Financial Education

Suppose an analysis finds that semiconductor sales have a strong relationship with semiconductor equipment sales. There are three possible explanations for the relationship:

1. Higher semiconductor sales result in a need for more semiconductor equipment (A predicts B)
2. Having more equipment to make semiconductors results in higher sales (B predicts A)
3. Some other factor (such as economic conditions) results in higher need for both semiconductors and semiconductor equipment (C predicts A and B)

Without investigating and modeling the underlying linkages, using correlations relationships in a prediction model can lead to significant errors.

Equally important, suppose that no correlation is found between semiconductors and semiconductor equipment. They may still have a strong (but nonlinear) relationship that should be considered. Such relationships may be found by using multiple regression techniques.

Call based securities markets attempt to gather all the bids and asks for a security at a specific time, with the intent being to price a trade that will match the quantity demanded with the quantity supplied.

Many markets use a call system to set the opening price for securities. The opening price then reflects all the buy and sell orders placed since the previous close.

Peak and trough progressions are a simple tool used in technical analysis to determine the primary trend and identify reversals in the trend. It is based on the theory that markets progress in waves.

In an uptrend, each successive peak and trough will be at a higher point than the preceding one (higher highs and higher lows). In a downtrend, each peak and trough will be lower (lower highs and lower lows) than the preceding.

When a series of rising or falling peaks and troughs is interrupted, it is a signal that a trend reversal may be taking place. For a true reversal signal in a bull market, both a lower trough and a subsequent lower peak must be identified.

Further, the length of time between peaks and troughs can signal whether a trend is a primary, intermediate, or short-term trend.

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.

Previous studies based on returns-based analysis have found no evidence of market-timing ability by mutual funds. In the December 2007 Journal of Financial Economics, Jiang Yao and Yu conduct a holdings-based analysis of 2,300 equity mutual funds and conclude that mutual fund managers have positive and statistically significant market timing ability for three- and six-month periods.

Mutual fund characteristics associated with positive market timing ability include high industry concentrations, large size, and small-capitalization orientations. The authors also find that stronger market timing results are associated with shifting between industries than by adjusting allocations within an industry.

The information ratio is a generalized form of the Sharpe ratio, with active return in the numerator and active risk in the denominator.

Active return is measured as the difference between the portfolio’s return and that of the benchmark. Active risk is the standard deviation of active return.

The information ratio measures the reward earned by the manager for each unit of risk created by deviating from benchmark holdings.

When mutual funds experience large investor outflows, they must often quickly reduce their holdings to return funds to investors. Such forced liquidation can lead to asset sales at “fire sale” prices. In the November 2007 Journal of Financial Economics, Coval and Stafford show that mutual funds do not allow for the risk of such events, and that such flows are predictable – resulting in an incentive to front run the funds.

Funds in the highest and lowest deciles ranked by performance and prior outflows predictably face large inflows and outflows in subsequent periods. Investors can anticipate such flows by buying or selling the largest fund holdings ahead of the cash flows and reversing the position afterward.

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

Several steps are needed to construct a custom benchmark for a portfolio.

1. Identify prominent aspects of the manager’s investment process
2. Select securities that are consistent with that process
3. Devise a weighting scheme for the benchmark securities, including an appropriate allocation to cash
4. Review the preliminary benchmark and make modifications
5. Rebalance the benchmark portfolio on a predetermined schedule