{"id":4209,"date":"2019-02-21T20:45:30","date_gmt":"2019-02-21T20:45:30","guid":{"rendered":"http:\/\/quantpedia.com\/why-is-allocation-to-trend-following-strategy-so-low\/"},"modified":"2025-06-04T13:57:48","modified_gmt":"2025-06-04T11:57:48","slug":"why-is-allocation-to-trend-following-strategy-so-low","status":"publish","type":"post","link":"https:\/\/vvv.quantpedia.com\/es\/why-is-allocation-to-trend-following-strategy-so-low\/","title":{"rendered":"Why Is Allocation to Trend-Following Strategy So Low?"},"content":{"rendered":"Related to all trendfollowing strategies:<\/strong>\n\nAuthors:<\/strong> Dugan, Greyserman\n\nTitle: <\/strong>Skew and Trend Aversion\n\nLink:<\/strong> https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3315719<\/a>\n\nAbstract:<\/strong>\n\nDespite evidence of the benefits to portfolio Sharpe ratio and variance, actual investor allocations to Trend Following strategies are typically 5% or less. Why is there such a significant discrepancy between the optimal allocation and actual allocation to Trend? We investigate known behavioral biases as a potential reason. While decision makers have other reasons to exclude Trend Following from their portfolios, in this paper, we explore loss aversion, recency bias, and the ambiguity effect as they pertain to Trend Following, and we call the combination of the three Trend Aversion. We quantify Trend Aversion and show that these biases are a viable explanation for suboptimal allocations to Trend. We demonstrate a direct connection between quantifications of known behavioral biases and current suboptimal allocations to Trend Following. Recognition of these relationships will help highlight the pitfalls of behavioral biases.\n\nNotable quotations from the academic research paper:<\/strong>\n\n“Investors may have reasons for excluding Trend Following from their portfolios ranging from time-horizon for performance, to drawdowns, to potential capacity issues. However, the strategy’s long performance history shows that a meaningful allocation would have increased portfolio Sharpe ratio and reduced portfolio variance, and yet typical investments remain at or below 5%. Some investors have no exposure.\n\nThe strategy’s quantitative nature, positive skew, and frequent but small losses act in concert to trigger loss aversion, recency bias, and the ambiguity e\u000bffect. We call the combination of the three Trend Aversion.\n\n\"Sharpe\n\n\n\n
Algo Trading Data Discounts<\/strong><\/a> are available exclusively for Quantpedia\u2019s readers.<\/span><\/span><\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\nOur results show Trend Aversion is a viable explanation of suboptimal allocations to Trend Following. Decades of psychological research show that people mentally inflate losses by a factor of two. In this paper, we demonstrated that a loss multiplier between 1.5 and 2.5 would cause the typical allocation to Trend of 5% in a simple two asset portfolio, in an 11-asset portfolio with random allocations, and in two other 11-asset portfolio constructions with dynamic allocations. We showed that loss aversion can decrease allocators Sharpe ratios by up to 50%. Using lookback windows in a dynamically allocated portfolio, we demonstrated that recency bias drives down allocations to Trend. Finally, we showed that combinations of loss aversion and recency bias also drive Trend allocations to suboptimal levels.\n\nMany investors who are subject to Trend Aversion as a practical matter, for example due to investment committees or reporting structures, are unsure of how to balance Trend Aversion with the bene\fts of Trend Following to reach an allocation decision. By establishing a methodology to optimize allocations under loss aversion, we provide a framework which investors can use to formalize their allocation decisions. Investors who are subject to typical loss aversion should permanently allocate at least 5% to Trend Following, while investors whose loss aversion is lower can benefi\ft substantially by allocating materially more than 5%.”\n\n\n
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\n\tRelated to all trendfollowing strategies:<\/strong><\/p>\n

\n\tAuthors:<\/strong> Dugan, Greyserman<\/p>\n

\n\tTitle: <\/strong>Skew and Trend Aversion<\/p>\n

\n\tLink:<\/strong> https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3315719<\/a><\/p>\n

\n\tAbstract:<\/strong><\/p>\n

\n\tDespite evidence of the benefits to portfolio Sharpe ratio and variance, actual investor allocations to Trend Following strategies are typically 5% or less. Why is there such a significant discrepancy between the optimal allocation and actual allocation to Trend? We investigate known behavioral biases as a potential reason. While decision makers have other reasons to exclude Trend Following from their portfolios, in this paper, we explore loss aversion, recency bias, and the ambiguity effect as they pertain to Trend Following, and we call the combination of the three Trend Aversion. We quantify Trend Aversion and show that these biases are a viable explanation for suboptimal allocations to Trend. We demonstrate a direct connection between quantifications of known behavioral biases and current suboptimal allocations to Trend Following. Recognition of these relationships will help highlight the pitfalls of behavioral biases.<\/p>\n

\n\tNotable quotations from the academic research paper:<\/strong><\/p>\n

\n\t"Investors may have reasons for excluding Trend Following from their portfolios ranging from time-horizon for performance, to drawdowns, to potential capacity issues. However, the strategy's long performance history shows that a meaningful allocation would have increased portfolio Sharpe ratio and reduced portfolio variance, and yet typical investments remain at or below 5%. Some investors have no exposure.<\/p>\n

\n\tThe strategy's quantitative nature, positive skew, and frequent but small losses act in concert to trigger loss aversion, recency bias, and the ambiguity e ffect. We call the combination of the three Trend Aversion.<\/p>\n

\n\t\"Sharpe<\/p>\n

\n\t
\n\tOur results show Trend Aversion is a viable explanation of suboptimal allocations to Trend Following. Decades of psychological research show that people mentally inflate losses by a factor of two. In this paper, we demonstrated that a loss multiplier between 1.5 and 2.5 would cause the typical allocation to Trend of 5% in a simple two asset portfolio, in an 11-asset portfolio with random allocations, and in two other 11-asset portfolio constructions with dynamic allocations. We showed that loss aversion can decrease allocators Sharpe ratios by up to 50%. Using lookback windows in a dynamically allocated portfolio, we demonstrated that recency bias drives down allocations to Trend. Finally, we showed that combinations of loss aversion and recency bias also drive Trend allocations to suboptimal levels.<\/p>\n

\n\tMany investors who are subject to Trend Aversion as a practical matter, for example due to investment committees or reporting structures, are unsure of how to balance Trend Aversion with the bene ts of Trend Following to reach an allocation decision. By establishing a methodology to optimize allocations under loss aversion, we provide a framework which investors can use to formalize their allocation decisions. Investors who are subject to typical loss aversion should permanently allocate at least 5% to Trend Following, while investors whose loss aversion is lower can benefi t substantially by allocating materially more than 5%."<\/p>\n

\n

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