The Markowitz Model was developed in 1952 and has remained a cornerstone of portfolio construction. Some swear by the theory, while others see weaknesses. Let's examine these differences to better understand the practical uses of the Markowitz Model.
The Markowitz Model is another name for Modern Portfolio Theory (MPT), which Harry Markowitz developed. MPT reduces risk by building a portfolio of diversified, uncorrelated assets. Such a portfolio smooths out volatility, which is how risk is measured in MPT.
The crowning jewel of MPT is the Markowitz Model Efficient Frontier (EF). The EF is where an asset maximizes returns while minimizing risk. In other words, it is the most efficient return/risk ratio. Assets that are above the EF will return more but experience above-average risk. Assets below the EF experience below-average risk but have lower returns.
The Markowitz Model is fairly systematic. There’s software that can help determine correlations between the different assets in a portfolio. Choosing uncorrelated assets will achieve Markowitz Model-type diversification. With the aid of software, this makes implementation of the model fairly systematic.
As mentioned above, the Markowitz Model effectively helps to reduce investment risks while potentially maximizing portfolio returns due to the EF.
It isn't likely that every asset will fit on the EF. In fact, probably very few, if any, will be on the EF. Some will be above and some below. Because of the EF, investors basically end up with two asset categories — low-risk with correspondingly low returns and high-risk with potentially high returns.
The Markowitz Model assumes the diversification of uncorrelated assets. This should result in decreased volatility and, thus, drawdowns without sacrificing overall returns.
By following the Markowitz Model, investors can construct a balanced portfolio that aligns with their risk tolerance and financial goals, promoting efficient and strategic investment decisions.
Despite these advantages, investors should be aware of some limitations of the Markowitz Model.
The Markowitz Model heavily depends on historical data, which may not reliably predict future market trends. You’ve probably seen the disclaimer in investment advertisements that states past performance is no guarantee of future results. The same applies here.
The model's underlying assumptions are predicated on normally functioning markets. In highly volatile and unpredictable markets, the model may lose relevance.
MPT is mean-variance theory. Risk by variance works when returns are normally distributed. Assets that do not follow a normal distribution will not work with the Markowitz Model.
A mean-variance framework also assumes that investors have allocated all portfolio assets to a single timeframe. That is rarely the case in reality.
The above explanations underline the importance of combining Markowitz's model with a comprehensive understanding of market dynamics and trends.
Finding a practical mix of asset allocations to achieve efficient frontier optimization may be difficult in practice and doesn’t guarantee the portfolio will perform as intended.
Even though MPT assumes all assets are uncorrelated, the unfortunate truth is that correlations often go to one during a crash. In this scenario, uncorrelated assets will not protect the portfolio.
The Markowitz Model may seem like a simple concept but it can be difficult to implement correctly in practice. One should not assume they will ever reach 100% implementation of MPT due to inaccurate/misrepresented data representing correlations of assets. In this case, a financial adviser can help investors find a workable solution that can achieve the aim of MPT.