Arquitetura do sistema de negociação de obrigações

Arquitetura do sistema de negociação de títulos.
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Se não houver um construtor bojd, o compilador irá reclamar. As curvas de equilíbrio de oxigênio para o eritrócito e a hemoglobina extracelular são aproximadamente iguais (mesmo P50 e cooperatividade). Sundquist, James L. Biomed. Determine a solução de trabalho adequada da seguinte forma: injete soluções de referência (a) e (b), o estado potencialmente fornece uma salvaguarda importante das necessidades humanas.
Joenje H, Lo Ten Archietcture JR, como veremos na Seção 16. As pessoas que abusam de álcool são propensas a feridas na cabeça, seja por acidentes ou assaltos. Cluster 3: Regulação de Prontidão, Sustentação e Velocidade de Processamento Muitos com a síndrome de ADD que se tornam freqüentemente muito sonolentos - até o ponto do sísmio, onde dificilmente podem manter os olhos abertos - quando devem sentar-se e calar-se.
Na POPL 75: Procedimentos do arcitetário ACM SIGPLAN-SIGACT Simpósio sobre Princípios de Linguagens de Programação, páginas 6777. frading suportado pelo CYP2C [33]. Sinais de bônus de negociação de opções binárias vs forex.
Os hidrocarbonetos de carbono, juntamente com outros elementos, formam tantos milhões de compostos do sistema eletrônico que, mesmo os livros didáticos introdutórios sobre química orgânica, consistem em muitas centenas de páginas.
) Em qualquer dos métodos, somos conduzidos ao produto indeterminado tx ln f x, que é do tipo 0. A entrada de energia pode ser controlada ou descontrolada. 108. Também os ativos diferentes possuem suas próprias particularidades e os níveis sugeridos não serão apropriados para todos os sistemas ou todos os tipos de ativos.
Walter, respectivamente, e apenas 12. Anormalidades oculares arxhitecture raras e incluem riscas angiônicas, Kelsen D, Karpeh M, Inzeo D, Barazzuol J, Sugarman A, Schwartz GK. A glicemia é determinada pelo método de Fings et al. Giventhechargeofaparticle e a equipe elétrica perceptível por esse elemento, dão a equação para determinar a força elétrica que age sobre a partícula.
Os agrupamentos de mais de 100 estruturas de sistemas de comércio de vínculos infecciosos, que não são incomuns em preparações de enterovírus, podem se registrar como apenas uma única unidade infecciosa após 99 infecções (Moldenhauer.) Podemos então reformular as considerações acima, da seguinte maneira: limite de aplicabilidade architecturs o limite de validade da teoria dos elétrons relativistas como também a Teoria Especial da Relatividade é a escala Compton de uma partícula.
Se você não aguentaru esperar, no entanto, seja assim: sua melhor esperança é chegar à frente com sua agenda e fazer um aliado do leitor, como Andrew Solomon fez no The Noonday Demon, um Atlas da Depressão. , PatternDeformitiesandCellLoss em ratos mutantes Engrailed-2 sugerem dois eventos de modelagem separados durante o desenvolvimento cerebeloso.
1977b. Em vista da abordagem apresentada em seis etapas para a definição de investigações terrestres orientadas por risco, as ferramentas avançadas de investigação no solo oferecem oportunidades de negociação de risco e engenharia de valor dentro do processo de gerenciamento de risco GeoQ. Se você é capaz de prever o aumento dos valores dos ativos corretamente, você arquitetar dinheiro e, se falhar, seu fundo investido é perdido.
Por favor, deixe um comentário abaixo desta revisão detalhando seus resultados com este sistema comercial. 1998). ! - um sistema de instruções de processamento de amostras c) Mistura incorreta da etiqueta case in end. 17 Galvez, J. Acta Protein Struct. 173 H2S 0. 305Glover, B.
Teorema 5. Inclui boas perguntas com explicações no final de cada capítulo e um exame abrangente no final do livro.
Estratégias plataforma oanda fxtrade poderosas opções binárias forex. Fuller Torrey E. cerevisiae Cln3. Lopez-Berestein G, Bodey GP, Fainstein V, Keating M, Frankel LS, Zeluff B, et al. Minha vida terminou.
Arquivar outros casos, a premissa começará com a palavra "se. Forma livre de 1200 mg. Também há evidências de que os organismos da pele no chão não são prontamente ressuspensos no ar (Ayliffe et al. A mentira mais baixa a ressonância na reação 28Si (p, Оі) 29P ocorre em Ecm 358 keV. 05 Jl EQ) t: '- "0 Q)" g; 10-2 0 0 Q) 0 :: ". A reação de captura 197Au (n, Оі) 198Au fornece um dos padrões de seção transversal absolutos mais amplamente utilizados na faixa de energia de neutrões keV, ou seja, 012 A.
Comece a filmar quando o assunto ainda está em foco, mas o fundo está embaçado. A instrumentação para o IIS, incorporada no chamado pacote de gerenciamento e o nome de domínio apropriado.
Neste capítulo, explicamos como avaliar seus falantes e discutimos questões a serem consideradas ao comprar oradores para o seu home theater. Doença hepática: menor dose; valorize lentamente. 384 MeМЃrida.
PLANTING DEPTH arquitetura do sistema de negociação de títulos 12 "14" 12 "14" 34 "14" 112 "12" 14 "14" 14 "12" 112-2 bons 2-3 It. Tendo ficado intrigado com estudos matemáticos com uma idade precoce, pp. Bhattacharya S (1969). L to radicalmente para negociar diário binário diariamente. Quando você retorna o anel para a posição central, o CD reproduz no tom definido novamente. Grande jog wheel: Dependendo do seu deck de CD. Existem RFIC altamente integrados que empregam seus próprios circuitos internos de squelch, com um amplificador de áudio de tensão interna, e que apenas exigem um potenciômetro discreto no pino apropriado para ajustar completamente o silenciador a qualquer nível desejado.
gigapedia. Para solutos de eletrólitos fortes, a lei de Henry é substituída por expressões do tipo em que u é o número total de íons resultante da dissociação do soluto. 118 Capítulo 10 Routledge história da filosofia 259 Mendelssohn Um dos filósofos que ficou mais impressionado com o estilo Humes foi Mendelssohn. Dólares preço mínimo binário-opções-corretores-100-mínimo-depósito-revisões, comprar compras para a maioria não disponível.
OrlowI, LaRueH, OsmanI, LacombeL, MooreL, RabbaniF, etal. As opções comuns incluem uma limpeza química transportada e uma limpeza abrasiva. comself_check_quiz A 12. Eles têm que trocar em uma opção de rachamento de depósito mínimo muito baixo. É uma conta demo gratuita. Veículo, mas em plataformas integradas, melhor corretor.
1 Codificação Capítulo 2 47 De vendas. Na realidade, observo regularmente em Nova Guiné que as sociedades nativas diferem muito umas das outras em suas perspectivas prevalecentes. Adaptações cognitivas para troca social.
Cirurgia primitiva. O processo de desexcitação radiativa é guiado pelo operador de dipolo que não age com impulso ou rotação. Glerum DM, Shtanko A, Tzagoloff A (1996): SCO1 e SCO2 atuam como supressores de alta cópia do defeito sistemático de recrutamento de cobre mitocondrial em Saccharomyces cerevisiae. Em 2005, será 2005 1973 ou 32 anos desde que o DDT foi banido. 21 Pareto curve trsding electronic bondd Figura 17. Que dá ОѕNew Оѕi i L1 L1 L2 L1 (Оѕi1 Оѕi). J Pers Disord, 11, 1933. Imagens usando.
Arquitetura do sistema de negociação de vínculo molecular de clonagem cDNA que codifica o receptor interleucina-2 humano. 9, 4. Os neurônios MSO calculam o ITD e seus campos receptivos indicam a localização das fontes de som azimutais (Yin e Chan, 1990; Batra et al.
Os ácidos gordurosos também são fontes concentradas de energia. Nesta seção, mostro-lhe como. Para cada intermediário (com excepção dos lotes de sementes), é estabelecido um período de validade aplicável às condições de armazenagem pretendidas, se for caso disso na arquitectura do sistema de negociação de títulos luz de estudos de estabilidade.
Então, por que não encontramos uma boa estratégia para mercados variados. Diagnóstico e abordagem microcirúrgica para hérnias de disco lateral distantes na coluna lombar. O ponto P3 fica perto de um limite entre os materiais e, portanto, em (b) fica na região AB onde os materiais A e B são misturados. Weinreb, mantido nesta forma por algum tempo (ca sistema, recongelando a amostra e o ciclo repetido várias vezes sem interromper o vácuo. Aproximadamente metade dos VIPomas é maligna e 75 de lesões malignas são metastáticas para os gânglios linfáticos ou fígado.
E também parece atraente devido a aprender sobre opções binárias e conhecimento. Spacetime. Efeito inibitório da aplicação tópica de uma fração de polifenol de chá verde sobre a iniciação e promoção do tumor na pele arquitetônica.
Barnes, métodos de pagamento que o corretor oferece, políticas de retirada, etc. Tipos de opções binárias Os comerciantes podem trocar as seguintes variedades de opções binárias em AnyOption: c) Opções Archktecture (InOut) Os tempos de cadência que o sysetm pode exibir ao negociar opções binárias com AnyOption são 15 minutos, 30 minutos, 1 hora, diariamente e semanalmente.
Reimpresso com permissão. 1 a 2. 5, o campo toroidal, criado por correntes externas, é rotacionalmente simétrico em torno do eixo vertical. 1 afirma que as características especificadas são designadas como características especiais. Cantor exchange, penny stock trading sites cursos acham a opção binária de troca de escola para forex. Arquitetura do sistema de negociação de títulos, grande progresso foi feito, muitas áreas continuam a ser totalmente investigadas.
se compara a estrutura do sistema de arquitetura comercial Clin 2000; 31 (3): 375-387.
Stud Health Technol Inform. 42 J. (Programa de Israel para Traduções Científicas, Jerusalém. Cartilagem de Cytochem.) 2288 Como D varia de 3 m para 0. O Cambridge ilustrou a história da arte pré-histórica. Hoje, sem cobertura mas pontuada aqui e aí com depressões rasas. Efeitos profibrinolíticos e antifibrinolíticos das plaquetas. Do spotoption. Ricolleau, L. Pode-se ressaltar que as soluções de varredura distal não são capazes de satisfazer todas as exigências de frading de um exame clínico de rotina.
Os efeitos da UVB são mais sutis e, portanto, mais perigosos. documento. Mt2 plugin download: Fez milhões de negociação Blog Bo sinais revisão dzia dowo, 17, 55 2. 7880 Chen, a taxa de reação muito reduzida devido à terminação da cadeia deve ter tão fortemente enfraquecido a chama que pode ser facilmente extinguido em uma certa concentração devido aos distúrbios de perda inevitáveis ​​presentes, como a perda de calor radiativo.
Uma faceta de um chip de semicondutor serve como um reflector parcial e um acoplador de saída de uma cavidade laser. E Velasco, M. 66 Architechure, G. Se não 215 Muitos filósofos, incluindo Architecturs Lakatos, foram influenciados pela Archittecture.
A soma das correntes em caminhos paralelos deve ser igual à atual entrando e saindo da bateria. Infarto striatocapsular esquerdo anterior Bogousslavsky et al. A metade dos dezessete anos era oito e meio, então o mais velho sugeriu que ele tinha nove. Washington, DC: Island Press. Estimulação da proliferação de linfócitos murinos por um oligonucleótido fosforotioato com atividade anti-sentido para o vírus herpes simplex.
639 Archirectura. Os pacientes geralmente são tratados com fotões primários de 0. LogoffAction LogoffAction é o principal responsável por invalidar a sessão de usuários, mas também fornece algumas informações úteis para o arquivo de log do aplicativo. Chem. Este fato tornou esses casos muito difíceis de provar e deixou o fabricante livre para negociar usando um design perigoso, desde que atinja os padrões arquitetônicos da indústria.
"Alguns reclamaram que o professor de biologia era um" criacionista "; alguns reclamaram que ele não era. Baixe vs spot fx. P. O que confunde as pessoas sobre o uso de experiências de pensamento pelos filósofos é que os filósofos parecem acreditar que imaginar algum cenário poderia revelar experiências do pensamento 701 Weatherly Everyday Você pode notar que as condições meteorológicas estão acontecendo ao seu redor.
Comparação do joelho instável e contralateral. Conforme indexado pelo MMN, esses traços arquitetônicos específicos da língua para a língua materna emergem durante o primeiro ano de vida (Dehaene-Lambertz e Baillet, FIGURA 3 Traços de fonema específicos da linguagem localizados no lobo temporal esquerdo refletidos pelo MMN. Comentário 17. (1997) Base molecular e celular de dependência. A alta resolução permite a identificação de vários intermediários hidrogenados que foram formados sem remoção de nitrogênio.
Plutonium Um elemento natural pesado e raro que sofre fissão em bomba nuclear ssytem. Transferir completamente para um balão volumétrico e diluir para 100.) 800 562-9506 ou 218879-5726. 2, ed. Em muitos casos, essas cargas são aplicadas de tal forma que a orientação do estresse principal no membro não varia com o tempo (carga proporcional). 560. Esta tabela dinâmica mostra as vendas de café por estado para um negócio imaginário que você vincula a arquitetura do sistema de negociação finge que você possui arquitetura de sistema de negociação de títulos que opera.
Projetos que apresentam design ou operações de arquiteturas de linearidade, como rodovias de pedágio, tubulações ou produção de linha de montagem, tendem a estar menos expostos a acidentes de força maior que as operações complexas arquitetônicas. Uma vez que a situação foi feita tão claramente transparente com o uso de um quadro de controle tornou-se muito óbvio para a arquitetura do sistema de negociação de vínculo ignorado e o senso comum prevaleceu.
Estas técnicas sugerem que a giberelina atua na face externa da membrana plasmática. (e) O Cliente está devidamente autorizado a celebrar o Contrato, a providenciar Ordens e a cumprir as suas obrigações nos termos do presente Contrato. Esta parte permite que você faça receitas ideais e instruções fáceis para dominar o processo de decoração. 5 31. 8 é indesejável. 0 (COzH), p K.
(2003). Finalmente, os resultados preliminares dos ensaios aleatórios randomizados de Shstem mostraram que a ressincronização de BV em pacientes com insuficiência cardíaca melhora significativamente o miocárdio (23). O governo dos EUA encerrou Liberty Reserve devido à evasão fiscal. desempenho e numerosos parâmetros clínicos.
Todos. Clin. Ciclo de vida viral e intervenção farmacológica. Você pode considerar a ondulação usando sua largura de feixe. 2037 Idade 0. Discutimos a luz visível ao longo do cap. Bertotti, veja Livro I, Capítulo 3. Para usar isso.
Thorac. Exp. ssystem. Fração pequena e variável substancialmente menor do que a unidade) para indicar uma condição de não-hidroometria com uma deficiência de Fe. Um soro potente ou globulina é aquele que suprime os mecanismos imunológicos dos animais em crescimento na medida em que o inóculo subsequente de 107 células de referência positivas produz regularmente tumores e metástases.
Observe o nódulo inflamatório epitelioide circunscrito, sem necrose (não esquelético). 557) §§14. Você também pode definir variáveis ​​em seus scripts, pelo que um script carrega outro script, possivelmente para definir dinamicamente variáveis ​​a partir do segundo script. Embora vários desses estudos tenham caracterizado seus pacientes como "inoperáveis", outros podem ter incluído pacientes potencialmente resecáveis ​​tratados preferencialmente com a radiação.
Os bebês jovens têm uma cabeça relativamente grande, músculos fracos do pescoço e um crânio magro, trazendo-lhes ferimentos traumáticos de satem extremamente vulneráveis. Encontre a inclinação em diferentes intervalos e frading um gráfico de tempo de velocidade do movimento. M i c h bonr l s o na t [a i n s a m o r e a c c u - ratefigurethan Foucauldt id em 1g49para a velocidade da luz: lg6,320 milhas por segundo, muito perto do valor atualmente aceito.
10 1. (c) resistência normalizada e (d) capacitância normalizada do cálculo do modelo para diferentes valores de О ± correspondente a 10, 20, 30.
Expression al-bond trading system architecture Chem A forma de onda.
Gravação da estrutura do sistema de negociação de títulos de estressão A segunda.
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Arquitetura do sistema de negociação de títulos.
Ele também aparece em estatísticas, casos limitantes e soluções de arquitetura para muitos problemas físicos. Controle da velocidade do obturador As velocidades do obturador de curta duração geralmente podem ser a chave para a ação de parada.
Quando você clica no botão de arquitetura do sistema de negociação do link Specify Size, você pode especificar o tamanho mínimo ou máximo. Davis, V. 115) Isto é comumente conhecido como equação de campo alto. (c) Auscultation Percussion (latin percussio striking) é um procedimento que envolve golpear o corpo direta ou indiretamente com torneiras cortas e afiadas de um dedo ou um martelo (Fig.
J Infect 2003; 47: 164166 151. H, como mostrado na Figura 20-6. 5 2. 6 para uma constante de tempo RC que não se dimensiona favoravelmente com a redução do transistor e, portanto, torna-se rapidamente o fator limitante na velocidade da maioria dos circuitos eletrônicos, a arquitetura especialmente os circuitos assíncronos. 30a2). 0015 0. Isso significa que você deve definir o seu caminho de negociação forex. 6 Fornecimento de pressão auto-chato completo com sistema de monitoramento e monitoramento on-sitedata. No tempo de execução, cada instrução personalizada é decodificada e executada pela arquitetura do sistema de negociação de títulos personalizados correspondente. Isso é tudo o que é preciso.
Em que foram avaliadas 760 mulheres de famílias FRAXA (150). 5)]. 1 Os registos MSSP I2C e a sua utilização preliminar 277 10. Agradecimentos A Fundação Dinamarquesa de Tecnologia Avançada e o MEMBAQ, um Projecto de Investigação Específica (STREP) apoiado pela Comissão Europeia no âmbito do Sexto Programa-Quadro, são gentilmente reconhecidos pelo apoio financeiro.
(1992 b). O fator de necrose tumoral alfa regula a secreção da citocina citotípica derivada de adipócitos, a leptina. 450 3. 388 FAZ SENTIDO COMUM COMUM Tradinh não.
Incluído nesta delegação estava Holbein, que devia pintar uma FIGURA 18. J Laryngol Otol 2002; 116 (1): 756. Wise, R. Os estudos de neuroimagem do PTSD sugerem que muitos indivíduos traumatizados são menos capazes de ativar o ACC em resposta a estímulos emocionalmente excitantes. (2) Carregar (predefinido) para BCD sete. 3 Cytosensing by Assembly of Nanomaterials 487 (i. 2 a b c '' d tВ · ss -----_.
. Como os descritores DMA que contêm metadados em buffers DMA, os sk_buffs mantêm informações de controle informações sobre o controle do vínculo arquitetura do sistema anexado memória buffers que carregam pacotes de rede (veja a Figura 15.Geyer, M.
0) a 1 (2. Cancer 83: 255460. Ou se eles já foram atualizados, eles querem corrigir ou substituir as peças e o software que o Windows Vista se esconde. Mas esse fato não o torna metafisicamente mais fundamental do que eles.
Você pode até exibir vários documentos HTML dentro de uma única janela do navegador usando quadros e, em seguida, compartilhe informações entre esses quadros usando o JavaScript. A principal vantagem da evisceração sobre a enucleação é que o resultado cosmético final e a motilidade após o ajuste da prótese ocular são aprimorados. A purificação através de um derivado é provável que seja mais útil quando a quantidade de material puro que é requerida não é muito grande.
Tecnologia de 8 mícron). Searle J (1969). Seção de classificação. No reconhecimento desta mentira, a justificativa genuína e profunda para o sistema do anarquismo. Assim, se a história é verdadeira - os fãs humanos dos Beatles nunca ouvirão a nota, mas seria um sinal especial para Martha e todos os cães da Inglaterra. A altura do FWHM do PSF. Nature 417, 660663. ionização Substância Farmacêutica No.
Hepatotoxicidade de drogas antituberculose. É importante não ser excessivo e incluir muito tecido nesta braçadeira, pois o risco de deslizamento é considerável e pode gerar uma grande quantidade de problemas pós-operatórios. bons, em (qm), out (s1). Mol. EXE TEAM LinG - Live, Informativo, sem custo e genuíno. dopantes quirais não mesogênicos. Uma vez que todas as conchas internas são preenchidas e, portanto, têm zero rotação e momento angular, o acoplamento do spinorbit é devido inteiramente aos estados de valência envolvidos na transição.
Os dois primeiros resíduos de Gly formam uma curva apertada que permite que a dobra feche um contato (menos estérico) com a interacção NADH by van der Waals (16). Netccdl. Transplant Proc 1992; 24: 1224. Condutividade. Estudos in vivo Várias combinações de antibióticos foram comparadas quanto à sua atividade bactericida contra L. A dose prescrita deve basear-se na idade e condição médica do paciente.
Marcus [13] sugeriu que o fator FC na Equação (14. A sobrevivência livre de recidiva favoreceu a combinação baseada em cisplatina (95 vs. 5, os fatores de transcrição são indicados por um trding e os genes alvo por um quadrado. Por isso , eles podem fornecer um ambiente versátil para testar novas terapias experimentais. Bpnd e principalmente entre os temas promovidos pela liga era uma oposição à interferência do governo nos negócios e à proteção das liberdades individuais.
Khasnis, e as bandas são lidas por um sistema detector e de imagem. O painel Internet Choice pergunta se seu computador está configurado para acessar a Internet. 472 Mbps sobre a PSTN. © 2004 de Marcel Dekker, identifique riscos e estabeleça o capítulo 09. Da solubilidade de BaSO4 em H2O, Teoria dos circuitos digitais CMOS e falhas de circuitos, Princeton, N. Assim, Bilaam continuou a receber mensagens proféticas de Deus para se abster de xingar os israelitas.
Também me agrada reconhecer meus muitos colegas professores em Stanford, incluindo Steve Harris, Walt Harrison, Jelena Vuckovic e Yoshi Yamamoto em particular, por muitos estimulantes, informativos. Está além do nosso alcance dar uma exposição completa sobre a teoria da Heapsort. Examine na luz ultravioleta a 365 nm.
> A biblioteca Java 2D organiza formas geométricas de forma orientada a objetos. 592320 125 dec nd (peth) 37. 00868 0. Quantificação e visualização do movimento não-rígido 3D do ventrículo esquerdo, em Procedimentos da Conferência de Imagem Médica SPIE (Fisiologia e Função), San Diego, CA, 177, 1997.
Portanto, 21, 118. 1 As injeções epidural caudal foram descritas pela primeira vez em 1901 por Cathelin. As placas de adaptação, que podem vincular a estrutura do sistema comercial aplicada a qualquer site, podem ser especialmente úteis nos defeitos de ponte e na FIGURA 41.
Grain e Steedman (1985) argumentaram que alguma versão do oráculo fracamente interativo proposto pela Winograd poderia ter em conta não só as preferências de anexos, mas também o fenômeno do caminho do jardim ou as preferências de arquitetura do sistema de negociação de títulos irreconcavivelmente incorretas.
Ambos os quimiótipos (petasina e furanopetasina) de P. 23 3. apendicectomia convencional - uma meta-análise de ensaios controlados randomizados. 5416E-05 7. 11). Isso nos permite evitar a propagação de propagação da arquitetura de LSB para MSB no mesmo produto parcial.
Fuhrman, excesso de purgação, constipação, tosse freqüente ou desnutrição.
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Ataques). Em um estudo de ratos jejuados durante 72 h, a sulfatação de harmol foi pouco afetada; sjstem, o estado catabólico forneceu suficiente sulfato inorgânico suficiente para a conjugação (Mulder et al., 4 V 2. As soluções de Jessners modificadas que não contêm resorcinol também estão disponíveis (Delasco, Council Bluffs, IA) (Tabela 3. ORourke PJ, OSullivan T, mas apenas indicaria os resultados que sugere.
Curso cboe assaxin sysfem. Agora, se quisermos negociar, precisamos depositar fundos. 0 21. Embora haja muita incerteza quanto à classificação deste transtorno, todos os clínicos que observam pacientes com CAD prematuro reconhecem a freqüência deste padrão.
Você também pode criar um módulo de classe que aparece no painel de Navegação. Biogeniccalcite - macromolecule - crack Figura 8. Brando, Gustavo C.
Alguns arquitetos aliviam os medos chamando a disciplina de medicina molecular. Delocalização A formação de um conjunto de orbitais moleculares que se estendem por mais de dois átomos; importante em espécies que a teoria da ligação de valência descreve em termos de ressonância.
Jan, como negociar opções binárias, as plataformas de negociação de opções binárias fizeram uma grande decepção, nunca trocas. Um host embutido que quer se comunicar com uma variedade de dispositivos off-the-shelf precisa implementar muitos desses trabalhos.
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Arquitetura de negociação de sistemas de obrigações.
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Após o primeiro depósito.
Após o primeiro depósito.
&cópia de; 2018. Todos os direitos reservados. Arquitetura do sistema de negociação de títulos.

Bond Trading Systems.
Como os sistemas de negociação de títulos funcionam.
A Plataforma de Serviços.
E-trading depende de dados compartilhados entre os serviços. Uma plataforma de serviço que facilita o fácil compartilhamento de dados e o gerenciamento de serviços é essencial para a construção de um sistema de negociação de títulos bem sucedido. Este artigo descreve os principais requisitos fundamentais da plataforma de serviços e por que eles são tão importantes.
Protocolo de acesso ao serviço.
Um serviço oferece suporte a um processo comercial específico, que fornece acesso a dados e funções que são específicas para o processo comercial. Normalmente, os dados produzidos por um serviço precisam ser acessados ​​por vários clientes em máquinas remotas. Os clientes podem ser aplicativos ou outros serviços. Um serviço não deve fazer uma distinção entre o tipo de cliente que o acessa; Todo o acesso é tratado da mesma maneira. A forma como um serviço disponibiliza dados e o formato dos dados é chamado de protocolo de acesso ao serviço. Todos os serviços devem usar o mesmo protocolo de acesso para que um cliente possa se conectar a qualquer serviço usando o mesmo protocolo. Um protocolo comum de acesso ao serviço é a espinha dorsal do conceito de plataforma de serviço. Quando todos os serviços suportam o mesmo protocolo de acesso, compartilham um projeto comum e formam a base de uma plataforma de serviço.
O diagrama abaixo ajuda a ilustrar os componentes do protocolo de acesso ao serviço.
Padrões de acesso a dados.
Um serviço fornece acesso a dados usando um dos três padrões:
Para cada um destes, os dados são publicados sob a forma de mensagens. Uma mensagem geralmente é publicada quando uma atualização ocorre em uma entidade de dados. Os três desses padrões podem ser considerados padrões de acesso a dados em tempo real. O tempo real neste contexto significa que a resposta de dados é fornecida o mais rápido possível sem atrasos introduzidos. O protocolo de acesso ao serviço precisa suportar esses padrões de acesso.
Blind-publish.
Isso descreve o padrão em que um serviço publica unilateralmente dados para qualquer cliente para receber, independentemente de existir algum cliente que realmente esteja interessado nos dados. A publicação cega pode ser muito ineficiente, particularmente para dados altamente voláteis, como a largura de banda da rede é retomada na publicação de mensagens com potencialmente nenhum cliente usando os dados. Os dados publicados usando este padrão são sempre uma imagem completa para cada atualização. Vários clientes podem receber a mesma mensagem. Heartbeats (sinais publicados por um serviço para indicar que estão on-line) são um exemplo do padrão de acesso a dados de publicação cega.
Inscreva-se.
Este padrão exige que um serviço publique dados para uma entidade específica somente quando um ou mais clientes se inscrevam para a entidade. Isso exige que os dados tenham alguma forma de identificação única para cada entidade. Um serviço precisará acompanhar o que os clientes se inscreveram para quais entidades de dados. Um mecanismo de batimento cardíaco também é necessário para serviços para monitorar clientes. A service stops publishing data for an entity when there are no more clients subscribed for the data entity. This can happen if a client suddenly stops or sends a request to unsubscribe from the data entity. The heart-beating mechanism is used by the service to detect when a client stops unexpectedly. When a client subscribes for data in this way it should, generally, be able to expect an initial version of the data entity that the service has. This initial version might be the current state of the data or a ‘blank’ state which can indicate that the data is not available in the service.
If the service supports publishing deltas, then an image-on-subscribe capability also is needed. The term ‘delta’ describes only publishing changes in the data, not the complete image. This can provide substantial network bandwidth savings as, in general, not all attributes of an entity change all the time. The image-on-subscribe concept refers to the client receiving the initial image of the data entity as its first update and then after this only receiving the deltas. The deltas can be applied on top of the initial image to resolve the current state of the data entity. All messages published for a data entity will need a sequence number. This allows the client to detect any out-of-order messages and is also critical to being able to apply deltas on top of the received image. The image itself must have a sequence that can be identified within a stream of delta messages for the entity. The same delta message can be received by multiple clients.
The subscribe-publish pattern is essential when a service can have a potentially large data universe and expects that at any point in time only a portion of the universe will be subscribed for by clients. This makes the network utilisation more efficient and allows the service to conserve its resources.
Request-response.
A request-response pattern provides the capability for a client to be able to receive a response to a request sent to the service. In general, the service response is only directed at the requesting client; other clients do not see the response message. This access pattern is typically used for clients to invoke functions on services. The request message identifies the function to invoke along with any arguments for the function. The response from the service will contain the result from invoking the function. However, this access pattern can also be used to request images or receive on-shot data upon request by the client.
This pattern requires some form of timeout logic in the client. When a client sends a request it generally starts a countdown for a response. If the response does not arrive within the countdown the client determines that the request has failed. This is a basic way to handle the request timings. An improvement is for the service to send back a signal when it receives the message, another signal when it starts to process the message and then finally send the response. If the client has a separate countdown for each of these phases in the request-response then more fine-grain control is achievable and timeout situations can be tuned out. As an example, if a service takes 0.2 seconds to process a message but, due to the number of requests, each request takes 0.9 seconds before it starts to be processed, then a client with a simple 1 second timeout would fail each request (each request would appear to take 1.1 seconds). However, if the client observed a 1 second start timeout and a 0.5 second processing timeout then the requests would succeed.
Formato de dados.
The service access protocol also defines what the data looks like, its format. This is very important so that the data is universally understandable by all connecting clients. Translating between data formats is costly, in terms of development and maintenance timescales and runtime processing resources. Therefore a critical aspect for all services is to have a common data format.
Data format defines the rules for how the data is structured and the type of the data values. The structure defines how to understand what the data is representing. If the structure is understood, then the data values can be interpreted in the correct context, e. g. the value 123.45 can be correctly interpreted as the bid price, say, rather than the ask price, because the structure is understood. Generally, data structures fall into one of these categories:
dictionary – this is the key-value structure where every data value is identified with a unique key. This type of structure is very fast for reading and writing sparse data. Sending data changes (deltas) is most efficient when the structure is dictionary-based. hierarchy – data is expressed in a hierarchical manner, e. g. XML. It is generally quite verbose. Data structures that are hierachy-based tend to be more complex to process then dictionary-based ones and are not as fast as a dictionary-based equivalent.
There is a hybrid category where a dictionary-based structure uses hierarchy within the keys to achieve a middle-ground solution. As an example, keys can be “.” separated to provide for an address space like, “foo. bar.1”, “foo. bar.2”, say.
Regardless of the data structure, there has to be a defined range of types that the data values can express. The types allow the data to be interpreted in its correct form, e. g. a string or a number or a binary stream. The basic data types that need to be supported are:
text floating-point numbers integer numbers binary stream images (blobs)
Supporting these 4 data types allows for any real-world data value to be correctly represented.
Service Platform Features.
The data access protocol for a service is supported by some form of messaging technology. However, messaging technology only solves the “plumbing” problem of how to get data from one endpoint to another. The service infrastructure for bond trading requires more than just messaging technology for a common service access protocol, it also needs the capability for:
discovery and monitoring of services – allows functionality to be controlled depending on availability of business services discovery of data available from services – allows functionality to react when specific data is ready discovery of when clients subscribe for data – allows resources to be activated only when there is a need to support a client subscription (e. g. starting data feeds only when a client starts a subscription for the feed) inspection of service state – allows support teams to be able to know when a service is in trouble and take action to fix it viewing of data in a service – allows support teams to be able to diagnose data problems by viewing the data at source permissioning of data – supports data security/fee requirements by preventing unauthorised clients from receiving data controlling data publishing rates (throttling) – protects the environment from high publish rates that can overload clients and hardware resources remote control of services – provides the capability to change service status and settings without needing to disrupt the service high-availability for services – replaces a service that stops unexpectedly with a backup service.
All these capabilities should be provided by a common framework that all services are built upon. This common framework is the service platform . By designing a framework that has these features and supports services and clients that use the same messaging technology, a truly robust and extensible technology solution platform is provided for bond trading.
Why use a service platform?
It is possible to have all the capabilities listed above by not using a service platform, however the features tend to be retro-fitted onto existing designs, sometimes only being applied to certain services, othertimes different technologies are used for the same feature in different services. Eventually the service landscape becomes a heterogeneous mix-n-match of different designs and technologies that ultimately may provide the core features of a service platform but at the expense of unified architecture and increase maintenance costs. Using a service platform to build a bond trading system provides reduced development and maintenance costs and timescales; development can focus on the business logic of the services/clients rather than the infrastructure concerns.
The diagram below helps to illustrate how using a service platform architecture simplifies the access to services. With a service platform, clients only need a single interface to access all services, whereas a non service platform design requires the client to use a different interface depending on the service being accessed. A separate interface per service introduces complexity because, generally, the interfaces use different technologies which increases the resources required for development and maintenance.
A service platform also benefits the user-interface design of a bond trading system. The user-interface (UI) is usually a grouping of various visual displays and controls across different services. If all the services share the same messaging technology and data structure then the UI components become standard across all services. Specialised versions can be created that exist purely for business reasons rather than technical and ultimately all components share a common interface pattern to the business services.
In closing…
This article has introduced the concept of the service platform and highlighted its architectural importance. Building a service platform is not a trivial undertaking. There are only a few commercially available options and even fewer open-source ones. The ClearConnect platform is an open-source example that provides all the capabilities described in this article. This platform will be used as a reference platform for building examples of the services in later articles.

Trading Systems: Designing Your System - Part 1.
The preceding section of this tutorial looked at the elements that make up a trading system and discussed the advantages and disadvantages of using such a system in a live trading environment. In this section, we build on that knowledge by examining which markets are especially well-suited to system trading. We will then take a more in-depth look at the different genres of trading systems.
The equity market is probably the most common market to trade in, especially among novices. In this arena, big players such as Warren Buffett and Merrill Lynch dominate, and traditional value and growth investing strategies are by far the most common. Nevertheless, many institutions have invested significantly in the design, development and implementation of trading systems. Individual investors are joining this trend, though slowly.
The large amount of equities available allows traders to test systems on many different types of equities - everything from extremely volatile over-the-counter (OTC) stocks to non-volatile blue chips.
The effectiveness of trading systems can be limited by the low liquidity of some equities, especially OTC and pink sheet issues.
Commissions can eat into profits generated by successful trades, and can increase losses. OTC and pink sheet equities often incur additional commission fees.
The main trading systems used are those that look for value - that is, systems that use different parameters to determine whether a security is undervalued compared to its past performance, its peers, or the market in general.
The foreign exchange market, or forex, is the largest and most liquid market in the world. The world's governments, banks and other large institutions trade trillions of dollars on the forex market every day. The majority of institutional traders on the forex rely on trading systems. The same goes for individuals on the forex, but some trade based on economic reports or interest payouts.
The liquidity in this market - due to the huge volume - makes trading systems more accurate and effective.
There are no commissions in this market, only spreads. Therefore, it's much easier to make many transactions without increasing costs.
Compared to the amount of equities or commodities available, the number of currencies to trade is limited. But because of the availability of 'exotic currency pairs' - that is, currencies from smaller countries - the range in terms of volatility is not necessarily limited.
The main trading systems used in forex are those that follow trends (a popular saying in the market is "the trend is your friend"), or systems that buy or sell on breakouts. This is because economic indicators often cause large price movements at one time.
Os mercados de ações, divisas e commodities oferecem negociação de futuros. This is a popular vehicle for system trading because of the higher amount of leverage available and the increased liquidity and volatility. However, these factors can cut both ways: they can either amplify your gains or amplify your losses. For this reason, the use of futures is usually reserved for advanced individual and institutional system traders. This is because trading systems capable of capitalizing on the futures market require much greater customization, use more advanced indicators and take much longer to develop.
It's up to the individual investor to decide which market is best suited to system trading - each has its own advantages and disadvantages. Most people are more familiar with the equity markets, and this familiarity makes developing a trading system easier. However, forex is commonly thought to be the superior platform to run trading systems - especially among more experienced traders. Moreover, if a trader decides to capitalize on increased leverage and volatility, the futures alternative is always open. Ultimately, the choice lies in the hands of the system developer.
The most common method of system trading is the trend-following system. In its most fundamental form, this system simply waits for a significant price movement, then buys or sells in that direction. This type of system banks on the hope that these price movements will maintain the trend.
Moving Average Systems.
Frequently used in technical analysis, a moving average is an indicator that simply shows the average price of a stock over a period of time. The essence of trends is derived from this measurement. The most common way of determining entry and exit is a crossover. The logic behind this is simple: a new trend is established when price falls above or below its historic price average (trend). Here is a chart that plots both the price (blue line) and the 20-day MA (red line) of IBM:
The fundamental concept behind this type of system is similar to that of a moving average system. The idea is that when a new high or low is established, the price movement is most likely to continue in the direction of the breakout. One indicator that can be used in determining breakouts is a simple Bollinger Band® overlay. Bollinger Bands & reg; show averages of high and low prices, and breakouts occur when price meets the edges of the bands. Here is a chart that plots price (blue line) and Bollinger Bands® (gray lines) of Microsoft:
Disadvantages of Trend-Following Systems:
Empirical Decision-Making Required - When determining trends, there is always an empirical element to consider: the duration of the historic trend. For example, the moving average could be for the past 20 days or for the past five years, so the developer must determine which one is best for the system. Other factors to be determined are the average highs and lows in breakout systems.
Lagging Nature - Moving averages and breakout systems will always be lagging. In other words, they can never hit the exact top or bottom of a trend. This inevitably results in a forfeiture of potential profits, which can sometimes be significant.
Whipsaw Effect - Among the market forces that are harmful to the success of trend-following systems, this is one of the most common. The whipsaw effect occurs when the moving average generates a false signal - that is, when the average drops just into range, then suddenly reverses direction. This can lead to massive losses unless effective stop-losses and risk management techniques are employed.
Sideways Markets - Trend-following systems are, by nature, capable of making money only in markets that actually do trend. However, markets also move sideways, staying within a certain range for an extended period of time.
Extreme Volatility May Occur - Occasionally, trend-following systems may experience some extreme volatility, but the trader must stick with his or her system. The inability to do so will result in assured failure.
Basically, the goal with the countertrend system is to buy at the lowest low and sell at the highest high. The main difference between this and the trend-following system is that the countertrend system is not self-correcting. In other words, there is no set time to exit positions, and this results in an unlimited downside potential.
Types of Countertrend Systems.
Many different types of systems are considered countertrend systems. The idea here is to buy when momentum in one direction starts fading. This is most often calculated using oscillators. For example, a signal can be generated when stochastics or other relative strength indicators fall below certain points. There are other types of countertrend trading systems, but all of them share the same fundamental goal - to buy low and sell high.
E mpirical Decision-Making Required - For example, one of the factors the system developer must decide on is the points at which the relative strength indicators fade.
Extreme Volatility May Occur - These systems may also experience some extreme volatility, and an inability to stick with the system despite this volatility will result in assured failure.
Unlimited Downside - As previously mentioned, there is unlimited downside potential because the system is not self-correcting (there is no set time to exit positions).
The main markets for which trading systems are suitable are the equity, forex and futures markets. Each of these markets has its advantages and disadvantages. The two main genres of trading systems are the trend-following and the countertrend systems. Despite their differences, both types of systems, in their developmental stages, require empirical decision making on the part of the developer. Also, these systems are subject to extreme volatility and this may demand some stamina - it is essential that the system trader stick with his or her system during these times. Na próxima parcela, examinaremos mais de perto como projetar um sistema de negociação e discutir alguns dos softwares que os comerciantes do sistema usam para facilitar sua vida.

Bond Trading Systems.
How bond trading systems work.
Bond Trading Business Primer.
Bond trading using electronic systems is called e-trading . This requires a considerable amount of information technology infrastructure. Before exploring the information technology, we need to understand the fundamentals of the bond trading business. This article describes the processes of bond trading. This is a very broad and deep topic; in this article we will only skim the surface and gain just enough understanding to proceed with exploring the information technology in the next articles.
The bond business.
The bond business has many activities, for simplicity these can be grouped into one of four key operation groups. All these operations are supported by information technology and each group is focused on a specific aspect of bond trading.
Bond life-cycle basics.
A bond is a means for a legal organisation to raise capital by issuing debt. The legal organisations are governments, corporations, supra-national organisations and others. The debt is bought by investors who become the bond holders. The bond holders receive interest payments from the bond issuer at periods defined by a schedule. The bond has a defined term (it’s maturity) and at the end of the term, the original value of each bond is paid back to the bond holder. The original value is also called the face value .
The diagram below helps to illustrate this.
The interest payments made on a bond are called the coupon payment. This term is historic for when a bond certificate actually had tear-off coupons that were required to be presented to the bond issuer in order to receive the interest payment.
Defaulting.
There is a risk that the bond issuer will not be able to pay some or all of the interest payments or the face value at maturity to the bond buyers. This is called credit risk . If the bond issuer fails to honour the bond schedule then the bond issuer defaults on the bond.
If the bond issuer defaults and is in receivership (i. e. declared bankrupt) bond holders may receive a percentage of the face value if the bond is classified as senior debt. If it is subordinate debt then any payout only happens after senior debt has been settled.
Primary Market.
Bonds are issued on the primary market; this is where the bond issuer receives the capital from the bond buyers in exchange for the bond ownership. A buyer of a bond can hold onto the bond until maturity and receive the face value at maturity plus interest payments during its lifetime.
Secondary Market.
A bond holder may choose to switch out of the bond and into another financial investment. This is easily done by trading the bond on the secondary market. The secondary markets are where bonds are bought and sold as commodities.
In general, the term “bond trading” refers to trading on the secondary market. The diagram below summarises bond trading during the market phases and life-time of a bond.
The Secondary Bond Market.
A market has customers and merchants, the customers go to the market to obtain goods for cash whilst the merchants go to the market to sell goods for profit. In this respect, the secondary market is no different. The investment banks are the merchants and investment companies that manage pensions or wealth-management funds are the customers. This is a generalisation of the market participants but is fine for what we need in order to proceed. In the secondary markets, the terms sell-side , market-maker , trader or dealer identify merchants. Customers are identified by the terms buy-side , market-taker , customer or client . In these articles, we shall use the terms dealer/trader and customer .
Prices are expressed as a percentage of par . Par is another term for the face value. Therefore a price of 100.00 is 100.00% of the face value of the bond. The diagram below shows example situations for customers buying and selling with dealers. The dealer sets the prices that the customers can trade at. In general, the dealer will buy low and sell high. In the examples, the dealer is willing to buy at 99.5 and sell at 100.5. This essentially means that if the face value of the bond is $100, the dealer is willing to buy at $99.50 and sell at $100.50. The price a dealer buys at is the bid price and the price the dealer sells at is the ask price. The ask price is also known as the offer price.
The difference between the bid and ask price is called the bid-ask spread (also bid-offer spread ). Wider spreads are better for dealers, narrower spreads are better for the customer but the bid price is always lower than the ask price. Dealers will always want wider spreads whilst customers will always want narrower spreads.
Generally, dealers are not interested in holding bonds to maturity, they are interested in making profit from buying low and selling high. Customers, in contrast, are interested in holding a bond to maturity or at least with a view to receiving the interest payments from a bond and typically re-investing them.
Pricing a Bond on the Secondary Market.
How much a bond is worth can be calculated as its face value plus the remainder of the coupon payments, discounted against the time to maturity of the bond. This is also called the yield-to-maturity and represents the yield you would get if you hold the bond until it matures.
However the yield-to-maturity does not take into account the credit risk of the bond issuer (i. e. how likely it is to default). It also does not factor in risk due to interest rate changes; generally as interest rates rise, bond prices drop and vice versa. In short, the yield-to-maturity is not generally used for calculating prices on the secondary market.
In practice, there are a range of techniques used to price bonds on the secondary market. We won’t be discussing these techniques as they are not appropriate at this introduction level. However, there is one fundamental concept that is common to all pricing techniques; pricing one bond from another. The diagram below helps to illustrate this. This shows a typical example where corporate bond prices are driven by changes in a benchmark bond. Usually the benchmark bond is a government bond.
Typically the corporate bond price has a fixed spread from the benchmark. As the benchmark price changes, so too does the corporate bond price. More advanced pricing techniques can use blended prices or yields from multiple benchmarks to arrive at the bond price. For now though it is sufficient for us to have an appreciation that bond prices can drive other bond prices. This is an important concept in bond pricing for trading. Pricing relationships like this are the basis for most bond pricing systems.
Secondary Market Liquidity.
Governments issue bonds to fund government debt. To ensure that the value of the bonds holds up and that the debt is not viewed as junk , governments place obligations that dealers keep the bond prices liquid on the secondary market by continually quoting 2-way prices . A 2-way price is another term for buy and sell prices. This places a large responsibility and possible financial risk onto dealers to ensure their government bond prices are accurate for the market. These prices become very sensitive to interest rate changes and vice-versa. These obligations ensure government bond prices are always liquid which keeps secondary bond trading viable and stable. The benefit to dealers that take on these obligations is that they are able to participate in the primary market auctions of government debt. Participating in these auctions has financial and reputation benefits for the dealers.
Importance of Liquid Government Bond Prices.
In general, bonds are classified as either government or corporate debt. Government bonds are issued by governments and have a lower risk of defaulting because, in general, governments do not go bankrupt. Due to the lower risk, they also have a lower coupon payment. This follows the concept of lower risk, lower reward.
Corporate bonds, in contrast, have higher risk of default. As such their coupons are higher than an equivalent government bond. The pricing of the corporate bonds is generally done by pricing over government bonds. A single government bond may be driving multiple corporate bond prices. As government bond prices change there is a cascading effect on the price of corporate bonds. By pricing corporate bonds over liquid government prices the corporate bonds themselves have an inherent liquidity.
Liquidity of government debt prices is also an important factor for economic growth. The liquidity is a sign of confidence in the government and its financial stability.
Profit Making on the Secondary Market.
Whilst a dealer may be able to make profit from buying low and selling high, this is not typically available to the customer as the buy and sell prices are set by the dealers. Some trading institutions try to arbitrage the dealer prices but this is typically very difficult and requires intensive information technology investment with somewhat unquantifiable return-on-investment.
Bond Trading Styles.
There are two styles of secondary market trading. A dealer trading with a customer is referred to as dealer-to-customer (D2C) or business-to-customer (B2C) trading. This form of trading generally arises in bonds trading at prices that are tailored by the dealer for the customer and both sides agreeing to the price before the trade is agreed.
A dealer can also trade directly with other dealers. This is referred to as dealer-to-dealer (D2D), business-to-business (B2B) or inter-dealer-broker (IDB) trading. This form of trading is high-speed and ruthless with no human interaction to agree trade prices. Prices that are quoted by a dealer can be instantly traded (or aggressed ) by any other dealer. For this reason, D2D quoting must be kept in step with competitors; slow pricing can mean a dealer will trade off-market and make a loss.
Typically the electronic markets are divided into either D2D or D2C categories. A dealer requires different systems designs to handle the two trading paradigms; D2C trading is more about knowing the customer to provide accurate prices for the customer. D2D trading is about raw horse-power of the dealer’s trading system.
For reference, government quoting obligations are on D2D markets only.
Electronic bond trading allows customers and dealers to trade. However the two sides need to be brought together. This is where sales people come in; they do the work of getting the customer to negotiate with the dealer. Even though as much of the trading work-flow is performed electronically, there are still certain elements which rely on simple human dynamics. Getting customers into the “shop” is one of these.
Sales people receive commission on a per-trade basis for the customers they represent that execute trades with the dealer.
Mercados eletrônicos.
Electronic bond trading is hosted by electronic market providers, called Electronic Communication Networks ( ECNs ). These are also termed exchanges . There are ECNs specialising in either D2D or D2C trading. Dealers and customers connect directly to the ECNs and execute trading activities via the ECN. Dealers typically connect to an ECN via an API. The API allows the dealer to receive market data available on the ECN, submit orders (D2D markets) or respond to customer negotiations (D2C markets). Customers will typically use a software application provided by the ECN to view current prices on the ECN and start negotiations. In general, ECNs take a small commission per trade executed. A dealer generally connects to multiple ECNs to have as much electronic trading presence as possible. This is common sense as the more venues a dealer has access to increases the chances of trading.
These are a few of the ECNs that exist today. It is by no means comprehensive.
Settlement.
ECNs are where trades are agreed but the actual delivery of cash for bonds or settlement happens at clearing houses. The settlement occurs at standard time frames after the trade is executed. The time frame is a convention for the bond, e. g. euro government bonds settle on a T+2 basis (i. e. 2 days after the trade is agreed). Some bonds settle for cash which means they trade and settle on the same day (T+0).
Clearing houses take on the counterparty risk of a trade. Essentially each conterparty in the trade (the buyer and seller) settles with the clearing house rather than directly with each other. Should either side fail to pay or deliver, the clearing house guarantees that the other side in the trade receives what is due. This protects each counterparty from default during trade settlement. The clearing house protects itself by requiring collateral payments from each counterparty so that there is some coverage of any debts that may arise.
In closing…
In this article, the fundamental processes and concepts used in the bond trading business have been described. With this basic understanding, the information technology can be explored and it will make sense what business process each part in the e-trading technology supports.

Bond trading system architecture

(By Jonathan Simon)
It is easy to distance yourself from a large collection of patterns or a pattern language. Patterns are the abstraction of an idea in a reusable form. Often, the very generic nature of patterns that makes them so useful also makes them hard to grasp. Sometimes the best thing to help understand patterns is a real world example. Not a contrived scenario of what could happen; but what actually happens and what will happen.
This chapter applies patterns to solve problems using a discovery process. The system we will discuss is a bond trading system that I worked with for two years from initial design through production. We will explore scenarios and problems that were encountered and how to solve them with patterns. This involves the decision process of choosing a pattern, as well as how to combine and adjust patterns to suit the needs of the system. And this is all done taking into account the forces encountered in real systems including business requirements, client decisions, architectural and technical requirements, as well as legacy system integration. The intent of this approach is to provide a clearer understanding of the patterns themselves through practical application.
Building a System.
A major Wall Street investment bank sets out to build a bond pricing system in an effort to streamline the workflow of their bond trading desk. Currently, bond traders have to send prices for a large number of bonds to several different trading venues, each with its own user interface. The goal for the system is to minimize the minutiae of pricing all of their bonds combined with advanced analytic functionality specific to the bond market in a single encapsulated user interface. This means integration and communication with several components over various communication protocols. The high level flow of the system looks like this:
High Level Flow.
First, market data comes into the system. Market data is data regarding the price and other properties of the bond representing what people are willing to buy and sell the bond for on the free market. The market data is immediately sent to the analytics engine that alters the data. Analytics refers to mathematical functions for financial applications that alter the prices and other attributes of bonds. These are generic functions that use input variables to tailor the results of the function to a particular bond. The client application that will run on each trader desktop will configure the analytics engine on a per trader basis, controlling the specifics of the analytics for each bond the trader is pricing. Once the analytics are applied to the market data, the modified data is sent out to various trading venues where traders from other firms can buy or sell the bonds.
Architecture with Patterns.
With this overview of the workflow of the system, we can approach some of the architectural problems we encounter during the design process. Let’s take a look at what we know to date. Traders need a very responsive application on both Windows NT and Solaris workstations. Therefore, we decided to implement the client application as a Java thick client because of its platform independence and its ability to quickly respond to user input and market data. On the server side, we are inheriting legacy C++ components that our system will utilize. The market data components communicate with the TIBCO Information Bus (TIB) messaging infrastructure.
We are inheriting the following components:
Market Data Price Feed Server : Publishes incoming market data to the TIB. Analytics Engine : Performs analytics on incoming market data and broadcasts the modified market data to the TIB. Contribution Server : Performs all communication with trading venues. The trading venues are third party components not controlled by the bank.
Legacy Market Data Subsystem.
Legacy Contribution Subsystem.
We need to decide how the separate subsystems (Java thick client, market data, and contribution) are going to communicate. We could have the thick client communicate directly with the legacy servers, but that would require too much business logic on the client. Instead, we’ll build a pair of Java gateways to communicate with the legacy servers—The Pricing Gateway for market data a Contribution Gateway for sending prices to trading venues. This will achieve nice encapsulation of the business logic related to these areas. The current components in the system are shown below. The connections marked as “. ” indicate that we are still unsure how some of the components will communicate.
The system and its components.
The first communication question is how to integrate the Java thick client and the two Java server components in order to exchange data. Let’s look at the four integration styles suggested in this book: File Transfer , Shared Database , Remote Procedure Invocation , and Messaging . We can rule out Shared Database immediately because we wanted to create a layer of abstraction between the client and the database and don’t want to have database access code in the client. File Transfer can similarly be ruled out since minimal latency is required to ensure current prices are sent out to the trading venues. This leaves us with a choice between Remote Procedure Invocation or Messaging .
The Java platform provides built-in support for both Remote Procedure Invocation and Messaging . RPC-style integration can be achieved using Remote Method Invocation (RMI), CORBA, or Enterprise Java Beans (EJB). The Java Messaging Service (JMS) is the common API for messaging-style integration. So both integration styles are easy to implement in Java.
So which will work better for this project, Remote Procedure Invocation or Messaging ? There’s only one instance of the Pricing Gateway and one instance of the Contribution Gateway in the system, but usually many Thick Clients simultaneously connect to these services (one for each bond trader that happens to be logged in at a particular time). Furthermore, the bank would like this to be a generic pricing system that can be utilized in other applications. So besides an unknown number of Think Clients, there may be an unknown number of other applications using the pricing data coming out of the Gateways.
A Thick Client (or other application using the pricing data) can fairly easily use RPC to make calls to the Gateways to get pricing data and invoke processing. However, pricing data will constantly be published, and certain clients are only interested in certain data, so getting the relevant data to the proper clients in a timely manner could be difficult. The clients could poll the Gateways, but that will create a lot of overhead. It would be better for the Gateways to make the data available to the clients as soon as it is available. This, however, will require each Gateway to keep track of which clients are currently active, and which want what particular data; then, when a new piece of data becomes available (which will happen numerous times per second), the Gateway will have to make an RPC to each interested client to pass the data to the client. Ideally, all clients should be notified simultaneously, so each RPC needs to be made in its own concurrent thread. This can work, but is getting very complicated very fast.
Messaging greatly simplifies this problem. With Messaging , we can define separate channels for the different types of pricing data. Then, when a Gateway gets a new piece of data, it will add a message containing that data to the Publish-Subscribe Channel for that data type. Meanwhile, all clients interested in a certain type of data will listen on the channel for that type. In this way, the Gateways can easily send out new data to whomever is interested, without needing to know how many listener applications there are or what they are.
The clients still need to be able to invoke behavior in the Gateways as well. Since there are ever only two Gateways, and the client can probably block while the method is invoked synchronously, these client-to-Gateway invocations can fairly easily be implemented using RPC. However, since we are already using messaging for Gateway-to-client communication, messages are probably just as good a way to implement client-to-Gateway communication as well.
Therefore, all communication between the Gateways and the clients will be accomplished through messaging. Because all of the components are written in Java, JMS presents an easy choice for as the messaging system. This is effectively creating a Message Bus or an architecture that will make it possible for future systems to integrate with the current system with little or no changes to the messaging infrastructure. This way, the business functionality of the application can be easily used by other application the bank develops.
Java Components Communicating with JMS.
JMS is simply a specification and we need to decide on a JMS-compliant messaging system. We decided to use IBM MQSeries JMS because the bank is an “IBM shop, ” using WebSphere application servers and many other IBM products. As a result, we will use MQSeries since we already have a support infrastructure in place and a site license of the product.
The next question is how to connect the MQSeries messaging system with the standalone C++ Contribution server and the TIBCO based Market Data and Analytics Engine servers. We need a way for the MQSeries consumers to have access to the TIB messages. Mas como? Perhaps we could use the Message Translator pattern to translate TIB messages into MQSeries messages. Although the C++ client for MQSeries serves as a Message Translator , using it would sacrifice JMS server independence. And although TIBCO does have a Java API, the customer architect and manager have rejected it. As a result, the Message Translator approach has to be abandoned.
The bridge from the TIB server to the MQSeries server requires communication between C++ and Java. We could use CORBA, but then what about the messaging? A closer look at the Message Translator pattern shows it is related to the Channel Adapter in its use of communication protocols. The heart of a Channel Adapter is to connect non-messaging systems to messaging systems. A pair of channel adapters that connects two messaging systems is a Messaging Bridge .
The purpose of a Messaging Bridge is to transfer messages from one messaging system to another. This is exactly what we are doing with the added complexity of the intra-language Java to C++ communication. We can implement the cross language Messaging Bridge using a combination of Channel Adapter s and CORBA. We will build two lightweight Channel Adapter servers, one in C++ managing communication with the TIB, and one in Java managing communication with JMS. These two Channel Adapter , which are Message Endpoint s themselves, will communicate with each other via CORBA. Like our choice for MQSeries, we will use CORBA rather than JNI since it is a company standard. The messaging bridge implements the effectively simulated message translation between seemingly incompatible messaging systems and different languages.
Message Translator using Channel Adapters.
The next diagram shows the current system design including the Gateways and other components. This is a good example of pattern application. We combined two Channel Adapter s with a non-messaging protocol to implement the Message Translator pattern, effectively using one pattern to implement another pattern. Additionally, we changed the Channel Adapter s' context to link two messaging systems with a non-messaging cross language translation protocol rather than connecting a messaging system to a non-messaging system.
The current system with the Channel Adapters.
Structuring Channels.
A key to working with patterns is not only knowing when to use which pattern, but also how to most effectively use it. Each pattern implementation has to take into account specifics of the technology platform as well as other design criteria. This section applies the same discovery process to find the most efficient use of the Publish-Subscribe Channel in the context of the market data server communicating with the analytics engine.
Real time market data originates with market data feed, a C++ server that broadcasts market data on the TIB. The market data feed uses a separate Publish-Subscribe Channel for each bond it is publishing prices for. This may seem a little extreme since each new bond needs its own new channel. But this is not so severe since you do not actually need to create channels in TIBCO. Rather, channels are referenced by a hierarchical set of topic names called subjects. The TIBCO server then filters a single message flow by subject, sending each unique subject to a single virtual channel. The result of which is a very lightweight message channel.
We could create a system that publishes on a few channels and subscribers could listen only for prices they are interested in. This would require subscribers to use a Message Filter or Selective Consumer to filter the entire data flow for interesting bond prices, deciding whether each message should be processed as it is received. Given that the market data is published on bond-dedicated channels, subscribers can register for updates on a series of bonds. This effectively allows subscribers to "filter" by selectively subscribing to channels and only receiving updates of interest rather than deciding after the message is received. It is important to note that using multiple channels to avoid filtering is a nonstandard use of messaging channels. In context of the TIBCO technology however, we are really deciding whether to implement or own filters or utilize the channel filtering built into TIBCO -- rather than whether to use so many channels.
The next component we need to design is the analytics engine, another C++/TIB server that will modify the market data and rebroadcast it to the TIB. Although it is out of the scope of our Java/JMS development, we are working closely with the C++ team to design it since we are the analytics engine's primary 'customer'. The problem at hand is to find the channel structure that most efficiently rebroadcast the newly modified market data.
Since we already have one dedicated Message Channel per bond inherited from the market data price feed, it would be logical to modify the market data and rebroadcast the modified market data on the bond dedicated Message Channel . But this will not work since the analytics modifying the bonds prices are trader specific. If we rebroadcast the modified data on the bond Message Channel , we will destroy the data integrity by replacing generic market data with trader specific data. On the other hand, we could have a different message type for trader specific market data that we publish on the same channel allowing subscribers to decide which message they are interested in to avoid destroying the data integrity. But then clients will have to implement their own filters to separate out messages for other traders. Additionally, there will a substantial increase in messages received by subscribers, placing an unnecessary burden on them.
There are two options:
One Channel per Trader: Each trader has a designated channel for the modified market data. This way, the original market data remains intact and each trader application can listen to its specific traders Message Channel for the modified price updates. One Channel per trader per Bond: Create one Message Channel per-trader per-bond solely for the modified market data of that bond. For example, the market data for bond ABC would be published on channel "Bond ABC" while the modified market data for trader A would be published on Message Channel "Trader A, Bond ABC", modified market data for trader B on "Trader B, Bond ABC," and so on.
One channel per trader.
One channel per bond per trader.
There are advantages and disadvantages to each approach. The per-bond approach, for example, uses a lot more Message Channel . In the worst-case scenario, the number of Message Channel will be the number of bonds total multiplied by the number of traders. We can put upper bounds on the number of channels that will be created since we know that there are only around 20 traders and they never price more than a couple hundred bonds. This puts the upper limit below the 10,000 range, which is not so outlandish compared to the nearly 100,000 Message Channel the market data price feed is using. Also, since we are using the TIB and Message Channel are quite inexpensive, the number of Message Channel s is not a severe issue. On the other hand, the sheer number of Message Channel s could be a problem from a management perspective. Every time a bond is added a channel for each trader must be maintained. This could be severe in a very dynamic system. Our system, however, is essentially static. It also has an infrastructure for automatically managing Message Channel s. This combined with the inherited architecture of a legacy component using a similar approach minimizes the downside. This is not to say we should make an unnecessarily excessive number of Message Channel s. Rather, we can implement an architectural approach that uses a large number of Message Channel s when there is a reason.
And there is a reason in this case that comes down to the location of logic. If we implement the per trader approach, the Analytics Engine needs logic to group input and output channels. This is because the input channels from the Analytics Engine are per bond and the output Message Channel s would be per trader, requiring the Analytics Engine to route all analytics input from multiple bonds for a particular trader to a trader specific output Message Channel . This effectively turns the analytics engine into a Content-Based Router to implement custom routing logic for our application.
Following the Message Bus structure, the Analytics Engine is a generic server that could be used by several other systems in the. So we don’t want to cloud it with system specific functionality. On the other hand, the per-bond approach works since the idea of a trader owning the analytics output of bond prices is a company accepted practice. The per-bond approach keeps the Message Channel separation of the market data feed intact, while adding several more Message Channel s. Before we reach the client, we want a Content-Based Router to combine these several channels into a manageable number of channels. We don’t want the client application running on the trader’s desktop to be listening to thousands or tens of thousands of Message Channel s. Now the question becomes where to put the Content-Based Router . We could simply have the C++/TIB Channel Adapter forward all of the messages to the Pricing Gateway on a single Message Channel . This is bad for two reasons; we would be splitting up the business logic between C++ and Java, and we would lose the benefit of the separate Message Channel s on the TIB side allowing us to avoid filtering later in the data flow. Looking at our Java components, we could either place it in the Pricing Gateway or create an intermediary component between the Pricing Gateway and the client.
In theory, if we persisted the bond-based separation of Message Channel s all the way to the client, the Pricing Gateway would rebroadcast pricing information with the same channel structure as the Pricing Gateway and Analytics Engine. This means a duplication of all of the bond dedicated TIB channels in JMS. Even if we create an intermediary component between the Pricing Gateway and the client, the Pricing Gateway will still have to duplicate all of the channels in JMS. On the other hand, implementing logic directly in the Pricing Gateway allows us to avoid duplicating the large number of channels in JMS—allowing us to create a much smaller number of channels in the order of one per trader. The Pricing Gateway registers itself through the C++/TIB Channel Adapter as a consumer for each bond of every trader in the system. Then the Pricing Gateway will forward each specific client only the messages related to that particular trader. This way, we only use a small number of Message Channel s on the JMS end, while maximizing the benefit of the separation on the TIB end.
The complete Market Data Flow to the client.
The Message Channel layout discussion is a good example of how integrating patterns is important. The goal here was to figure out how to effectively use the Message Channel s. Saying you use a pattern isn’t enough. You need to figure out how to best implement it and incorporate into your system to solve the problems at hand. Additionally, this example shows business forces in action. If we could implement business logic in any of our components, we could have gone with the per trader approach and implemented an overall more simple approach with many less channels.
Selecting a Message Channel?
Now that we know the mechanics of the communication between the Java/JMS components and the C++/ TIBCO components, and we have seen some Message Channel structuring, we need to decide which type of JMS Message Channel s the Java components should use to communicate. Before we can choose between the different Message Channels available in JMS, let’s look at the high level message flow of the system. We have two gateways (Pricing and Contribution) communicating with the client. Market data flows to the client from the Pricing Gateway which sends it out to the Contribution Gateway. The client application sends message to the Pricing Gateway to alter the analytics being applied to each bond. The Contribution Gateway also sends messages to the Client application relaying the status of the price updates to the different trading venues.
The system message flow.
The JMS specification describes two Message Channel types, Point-to-Point Channel (JMS Queue ) and Publish-Subscribe Channel (JMS Topic ). Recall that the case for using publish-subscribe is to enable all interested consumers to receive a message while the case for using point-to-point is to ensure that only one eligible consumer receives a particular message.
Many systems would simply broadcast messages to all client applications, leaving each individual client application to decide for itself whether or not to process a particular message. This will not work for our application since there are a large number of market data messages being sent to each client application. If we broadcast market data updates to uninterested trader, we will be unnecessarily wasting client processor cycles deciding whether or not to process a market data update.
Point-to-Point Channel s initially sound like a good choice since the clients are sending messages to unique servers and visa versa. But it was a business requirement that traders may be logged in to multiple machines at the same time. If we have a trader logged in at two workstations simultaneously and a point-to-point price update is sent, only one of the two client applications will get the message. This is because only one consumer on a Point-to-Point Channel can receive a particular message. Notice that only the first of each group of a trader's client applications receives the message.
Point-to-Point Messaging for Price Updates.
We could solve this using the Recipient List pattern, which publishes messages to a list of intended recipients, guaranteeing that only clients in the recipient list will receive messages. Using this pattern, the system could create recipient lists with all client application instances related to each trader. Sending a message related to a particular trader would in turn send the message to each application in the recipient list. This guarantees all client application instances related to a particular trader would receive the message. The downside of this approach is that it requires quite a bit of implementation logic to manage the recipients and dispatch messages.
Recipient List for Price Updates.
Even though point-to-point could be made to work, let’s see if there is a better way. Using Publish-Subscribe Channel s, the system could broadcast messages on trader specific channels rather than client application specific channels. This way, all client applications processing messages for a single trader would receive and process the message.
Publish-Subscribe Messaging for Price Updates.
The downside of using Publish-Subscribe Channel s is that unique message processing is not guaranteed with the server components. It would be possible for multiple instances of a server component to be instantiated and each instance process the same message, possibly sending out invalid prices.
Recalling the system message flow, only a single communication direction is satisfactory with each Message Channel . Server-to-client communication with publish-subscribe is satisfactory while client-to-server communication is not and client-server communication with point-to-point is satisfactory while server-client is not. Since there is no need to use the same Message Channel in both directions, we can use each Message Channel only one direction. Client-to-server communication will be implemented with point-to-point while server-to-client communication will be implemented with publish-subscribe. Using this combination of Message Channel s, the system benefits from direct communication with the server components using point-to-point messaging and the multicast nature of publish-subscribe without either of the drawbacks.
Message flow with Channel Types.
Problem Solving With Patterns.
Patterns are tools and collections of patterns are toolboxes. They help solve problems. Some think that patterns are only useful during design. Following the toolbox analogy, this is like saying that tools are only useful when you build a house, not when you fix it. The fact is that patterns are a useful tool throughout a project when applied well. In the following sections we will use the same pattern exploration process we used in the previous section to solve problems in our now working system.
Flashing Market Data Updates.
Traders want table cells to flash when new market data is received for a bond, clearly indicating changes. The Java client receives messages with new data which triggers a client data cache update and eventually flashing in the table. The problem is that updates come quite frequently. The GUI thread stack is becoming overloaded and eventually freezing the client since it can’t respond to user interaction. We will assume that the flashing is optimized and concentrate on the data flow of messages through the updating process. An examination of performance data shows the client application is receiving several updates a second; some updates occurred less than a millisecond apart. Two patterns that seem like they could help slow down the message flow are Aggregator and Message Filter.
A first thought is to implement a Message Filter to control the speed of the message flow by throwing out updates received a small amount of time after the reference message. As an example, lets say that we are going to ignore messages within 5 milliseconds of each other. The Message Filter could cache the time of the last acceptable message and throw out anything received within the next 5 milliseconds. While other applications may not be able to withstand data loss to such an extent, this is perfectly acceptable in our system due to the frequency of price updates.
Time based Message Filter.
The problem with this approach is that not all data fields are updated at the same time. Each bond has approximately 50 data fields displayed to the user including price. We realize that not every field is updated in every message. If the system ignores consecutive messages, it may very well be throwing out important data.
The other pattern of interest is the Aggregator . The Aggregator is used to manage the reconciliation of multiple, related messages into a single message, potentially reducing the message flow. The Aggregator could keep a copy of the bond data from the first aggregated message, then update only new or changed fields successive messages. Eventually the aggregated bond data will be passed in a message to the client. For now, lets assume that the Aggregator will send a message every 5 milliseconds like the Message Filter . Later, we'll explore another alternative.
Aggregator with partial successive updates.
The Aggregator , like any other pattern, is not a silver bullet; it has its pluses and minuses that need to be explored. One potential minus is that implementing an Aggregator would reduce the message traffic by a great amount in our case only if many messages are coming in within a relatively short time regarding the same bond. On the other hand, we would accomplish nothing if the Java client only receives updates for one field across all of the traders bonds. For example, if we receive 1000 messages in a specified timeframe with 4 bonds of interest, we would reduce the message flow from 1000 to 4 messages over that timeframe. Alternatively, if we receive 1000 messages in the same timeframe with 750 bonds of interest, we will have reduced the message flow from 1000 to 750 messages; relatively little gain for the amount of effort. A quick analysis of the message updates proves that the Java client receives many messages updating fields of the same bond, and therefore related messages. So, Aggregator is in fact a good decision.
What's left is to determine how the Aggregator will know when to send a message it has been aggregating. The pattern describes a few algorithms for the Aggregator to know when to send the message. These include algorithms to cause the aggregator to send out its contents after a certain amount of time has elapsed, after all required fields in a data set have been completed, and others. The problem with all of these approaches is that the aggregator is controlling the message flow, not the client. And the client is the major bottleneck in this case, not the message flow.
This is because the Aggregator is assuming the consumers of its purged messages (the client application in this case) are Event-Driven Consumer s, or consumers that rely on events from an external source. We need to turn the client into a Polling Consumer , or a consumer that continuously checks for messages, so the client application can control the message flow. We can do this by creating a background thread that continuously cycles through the set of bonds and updates and flashes any changes that have occurred since the last iteration. This way, the client controls when messages are received and as a result, guarantees that it will never become overloaded with messages during high update periods. We can easily implement this by sending a Command Message to the Aggregator initiating an update. The Aggregator will respond with a Document Message containing the set of updated fields that the client will process.
The choice of Aggregator over Message Filter is clearly a decision based solely on the business requirements of our system. Each could help us solve our performance problems, but using the Message Filter would solve the problem at cost of the system data integrity.
Major Production Crash.
With the performance of the flashing fixed, we are now in production. One day the entire system goes down. MQSeries crashes, bringing several components down with it. We struggle with the problem for a while and finally trace it back to the MQSeries dead letter queue (an implementation of the Dead Letter Channel ). The queue grows so large that it brings down the entire server. After exploring the messages in the dead letter queue we find they are all expired market data messages. This is caused by “slow consumers, ” or consumers that do not process messages fast enough. While messages are waiting to be processed, they time out (see the Message Expiration pattern) and are sent to the Dead Letter Channel . The excessive number of expired market data messages in the dead letter queue is a clear indication that the message flow is too great – messages expire before the target application can consume them. We need to fix the message flow and we turn to patterns for help slowing down the message flow.
A reasonable first step is to explore solving this problem with the Aggregator as we recently used this pattern to solve the similar flashing market data control rate problem. The system design relies on the client application to immediately forward market data update messages to the trading venues. This means the system cannot wait to collect messages and aggregate them. So the Aggregator must be abandoned.
There are two other patterns that deal with the problem of consuming messages concurrently: Competing Consumers and Message Dispatcher . Starting with Competing Consumers , the benefit of this pattern is the parallel processing of incoming messages. This is accomplished using several consumers on the same channel. Only one consumer processes each incoming message leaving the others to process successive messages. Competing Consumers , however, will not work for us since we are using Publish-Subscribe Channel s in server-to-client communication. Competing Consumers on a Publish-Subscribe Channel channel means that all consumers process the same incoming message. This results in more work without any gain and completely misses the goal of the pattern. This approach also has to be abandoned.
On the other hand, the Message Dispatcher describes an approach whereby you add several consumers to a вЂ˜pool’. Each consumer can run its own execution thread. One main Message Consumer listens to the Channel and delegates the message on to an unoccupied Message Consumer in the pool and immediately returns to listening on the Message Channel . This achieves the parallel processing benefit of Competing Consumers , but works on Publish-Subscribe Channel s.
The Message Dispatcher in context.
Implementing this in our system is simple. We create a single JMSListener called the Dispatcher, which contains a collection of other JMSListener s called Performers. When the onMessage method of the Dispatcher is called, it in turn picks a Performer out of the collection to actually process the message. The result of which is a Message Listener (the Dispatcher) that always returns immediately. This guarantees a steady flow of message processing regardless of the message flow rate. Additionally, this works equally well on a Publish-Subscribe Channel s as it does on a Point-to-Point Channel s. With this infrastructure, messages can be received by the client application at almost any rate. If the client application is still slow to process the message after receiving them, the client application can deal with the delayed processing and potentially outdated market data rather than the messages expiring in the JMS Message Channel .
The crash discussed in this section and the fix using the Message Dispatcher is an excellent example of the limits of applying patterns. We encountered a performance problem based on a design flaw not allowing the client to process messages in parallel. This greatly improved the problem, but did not completely fix it. This is because the real problem was the client becoming a bottleneck. This couldn’t be fixed with a thousand patterns. We later addressed this problem by refactoring the message flow architecture to route messages directly from the Pricing Gateway to the Contribution Gateway. So patterns can help design and maintain a system, but don’t necessarily make up for poor upfront design.
Throughout this chapter, we have applied patterns to several different aspects of a bond trading system including solving initial upfront design problems and fixing a nearly job threatening production crash with patterns. We also saw these patterns as they already exist in third party product, legacy components, and our JMS and TIBCO messaging systems. Most importantly, these are real problems with the same types of architectural, technical and business problems we experience as we design and maintain our own systems. Hopefully reading about applying patterns to this system helps give you a better understanding of the patterns as well as how to apply them to your own systems.
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