Archive for the 'Governance' Category

Portfolio Stress Testing

Portfolio stress testing is a means of identifying unusual circumstances that could lead to larger than expected losses. It frequently takes the form of scenario analysis or a simulation of historical or hypothetical events.

In a scenario analysis, stylized scenarios ranging from modest to extreme outcomes are modeled individually. For example, scenarios could include a 10-basis point interest rate move in either direction, a 100-basis point move in either direction, and a steepening or flattening of the yield curve. By using standard measures such as these, scenario analysis can facilitate risk comparisons across assets. However, it does not account for correlations between risk exposures – for example, the effect of both a 100-basis point move in interest rates and a steepening yield curve would not be known.

Simulation of hypothetical or actual historical events is used to see how the entire portfolio would perform when subjected to a given set of extreme conditions. It is particularly useful when extreme breaks (price gaps) are considered more likely that the model being used assumes.

Posted on 29th October 2008
Under: Governance, Portfolio Management, Risk Management | No Comments »

Extensions and Supplements to Value at Risk (VaR)

The risk management concept of Value at Risk (VaR) has met with wide acceptance and has spawned a number of extensions and supplements to the original concept. These include cash flow at risk, earnings at risk and tail value at risk.

Cash flow at risk and earnings at risk measure the risk to either cash flow or earnings (rather than market value) for a given risk factor. It can be useful when assessing assets that generate cash flow or earnings but are difficult to value. It can also be used as a sensitivity test for valuation models.

Tail value at risk adjusts VaR to not only express the minimum loss but also the expected loss when extreme outcomes occur. It is expressed as VaR plus the expected loss in excess of VaR. For example, the tail value at risk for a 5% VaR would be the average of the worst 5% of outcomes.

Posted on 29th September 2008
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The Monte Carlo Method for Estimating Value at Risk (VaR)

Using the Monte Carlo method to estimate Value at Risk (VaR) produces a set of random outcomes reflecting the effects of particular sets of risks. Each set of outcomes is based on a probability distribution for each variable of interest. The distributions for each variable can be normal or non-normal.

Monte Carlo simulations are frequently the only method that provides a practical means to generate necessary risk management information. However, it can become quite a hog of computer resources for large portfolios.

Posted on 29th July 2008
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The Historical Method for Estimating Value at Risk (VaR)

One way to estimate VaR is to use the historical method, which graphs the actual daily returns over a user-specified past period into a histogram. For a two-year observation period (500 trading days) the 1% VaR would be the loss on the fifth-worst day, and the 5% VaR would be the loss on the 25th-worst day.

The results reflect past results, not necessarily those that will be encountered in the future. It is also important to adjust for a moving investment horizon. For example, calculating the VaR for bonds expiring in 2020 from historical results of the prior year would be best done using bonds expiring in 2019.

An advantage of the historical method is that it is non-parametric, which means it does not require assumptions for probability distribution. The disadvantage is that the past may have very different risk characteristics from the future.

Posted on 29th June 2008
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Portfolio Monitoring

Investment managers often have a fiduciary duty to their clients, which means their investment actions must consider the portfolio’s appropriateness in terms of:

  1. the needs and circumstances of the client
  2. the basic characteristics of an investment
  3. the basic characteristics of the overall portfolio

Since each of these factors can change over time, fiduciary duty requires actively monitoring each using a systematic process.

Posted on 4th June 2008
Under: Active Management, Asset Allocation, Ethics, FInancial Planning, Governance, Institutional Investing, Investment Returns, Portfolio Management | No Comments »

The Analytical (Variance-Covariance) Method for Estimating Value at Risk (VaR)

One way to estimate VaR is the analytical method, also called the variance-covariance method.

This method assumes a normal distribution of portfolio returns, which requires estimating the expected return and standard deviation of returns for each asset. As the number of securities in a portfolio increases, these calculations can become unwieldy. As a result, a simplifying assumption of zero expected return is sometimes made. This assumption has little effect on the outcome for short-term (daily) VaR calculations but is inappropriate for longer-term measures of VaR.

The advantage of this method is its simplicity. The disadvantage is that the assumption of a normal return distribution can be unrealistic.

Posted on 29th May 2008
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“Best Execution”

Part of the responsibility of any investment manager is to seek the best possible execution for clients. Best execution is the trading strategy that maximizes the value of the client’s portfolio, subject to the investor’s objectives and constraints.

Some characteristics of best execution include:

  • A tie to the investment decision (obtaining the right price or capitalizing on the information)
  • Inability to know what the best execution will be prior to the actual execution, but an ability to measure and analyze the execution afterward
  • A component of complex practices and relationships that are undergoing continuous refinement

To help achieve best execution, firms should establish processes around maximizing the asset value of client portfolios, and establish guidelines for measuring and managing execution. The compliance with these procedures should be documented and disclosed to clients.

Firms should also disclose general information about their trading techniques, venues and agents and also any potential conflicts of interest that may result.

Posted on 4th May 2008
Under: Active Management, Governance, Institutional Investing, Investing in Stocks, Passive Management, Portfolio Management, Risk Management, Trading Execution | No Comments »

Value at Risk (VaR)

Value at Risk (VaR) has come to be regarded as the premier risk management technique for the financial industry. It measures the probability-based measure of potential loss that can be measured for specific transactions, business units or the total enterprise.

VaR estimates the loss in money terms that could be exceeded (i.e. it represents the minimum loss) at a given level of probability. For example, a $5 million one-day VaR at 5% indicates a 5% chance that losses could exceed $5 million on a given day.

All else equal, a higher loss has a lower probability of occurrence. Likewise, reducing the probability level from 5% to 1% (the two most common levels in use) would result in a higher VaR at the lower probability level.

Posted on 29th April 2008
Under: Asset Allocation, Governance, Portfolio Management, Risk Management | No Comments »

Identifying Nonfinancial Risk Exposures

Portfolios and firms face a number of non-financial risks that must be identified, measured and monitored. These include:

  • Operational risk – the loss caused by failures in systems and procedures, or from external events
  • Model risk – incorrect or misspecified valuation models
  • Settlement (Herstatt) risk – occurs when one counterparty to a transaction is settling the account, while the other party is declaring bankruptcy
  • Regulatory risks – uncertainty regarding how transactions will be regulated or how regulations may change
  • Legal/contract risk – the potential loss when a contract is not upheld
  • Tax risk – uncertainty surrounding tax laws
  • Accounting risk – uncertainty regarding proper way to record transactions or regarding potential rule changes
  • Sovereign and political risks – regime changes that could affect business relationships, or the potential default of a sovereign borrower

Posted on 29th March 2008
Under: Governance, Portfolio Management, Risk Management | No Comments »

Does Institutional Ownership Improve Corporate Operating Performance?

Institutional investors are increasingly using their voting rights to influence the management teams at companies in which they invest. In the June 2007 Journal of Banking and Finance, Cornett, Marcus, Saunders and Tehranian examine whether such actions actually improve the operating performance of the investee companies.

Using institutional ownership data from 13-F statements and cash flow ROA as a measure of operating performance, the authors find that operating performance is related to the degree of institutional ownership.  (Higher institutional ownership indicates better operating performance.)

Posted on 10th March 2008
Under: Active Management, Corporate Governance, Governance, Institutional Investing, Investing in Stocks, Investment Returns | No Comments »