How to Apply Modern Portfolio Theory (MPT)

Modern portfolio theory (MPT) is a theory in investment and portfolio management that shows how an investor can maximize a portfolio’s expected return with the risks involved. Given a level of expected return, an investor can alter what’s in the portfolio to reduce risk to the lowest possible.

Key Takeaways

• Modern portfolio theory (MPT) details the comparable rates of risk and potential rewards for assets in your portfolio.
• According to MPT, an investor must take on a higher level of risk to achieve greater expected returns; lower risk means a lower level of expected returns.
• Through diversification across a wide variety of security types, a portfolio’s overall risk may be reduced.

Key Assumptions of Modern Portfolio Theory

MPT is founded on the idea that risk and return are directly linked. This means that an investor must take on a higher level of risk to achieve greater expected returns. Another central concept of MPT is that a portfolio’s overall risk may be reduced through diversification across various security types. If an investor is presented with two portfolios offering the same expected return, the rational approach should be choosing the portfolio with the lower risk.

To arrive at its conclusions, MPT must assume the following:

1. Investors try to maximize returns in terms of their unique situation: Considering their individual financial goals, risk tolerance, and investment time frame, investors are out for the highest profit possible.
2. Asset returns are normally distributed: This implies that the returns on investments, such as stocks or bonds, follow a bell curve distribution, and any extreme losses or profits are outliers.
3. Investors are rational and avoid unnecessary risk: People decide based on logical analysis, seeking to minimize risk whenever possible. Moreover, when we can, we avoid impulsive or emotional behaviors.
4. All investors have access to the same information: When trading, we have the same equal ability to gather the relevant financial data and other information we need; there are no unfair advantages.
5. Investors have the same views on expected returns: Given that we can all access the same information, we should, if we use it, form the same views on the potential profits or risks from an investment.
6. Taxes and trading costs are not considered: While these certainly impact our portfolio returns, we can bracket them when considering the risks and benefits of investments against one another.
7. Single investors are not sizable enough to influence market prices: Prices come through actions within a collective market, not manipulation from one participant. That is, the law of supply and demand follows here.
8. Unlimited amounts of capital can be borrowed at the risk-free rate: We can hypothetically borrow as much money as we need for investment purposes at a rate of interest that carries no risk.

Since the arrival of MPT in the mid-20th century, economists and other researchers have devoted plenty of books and articles to debating each of these. Many of these are ideals not found in real-world markets, but we must start somewhere when considering where to invest. Thus, even if some or all these assumptions never hold, MPT can still be useful.

Examples of Applying Modern Portfolio Theory

Our first example of applying MPT concerns determining a portfolio’s expected return. MPT says that the overall expected return of a portfolio is the weighted average of the individual assets’ expected returns. That is, MPT says if you toss in a few risky assets among mostly stable and predictable ones, your risk is going to average out, and you should be okay, given that the higher risk applies only to one part of your portfolio.

Suppose an investor has a two-asset portfolio worth $1 million. Asset X has an expected return of 5%, and Asset Y has an expected return of 10%. The portfolio has $800,000 in Asset X and $200,000 in Asset Y. Based on these figures, we can calculate the expected return of the portfolio overall:

Portfolio expected return = [($800,000 / $1 million) x 5%] + [($200,000 / $1 million) x 10%] = 4% + 2% = 6%

If the investor wants to increase the portfolio’s expected return to 7.5%, the investor needs to shift capital from Asset X (the less risky asset) to Asset Y. In this case, let’s say the weight for each asset in this simple portfolio is 50%:

Expected return of 7.5% = (50% x 5%) + (50% x 10%) = 2.5% + 5% = 7.5%

This same idea applies to risk. One risk metric from MPT, beta, measures a portfolio’s vulnerability to broad market events. A beta of 1.0 means that the portfolio has the same amount of systematic risk as the market. A beta higher than 1.0 means your portfolio is riskier than the market in general. For example, a beta of 1.5 means your portfolio has a 50% greater risk than the market. The higher the beta, the greater the risk compared with the market. Betas lower than 1.0 are less volatile than the market.

With these points in mind, suppose an investor has a $1 million portfolio invested in four assets:

Asset A: Beta of 1, $250,000 invested
Asset B: Beta of 1.6, $250,000 invested
Asset C: Beta of 0.75, $250,000 invested
Asset D: Beta of 0.5, $250,000 invested

Calculating the beta is relatively straightforward. (Online calculators, like Omni Calculator, make this easy.)

Beta = (25% x 1) + (25% x 1.6) + (25% x 0.75) + (25% x 0.5) = 0.96

The 0.96 beta is very close to 1.0, which means the portfolio has as much systematic risk as the market in general.

Suppose the investor wants to take on more risk, hoping to achieve more returns, and decides a beta of 1.2 is ideal. MPT holds that the desired beta can be achieved by adjusting the weights of these assets in the portfolio. There are many ways to get to that beta (moving capital among the various parts of the portfolio in different ratios), but here is one way to get to a beta of 1.2:

Shift 5% away from Asset A and 10% away from Asset C and Asset D. Invest this capital in Asset B:

New beta = (20% x 1) + (50% x 1.6) + (15% x 0.75) + (15% x 0.5) = 1.19

The desired beta is almost perfectly achieved with a few portfolio changes. This is a key insight from MPT.

The Efficient Frontier

The efficient frontier is a graphical depiction of the best possible investment portfolios—those that offer the highest returns for a given level of risk. The returns you get from your portfolio depend on the mix of different investments (like stocks, bonds, etc.) it contains. The risk here is essentially measured by how much the security price tends to go up and down, which is mathematically discussed by its standard deviation. A higher standard deviation means the security price is more unpredictable, making it riskier.

When you combine different investments in a portfolio, you are looking for a mix that gives you the best possible return for the worry you’ll have about losing your money. The efficient frontier helps identify that sweet spot, where you take on no more stress for yourself or risk for your portfolio than needed to get the returns you want. After all, you don’t want to be kept up at night if your potential returns are as good as buying U.S. Treasurys. This also works the other way: you name how much risk you can take, and MPT will tell you your optimum expected returns.

Most importantly, because assets have different risks and for different reasons (bonds tend to go up, for example, when stocks are down), you can actually have a lower level of risk for your portfolio than for each asset individually. Thus, MPT allows investors to choose a portfolio from the efficient frontier based on their risk tolerance. In addition, the efficient frontier helps with asset allocation as well, guiding investors in deciding how to allocate their investments among various asset classes to achieve the optimal balance for them between risk and return.

The efficient frontier can also be used as a benchmark to evaluate the performance of your portfolio. If it’s below the efficient frontier, you can try to increase returns for the same level of risk or reduce your risk for the same level of return.

The Advantages and Disadvantages of Modern Portfolio Theory

Pros

• Risk-return trade-off

• Diversification

• Quantitative approach

• Efficient frontier

• Asset allocation

Cons

• Normal distribution assumption

• Historical data dependency

• Static model

• Rational investor assumptions

• Single-period framework

• Underestimates extreme events

MPT offers a systematic approach to portfolio optimization, emphasizing the importance of diversification and the trade-off between risk and return. Essentially, it mathematically works out two clichés from over the centuries: no pain (risk), no gain (returns), and don’t put your eggs all in one basket.

However, like any theory, there are advantages and disadvantages. MPT remains a cornerstone in the field of finance, providing valuable insights into portfolio construction and risk management. However, investors and portfolio managers should be aware of its limits and consider supplementing MPT with other approaches like behavioral finance and scenario analysis, as they navigate the complexities of real-world investing.

Advantages of Modern Portfolio Theory

The advantages of MPT are as follows:

• Risk-return trade-off: MPT brings mathematical precision to the idea that there is a risk-return trade-off, encouraging investors to consider both expected returns and the risk associated with their investments.
• Diversification: MPT shows how a well-diversified portfolio can reduce systematic risk without sacrificing expected returns.
• Quantitative approach: MPT provides a quantitative framework, allowing investors to calculate and compare the expected returns, variances, and covariances of different portfolios.
• Efficient frontier: The efficient frontier helps investors identify the most efficient portfolios for their needs.
• Asset allocation: MPT aids in strategic asset allocation, guiding investors on optimally allocating their capital among various asset classes.

Disadvantages of Modern Portfolio Theory

The disadvantages of MPT are as follows:

• Assumes a normal distribution: MPT presupposes that returns are normally distributed, which does not always hold in the real world, especially during periods of market stress.
• Dependent on historical data: The theory relies on historical data to predict future returns and risks, which can be misleading as past performance does not always indicate future results.
• Static model: MPT also doesn’t adequately account for changing market conditions and investor circumstances over time.
• Rational investor assumptions: The theory presumes that all investors are rational and will always aim at maximizing their utility, which overlooks the complexities of human behavior in financial markets. The theory that explores this behavior is known as behavioral finance.
• Single-period framework: MPT is a single-period model, which may not be suitable for long-term investors facing multiple-period investment horizons and life events.
• Underestimates extreme events: MPT may underestimate the likelihood and impact of extreme market events, also known as tail risks. This can lead to potential underperformance in turbulent market conditions.

Can Modern Portfolio Theory Adapt to Changes in the Market or Downturns?

MPT provides a framework for long-term investment strategies, emphasizing diversification to manage risk. During market changes or economic downturns, the diversified nature of portfolios based on MPT should (theoretically) help mitigate losses. However, it’s important that you regularly review and look to rebalance your portfolio in light of changing market conditions and personal investment goals. MPT doesn’t predict market trends but offers an approach that manages risk over time.

What Other Portfolio Theories are There?

Several other portfolio theories and models have been developed to address MPT’s limits and offer alternative perspectives on portfolio construction and risk management. These theories and models include the following:

• The capital asset pricing model: A framework that relates the expected return of an investment to its risk, specifically focusing on the risk compared with the overall market.
• The arbitrage pricing theory: This is used to estimate the price of assets based on the relationship between their expected returns and macroeconomic factors.
• The behavioral portfolio theory: This framework attempts to incorporate psychological factors and investor behavior into understanding portfolio construction and risk.
• The Fama-French three-factor model: This builds on the capital asset pricing model by including three key factors to explain returns on stocks: market risk, the size of the firms, and book-to-market value.

How Does Modern Portfolio Theory Apply to Those With Limited Resources?

MPT is not just for large investors or institutions; it’s also highly relevant for individual investors, even those with limited resources. The core principle of diversification can be applied to anyone investing in a mix of stocks and bonds or using mutual funds and exchange-traded funds.

The Bottom Line

MPT, introduced by Harry Markowitz in the 1950s, gave specific metrics for investment professionals to think about investments and portfolio construction. At its core, MPT is built on the premise that investors can optimize their portfolios through diversification, balancing the trade-off between risk and return.

Key assumptions of MPT include the notion that investors are rational and risk-averse, returns follow a normal distribution, and investors base decisions solely on risk and return. The theory’s most significant contributions include the introduction of the efficient frontier, which aids in identifying optimal portfolios and emphasizing diversification to reduce risk. MPT’s quantitative approach provides a structured framework for portfolio optimization, making it a foundational tool in investment strategy.

However, MPT has limits and has received wide-ranging critiques. Nevertheless, MPT continues to be a valuable starting point for investment management, offering a systematic approach to understanding the relationship between risk and return. Its principles remain influential, even as newer theories and models emerge to address its shortcomings and adapt it to the evolving financial landscape.

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