Quote-driven Dealers Market

Quote-driven markets are the most commonly used execution systems for markets such as bonds, currencies and commodities. They are referred to as a dealers market because each trade is executed through a dealer. The dealers, working with investment banks, commercial banks, and broker-dealers, provide quotes for different instruments and all customers need to trade through them at the quoted prices. It’s also referred to as a dealer or price-driven market. The following are some of the key points about the quote-driven market.

  • The traders can either accept the prices quoted by the dealers or thy can even negotiate prices with them, either themselves or through their broker or agent.
  • In a pure quote-driven market, all traders must trade only through a dealer however dealers can trade among themselves with the help of inter-dealer brokers.
  • Dealers supply all the liquidity in the market.
  • There are some dealers markets where traders can trade directly with each other. However such a market is not a pure quotes-driven market. For example, Nasdaq Stock Market is a quotes-driven market in which even trades are brokered directly between traders.
  • The traders build relationship with dealers and choose who they want to trade with based on the prices and quality of service offered.
  • Dealers may choose not to execute a trade for a specific client.
  • Many dealers specialize in what kind of clients they service such as retail or institutional.
  • Examples of quotes-driven market include: Nasdaq Stock Market, London Stock Exchange, and eSpeed government bond trading system.
  • In these markets trades are conducted through inhouse digital communication systems, telephone or even though instant messaging.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.