A typical long-term investor may seek exposure to riskier asset classes in their portfolios with the hopes of higher returns and better outcomes. While the long-term historical returns for higher risk asset classes (such as equities, real estate, and commodities) have been higher relative to safer assets (like short-term U.S. Treasuries), losses can be substantial in downturns. In times of distress, market participants may tactically allocate to safe haven investments, such as cash or government bonds. Nevertheless, knowing when to be fully “risk on” and when to move to safety is not an easy undertaking.
The capital asset pricing model (CAPM) assumes that investors are rational and risk averse. However, in reality, behavior biases affect investor decision-making. In fact, research has shown that when investor performance lags the market, it is often attributable to these biases (Elan, 2010 and Feldman, 2011).
Behavioral biases, such as loss aversion, overconfidence, anchoring, or impulse, can lead to ill-timed or ill-advised investment decisions, resulting in less desirable outcomes (Kahneman and Ripe, 1998 and Pompian, 2018). Investors can be hardwired to want to take action in times of volatility, whether warranted or not. Although it can be challenging to overcome these behavioral tendencies, a systematic and dynamic allocation approach to control portfolio volatility can help prevent an unnecessary “anxious exit” from the market.
In this paper, we introduce the S&P Dynamic Tactical Allocation Index (DTAQ), which uses a systematic approach to asset allocation by incorporating dynamic and tactical investment strategies into the index design. We first review the portfolio construction methodology, providing empirically driven rationale for the asset class building blocks and overall ruleset. In part two of the paper, we review the historical index performance. We compare the strategy with hypothetical static allocation versions and the classic 60/40 equity/bond portfolio.