Financial Markets and Portfolio Management最新文献

英文中文

Will the reddit rebellion take you to the moon? Evidence from WallStreetBets. reddit的叛乱会带你去月球吗?来自WallStreetBets的证据。

IF 1.9 Q3 BUSINESS, FINANCE

Financial Markets and Portfolio Management

Pub Date : 2023-01-01 DOI: 10.1007/s11408-022-00415-w

Ryan G Chacon, Thibaut G Morillon, Ruixiang Wang

In early 2021, several stocks receiving attention from retail traders known as "meme stocks" soared in value. A primary source of information regarding these stocks is from the social media platform Reddit, specifically from a subreddit known as WallStreetBets (WSB).This paper investigates whether a simple and easily implementable trading strategy following the WallStreetBets (WSB) subreddit can produce alpha. We document no evidence this is the case. Though we do observe a positive relation between WSB submissions and abnormal trading volume, we find that a portfolio that goes long buy recommendations and short sell recommendations each day is not profitable on a risk-adjusted basis. Holding periods from one day to one year fail to produce alpha. These findings are robust to a variety of different portfolio formation strategies. Our results provide an early look at the data following the explosion of interest in social media inspired retail investing.

2021年初，几只受到零售交易员关注的股票(被称为“模因股”)价值飙升。有关这些股票的主要信息来源是社交媒体平台Reddit，特别是Reddit的一个名为WallStreetBets (WSB)的分支。本文研究了遵循WallStreetBets (WSB)子reddit的简单且易于实现的交易策略是否可以产生alpha。我们没有证据证明这是真的。虽然我们确实观察到WSB提交与异常交易量之间存在正相关关系，但我们发现，在风险调整的基础上，每天做多买入推荐和做空推荐的投资组合是不盈利的。从一天到一年的持有期都不能产生alpha。这些发现适用于各种不同的投资组合形成策略。我们的研究结果提供了对社交媒体激发的散户投资兴趣爆炸式增长之后的数据的早期观察。

引用次数: 5

Report of the Editor 2022. 编者报告2022。

IF 1.9 Q3 BUSINESS, FINANCE

Financial Markets and Portfolio Management

Pub Date : 2023-01-01 DOI: 10.1007/s11408-023-00426-1

Markus Schmid

引用次数: 0

Constrained portfolio strategies in a regime-switching economy. 制度转换经济中的约束投资组合策略。

IF 1.9 Q3 BUSINESS, FINANCE

Financial Markets and Portfolio Management

Pub Date : 2023-01-01 DOI: 10.1007/s11408-022-00414-x

Marcelo Lewin, Carlos Heitor Campani

We implement an allocation strategy through a regime-switching model using recursive utility preferences in an out-of-sample exercise accounting for transaction costs. We study portfolios turnover and leverage, proposing two procedures to constrain the allocation strategies: a low-turnover control (LoT) and a maximum leverage control (MaxLev). LoT sets a dynamic threshold to trim minor rebalancing, reducing portfolio turnover, mitigating costs. MaxLev calculates dynamic adjustments to the risk aversion parameter to constrain the portfolio leverage. The MaxLev adjustments depend on the risk aversion and permitted portfolio leverage, which enables optimal strategies considering the leverage constraints. The study uses US equity portfolios, and shows that, first, models with LoT result in superior return-to-risk measures than those without it when transaction costs increase. Second, considering transaction costs, the return-to-risk measures of the models using MaxLev closely match or exceed those from the corresponding unconstrained regime-switching benchmarks. Third, MaxLev returns have lower volatility and higher return-to-risk than conventional numerically constrained benchmarks. Fourth, the certainty equivalent returns indicate that models using MaxLev and LoT outperform both single-state models and unconstrained regime-switching models with statistical significance.

Supplementary information: The online version contains supplementary material available at 10.1007/s11408-022-00414-x.

我们通过使用递归效用偏好的制度切换模型实现分配策略，该模型用于计算交易成本的样本外练习。我们研究了投资组合的周转率和杠杆率，提出了两种约束配置策略的程序:低周转率控制(LoT)和最大杠杆控制(MaxLev)。LoT设置了一个动态阈值，以减少轻微的再平衡，减少投资组合周转率，降低成本。MaxLev计算对风险厌恶参数的动态调整，以约束投资组合杠杆。MaxLev调整取决于风险规避和允许的投资组合杠杆，这使得考虑杠杆约束的最优策略成为可能。该研究使用了美国股票投资组合，结果表明，首先，当交易成本增加时，有LoT的模型比没有LoT的模型产生了更好的风险回报。其次，考虑到交易成本，使用MaxLev的模型的风险回报指标接近或超过了相应的无约束制度切换基准。第三，与传统的数值约束基准相比，MaxLev回报率具有更低的波动性和更高的风险回报。第四，确定性等效回报表明，使用MaxLev和LoT的模型优于单状态模型和无约束状态切换模型，且具有统计显著性。补充信息:在线版本包含补充资料，提供地址为10.1007/s11408-022-00414-x。

{"title":"Constrained portfolio strategies in a regime-switching economy.","authors":"Marcelo Lewin, Carlos Heitor Campani","doi":"10.1007/s11408-022-00414-x","DOIUrl":"https://doi.org/10.1007/s11408-022-00414-x","url":null,"abstract":"We implement an allocation strategy through a regime-switching model using recursive utility preferences in an out-of-sample exercise accounting for transaction costs. We study portfolios turnover and leverage, proposing two procedures to constrain the allocation strategies: a low-turnover control (LoT) and a maximum leverage control (MaxLev). LoT sets a dynamic threshold to trim minor rebalancing, reducing portfolio turnover, mitigating costs. MaxLev calculates dynamic adjustments to the risk aversion parameter to constrain the portfolio leverage. The MaxLev adjustments depend on the risk aversion and permitted portfolio leverage, which enables optimal strategies considering the leverage constraints. The study uses US equity portfolios, and shows that, first, models with LoT result in superior return-to-risk measures than those without it when transaction costs increase. Second, considering transaction costs, the return-to-risk measures of the models using MaxLev closely match or exceed those from the corresponding unconstrained regime-switching benchmarks. Third, MaxLev returns have lower volatility and higher return-to-risk than conventional numerically constrained benchmarks. Fourth, the certainty equivalent returns indicate that models using MaxLev and LoT outperform both single-state models and unconstrained regime-switching models with statistical significance.Supplementary information: The online version contains supplementary material available at 10.1007/s11408-022-00414-x.","PeriodicalId":44895,"journal":{"name":"Financial Markets and Portfolio Management","volume":"37 1","pages":"27-59"},"PeriodicalIF":1.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243879/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9129239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The palgrave handbook of FinTech and blockchain 帕尔格雷夫金融科技和区块链手册

IF 1.9 Q3 BUSINESS, FINANCE

Financial Markets and Portfolio Management

Pub Date : 2022-12-10 DOI: 10.1007/s11408-022-00423-w

Luca J. Liebi