Overview of Currency Markets

  • Spot market the market where currencies trade for immediate exchange.

  • Forward market – the market where currencies trade for future delivery.

  • Understanding currency markets requires an understanding of direct and indirect currency quotation.  The example below illustrates the concept.

  • Example: $1.62/£

    • This is a direct quote for the British pound sterling, in terms of US dollars.
    • This is an indirect quote for the US dollar in terms of British pound Sterling.
    • In a direct quotation, the numerator (USD) is considered the domestic currency and the denominator (the pound) is the foreign currency.
    • In this example, the pound is “stronger” than the dollar as it takes more than one dollar to buy a single pound.
    • Markets typically display quotes as direct quotes for the USD against another currency, placing the $ in the denominator (which makes the dollar the foreign currency).
      • Common exceptions to this norm are quotes for the British Pound and Euro, as these two currencies are commonly treated as foreign currency (placed in the denominator) when quoted against the US dollar.
    • Direct and indirect quotes are reciprocals of one another:
      • 1/Indirect Quote = Direct Quote
  • Currency dealers make a profit through the bid-ask spread and the public trader is disadvantaged by this spread.

    • % Spread = ((Ask Price – Bid Price)/Ask Price) * 100
  • Currency spreads become wider (and thus more expensive to trade) when:

  • The political or economic climate of a country becomes uncertain.

  • Trading volume in the currency is low.

  • Forward contracts have more distant expirations (nearer term contracts are more heavily traded).

  • Cross exchange rates can be calculated when an analyst has two spot exchange rates involving three different currencies (this is a good thing to practice).

  • When performing a cross rate calculation and given a bid-ask dealer spread, always choose the quotes that produce the largest dealer spread.

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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.