The Security Market Line (SML) is a visualization of the Capital Asset Pricing Model (CAPM) and shows the theoretical relationship between risk and return between securities and the entire market. The SML is plotted on a graph bound by an x-axis, which represents Beta (volatility above or below the market average), and a y-axis, which represents the rate of return.
Beta is a volatility indicator that measures how many changes in price, and by how much, a security experiences over an amount of time. It describes whether the risk associated with a particular security is above or below the average of the market (or a more specific index), where 1 is a correlation with the market, and numbers above or below describe increased or decreased volatility, respectively.
The slope of the SML is the Market Risk Premium – the expected return on a risk asset, minus the risk-free rate – and is the rate of increased return an investor can hypothetically expect for an amount of increased risk taken, in a particular market environment. To plot the SML, the current risk-free rate (Treasury yield) is plotted as the y-intercept, and the market return (expected or historical) is at a Beta of 1 on the x-axis. It can be used for valuation purposes.
Theoretically, a risk taken above the market average should result in a higher return to compensate the investor for the risk taken, which is why the SML shows a positive relationship (inclining upwards to the right). It is as analogous to the investor receiving a premium from the company (or the market) for accepting the additional risk.
If a security is plotted next to the SML and is above the line, the security can be considered undervalued because it is getting a higher return than other securities with the same amount of risk. Below the line, the security can be considered overvalued. The value being measured here, however, is the risk/return value, and not necessarily the actual price of the security.
Theoretically, in an efficient market, these securities would be priced/valued based on their risk-return ratio, and a deviation from the Security Market Line indicates an inefficiency that can possibly be exploited for profit.
Thirty years ago, the notion of an efficient market was more of a theory than an observable phenomenon, and plenty of inefficiencies in the dissemination of information and the pricing of securities could be identified. But today, computers disseminate information far more quickly than before; coupled with higher numbers of active investors, something close to market efficiency is far more obtainable than ever before. As a result, deviations from the SML are potentially more accurate indicators of opportunities for profitable trades than in the past.
The Capital Asset Pricing Model also includes the Capital Allocation Line and Capital Market Line, each virtually identical to the SML. They deal with the same theories, but have slightly different uses and structures, such as using Standard Deviation instead of Beta and other nuances. The Capital Market Line, for example, is a complex concept that can be boiled down to a calculation meant to give the investor/analyst a range of potential returns for a portfolio, based on the risk free rate and the standard deviation of the portfolio. As such, an investor can alter the capital market line (and expected returns), by altering the relative weights of the risk assets and the risk-free assets in the portfolio.
Regardless of the methodology employed by traders, artificial intelligence technology can further help traders identify and execute advantageous trades. Technical indicators can find inefficiencies or price fluctuations that traders believe will make for successful trades, as well as confirm insights from tools like the SML. These charting tools serve as guidelines for buying and selling opportunities. There are thousands of technical indicators, but the most popular ones are the MACD, Bollinger Bands, Stochastic Oscillators, the Directional Movement Indicator and various patterns of price behavior, such as the Cup-and-Handle pattern, the Head-and-Shoulders pattern, the Pennant pattern, and the Broadening Wedge patterns.
Artificial intelligence tools can help locate these patterns for traders to capitalize on. There are myriad ways to use technical analysis in trading, and which indicator or methodology a trader decides to use usually depends on their experience, skillset, and the quality of the tools (A.I.) available to help them find trade ideas.