{"title":"Using a Simple Technical Analysis Indicator to Guide Asset Allocation Decisions","authors":"Bryan Foltice, Steven D. Dolvin","doi":"10.3905/jwm.2021.1.148","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":39998,"journal":{"name":"Journal of Wealth Management","volume":"24 1","pages":"31 - 41"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Wealth Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3905/jwm.2021.1.148","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.