Financial Education

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.

A value weighted security index is calculated by summing the market capitalization of each stock in the index. A derivation of a value weighted index is the float weighted index, which uses only the freely trading shares to calculate market capitalization. Today, most capitalization weighted indexes are actually float-weighted.

A major advantage of value weighted indexes is that they automatically adjust for corporate actions such as stock splits. The decline in value per share following a split is exactly offset by the increase in the total shares outstanding. Stocks with higher market capitalization receive relatively more weight in the index.

The efficient market hypothesis implies that, on average, active managers will not be able to outperform the overall market on a risk-adjusted basis, after fees. The implication of this is that, unless the manager has access to superior research analysts, portfolios should be managed passively. Passive management should result in lower fees for the same average performance.

Index funds are designed to passively mirror the performance of a given index, thus providing passive management.

The weak form of the efficient market hypothesis assumes that current stock prices fully reflect all security market information. Security market information includes historical price and volume data, as well as other market-generated information such as odd-lot trades and short interest.

If the weak-form EMH holds, security market information should have no relationship with future returns. Technical analysis and trading rules should not allow investors to earn excess returns.

Enhanced index strategies attempt to add modest additional return while minimizing tracking risk relative to a benchmark index. In fixed income portfolios, the following factors are the primary contributors to tracking risk.

• Portfolio duration – exposure to parallel shifts in the yield curve
• Key rate duration – exposure to nonparallel shifts in the yield curve
• Sector and quality – the percentage of bonds in the portfolio with given credit ratings, yields or sector exposures
• Sector duration – exposure to changes in sector spreads
• Quality spread duration – exposure to changes in credit spreads
• Sector/coupon/maturity cell weights – a matrix design to put sets of securities into cells that largely replicate various qualities
• Issuer exposure – controls against issuer-specific event risks

In order to function well, a securities market must have the following attributes:

• Information – timely, accurate information regarding volume, prices, bids and offers
• Liquidity – the ability to buy or sell quickly at a known price (near the most recent price). Continuity in prices means that the prices flow rather than gap. This requires depth – a large number of participants willing to buy and sell at prices above and below the current price.
• Low transaction costs, including the cost of reaching the market, brokerage costs, and transfer costs.
• Rapid adjustment of prices to reflect new information, which means the current price reflects all available information.

Fundamental indexing strategies attempt to form benchmarks based on fundamental factors such as book value, dividends or earnings rather than market capitalization. Proponents claim that the fundamentals provide a less biased estimate of a security’s fair value, and thus explain the value premium. Detractors claim that the strategies are simply “value investing in a shiny new wrapper.”

In the January/February 2008 Financial Analysts Journal,  Kaplan argues both fundamental and market-cap weightings provide valuable information, and argues in favor of approaches that combine both.

A price weighted index such as the Dow Jones Industrial Average represents the arithmetic mean of the prices of each security in the index.

The Dow Jones Industrial Average is calculated by adding up the prices of each stock in the index, then dividing the total by a divisor, which is an adjustment to reflect the impact of stock splits, dividends and changes in the index components over time.

In a price weighted index, returns are influenced by the stocks trading at the highest price. A stock trading at $100 will have twice as much impact on the index return as will a stock trading at $50.

Long only active portfolios have exposure to both beta (market return) and alpha (manager skill).  A long-short market neutral portfolio, by contrast, is designed to have no beta exposure.

Some investors prefer to separate alpha and beta by getting beta exposure from passive (indexed) strategies and alpha exposure from long-short market neutral portfolios. This offers several advantages:

• Beta exposure can be obtained cheaply through indexed portfolios.
• Fees paid for alpha can be explicitly specified
• Broadens the opportunities to gain alpha
• Allows mixing of alpha of one style or asset class with beta of another when a particular benchmark may offer few opportunities to generate alpha

Such strategies are often called portable alpha.

At the CFA Intstitute Efficient Market and Behavioral Finance conference in June 2007, Legg Mason’s Michael Mauboussin suggested that both market efficiency and behavioral anomalies could be explained by viewing the market as a complex adaptive system.

Under this model the only conditions required are that investors have diverse opinions, that there is an aggregation mechanism to bring information together, and that there are incentives for being right and penalties for being wrong.

The model explains breakdowns in market efficiency (bubbles and busts) as violations of one or more of the conditions. The most likely violation is diversity of opinion, and the occasional herding tendency of investors. It can also occur on a smaller scale when short-term noise is interpreted incorrectly as signal.