Diversification cannot eliminate risk because markets tend to move up and down together, but William Sharpe, John Lintner, and Fischer Black developed a method called “beta.” Beta increases risk in areas of a portfolio that cannot be solved by diversification, which in turn increases overall returns. Beta measures an individual stock relative to the market, called systematic risk, in which a high beta value represents higher fluctuations in stock value relative to the market. If the market rises by 10%, a stock with a beta of 2 rises 20%, called aggressive, while a stock with a beta of 0.5 rises only 5%, called defensive. Unsystematic risk is specific to individual stocks, and it is the risk that can be reduced through diversification, meaning all legitimate risk, and thus increased price from risk, is tied to a stock’s beta. The capital-asset pricing model, or CAPM, eliminated the risk premium for unsystematic risk, as diversification should, in a good portfolio, eliminate that risk, leaning on the systematic risk, or beta, as a driving indicator of risk premium. As such, including high-beta stocks in a portfolio increases overall returns while increasing risk.

Studies have shown, however, that beta is not a useful measure of the material returns on various stocks and portfolios because it cannot account for all possible elements involved in the market. This then led to the creation of more inventive ways to manipulate beta into a practical variable in determining investments. Arbitrage Pricing Theory, or APT, tries to include more of the variable involved in determining risk than the traditional beta of CAPM, but Malkiel notes that APT is prone to many of the same gaps as CAPM. The Fama-French method uses beta alongside measurements of size and value of a given company and stock to provide a more accurate risk measurement, but the significance of factors used in Fama-French measurements is debatable. Combinations of different factors involved in risk measurement are used to generate “smart beta” portfolios. Ultimately, measuring risk, like predicting stock values over time, is tenuous at best, presenting information that, while interesting and potentially useful, cannot guarantee any given outcome.

Behavioral finance seeks to quantify the irrational decisions of investors using four factors: “overconfidence, biased judgments, herd mentality, and loss aversion” (227). Overconfidence assumes that an individual’s skill is greater than average, and overconfidence often fuels bad decisions. The principle of hindsight bias, in which the individual rationalizes a decision after the fact, then reinforces further bad decisions. Biased judgments come from an overestimation of an individual’s control over a situation. People tend to forget base rates, or the actual rates of an occurrence, leading them to overestimate the validity of a trend or assume information to be correct despite the odds. Herd behavior reflects the same trends that led to bubbles like the tulip boom and South Sea Company, as investors are more likely to invest in stocks in which others have already invested. Even portfolio managers tend to invest in the same stocks as other portfolios in their area, which can lead to massive losses depending on the timing and relative success or failure of the stocks. Loss aversion is the tendency to make decisions based on minimizing loss, even when gains outweigh losses. Studies found that potential gains needed to be 2.5 times greater than potential losses to get individuals to agree to a gamble. Framing decisions in terms of gains, as well, led to risk aversion, while framing in terms of guaranteed losses led to riskier behavior. Additionally, pride often leads investors to sell early, despite losses from fees and taxes, and hold stocks that are failing to avoid feelings of regret.

These irrationalities can be covered by arbitrage, or the exploitation of differences across or within a market, such as differing prices for the same stock in two markets, but behavioralists argue that arbitrage is never perfect. In fact, arbitrageurs often run greater risks, meet with impediments to arbitrage that prevent corrective action, or succumb to the same psychological trends listed above. Malkiel advises investors to avoid succumbing to herd mentality, avoid trading too frequently, sell poor performing stocks rather than successful ones, avoid buying initial public offerings (IPOs), ignore “hot tips” from friends and relatives, and ignore supposed “foolproof” schemes. In each of these cases, the advice to be gained from behavioralists is to try to avoid falling into the irrational investing patterns they have identified.

“Smart beta,” or factor-based investing, tries to outperform the market using techniques like the Sharpe Ratio, which compares returns and risk, to narrow down a portfolio from the broad index fund with a particular “flavor” or focus, such as small companies or low-volatility stocks. The value “flavor” follows a GARP, or “growth at a reasonable price” (260), policy of buying stocks that are selling at a low earnings multiple and have not yet been discovered by the market. “Growth” and “value” are two categories into which investors can organize potential stock purchases, and many portfolios specialize in either growth or value. Smaller firms tend to have higher returns on investment, but Malkiel notes that smaller firms also present greater risk, making the increased return a compensation for that risk. Momentum can yield high returns over short periods, and some portfolios take an approach of trying to hold the best-performing stocks to ride momentum while shorting stocks that do not perform as well, though Malkiel notes the high risk involved in attempting to track trends. Low volatility, profitability, and quality are also factors used in smart beta calculations. No single factor fund has consistently outperformed broad-based index funds, however, though funds tracking momentum have outperformed the market on occasion. Some funds mix different smart beta factors, but, while many have some years in which they outperform the market, they generally undergo large periods of underperformance.

The premise of risk parity is increasing the risk of low-beta stocks by buying on margin, theoretically outperforming the market by employing sufficient leverage, meaning buying excess stocks using borrowed money. By purchasing bonds in a greater ratio than most portfolios, with most portfolios holding 60/40 stocks to bonds, risk parity funds can outperform standard 60/40 portfolios by matching their risk through leverage. Risk parity techniques do not outperform broad-based index funds, but Malkiel notes that leverage is a critical technique for investors to employ when possible, mentioning that investors with sufficient capital might consider adding a risk parity fund to their portfolio to increase returns through leverage. ESG, or Environmental, Social, and Governance funds claim to invest only in companies that show responsibility and ethics regarding social concerns, such as climate change and diversity. Malkiel notes that various groups assign ESG scores to different companies, and these groups rarely agree. ESG funds do not seem to outperform index funds.