What is Alpha

"Alpha" (the Greek letter 伪) is a term used in investing to describe a strategy's ability to beat the market, or it's "edge."聽Alpha is thus also often referred to as 鈥excess return鈥 or 鈥abnormal rate of return,鈥 which refers to the idea that markets are efficient, and so there is no way to systematically earn returns that exceed the broad market as a whole. Alpha is often used in conjunction with聽beta (the Greek letter 尾) , which measures the broad market's overall volatility聽or聽risk, known as systematic market risk.

Alpha is used in finance as a measure of聽performance, indicating when a strategy, trader, or portfolio manager has managed to beat the market return over some period. Alpha, often considered the聽active return聽on an investment, gauges the performance of an investment against a聽market index聽or benchmark that is considered to represent the聽market鈥檚聽movement as a whole. The聽excess return聽of an investment relative to the聽return聽of a benchmark聽index聽is the investment鈥檚 alpha. Alpha may be positive or negative and is the result of active investing. Beta, on the other hand, can be earned through passive聽index聽investing.

Alpha is commonly used to rank active mutual funds as well as聽all other types of investments. It is often represented as a single number (like +3.0 or -5.0), and this typically refers to a percentage measuring how the聽portfolio聽or fund performed compared to the referenced benchmark index (i.e., 3% better or 5% worse).

Deeper analysis of alpha may also include "Jensen鈥檚 alpha." Jensen鈥檚 alpha takes into consideration the capital asset pricing model (CAPM) market theory and includes a risk-adjusted component in its calculation. Beta (or the beta coefficient) is used in the CAPM, which calculates the expected return of an asset based on its own particular beta and the expected market returns. Alpha and beta are used together by investment managers to calculate, compare, and analyze returns.


Trading With Alpha


Alpha is one of five popular technical聽risk ratios. The others are beta,聽standard deviation,聽R-squared and the聽Sharpe ratio. These are all statistical measurements used in聽modern portfolio theory (MPT). All of these聽indicators聽are intended to help investors determine the聽risk-return聽profile of an investment.

Active portfolio managers seek to generate alpha in diversified聽portfolios, with diversification intended to eliminate聽unsystematic risk. Because alpha represents the performance of a portfolio relative to a benchmark, it is often considered to represent the value that a聽portfolio manager聽adds to or subtracts from a fund's return. In other words, alpha is the聽return on an investment聽that is not a result of general movement in the greater market. As such, an alpha of zero would indicate that the portfolio or fund is tracking perfectly with the benchmark index and that the manager has not added or lost any additional value compared to the broad market.

The concept of alpha became more popular with the advent of smart beta index funds tied to indexes like the聽Standard & Poor's 500 index聽and the "Wilshire 5000 Total Market Index. These funds attempt to enhance the performance of a portfolio that tracks a targeted subset of the market.

Despite the considerable desirability of alpha in a portfolio, many index benchmarks manage to聽 the vast majority of the time. Due in part to a growing lack of faith in traditional financial advising brought about by this trend,聽more and more investors are switching聽to low-cost,聽passive聽online聽advisors聽(often called聽robo-advisors鈥) who exclusively or almost exclusively invest clients鈥櫬燾apital聽into聽index-tracking funds, the rationale being that if they cannot beat the market they may as well join it.

Moreover, because most 鈥渢raditional鈥 financial advisors charge a fee, when one manages a portfolio and nets an alpha of zero, it actually represents a slight聽net聽loss聽for the investor. For example, suppose that Jim, a financial advisor, charges 1% of a portfolio鈥檚 value for his services and that during a 12-month period Jim managed to produce an alpha of 0.75 for the portfolio of one of his clients, Frank. While Jim has indeed helped the performance of Frank鈥檚 portfolio, the fee that Jim charges is in excess of the alpha he has generated, so Frank鈥檚 portfolio has experienced a net loss. For investors, the example highlights the importance of considering fees in conjunction with performance returns and alpha.

The Efficient Market Hypothesis聽(EMH) postulates that market prices incorporate all available information at all times, and so securities are always properly priced (the market is efficient.) Therefore, according to the EMH, there is no way to systematically identify and take advantage of mispricings in the market because they do not exist. If mispricings are identified, they are quickly arbitraged away and so persistent patterns of market anomalies that can be taken advantage of tend to be few and far between. Empirical evidence comparing historical returns of active mutual funds relative to their passive benchmarks indicates that fewer than 10% of all active funds are able to earn a positive alpha over a 10-plus year time period, and this percentage falls once taxes and fees are taken into consideration. In other words, alpha is hard to come by, especially after taxes and fees. Because beta risk can be isolated by diversifying and hedging various risks (which comes聽with various transaction costs), some have proposed that alpha does not really exist, but that it simply represents the compensation for taking some un-hedged risk that hadn't been identified or was overlooked.

Seeking Investment Alpha

The entire investing universe offers a broad range of securities, investment products and advisory options for investors to consider. Different market cycles also have an influence on the alpha of investments across different asset classes. This is why risk-return metrics are important to consider in conjunction with alpha.

This is illustrated in the following two historical examples for a fixed income ETF and an equity ETF:

The iShares Convertible Bond ETF (ICVT) is a fixed income investment with low risk. It tracks a customized index called the Bloomberg Barclays U.S. Convertible Cash Pay Bond > $250MM Index.

ICVT had a relatively low annual standard deviation of 4.72%. Year-to-date, as of November 15, 2017, its return was 13.17%. The Bloomberg Barclays U.S. Aggregate Index had a return of 3.06% over the same period. Therefore, the alpha for ICVT was 10.11% in comparison to the Bloomberg Barclays U.S. Aggregate Index and for a relatively low risk with a standard deviation of 4.72%. However, since the aggregate bond index is not the proper benchmark for ICVT (it should be the Bloomberg Barclay's Convertible index), this alpha may not be as large as initially thought, and in fact may be misattributed since convertible bonds have far riskier profiles than plain vanilla bonds.

WisdomTree U.S. Quality Dividend Growth Fund (DGRW) is an equity investment with higher market risk that seeks to invest in dividend growth equities. Its holdings track a customized index called the WisdomTree U.S. Quality Dividend Growth Index.

It has a three-year annualized standard deviation of 10.58%, higher than ICVT. Its year-to-date return as of November 15, 2017 is 18.24% which is higher than the S&P 500 at 14.67%, so it has an alpha of 3.57% in comparison to the S&P 500. But, again, the S&P 500 may not be the correct benchmark for this ETF, since dividend-paying growth stocks are a very particular subset of the overall stock market, and may not even be inclusive of the 500 most valuable stocks in America.

The above example illustrates the success of two fund managers in generating alpha. Evidence, however, shows that聽active managers鈥聽rates of achieving alpha in funds and portfolios across the investment universe are not always this successful. . Experts attribute this trend to many causes, including:

  • The growing expertise of financial advisors
  • Advancements in聽financial technology聽and software that聽advisors have at their disposal
  • Increasing opportunity for would-be investors to engage in the market due to the growth of the Internet
  • A shrinking proportion of investors taking on risk in their portfolios, and
  • The growing amount of money being invested in pursuit of alpha

Alpha Considerations

While ,聽and as such, receives a lot of attention from investors and advisors alike, there are a couple of important considerations that one should take into account when using alpha.

1. A basic calculation of alpha subtracts the total return of an investment from a comparable benchmark in its asset category. This alpha calculation is primarily only used against a comparable asset category benchmark, as noted in the examples above. Therefore, it does not measure the outperformance of an equity ETF versus a fixed income benchmark. This alpha is also best used when comparing performance of similar asset investments. Thus, the alpha of the equity ETF, DGRW, is not relatively comparable to the alpha of the fixed income ETF, ICVT.

2. Some references to alpha may refer to a more advanced technique. Jensen鈥檚 alpha takes into consideration CAPM theory and risk-adjusted measures by utilizing the risk free rate and beta.

When using a generated alpha calculation it is important to understand the calculations involved. Alpha can be calculated using various different index benchmarks within an asset class. In some cases there might not be a suitable pre-existing index, in which case advisors may use algorithms聽and other models to simulate an index for comparative alpha calculation purposes.

Alpha can also refer to the abnormal rate of return on a聽security聽or portfolio in excess of what would be predicted by an聽equilibrium聽model like聽CAPM. In this instance, a CAPM model might aim to estimate returns for investors at various points along an efficient frontier. The CAPM聽analysis might estimate that a portfolio should earn 10% based on the portfolio鈥檚聽risk profile. If the portfolio actually earns 15%, the portfolio's alpha would be 5.0, or +5% over what was predicted in the聽CAPM聽model.