Analyzing Market Risks: Three Key Exposures

Corporates analyze market risks (in particular FX risks) in terms of three key exposures: transaction exposures, economic exposures, and translation exposures. Let us discuss each of these exposures.

Transaction Exposures

Transaction exposures arise because of adverse changes in prices. For example, a US based company buying goods from a Japanese company will incur transaction risk because it is exposed to the exchange rate fluctuation (specifically rising yen).

The first step in analyzing the risk of any transaction is to decompose the risk of a transaction into component risks. Even a single transaction can have multiple component risks. For example, a USD-based investment manager with a DEM-denominated convertible bond position has the following component risks:

FX risk: Exposure to DEM depreciating vs. USD @ Interest rate risk: Exposure to rising rates, which make bond prices fall

Spread risk: Exposure to rising credit spreads (that is, deteriorating credit quality of issuer), which makes bond prices fall

Volatility risk: Exposure to falling equity volatility, which reduces the value of the equity conversion option

Equity risk: Exposure to falling stock price of the underlying company

These individual component risks can then be aggregated across a portfolio of instruments to highlight common risk factors.

Examples of Transaction Exposure

  • Purchasing or selling on credit when prices are stated in a foreign currency.
  • Borrowing or lending funds when repayment is to be made in a foreign currency.
  • Being a party to an unperformed foreign exchange forward contract.
  • Acquiring assets or incurring liabilities denominated in a foreign currency.

Economic Exposure

Economic exposure is the risk associated with changes in exchange rates, local regulations or business environment, which could disadvantage the company’s long-term economic model or favor the services or products of a competitor. This type of exposure is very difficult to mitigate.

Economic exposures due to foreign exchange movements are becoming a significant issue as markets are opening up and becoming deregulated. Changes in foreign exchange rates in particular can significantly change the competitive landscape.

For example, in our earlier example the US-based company might find that a rising dollar vs. yen would hurt product sales in Japan and furthermore give Japanese competitors an edge in U.S. markets. Therefore, while the US company has transaction exposure to rising yen, it has an economic exposure to falling yen vs. dollar.

At this point, it must be noted, that even purely domestic companies, with no foreign operations can be affected by fluctuation in exchange rates, due to competition from foreign companies. Similarly, changes in interest rates can also affect the firm because of the cost of the debt.

Translation Exposure

Translation exposure refers to foreign exchange or currency risk. It is the risk of adverse effects in a firm’s reported financial statements, or related financial ratios or borrowing covenant compliance, resulting from changes in the rates at which foreign currency-denominated assets and liabilities are translated into the reporting currency. This applies most commonly to the translation of monetary assets and liabilities and to the consolidation of overseas subsidiaries into group financial statements.

In our example, the US-based company’s Japanese operations are subject to translation exposure to USD.

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Data Science in Finance: 9-Book Bundle

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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.