- Risks Inherent in Trading Activities
- Basic Measures of Market Risk
- Market Risk Limits
- Credit Risk and Counterparty Credit Risk
- Credit Risk Measurement and Management in Trading
- Determination of Presettlement Risk in Different Instruments
- Measuring Potential Future Exposure
- Market Liquidity Risk of Trading Activities
- Unbundling and Dynamically Hedging Risks
- Concentrated Positions and Market Risk
- Market Liquidity Risk Limits
Market Liquidity Risk of Trading Activities
Market liquidity risk is the risk of not being able to close your open positions in a reasonably short time and in sufficient quantities, at a reasonable price. What this means is that in a highly liquid market, you should be able to close out your sufficiently large position quickly without paying a high price. If the market liquidity is low, you will end up paying a huge premium to dispose your positions, that will be the premium due to liquidity risk.
In case of a dealers market, where dealers provide bid-ask spreads for various instruments, the size of the bid-ask spread is an indicator of the liquidity and depth of the market. Generally, the smaller the bid-ask spread, the higher is the liquidity, and vice verse. If markets become illiquid for any reasons such as market disruption, less market makers, or execution of large block transactions, the bid-ask spreads will widen. The market disruptions may be specific to an instrument, such as a change in supply /demand of a financial product, or they could be broad affecting the entire market, such as a stock market crash. Liquidity may also be affected by the presense of large institutional investors. When they exit the market, the liquidity may significantly decline.
Over-the-Counter Instruments
In case of over-the-counter (OTC) markets, which is primarily dealers market, the market liquidity largely depends on the acceptance of credit risk of major market makers. If, for example, a market maker is downgraded, and is therefore not accepted as a counterparty, this will reduce the market liquidity. If the activity is already concentrated to just a few market makers, the impact of elimination of a market maker will be even more severe. Even market makers can have credit risk concerns about their counterparties and they impose restrictions such as credit limits, shortening maturities, requirement of collateral, etc, which further reduces liquidity.
Unlike cash and exchange-traded instruments, the OTC off-balance-sheet instruments do not have a liquid secondary market which makes it difficult to close OTC derivative positions effectively. In general, most OTC instruments are illiquid.
Exchange-traded Instruments
In case of exchange-traded instruments, the clearing house takes the counterparty credit exposures, and is managed using netting and margin arrangements. Both, the margin requirements and netting arrangements of clearinghouses, are designed to reduce the spreading of credit and liquidity issues in case some customers are unable to meet their obligations. If, however, the market prices change significantly (read fall), the clearing house will require more margin money to mitigate its credit risk, which will affect the liquidity. The market participants will have to sell their assets to meet these margin calls. Such action may further increase the liquidity problem.
For many exchange-traded instruments, the notion of liquidity is true as long as we are dealing with small lots. If one tries to execute a large block, it can significantly affect the price. Also, only a few instruments listed on exchanges trade heavily, exhibiting high trading volume, while others trade quite infrequently.
For exchange traded derivatives such as futures and options, the short-dated contracts are more actively traded than the long-term counterparts. In these contracts, the indicator of liquidity is the open interest or the transaction volume.
Data Science in Finance: 9-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 includes PDFs, explanations, instructions, data files, and R code for all examples.
Get the Bundle for $29 (Regular $57)Free Guides - Getting Started with R and Python
Enter your name and email address below and we will email you the guides for R programming and Python.