Financial Education

High quality securities markets are those that supply liquidity, transparency and assured completion.

Liquidity can be defined a number of ways:

• Tightness (low bid/ask spread)
• Depth (limited price impact from large trades)
• Resiliency (rapid adjustments for discrepancies between market price and intrinsic value)

Transparency means access to quotes is quick, easy and inexpensive. It also requires that trade details (size and price) are rapidly disseminated to the public.

Assurity of completion simply means that the counterparties of a trade can be trusted to honor the trade.

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.

For individuals drawing on retirement funds, a 4% withdrawal rate is generally recommended to result in only a small chance of the portfolio running out of money. In the October 2007 Journal of Financial Planning Spitzer, Strieter and Singh simulate thousands of 30-year periods to assess the overall probability of running out of funds.

They find that a standard 50/50 split between stocks and bonds can allow for a 4.4% withdrawal rate with just a 10% chance of depleting funds. Withdrawal rates of up to 6% can be supported with stock allocations of 75% or more.

Portfolio management theory asserts, based on the variance between a given asset and the rest of the portfolio, that as few as 8-20 stocks are sufficient to provide most of the benefits of diversification.

In the November 2007 Financial Review Domian, Louton and Racine challenge this assumption by proposing that long-term investors are likely to be more concerned with shortfall risk (failure to reach a target ending wealth) than with return variance.

Based on the returns of 1,000 stocks and a safety first criterion, they find that at least 164 stocks are necessary to reduce shortfall risk to no more than a 1% chance of underperforming Treasury bonds. Although smaller portfolios can be enhanced by diversifying across industries, the benefit is not as powerful as that provided by simply adding more stocks to the portfolio.

The growth in the hedge fund industry has increased the importance of measuring how hedge funds achieve their returns. Since many funds either explicitly or implicitly use leverage, a useful question is whether hedge funds merely represent an expensive way to use leverage.

In an article published in the Winter 2007 Journal of Wealth Management, Jean Brunel finds that simple leverage does not appear to be the primary determinant of market-neutral or long-short hedge fund returns. Instead, three broad themes emerge:

• Beta leverage is not a strong element of long-short or market neutral returns
• Hedge fund return replication requires dynamic management of leverage
• When hedge fund managers use leverage, they tend to lever their value added skills rather than generic risk exposures

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.

Since reported hedge fund performance is of doubtful significance and risk monitoring is difficult, due diligence takes on special significance when investments in hedge funds are being considered. Some of the things investors must determine include:

1. The structure of the fund
   • Legal entity
   • Identity of manager
   • Domicile
   • Regulatory regime
2. Strategy
   • Style
   • Instruments used
   • Benchmark
   • Niche
   • Current holdings
3. Performance data since inception for all funds under management
4. Risk management
   • What risks are measured
   • How are they measured
   • How are they controlled
   • How is leverage employed
5. Research
   • Has the firm’s research led to changes in strategy
   • Strength of research efforts
   • Research budget
   • Personnel
6. Administration
   • Lawsuits
   • Employee turnover
   • Disaster recovery plans
7. Legal and Regulatory
   • Fee structure
   • Lock-up period
   • Minimum and maximum subscription amounts
   • Drawback provisions
8. References
   • Professional
   • Other investors in the fund

Over time, small capitalization stocks have been shown to outperform large-capitalization stocks. However, timing changes in the relative performance between the two groups could lead to still-better performance. In the Fall 2007 Journal of Portfolio Management, L’Her, Mouakhar and Roberge test three nonparametric techniques derived from artificial intelligence and using 20 macroeconomic and financial variables as inputs.

The three approaches are recursive partitioning, a neural network and a genetic algorithm.

Each of the three techniques outperforms a naive small-minus-big strategy, but the best results are derived from taking the consensus of the three techniques.

One of the major advantages of international diversification is to reduce overall portfolio risk because the returns on international portfolios have low correlations with the returns on domestic portfolios. However, several studies have shown that correlations across markets are higher when the U.S. market is falling than when it is rising – reducing the value of diversification just when it is needed most.

In the September 2007 Review of Financial Studies Hong, Tu and Zhou sort the CRSP database for monthly returns on 10 style portfolios and the value weighted market index. They find that the correlation asymmetry primarily exists within the four smallest size portfolios.

When considering the asymmetries from an investment decision-making perspective, the authors find that investors with disappointment aversion should reduce their exposure to risky assets, and in particular to the smallest-capitalization stocks.

With the growth in the hedge fund industry has come a decline in the value added by hedge fund managers. Given the high fees typically charged by hedge funds, some have questioned whether passive approaches can be constructed that would provide returns similar to those of hedge funds while offering greater transparency and liquidity.

In the Winter 2007 Journal of Wealth Management Harry Kat discusses three general approaches to hedge fund replication:

• Factor Models
• Mechanical Trading Rules
• The author’s FundCreator product

In a factor model, linear regressions determine the market exposures experienced by a hedge fund or hedge fund index. Factors may include stock, bond, commodity and currency returns, or changes in credit spreads and market volatility. These exposures can then be taken via index products or derivative instruments.

In the case of funds that add value by timing short-term changes in market exposure, the investor’s trading behavior can be compared to mechanical trading rules.

The FundCreator product is a risk management tool that allows the investor to target the risk and correlation properties desired in order to maximize diversification potential.