Starting without the benefit of the long-term growth of beta means managing investments against a benchmark of pure risk and requires a highly specialized skill set. Alpha strategies depend on risk for return. Managing risk is a process of defining ranges of outcome before the occurrence (ex-ante). The expected ranges of volatility and ranges of correlation can be accurately measured and used in constructing sound transportable structures. Well-diversified portfolios of multiple hedge fund strategies can be managed to conform to tight ranges of volatility and correlation.

To create a combined alpha and beta portfolio, an investor needs an absolute-return strategy manager with a complete risk management tool kit. The manager must manage the portfolio of widely diversified absolute return strategies in a manner that stabilizes the alpha component. The most reliable source of absolute return is a widely diversified portfolio of hedge fund strategies.

Because the nature of hedge fund returns and their correlations change over time, the alpha manager must actively manage risk allocations and hedge fund selections to reach the following objectives: stable volatility; a low correlation to the index used for beta; and a high Sharpe Ratio.

Risk vectors are a helpful tool in measuring beta and alpha risks and correlations. The length of each line shows the amount of expected volatility. The angle created by the intersection of the two lines shows the correlation of their risks.

If we observe the risk of a portfolio comprising a combination of two perfectly correlated risks that are both long investments, the combined vectors are double the original volatility. Returns are also doubled, in both positive and negative directions. (Vector I)

If the portfolio comprises one long and one short vector of perfectly correlated risk, the result is zero volatility, and zero return. (Vector II)

When we add beta and alpha where the beta is an equity index such as the S&P 500, we can expect the beta volatility to be larger than that of the alpha. When alpha correlation is not properly managed, the vector angles swing against the beta, creating undesirable shifts in alpha + beta portfolio risk as shown by the length of the dotted lines below. (Vector III)

A typical long-short equity alpha strategy contains sufficient beta to show a correlation of 0.5 or higher. Table A shows the results of adding an alpha strategy with 0.5 correlation to the beta (see vector C). If one assumes a beta Sharpe Ratio of 0.3 and an alpha Sharpe of 1, the result is an increase in standard deviation to 18.3% from 16.

We can constrain our alpha and beta portfolio to a maximum risk tolerance of 0.5% increase in volatility over the beta benchmark. Using a portfolio risk budget of 16.5%, the 0.5 correlation drastically reduces the amount of alpha exposure we can employ for the portfolio to 1% from 4%. The return increases to 5.8% from 4.8% as shown in Table B.

The object of portable alpha is to hold the right angle of zero correlation to the beta vector and hold the length of the alpha vector constant at a selected target level as shown in Vector Series IV. When the alpha holds to a perfect zero correlation, mathematics produce desirable results as shown in the S&P 500 example in Vector Series V.

The beta + portable alpha portfolio generates a volatility level only slightly higher (16.5%) than the S&P (16%) and uses maximum diversification benefit to enhance the return and Sharpe Ratio of the portfolio.

As shown in Table C, the S&P example shows the significant increase in return to 8.8% from 4.8% for almost identical risk of the blended portfolio. The benefit of the portable alpha combined portfolio is driven by the improved Sharpe and low correlation of the imported alpha. Return is not only more reliable, but 300 basis points higher than the 0.5 correlation shown in Table B.

The Ferrell Heat Map summarizes the characteristics of alpha that is completely portable. The vertical axis represents the level of volatility and the horizontal scale shows range of volatility from correlation (-1) to 0 to +1 against the beta index.

The beta strategy, in this case the Lehman Bond index, rests at the five-year average of 4.3%. Since the index has a correlation to itself of 1, it stays locked at the far right of the Heat Map.

The alpha strategy should be managed within tight limits of volatility. In the example shown above, the alpha standard deviation varies only from 1.7% to 2.1%. The alpha strategy correlation will necessarily vary over time, but the portfolio should be managed to hold the range of correlation that maintains the powerful diversification value. The example shows an alpha strategy managed to maximize its diversification impact within a narrow (0.2) to 0.2 average range.

The bell curves applied to the "flying saucer" shape of the alpha performance characteristics provide the statistical probability of stable performance. An alpha portfolio that maintains the Heat Map pattern shown will greatly improve beta performance.