdom, the United States, Singapore, Hong Kong SAR and Japan – intermediated 77% of foreign exchange trading, up from 75% in April 2013 and 71% in April 2010.

Interbank (OTC) Market Infrastructure and Institutions.

From All change in the 2016 Euromoney FX rankings.

Citi holds on to the top ranking in this year’s Euromoney foreign exchange rankings, but elsewhere there have been unprecedented shifts.

Structural changes to the markets, management upheaval among many big banks, new non-bank entrants and lack of volumes and volatility have seemingly levelled the playing field among the industry’s biggest firms.

The biggest change in the rankings this year is the decline of the combined market share of the top five global banks. Their market share in the survey peaked in 2009 at 61.5% and was still above 60% as recently as 2014.

This year the top five banks account for just 44.7% of total volume. The hopes of many global FX heads and their investment bank bosses – that the share of the big banks would rise inexorably as the market became more automated and that they would be able to benefit from oligopolistic pricing power as a result – now seem like distant and deluded dreams.

One FX veteran tells Euromoney that the decline of the top five banks’ combined market share “is exactly what the regulators would want in a market they continue to keep a very close eye on.”

While the market share of the top 10 FX houses overall also declines, from over 75% last year to just 66% this year, the fall is entirely due to the performance of the top five banks. The banks ranked from sixth to 10th place overall produced a combined market share of 22%, roughly in line with the last five years of the survey and considerably higher than the 14% they managed in 2008.

Citi actually extends its lead over the second-placed bank in the survey, which market participants regard as the most accurate reflection of client-based activity in the global foreign exchange markets, to more than four percentage points – even though the bank’s own market share declined by more than three percentage points, from 16.11% in the 2015 survey to 12.91% of trading in 2016.

That winning market share is the lowest for any top-ranked bank in the survey since UBS won the survey in 2004.

Citi maintained its leadership overall in important product areas such as spot/forwards and swaps, as well as in the key real money and bank client categories. It rises one place this year to win in corporates and overall electronic market share, although it falls to third overall for options.

One big story in this year’s rankings is the decline of Deutsche Bank. It was once the undisputed leader in global foreign exchange, losing the top position in the Euromoney rankings three years ago after nearly a decade of dominance.

While new group CEO John Cryan has gone out of his way both publicly and privately to describe the FX business as one of the beleaguered bank’s crown jewels, the days when Deutsche Bank was able to secure an overall market share of more than 20% (as recently as 2009) are long gone.

In the latest set of rankings, Deutsche falls from second to fourth place overall: its market share of 7.86% is almost half what it was a year ago. Deutsche’s decline is widespread, and competitors say has been driven in part by the bank cutting back on the number of clients it covers. It falls from second to fifth in spot/forward; from second to eighth among real money clients and loses top spot among bank clients. It remains the leading overall options house.

Perhaps the most surprising fall of all is in its overall electronic market share. Deutsche’s Autobahn system revolutionized global FX trading and in banner years accounted for more than a quarter of all electronic trading. This year, Deutsche can only manage fourth place in e-market share, from holding the top ranking last year, and its share has fallen from 17.5% to 8.73%.

Two banks overtake Deutsche to move into the top three overall, but the similarities end there: the two banks in question have very different recent histories in global foreign exchange.

JPMorgan jumps to second place in the survey, with a market share of 8.77%, up from fourth place with 7.65% last year. For many years, competitors have said that JPMorgan has failed to punch its weight in FX; it has typically ranked outside the top five overall banks in the Euromoney survey for the last decade. Those accusations have less weight now, even though they have been replaced by rumours about the bank’s competitive pricing strategy.

The US bank rises across a range of categories. Its most notable successes are winning the leveraged fund category with a lead over second-placed UBS of almost eight percentage points and a market share of more than 18%; and jumping from fifth to second place in overall electronic trading. JPMorgan’s one poor ranking is now in options, where it comes a lowly eighth.

UBS returns to the top three global FX banks overall this year. A winner back in 2004, it has been outside the top three since 2009, and last challenged for the top spot overall a year earlier, when its market share of almost 16% was only beaten by Deutsche. Last year it fell to fifth place, its worst performance in a decade, with a market share of 7.3%.

Given the bank’s leadership has spent the last few years de-emphasizing the role of its investment bank, some competitors believed UBS was on a long, slow decline in FX.

But, quietly and consistently, UBS’s markets business has been recalibrating to the new capital and markets environment, as well as maintaining a commitment to best-in-class electronic platforms. Its overall market share rises to 8.76%; and it breaks into the top three overall in spot/forward, swaps, electronic market share and for bank clients. Like JPMorgan, it is a laggard in options, where it ranks seventh.

JPMorgan and UBS have one other important thing in common: while other banks have lost entire benches of senior management from their FX teams in recent years, JPMorgan and UBS have been relatively stable.

At the former, Troy Rohrbach has overseen the FX business since 2005 (he now also runs rates and public finance globally); at UBS, Chris Murphy and George Athanasopoulos, the global co-heads of FX, rates and credit, both joined the bank more than five years ago and have jointly run the division since 2013. Leadership, it seems, does count.

Bank of America Merrill Lynch continues its steady rise up the rankings of recent years, from a nadir of 12th place from 2009 to 2012. It finally breaks into the top five global FX houses overall, up from sixth place last year.

BAML jumped up the rankings into the top five for corporates and real money accounts, and gained ground in both swaps and options – in the latter, it ranks second globally. But BAML still has work to do in the electronic market, where its overall ranking fell from sixth to seventh place. Other US banks also performed well.

Goldman Sachs rose from ninth to seventh overall and Morgan Stanley jumped three places to break back into the top 10.

It has not been a good year in FX for Barclays. Perhaps the bank’s decision to not have a global head of foreign exchange has backfired. The UK-cum-transatlantic bank dropped from third place overall to sixth, and its market share from 8.11% to 5.67%.

Barclays slipped three places to seventh in spot/forward, four places to seventh in swaps and three places to ninth in options. Among client groups, its biggest reversal came among real money accounts, falling from fourth place last year to outside the top 10.

HSBC has also had a disappointing year, falling from seventh to eighth place overall. It also loses its top ranking among corporates last year, falling out of the top five of that client category altogether. Electronic trading remains the bank’s weakest link, and may even be getting weaker, as the bank falls to ninth place in overall e-market share.

Banks have always risen and fallen in the Euromoney rankings over the last 40 years, but this year sees a new phenomenon – the advent of the non-bank liquidity provider. Leading the way is XTX Markets, a spin-off of GSA Capital, whose co-CEO Zar Amrolia was a frequent winner of the Euromoney FX rankings in his previous role as head of Deutsche Bank’s FX business.

In its first year of eligibility, the spot-only XTX makes a stunning debut: ninth place in the overall rankings with a market share of 3.87%; fourth in spot/forwards; fifth for bank clients; third for FX trading platforms; fifth overall for e-market share; and third for electronic trading of spot, ahead of Deutsche Bank with a market share of more than 10%.

XTX is the leader, but not the only non-bank entrant to the survey. Tower Research Capital, Jump Trading, Virtu Financial, Lucid Markets and Citadel Securities all make the top 50 overall market share rankings.

XTX’s ninth place overall looks like a line in the sand for the FX markets. The banks above it are, for the most part, the remaining price-makers; the banks below often price-takers, with the ability to make markets in particular currencies or products.

Many of the banks ranked outside the top 10 overall this year are understood to be sourcing liquidity from non-bank providers such as XTX, Tower and Jump. They look set to gain more market share in the future, helped by new technology, more defined business models and a lower-cost infrastructure base than the traditional FX banks. They could look to build capability in forwards and other markets in the near future.

Among multi-dealer platforms, Thomson Reuters – through its FXall service – remains the clear leader with a 30% market share, although its margin over second-ranked FXConnect almost halved. The big riser among MDPs was third-ranked HotspotFXi, which increased its market share from less than 7% to almost 18% this year.

Total volumes in the Euromoney FX survey came in at almost $95 trillion, while the number of votes held steady compared with last year at around 3,500 clients. That represents a volume fall of around 23% on last year, in line with market expectations.

There are three types of trading platforms.

Trading platforms can be divided into three different types :

I nter-dealer electronic broking platforms . These platforms were developed in the 1990s and are regarded, according to the Bank for international Settlements (BiS, 2010), as the dominant source of interbank liquidity on the foreign exchange market. They mediate information on various market makers’ indicative prices. EBS and Reuters, based in London, are the two dominant platforms within this category. Multi-bank platforms . These platforms are also known as multi-bank ECNs (electronic communication networks). They were created in the first decade of this century and resemble the previous category in that they mediate several market makers’ prices. one difference is that they have freer access regulations for market makers, which makes it easier for market makers to join these platforms. Another difference is that they are largely used outside the interbank market, which is to say by market participants that are not banks. The US platforms Fx All, currenex, Hotspot Fx, State Street and Fx connect are examples of this type of trading platform. There are also platforms that provide standardised algorithmic trading functions as a service. currenex is one such platform. Single-bank platforms . This type of platform is run by an individual bank. The platform mediates only the individual bank’s own prices for various currency pairs, unlike the trading platforms discussed above, which mediate several market makers’ prices. in Sweden, SeB has a platform of this type, SeB Trading Station. other examples of banks with such platforms are JP Morgan, Deutsche Bank and citibank.

J. P. Morgan has significantly increased its footprint on these platforms over the past couple of years and now ranks first for penetration globally, followed closely by Citi. Bank of America Merrill Lynch, Deutsche Bank and HSBC round out the top five most prominent banks on MDPs.

B. Single Dealer Platforms.

While multi-dealer systems are clearly on the rise, an average of more than 20% of trading volume of banks and hedge funds is still executed on single-bank platforms. Barclays, Citi and Deutsche Bank are the clear top three most actively used single-dealer platforms globally.

“Proprietary platforms give banks a means of retaining profitable trading volumes, so dealers are expanding these systems to provide a range of liquidity choices that enable clients to access the market in a variety of ways, including disclosed and non-disclosed liquidity, agency and principal trades, and links to exchange-based execution,” says Greenwich Associates Managing Director Woody Canaday.

Dealers are also in the early days of what promises to be an all-out arms race in algorithmic trading. Currently only 13% of top-tier FX customers use algorithmic trading models. However, that share approaches one-quarter among the market’s biggest buy-side participants and 30% among hedge funds.

Two trends suggest that algorithmic trading is gaining traction in FX. First, market participants that use algo-rithmic models are tapping an expanding number of dealers for algorithms. Second, current users are routing growing shares of trading volume through the models, from 25% in 2014 to 28% in 2015. Hedge funds that trade algorithmically now use these models for about half of total trading volume.

A. Inter-dealer electronic broking platforms.

Reuters Dealing 3000 ICAP EBS.

EBS is the primary trading venue for EUR/USD, USD/JPY, EUR/JPY, USD/CHF, EUR/CHF and USD/CNH.

Thomson Reuters Matching is the primary trading venue for commonwealth (AUD/USD, NZD/USD, USD/CAD) and emerging market currency pairs.

EBS was created by a partnership of the world’s largest foreign exchange (FX) market making banks in 1990 to challenge Reuters’ threatened monopoly in interbank spot foreign exchange and provide effective competition. By 2007, approximately US$164 billion in spot foreign exchange transactions were traded every day over EBS’s central limit order book, EBS Market.

EBS’s closest competitor is Reuters Dealing 3000 Spot Matching . The decision by an FX trader whether to use EBS or Thomson Reuters Matching is driven largely by currency pair. In practice, EBS is the primary trading venue for EUR/USD, USD/JPY, EUR/JPY, USD/CHF, EUR/CHF and USD/CNH, and Thomson Reuters Matching is the primary trading venue for commonwealth (AUD/USD, NZD/USD, USD/CAD) and emerging market currency pairs.

EBS initiated e-trading in spot precious metals, spanning spot gold, silver, platinum and palladium, and remains the leading electronic broker in spot gold and silver through the Loco London Market.

They were the first organisation to facilitate orderly black box or algorithmic trading in spot FX, through an application programming interface (API). By 2007 this accounted for 60% of all EBS flow.

In addition to spot FX and Precious Metals, EBS has expanded trading products through its venues to include NDFs, forwards and FX options. It has also increased the range of trading style to include RFQ and streaming in disclosed and non-disclosed environments.

EBS was acquired by ICAP, the world’s largest inter-dealer broker, in June 2006. ICAP said that the acquisition would combine EBS’ strengths in electronic spot foreign exchange with ICAP’s Electronic Broking business to create a single global multi-product business with further growth potential and significant economies of scale. It went on to say that would provide customers with more efficient electronic trade execution, reduced integration costs and give access to broad liquidity across a wide product range.[1]

In 2014, EBS merged with BrokerTec – a leading service provider in the fixed income markets – to form EBS BrokerTec. BrokerTec’s offering comprises trading solutions for many US and European fixed income products including US Treasuries, European Government Bonds and European Repo.

EBS BrokerTec is now recognised as a market-leading e-trading technology and solutions provider, offering access to multiple execution options and diverse, valuable liquidity across the FX and fixed income markets.

ICAP EBS is one of the world’s premier inter-dealer brokers with average daily transaction volume in excess of USD 2.3 trillion. ICAP’s electronic EBS platform provides the primary market of natural interest for more than 2800 global FX, Precious Metals and NDF traders. ICAP EBS global access platform delivers anonymous, transparent and reliable FX Liquidity. Authoritative real-time and historical market data. Available for clearing only. Relationship with EBS required.

B. Multidealer Platforms – FX ECNs.

Since 1999, banks have been developing proprietary systems for their customers to trade foreign exchange and access research material over the internet. To trade with multiple banks online, customers therefore need to use a variety of authentication methods, websites and price request methods. Multi-bank platforms have evolved to allow customers to use a single website to request prices simultaneously from multiple banks and view research material online. Multi-bank platforms (also known as ECNs or electronic communication networks) offer significant advantages to customers, but fewer advantages to banks, and therefore active participation by banks in multi-bank platforms is driven largely by customer demand. However, for the banks it remains preferable for their customers to trade through bank proprietary systems as the banks avoid paying brokerage and customers are encouraged to focus only on the particular bank’s prices.

There are five main customer-facing FX ECNs:

FXall – founded by Bank of America, Credit Suisse First Boston, Goldman Sachs, HSBC, JP Morgan, Morgan Stanley Dean Witter and UBS.

Currenex – independent and venture backed by major market participants, e. g. Barclays Capital and Royal Dutch/Shell.

FX Connect – owned by State Street.

360T – independent and venture backed by financial and major private investors.

Hotspot FXi – independent privately held venture capital-backed company.

Currency Trading Shifts to Multi-Dealer Systems, Greenwich Says.

July 14, 2015, 11:28 AM EDT.

Currency investors are increasingly using electronic systems connected to multiple dealers as the market comes under greater scrutiny by regulators, according to Greenwich Associates.

Institutional investors and large corporations executed 49 percent of their foreign-exchange trading volumes on multi-dealer platforms last year, up from 45 percent in 2013 and 38 percent in 2008, the Stamford, Connecticut-based consultant said in a report. The increase comes as trading by traditional methods, such as phone, instant messaging and single-dealer platforms, has fallen.

“The FX ‘fixing scandal’ and related bank fines have already played a part in changing buy-side behavior,” wrote Kevin McPartland, head of research for market structure and technology at Greenwich, who co-authored the report based on interviews with more than 1,600 people participating in foreign-exchange markets globally.

Asset-management companies are boosting electronic trading as regulatory scrutiny discourages banks and dealers from providing “market color” to clients to avoid any perception of impropriety, according to Greenwich. The platforms are also becoming more popular as banks become less active in currency markets because of rising capital requirements.

“Asset managers have proactively worked to beef up internal policies to both ensure maximum returns for the impacted funds and to reassure customers, such as pension funds and sovereign wealth funds, that they’re getting the best the market has to offer at that moment in time,” McPartland wrote.

Thomson Reuters Corp.’s FXall platform had the largest volume-weighted share of trading last year at 21 percent, according to Greenwich. It’s followed in popularity by 360T, State Street Corp.’s Currenex, Bloomberg LP’s FXGO and FX Connect.

State Street FX Connect Thomson Reuters FXall State Street Currenex CBOE/BATS Hotspot FX Bloomberg FXGO.

C. Single Dealer FX Trading Platforms.

Barclays BARX Citi Velocity Deutsche Autobahn Morgan Stanley Matrix UBS Neo.

Best Single-Dealer FX Trading Platform.

Financial News is delighted to announce the . The winners will be announced at a gala dinner in London in October.

Here are the nominees in the category of Best Single-Dealer FX Trading Platform:

The BARX platform remains a dominant force among single-dealer platforms, with streaming prices in more than 80 currencies and 480 currency pairs, with a wide range of products available. Following the launch of BARX Gator, a liquidity aggregator, Barclays now gives clients access to the increasingly popular agency-style of execution.

Since its relaunch in 2012, Citi Velocity 2.0 has become a leading source of single-bank liquidity in FX cash, options and rates trading. Citi has also led the adoption of mobile and tablet technology in this space, and has focused its efforts with Velocity on delivering speed, lower transaction costs, cross-asset information, cross-asset trading, deep liquidity, and desktop efficiency.

Deutsche Bank has channelled significant resources into its electronic trading franchise in recent years, and Autobahn remains a major player across asset classes. In FX, Autobahn provides a single blotter for trades executed via both voice and electronic channels. Users can thus benefit from a combined view and take greater control over their portfolios.

While not a top-tier bank in FX, Morgan Stanley has sought to add unique value with its Matrix platform. That has been achieved in part through execution and post-trade services, but also through the bank’s quantitative solutions and innovations group, which develops unique analytical tools to help users make more informed trading and investment decisions.

Launched in 2013, UBS Neo is a cross-asset class platform providing a single point of access with a strong user experience, re-establishing the Swiss bank as a significant player in electronic trading. UBS Neo FX covers 550 currency pairs, with access to cash, NDFs and options available through the platform.

Trends in use of Electronic Platforms.

From The $4 trillion question: what explains FX growth since the 2007 survey?

Electronic execution methods are transforming the FX market The greater activity of all three of the above-mentioned customer types – highfrequency traders, banks as clients and retail investors – is closely related to the growth of electronic execution methods in FX markets. Greenwich Associates estimates that more than 50% of total foreign exchange trading volume is now being executed electronically (Graph 3, left-hand panel).

Electronic execution methods can be divided into three categories: electronic brokers , multi-bank trading systems and single-bank trading systems . Electronic brokers were introduced in the inter-dealer FX market as early as in 1992. For customers, however, the main channel for trading continued to be direct contact with dealers by telephone. In the rather opaque and fragmented FX market of the 1990s, barriers to entry were high and competition was limited. Customers typically paid large spreads on their FX trades.

The first multi-bank trading system was Currenex, which was launched in 1999. By providing customers with competing quotes from different FX dealers on a single page, Currenex increased transparency, reduced transaction costs and attracted a growing customer base. State Street’s FXConnect, which had been launched in 1996 as a single-bank trading system servicing only State Street’s clients, opened up in 2000 and became a multi-bank ECN.

In response to the increased competition, top FX dealers launched proprietary single-bank trading systems for their clients, such as Barclays’ BARX in 2001 , Deutsche Bank’s Autobahn in 2002 and Citigroup’s Velocity in 2006 . According to data provided to the BIS, daily average trading volumes on the top single-bank trading systems have increased by up to 200% over the past three years.

The Forex market is an international over-the-counter market (OTC). It means that it is a decentralized, self-regulated market with no central exchange or clearing house, unlike stocks and futures markets. This structure eliminates fees for exchange and clearing, thereby reducing transaction costs.

The Forex OTC market is formed by different participants – with varying needs and interests – that trade directly with each other. These participants can be divided in two groups: the interbank market and the retail market.

The interbank market designates Forex transactions that occur between central banks, commercial banks and financial institutions.

Central Banks – National central banks (such as the US Fed and the ECB) play an important role in the Forex market. As principal monetary authority, their role consists in achieving price stability and economic growth. To do so, they regulate the entire money supply in the economy by setting interest rates and reserve requirements. They also manage the country’s foreign exchange reserves that they can use in order to influence market conditions and exchange rates.

Commercial Banks – Os bancos comerciais (como o Deutsche Bank e o Barclays) fornecem liquidez ao mercado Forex devido ao volume de negociação que controlam todos os dias. Parte dessa negociação representa conversões de moeda estrangeira em nome de clientes & # 8217; precisa enquanto alguns é realizado pelos bancos & # 8217; mesa de negociação proprietária para fins especulativos.

Financial Institutions – Financial institutions such as money managers, investment funds, pension funds and brokerage companies trade foreign currencies as part of their obligations to seek the best investment opportunities for their clients. For example, a manager of an international equity portfolio will have to engage in currency trading in order to buy and sell foreign stocks.

The retail market designates transactions made by smaller speculators and investors. These transactions are executed through Forex brokers who act as a mediator between the retail market and the interbank market. The participants of the retail market are hedge funds, corporations and individuals.

Hedge Funds – Hedge funds are private investment funds that speculate in various assets classes using leverage. Macro Hedge Funds pursue trading opportunities in the Forex Market. They design and execute trades after conducting a macroeconomic analysis that reviews the challenges affecting a country and its currency. Due to their large amounts of liquidity and their aggressive strategies, they are a major contributor to the dynamic of Forex Market.

Corporations – They represent the companies that are engaged in import/export activities with foreign counterparts. Their primary business requires them to purchase and sell foreign currencies in exchange for goods, exposing them to currency risks. Through the Forex market, they convert currencies and hedge themselves against future fluctuations.

Indivíduos & # 8211; Individual traders or investors trade Forex on their own capital in order to profit from speculation on future exchange rates. They mainly operate through Forex platforms that offer tight spreads, immediate execution and highly leveraged margin accounts.

Only 200 billion daily turnover using exchanges.

Exchanges are staking out the $5tn a day global currency market as part of their latest efforts to tap this lucrative and booming sector that has long been dominated by global banks.

This week Bats Global Markets, the US’s second largest equities exchange, fired the latest salvo by offering three months of free trading on its forthcoming London-based Hotspot currency trading platform, the centrepiece of Bats’ $365m purchase of the venue from KCG Holdings in March.

That came only days after Deutsche Börse, Europe’s largest exchanges operator, bought 360T, one of the world’s largest currency trading networks, for €725m.

Their moves are audacious attempts to break into the world’s most liquid over-the-counter market, where a notional $5.3tn a day is traded in cash, or spot, and derivatives trades. It is dominated by banks, which continue to make billions of dollars in profits from it each year. Exchanges have generally been unable to establish a presence in this and other OTC markets, despite repeated attempts to do so.

In currencies, Chicago’s CME Group dominates futures trading , reflecting how it seized the terrain in the 1970s when the present era of floating foreign exchanges began. Markets in Moscow, Brazil and India also trade local currency, but of that $5.3tn total, global exchanges account for just $200bn according to Aite Group, a financial markets consultancy.

However, cracks are appearing in the market edifice, brought on by a combination of unlawful activity by banks, deep structural change and the emergence of cheap and reliable technology that has allowed alternative ways of trading to emerge.

“The banks as a whole will continue to have a substantial piece of the pie but the regulations will force them to let go of pieces of it,” says Javier Paz, an analyst at Aite Group.

Waves of post financial crisis regulation have accelerated change in equity and interest rate swaps markets, but global policymakers largely left the currency market alone.

However, the currency industry is mopping up after two of its own existential crises — the Wm/Reuters benchmark rate rigging scandal, which resulted in multibillion-dollar fines for banks, and the sudden move by the Swiss franc in January when the national central bank abolished its ceiling against the euro.

Market observers say that end users such as corporations, hedge funds and asset managers are now taking far more care with their orders, and they have the tools to do it, turning the banks more into agency brokers.

“End users are getting used to technology where they have a full view of the market. They are accessing more markets than they could ever do 10 years ago,” says Chris Concannon, chief executive of Bats Global Markets.

At the same time, incidents like the Swiss move have also raised the alarm among banks. By the end of that day in January some smaller retail brokers faced ruin but even several larger broker-dealers such as Barclays, Citigroup and Deutsche Bank nursed tens of millions of dollars in losses. That has also left the market seeking as many different venues as possible where they can offset their customers’ trades.

“People are not holding risk like they were a year ago. A year ago they would warehouse that risk and wait for another customer to come along,” says Mr Concannon.

Not helping matters is how foreign exchange market liquidity is highly concentrated among just a handful of trading pairs, known as the G10. Into the gap on the other side of the trade are stepping high-frequency traders such as the US’s Virtu Financial. It is one of the world’s largest currency market makers.

“Clients that are trading on anonymous platforms by definition have no insight into whom they are trading with, and as such are likely interacting with non-bank liquidity providers more often than they know,” notes a report by Greenwich Associates last month.

However, even if the diagnosis is right, e xchanges still face tough competition from well-established platforms not run by banks, such as Thomson Reuters, Bloomberg FXGO and ICAP’s EBS . These make up the majority of the $1.1tn average daily volume traded on electronic FX platforms and provide a role as a more centralised price benchmark independent of banks.

Bats, which has targeted London because it is the world’s main location for forex trading, will aim to provide a reliable venue for pricing and take more trading volume from the 220 banks, asset managers, hedge funds, dealers and retail brokers signed up to the venue.

Deutsche Börse sees 360T as a key part of its growth strategy, using it as a way to sell market data and develop futures, FX forwards and swaps trading to boost its Eurex derivatives business. But it is trading network, not an exchange-like central limit order book.

Critically, OTC markets are historically highly resistant to encroachment from exchanges and some see little sign of that changing.

The head of one currency trading platform says: “I don’t see any signs of moving to an exchange model. I don’t see a slam dunk here, I see some desperate buyers looking for a growth story.”

OTC FX trading becomes ‘exchange-like’

Thursday, April 21, 2016.

The acquisition of trading platforms Hotspot and 360T by Bats Global Markets and Deutsche Börse respectively last year were bold statements of intent by exchange operators to grab a larger chunk of the trillions of dollars traded in FX every day.

However, while consolidation in the venues supporting FX trading can be expected to result in exchanges becoming more involved in the FX space, any actual market structure change is likely to take a long time to materialize, according to.

FXSpotStream CEO Alan Schwarz.

“The FX market continues to do a good job of addressing regulatory requirements and meeting the demands of market participants,” ele diz.

“We have seen a shift in the FX market looking to trade more on a disclosed basis. Our business has continued to see year-on-year growth because there is a move taking place from exchange-like anonymous trading to bilateral, fully disclosed trading between counterparties.

“Unlike trading on an exchange, the relationship via FXSpotStream is transparent and trading with the liquidity providing banks is on a fully disclosed basis.”

Kevin McPartland, head of market structure and technology research at Greenwich Associates, believes that discussion of migration from OTC to exchange fails to take account of some of the nuances of the FX market and that the future lies in venues that support multiple trading models.

“There are a host of non-exchange electronic trading venues that allow clients to trade with each other in a variety of ways,” ele diz.

On the question of whether there is a discernible shift towards fully disclosed trading, McPartland refers to both central limit order book (CLOB) and request-for-quote (RFQ) having their merits.

Despite observations made by the likes of TeraExchange – that order book platforms offer a democratic marketplace through transparent, firm and executable prices – corporates have remained reluctant to abandon the RFQ model.

The key question for CLOB platform providers continues to be not why market participants have migrated to alternative models but rather when they will be in a position to win new business for products that are most suited for order books, such as the benchmarks and plain vanilla products.

“RGQ offers liquidity on demand and identification of counterparties, whereas CLOB is faster and its anonymity can be helpful,” says McPartland.

“But we are now seeing demand for a solution that provides the best of both worlds by enabling trading in an order book format while maintaining a bilateral relationship with counterparties.”

According to James Sinclair, CEO of MarketFactory, options and other derivatives are moving closer to an exchange model due to the direct effects of regulation and the increased costs of compliance in OTC markets.

He refers to CME FX options as an example, noting they are effectively options on futures.

“However, the situation in the spot market is more complicated – some aspects are becoming closer to an exchange, others are moving further away,” ele diz. “FX has its own market structure that is hard to fit into the OTC/exchange paradigm.”

One of the fundamental reasons why the market does not become centrally cleared, says Sinclair, is that a cleared model carries the cost of insurance against both settlement and market risk.

“CLS insures you against settlement risk but not the market risk,” he adds. “Counterparts still find it cheaper to self-insure against market risk in case of a counterparty default than to pay the extra cost of a fully cleared solution.”

A senior platform source observes that growth in exchange-traded products has largely come from futures traders who have looked for diversification and added FX as another asset class.

“Very little business has moved from OTC – some banks have added exchanges as additional liquidity sources to cover risk, but that is really the only business that has crossed the divide,” the source says.

OTC has become more exchange-like in that the largest banks have continued to extend their internalization of flow, so each now runs an order book trading structure internally.

However, our source also points out that the tightening of credit has reduced the number of prime brokers in FX and costs have risen “so the nearest thing that the FX OTC market has to centralized clearing has actually reduced its volume and capacity”, he concludes.

Evolution of Information Exchange in Trading Platforms.

Clients C Voice Broker VB Dealers D Electronic Broker EB Prime Broker PB Retail Aggregator – RA Multi Bank Trading – MBT Single Bank Trading – SBT.

Top 10 FX Turnover Locations.

Currencies and Currency Pairs.

US Dollar is the king in FX market. 87.6% of transactions include USD on one side of currency pair. Euro comes at second with 31%. Japanese Yen is at 21.6%. UK Pound Sterling is at 12.8%. Chinese Yuan has moved to 4%.

Currencies and Currencies Pairs.

Electronic Trading Algorithmic Trading High Frequency Trading Non Bank Liquidity Providers (Market Makers)

Non Bank Electronic Market Makers.

The diverse set of non-bank electronic market-makers includes.

These market-makers’ trading volume is captured in the Triennial because their trades are prime-brokered by a dealer bank. They are active on multilateral trading platforms, where they provide prices to banks’ e-trading desks, retail aggregators, hedge funds and institutional clients.

Second in Trade Finance Sixth in Payments Eighth in FX Trading.

Considering China’s Renminbi for International Settlement and Forex Trading.

On October 1, 2016, the International Monetary Fund added China’s renminbi1 (RMB) to its elite Special Drawing Right (SDR) basket of currencies, alongside the U. S. dollar, euro, yen and British pound. IMF said the change reflected China’s progress in reforming its monetary, foreign exchange and financial systems, and improving its financial market infrastructure.2 Short-term, this means countries can now include RMB assets in official FX reserves, making it easier for them to meet IMF guidelines.3 Beyond this, however, inclusion in SDR is a symbol of RMB’s emergence as an international currency for forex trading and settlement of global business transactions.

RMB’s ongoing progress is an important consideration for businesses involved in any FX trading, and particularly for those whose business or currency trading activities involve China.

O uso de RMB cresce no comércio e troca de moeda.

IMF’s decision arrives in the context of growing RMB usage in trade finance, international payments, and forex trading. In trade finance, RMB is now second amongst world currencies, reflecting enormous international trade with China.4.

Since 2013, according to the Society for Worldwide Interbank Financial Telecommunication’s (SWIFT’s) monthly Renminbi Tracker, China’s currency has risen from ninth to fifth worldwide in total payments sent and received by value, not counting payments by central banks. Durante esse período, superou a coroa sueca (SEK), o dólar canadense (CAD), o franco suíço (CHF), o dólar australiano (AUD) e, brevemente durante o verão de 2015, até mesmo o iene (JPY). RMB use is growing slowly in some markets (such as France, Switzerland and Germany), and is rapidly accelerating in others (e. g., the United Arab Emirates).5 SWIFT has elsewhere reported that 50 countries now use RMB for 10 percent or more of their trade with China.6.

Meanwhile, according to the Bank for International Settlements’ (BIS’) September 2016 Central Bank Survey, RMB has doubled its share of OTC currency trading transactions since 2013. It has surpassed Mexico’s peso to become the most active developing market currency on forex trading exchanges, and is now eighth in FX trading amongst all currencies worldwide. BIS’s report notes that “as much as 95 percent of renminbi trading volume was against the U. S. dollar.”7.

Building the Global Infrastructure for an Internationalized Currency.

To promote RMB usage abroad, the People’s Bank of China (PBOC) – China’s central bank – has authorized 18 new official clearing banks worldwide since December 2012. These have opened in locations including Toronto, Buenos Aires, London, Paris, Johannesburg, Sydney, Seoul and Taipei.8 In September 2016, PBOC announced the first RMB clearing and settlement services in the U. S.9.

Domesticamente, a China eliminou um teto para o número de empresas autorizadas a realizar assentamentos transfronteiriços de RMB. Any company permitted to engage in import-export business may settle in RMB, unless it appears on a “black name list” (in which case its transactions may be reviewed individually).10 Restrictions have also been relaxed on RMB-denominated investments by foreigners.11.

As Yu Yongding of the Asian Development Bank Institute has pointed out, China is the only country that has ever decided on its own to make internationalizing its currency a national priority.12 In determining how far RMB’s internationalization will go, China’s authorities appear to be balancing the benefits and risks of liberalization,13 carefully timing their decisions accordingly.

They face significant obstacles, not least the continuing downward pressure on the value of China’s currency on forex trading exchanges since it peaked against the U. S. dollar in early 2014. Some market observers believe RMB faces bank sector headwinds that might require a government bailout,14 as well as increased protectionist pressures in the U. S.15 and elsewhere. If these events lead to further reductions in RMB’s value, China could face accelerating capital flight,16 deepening internal opposition to the full elimination of capital controls.

China’s reforms have made it easier for companies that do business in China to settle their transactions in RMB if they so desire. Many of their Chinese trading partners would welcome this, and some may even offer discounts if they can invoice in RMB.17 China’s central bank has estimated that transacting in U. S. dollars may add 2-to-3 percent in administrative expenses alone.18.

O risco de flutuação cambial, no entanto, continua sendo uma questão importante. Existem veículos de cobertura; Claro, estes têm seus próprios custos. Ao tomar a decisão sobre transacionar negócios em RMB ou outra moeda, as empresas podem querer fazer avaliações cuidadosas e oportunas sobre o risco cambial.

As China’s financial and market reforms move forward, RMB is emerging as a leading international currency. It has become far easier for international businesses and currency traders to transact in China’s home currency. As empresas internacionais podem querer considerar cuidadosamente o risco cambial no desenvolvimento de seus próprios planos de negociação e liquidação de forex RMB.

PB (Prime Brokerages) Inter Dealer Multi Dealer Trading Single Dealer Trading HFT (High Frequency Trading) Market Makers Liquidity Providers Retail Aggregators Retail FX Systems Algorithmic Trading FX ECNs (Electronic Communication Networks) e-Trading Hedge Funds Institutional Clients Non Bank Liquidity Providers FXPB (Foreign Exchange Prime Brokerage)

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TheForeign Exchange andInterest Rate Derivatives Markets:Turnover in the United States, April 2016.

The foreign exchange and over-the-counter interest rate derivatives market in the United Kingdom.

Quarterly Bulletin 2016 Q4.

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Global Banking & Finance Review Awards – 2015.

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Citi sells its electronic FX platform.

Nasdaq poised to launch FX trading platform: top executive.

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Trends in Foreign Exchange Markets and the Challenges Ahead.

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2016 – Entering the Age of the “Non-Bank”

The New Wall Street: Even Big Banks Want Help Navigating Markets.

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High Frequency Traders Elbow Their Way Into the Currency Markets.

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Exclusive: U. S. investigates market-making operations of Citadel, KCG.

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