6/19/2023 0 Comments Portfolio drawdownHistorical estimates of returns and volatilities can vary significantly depending on the length of time series used. In terms of designing a drawdown portfolio, this data tends to be used for estimating returns and volatilities related to portfolio optimization, and for various historical return time series windows-for example, around the credit crunch-for stress testing candidate portfolios.Īlthough intuitive, these backward-looking approaches are limited. We will use the current COVID-19 pandemic and market data to put into perspective some of the decisions that must be made during the design process.Īny views presented in this document should not be considered financial advice.ĭespite the adage that past market performance is not indicative of future results, historical market data is being used widely on its own to produce analysis to support investment decision-making. In this document, we explore how modeling customer outcomes with forward-looking data can be used to produce more robust analysis to help design drawdown portfolios or communicate risks involved with those portfolios. Moreover, a typical optimization approach that involves looking at a mean-variance efficient frontier might not be informative enough to help determine the best option for drawdown clients, or even to explain the risks associated with selecting different portfolios. But taking this risk into account when designing portfolios is not easy, and the typical approach of looking only at past market events is not helpful. Sequencing risk-the risk of loss due to the order of returns earned in the market-matters greatly.
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