TY - JOUR
T1 - Using a Simple Technical Analysis Indicator to Guide Asset Allocation Decisions
AU - Foltice, Bryan
AU - Dolvin, Steven D
N1 - 1. Bryan Foltice 1. is an associate professor of finance at Butler University in Indianapolis, IN. (bfoltice{at}butler.edu) 2. Steven Dolvin 1. is a professor of finance at Butler University in Indianapolis, IN. (sdolvin{at}butler.edu) 1. To order reprints of this article, please contact David Rowe at d.rowe{at}pageantmedia.com or 646-891-2157.
PY - 2021
Y1 - 2021
N2 - This article examines the effectiveness of using a simple technical analysis indicator to dynamically guide asset allocation decisions. Using the 200-day simple moving average of the S&P 500 as our technical indicator, the authors employ two separate strategies. They adopt a risk-on asset allocation strategy (larger stock allocation) when the daily price of the S&P 500 is above the indicator line, and a risk-off strategy (reduced stock/increased bond allocation) when below. In contrast to prior research, when transitioning to risk-off, they do not necessarily liquidate all equity, but rather consider other less extreme allocations. Over the 1962–2020 time period, they find that following various risk-on/risk-off rules generates excess annual returns of up to 0.58%, after factoring in a marginal trading cost. Furthermore, this strategy also provides a reduction in overall risk for an overwhelming majority of the analyzed allocation combinations. Taken together, almost all 200-day technically based strategies post an increase in Sharpe ratios relative to their respective baseline buy-and-hold strategies.
Key Findings
Using the 200-day simple moving average as our indicator line, all of the risk-on/risk-off approaches outperform (i.e., have a higher Sharpe ratio) the respective buy-and-hold strategy. In both analyzed samples, the vast majority of approaches post higher Sharpe ratios compared to the buy-and-hold strategies. Across the various starting allocations, metrics generally improve (i.e., higher return and lower risk) as a more extreme move to a conservative risk-off approach is employed. We find that this trading strategy is most effective when the stock market posts negative returns. Conversely, in bull markets, the moving-average strategy generally lags the stock market returns.
AB - This article examines the effectiveness of using a simple technical analysis indicator to dynamically guide asset allocation decisions. Using the 200-day simple moving average of the S&P 500 as our technical indicator, the authors employ two separate strategies. They adopt a risk-on asset allocation strategy (larger stock allocation) when the daily price of the S&P 500 is above the indicator line, and a risk-off strategy (reduced stock/increased bond allocation) when below. In contrast to prior research, when transitioning to risk-off, they do not necessarily liquidate all equity, but rather consider other less extreme allocations. Over the 1962–2020 time period, they find that following various risk-on/risk-off rules generates excess annual returns of up to 0.58%, after factoring in a marginal trading cost. Furthermore, this strategy also provides a reduction in overall risk for an overwhelming majority of the analyzed allocation combinations. Taken together, almost all 200-day technically based strategies post an increase in Sharpe ratios relative to their respective baseline buy-and-hold strategies.
Key Findings
Using the 200-day simple moving average as our indicator line, all of the risk-on/risk-off approaches outperform (i.e., have a higher Sharpe ratio) the respective buy-and-hold strategy. In both analyzed samples, the vast majority of approaches post higher Sharpe ratios compared to the buy-and-hold strategies. Across the various starting allocations, metrics generally improve (i.e., higher return and lower risk) as a more extreme move to a conservative risk-off approach is employed. We find that this trading strategy is most effective when the stock market posts negative returns. Conversely, in bull markets, the moving-average strategy generally lags the stock market returns.
UR - https://doi.org/10.3905/jwm.2021.1.148
U2 - 10.3905/jwm.2021.1.148
DO - 10.3905/jwm.2021.1.148
M3 - Article
VL - 24
JO - The Journal of Wealth Management
JF - The Journal of Wealth Management
IS - 3
ER -