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 A fundamental premise of portfolio construction is to utilize assets that have low correlation with each other. A primary benefit of assembling a portfolio with low correlation among the constituent assets is a reduction in the volatility of the overall portfolio returns, which, in turn, reduces the portfolio's standard deviation of return. While this advantageous domino effect may have intuitive appeal, it may be difficult for many investors to put a specific value on.
It is generally assumed that a reduction in a portfolio's standard deviation of return is compellingly beneficial. To the extent that reducing standard deviation of return is perceived as analogous to reducing risk, this assumption seems reasonable. However, this study is based on the premise that most investors may be unable to quantify the value of that risk reduction, as measured by reduced standard deviation of return. Said more simply, most investors are probably unable to articulate the specific benefits of reducing the standard deviation of their portfolio's returns, though they undoubtedly have a general sense that doing so is a "good thing."
Therefore, this study attempts to quantify the value of volatility reduction achieved by assembling portfolios with progressively lower correlation among the constituent assets. This study also examines several additional benefits accrued from low correlation that may have more intuitive appeal to the general population than the common metric of standard deviation. A more specific segment of the population that stands to particularly benefit from creating low-correlation portfolios are retirees, as they are typically more sensitive to portfolio volatility.
Literature Review
The basic premise underlying diversification and portfolio selection can be summarized by a simple sentence from Harry Markowitz: "To reduce risk, it is necessary to avoid a portfolio whose securities are all highly correlated with each other." (Markowitz, 1991).
It is assumed that Markowitz was equating the term "risk" with volatility of returns. Additionally, William Bernstein observes that "the concept of correlation of assets is central to portfolio theory—the lower the correlation, the better." (Bernstein, 2001).
Reducing the volatility of returns in a portfolio is achieved by combining assets that tend to have low correlation to each other. Countless mean-variance studies have documented the ability of low correlation portfolios to reduce the volatility of a portfolio's returns (i.e., standard deviation of return) while maintaining a level of return that is typically superior to the performance of higher correlation portfolios. Thus, lowering correlation is integral in reducing volatility and enhancing risk-adjusted performance.
This study attempts to add to the body of literature by quantifying additional benefits (beyond the reduction of volatility) achieved by lowering the correlation among the assets in a portfolio. This study specifically examines the benefits of correlation reduction in retirement portfolios during the draw-down phase (or when a retirement portfolio is in "withdrawal mode," as money is being systematically withdrawn). The bulk of the extant mean-variance research literature is based on analysis which has assumed a buy-and-hold portfolio. As will be shown, a portfolio in withdrawal mode is far more sensitive to portfolio volatility (i.e., account value losses) than a buy-and-hold portfolio.
Description And Justification
This study examines the aggregate correlation among various assets in a variety of portfolios and the corresponding impact on portfolio performance as measured by standard deviation of annual returns, internal rate of return, maximum portfolio drawdown in any single year, frequency of loss and probability of portfolio recovery following a loss.
Maximum portfolio drawdown is a measure of the percentage of change in the portfolio account value from the end of one year to the end of the following year. It takes into account the increasing annual withdrawals which occur at the end of each year. Frequency of loss is a measure of the number of times the portfolio lost 10 percent or more in any one-year, two-year or three-year period as measured by internal rate of return (IRR). The historical probability of recovery from a 10 percent portfolio loss is measured by calculating the portfolio's performance over all contiguous three-year periods to determine if it generated a return sufficient to restore the portfolio account balance to its pre-loss level.
It is proposed that these three measures of portfolio risk—maximum portfolio drawdown, frequency of loss and probability of recovery from a loss—are more intuitively useful to the average investor than is the standard deviation of return.
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