Research On Industry Rotation Of Prosperity Factor Based On Drawdown Constraint Under Uncertainty Of Expected Returns

Industry rotation usually plays an important role in the macroeconomy,which means that as the economic cycle changes,industry stocks show alternating rise and fall,thus bringing investment opportunities.The prosperity of the industry determines the future performance of the industry,and as an important factor to promote the rotation of the industry,it has always attracted the attention of scholars and market participants.However,investors are pursuing stable,high-level earnings in industry stock portfolios while also hoping to minimize losses.Therefore,as an important risk measure,drawdown has become the key to portfolio optimization.In the field of quantitative investment,there have been a large number of mature research results on the multi-factor model of individual stocks.At present,how to effectively use the key elements and individual stock information that drive industry rotation,so as to build industry factors that can bring excess returns is still being actively explored.In addition,existing research on multi-factor stock selection less systematically considers risk optimization,resulting in real performance often deviating from backtesting results.This paper attempts to optimize the multi-factor industry rotation strategy with the help of the relevant theories of portfolio with drawdown constraint and expected utility maximization criterion.Existing studies are usually discussed in the framework of determining the mean return,so the uncertainty of financial markets is difficult to characterize.Uncertainty in the economy may result in the expected return of the portfolio being uncertain,which means that the current approach has certain limitations.In view of the above problems,this paper first improves the method of estimating the prosperity of individual stocks from the perspective of prosperity,and finds the industries with marginal improvement in fundamentals through the method of industry cross-sectional comparison,and constructs the industry rotation strategy of prosperity factor.Then,considering the mean uncertainty of return,the U-REDP algorithm is proposed based on the rolling risk asset economic max drawdown model(REDP model),which is used to study the drawdown control problem when the expected return of the portfolio is uncertain,and the optimal portfolio weights are solved in the best and worst cases of expected return.Finally,the drawdown constraint algorithm is combined with the initial prosperity factor industry rotation strategy to form a composite strategy,and the effectiveness of the model and strategy is explained through empirical analysis.It is found that the factors constructed from financial data and analyst expectation data can well characterize the industry prosperity,and empirical analysis shows that in the end,six single factors with weak correlation perform well,and the long combination constructed by composite factors synthesized by the equalization method or the maximum IC value weighting method has significant advantages in terms of return and risk.Secondly,the mean uncertainty can be used to describe whether the market is in a more active state or a sluggish state,and the quality of the market will affect the weight of the portfolio and the final return.In addition,after adding the U-REDP model to the boom industry rotation strategy,the stricter the drawdown constraint,the lower the portfolio return,if the drawdown target is set to 70%of the maximum drawdown of the original strategy,it can maintain high returns while controlling risks in both the best market and the worst market conditions.The research conclusions and empirical results of this paper can provide investors with reference.