How is risk defined in the portfolio optimization objective function? We typically use volatility indicators, especially those that focus on downside risk and losses.
However, this only illustrates one aspect of risk. It does not capture the entire distribution of outcomes an investor may experience. For example, not owning an asset or investment that subsequently outperformed could provoke an investor’s emotional reaction (eg, regret). This is similar to the reaction to more traditional definitions of risk.
That is why understanding risk for portfolio optimization purposes requires consideration of regret.
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For different investors, the performance of speculative assets such as cryptocurrencies can provoke different emotional reactions. I don’t have very favorable return expectations for cryptocurrencies, and I consider myself relatively reasonable, so I wouldn’t be too concerned if the price of Bitcoin were to rise to $1 million. .
But another investor with similarly unfavorable Bitcoin return expectations could react even more adversely. Fear of missing out on future Bitcoin price increases, they may even abandon all or part of their diversified portfolio to avoid such pain. Such diverse reactions to Bitcoin price movements suggest that allocations need to vary according to investors. However, applying a more traditional portfolio optimization function, assuming relatively unfavorable return expectations, the Bitcoin allocation would be the same for me as for other investors, possibly zero.
Thinking about regret means going beyond pure variance math and other metrics. It means trying to incorporate an underlying emotional response to a given outcome. From tech to real estate to tulips, investors have succumbed to greed and regret in countless bubbles over the years. That is why a small allocation to ‘periling assets’ reduces the likelihood that investors will abandon their prudent portfolios and invest in distressed assets if they start to perform well. If so, it might be worth it.
I’d like to introduce An Objective Function That Explicitly Incorporates Regrets into Portfolio Optimization Routines in a new study for portfolio management journal. More specifically, the function treats risk aversion and downside risk as distinct parameters by comparing portfolio returns to the performance of one or more regret benchmarks (returns less than 0% and other target return, etc.). Regret avoidance level is different. The model does not require assumptions about asset return distributions or normality, so it can incorporate lotteries and other assets with highly non-normal returns.
When performing a series of portfolio optimizations using a portfolio of individual securities, we find that regret considerations can have a significant impact on allocation decisions. The risk level, defined as downside risk, is likely to increase, especially for risk-averse investors, given regret. why? Because the assets that cause the most regret tend to be more speculative in nature. Investors with higher risk tolerance are more likely to achieve lower returns, assuming less efficient risky assets, with higher downside risk. However, more risk-averse investors may generate higher returns despite significantly greater downside risk. Additionally, the allocation to regrett assets may increase depending on the assumed volatility, which goes against conventional portfolio theory.
What are the implications of this research for different investors? First, assets that are only marginally less efficient within large portfolios and more likely to cause regret have higher expected returns and covariances. You may receive a higher quota depending on These findings also have an impact on how multi-asset funds are structured, particularly the potential benefits of explicitly providing investors with information about the distinct exposures of multi-asset portfolios compared to single funds. It could give, says Target Day Fund.
Of course, just because some customers may regret it doesn’t mean financial advisors and asset managers should start allocating to inefficient assets. Rather, it should consider each investor’s preferences and provide an approach that helps build portfolios that clearly consider regrets within the context of the portfolio as a whole.
Humans are not utility-maximizing robots, or “homo economicus.” We need to build our portfolio and solutions to reflect this. In doing so, we can help investors achieve better outcomes across a range of potential risk definitions.
Stay tuned for more information on Dr. David Blanchett, CFA, CPA.Redefining the optimal retirement income strategy,” from financial analyst journal.
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All posts are the opinion of the author. As such, they should not be construed as investment advice, and the opinions expressed do not necessarily reflect those of the CFA Institute or the author’s employer.
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