The Capital Asset Pricing Model: What to Know

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

Key Takeaways:

• The Capital Asset Pricing Model (CAPM) was introduced by Jack Treynor and William Sharpe, amongst others, as a way to split market risk into two types: systematic and non-systematic.
• Systematic is the risk that all trader movement is subjected to, regardless of diversification in a portfolio; non-systematic, also known as idiosyncratic or specific risk, refers to any risky individual asset.
• Modern portfolio theory (MPT) shows that risk can be limited through diversification.
• Beta measures the risk of an asset relative to the wider market and is not bound between -1 and 1; it measures the sensitivity between two assets.
• With the critiques of modern portfolio theory, many alternative techniques have been developed, such as post-modern portfolio theory (PMPT) and the Fama French model.

Introduction

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

Building a Portfolio Beyond Diversification

The Capital Asset Pricing Model (CAPM) was introduced by Jack Treynor, William Sharpe, and a few others as a way to split market 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 is the risk that all trader movement is 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 trader participating in a risky asset.
• Non-systematic, 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 (MPT) shows that risk can be limited through diversification. However, diversification does not solve the problem of systematic risk. Even in a hypothetical situation where a person owns every single stock or cryptocurrency, their portfolio would 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:

This means that, in the long run, any particular asset’s returns should be a function of its risk (beta), the risk-free rate, and the expected return on the market as a whole. Applying this theory to crypto trading is difficult, but there is one concept worth taking away: the beta metric.

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 BTC would be expected to move 15% when Bitcoin’s price moves 10%.

Like correlation, beta can be calculated 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 the market index or simply Bitcoin’s price movements).

Limitations of MPT and CAPM

As useful as the concepts of modern portfolio theory are, limitations remain with its use in making everyday crypto market decisions.

Volatility as a Measure of Risk

One of the assumptions made in MPT is that volatility is synonymous with risk. Volatility is used widely in portfolio management; it assumes that asset price returns follow a normal distribution and exceptionally large fluctuations in prices are vanishingly rare. In reality, market returns do not follow a normal distribution.

Instead, there is something called ‘fat tail’ risk, where extreme price movements occur more frequently than expected. This means that techniques like MPT will routinely underestimate the downside potential of a trader’s portfolio. Users should keep this in mind when making trading decisions.

For this reason, some portfolio managers who only care about an asset’s volatility when its price is falling prefer to use downside volatility as a risk measure instead. There are also many other types of risk metrics, such as value-at-risk (VaR), drawdown risk, and conditional tail expectation (CTE), amongst others.

Things Move: The Instability of Asset Correlations and Beta Over Time

Another critique of these portfolio management techniques is 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. Market participants 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 sell-offs of 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 trading digital assets and diversify risks.

Where to Go From Here

Despite the issues described above, it is possible to address some of the critiques of modern portfolio theory. 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 (PMPT) and the Fama French model, amongst others.

Nevertheless, simply understanding the basic concepts of volatility, diversification, and correlation can add a lot of value to any trader’s portfolio.

Due Diligence and Do Your Own Research

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Past performance is not a guarantee or predictor of future performance. The value of crypto assets can increase or decrease, and you could lose all or a substantial amount of your purchase price. When assessing a crypto asset, it’s essential for you to do your research and due diligence to make the best possible judgement, as any purchases shall be your sole responsibility.