The Capital Asset Pricing Model: What You Need to Know

Based on two key types of investments, systematic and non-systematic, the Capital Asset Pricing Model (CAPM) model goes beyond diversification to manage risk. Here’s how.

Jan 29, 2022

A modern take on investment theories, and one that may be well suited to managing your crypto assets, is the Capital Asset Pricing Model (CAPM). Based on two key types of investments, systematic and non-systematic, this model goes beyond diversification to manage risk. Read on to find out how.

The Capital Asset Pricing Model

The Capital Asset Pricing Model – Building a Portfolio Beyond Diversification

Building on the intro to modern portfolio theory, the Capital Asset Pricing Model (CAPM) was introduced by Jack Treynor, William Sharpe, and a few others. CAPM splits investment risk into two types: systematic and non-systematic. This theory goes deeper into how diversification can’t always be the answer to risk and market fluctuation.

  • Systematic Risk is the risk that all investments are subjected to, regardless of diversification in a portfolio. For example, recessions, wars, and natural disasters are examples of systematic risk that cannot be avoided by any investor investing in a risky asset.
  • Unsystematic Risk, also known as idiosyncratic or specific risk, refers to any risky individual asset. Typically, these are risks that are isolated to just that asset alone, for example, the risk of a poor earnings report on a stock or the utility of any particular cryptocurrency.

Modern portfolio theory shows that risk can be removed through diversification. However, diversification does not solve the problem of systematic risk. Even if you own every single stock or cryptocurrency, your portfolio will still fluctuate as the market moves up and down.

Subsequently, CAPM describes the relationship between systematic risk and expected return for risky assets, in particular stocks. The formula is as follows:

The Capital Asset Pricing Model

This means that any particular asset’s returns, in the long run, should be a function of its risk (beta), the risk-free rate, and the expected return on the market as a whole. Yes, applying this theory to crypto investing is difficult, but there is one concept we would like you to take away.

The beta metric

Beta is a handy metric that measures the risk of an asset relative to the wider market. Unlike correlation, beta is not bound between -1 and 1. While correlation only measures the relative relationship between two assets, beta measures the sensitivity of this relationship. For example, a token with a beta of 1.5 to bitcoin would be expected to move 15% when bitcoin’s price moves 10%.

Beta can be calculated, like correlation, by using a spreadsheet. The formula for beta is the covariance of two datasets divided by the variance of the underlying market (in the case of cryptocurrencies, we can use some market index or simply bitcoin’s price movements).

Limitations of Modern Portfolio Theory and CAPM

As useful as the concepts of modern portfolio theory (MPT) are, there are some limitations with its use in making everyday investment decisions.

Volatility as a measure of risk? Not so fast, my investor friend

One of the assumptions made in MPT is that volatility is synonymous with risk. Volatility is used widely in portfolio management and assumes that asset price returns follow a normal distribution.

The theory assumes that exceptionally large fluctuations in prices are vanishingly rare. Remember how three standard deviation moves are expected to occur only 0.3% of the time? Well, taking daily bitcoin price movements dating back to 2014, we have observed 37 daily moves greater than three standard deviations in 2162 days, which comes out to 1.7%, almost six times the expected frequency!

In reality, market returns do not follow a normal distribution. Instead, there is something called ‘fat tail’ risk, where extreme price movements occur much more frequently than expected. What this means is that techniques like MPT will routinely underestimate the downside potential of your portfolio. You should keep this in mind when making your investment decisions.

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For this reason, some portfolio managers prefer to use downside volatility as a risk measure instead since they only care about an asset’s volatility when its price is falling. After all, no sane person would complain that an asset whose price only goes up is too volatile! An investment’s Sortino ratio is its returns divided by the volatility of its negative returns, instead of the Sharpe ratio, which uses overall volatility in its denominator.

There are also many other types of risk metrics, such as value-at-risk (VaR), drawdown risk, conditional tail expectation (CTE), among others.

Things move: The instability of asset correlations and beta over time

Another critique of these portfolio management techniques is that they all assume that correlation and beta between assets are predictable in the long run using historical data. However, there is much empirical evidence that suggests otherwise.

Two assets that have historically been uncorrelated can suddenly become correlated due to a confluence of common factors leading both to sell off together. For example, during the financial crisis in 2008, most stocks plummeted together, regardless of sector or country. Investors believing they were holding onto a diversified, uncorrelated portfolio of stocks suffered severe losses despite their efforts at portfolio diversification.

This kind of experience can be applied directly to cryptocurrency trading. During large-scale selloffs in bitcoin or Ethereum, market panic tends to spread to all cryptocurrencies. Even tokens with good utility or fundamentals can decline together with the wider market. For this reason, it makes sense to exercise vigilance when investing in cryptocurrencies and to also invest in other asset classes to diversify your risks.

Where to invest from here

Despite the issues we have described above, it is possible to address some of the critiques of modern portfolio theory, as discussed in a recent article. The solution lies in adjusting the methodology. Many alternative techniques have been developed to make these theories more robust, such as post-modern portfolio theory, the Fama-French model, and many more.

Nevertheless, simply understanding the basic concepts of volatility, diversification, and correlation can add a lot of value to your investment and trading.






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