{"title":"Stock Returns, Market Trends, and Information Theory: A Statistical Equilibrium Approach","authors":"Emanuele Citera","doi":"10.2139/ssrn.3936846","DOIUrl":"https://doi.org/10.2139/ssrn.3936846","url":null,"abstract":"This paper attempts to develop a theory of statistical equilibrium based on an entropy- constrained framework, that allow us to explain the distribution of stock returns over di erent market trends. By making use of the Quantal Response Statistical Equilib- rium model (Scharfenaker and Foley, 2017), we recover the cross-sectional distribution of daily returns of individual company listed the S&P 500, over the period 1988-2019. We then make inference on the frequency distributions of returns by studying them over bull markets, bear markets and corrections. The results of the model shed light on the microscopic as well as macroscopic behavior of the stock market, in addition to provide insights in terms of stock returns distribution.","PeriodicalId":198417,"journal":{"name":"DecisionSciRN: Stock Market Decision-Making (Sub-Topic)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123117122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nicolae Gârleanu, Stavros Panageas, Geoffery Zheng
{"title":"A Long and a Short Leg Make For a Wobbly Equilibrium","authors":"Nicolae Gârleanu, Stavros Panageas, Geoffery Zheng","doi":"10.2139/ssrn.3945948","DOIUrl":"https://doi.org/10.2139/ssrn.3945948","url":null,"abstract":"We provide evidence that the online discussion on the WSB subreddit had a substantial negative impact on the profitability of shorting strategies across a number of stocks — even those that were neither heavily discussed on the subreddit, nor experienced an unusual increase in retail buying volume. We provide a model to explain how fears among short sellers can become self-fulfilling. In the model, the market for shares and the lending market must clear jointly. Despite standard assumptions, the model features multiple equilibria and \"run-type'' behavior by shorting agents. More broadly, the model provides a tractable framework to interpret several empirical observations on the relation between short interest, lending fees, and expected returns.","PeriodicalId":198417,"journal":{"name":"DecisionSciRN: Stock Market Decision-Making (Sub-Topic)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129363587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cross-sectional Return Predictability in Indian Stock Market: An Empirical Investigation","authors":"G. Goswami","doi":"10.2139/ssrn.3838938","DOIUrl":"https://doi.org/10.2139/ssrn.3838938","url":null,"abstract":"This paper provides a comprehensive analysis of stock return predictability in the Indian stock market by employing both the portfolio and cross-sectional regressions methods using the data from January 1994 and ending in December 2018. We find strong predictive power of size, cash-flow-to-price ratio, momentum and short-term-reversal, and in some cases of book-to-market-ratio, price-earnings-ratio. The total volatility, idiosyncratic volatility, and beta are not consistent stock return predictors in the Indian stock market. In cross-sectional regression analysis, size, short-term reversal, momentum, and cash-flow-to-price ratio predict the future stock returns. Overall, the two variables momentum and cash flow to price ratio demonstrate reliable forecasting power under all methods and both small and large size samples.","PeriodicalId":198417,"journal":{"name":"DecisionSciRN: Stock Market Decision-Making (Sub-Topic)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133830052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Turn-of-the-Year Effect in Asia Pacific Stock Markets: New Evidence","authors":"Nhan H. Huynh","doi":"10.2139/ssrn.3799914","DOIUrl":"https://doi.org/10.2139/ssrn.3799914","url":null,"abstract":"This paper examines a well-known seasonal anomaly - the turn-of-the-year (TOY) effect in fifteen Asia Pacific stock indices by using an updated dataset and forward-looking methods. The analysis utilizes daily dataset that spans from January 2000 to December 2018. Applying the Ordinary Least Square (OLS) regression and EGARCH approach, the results of this paper suggest that the TOY effect becomes detectable again after the GFC in developed stock markets with tax year not ending in December. Oppositely, the magnitude of this anomaly has diminished in the emerging financial markets after the GFC, which is consistent with the EMH. The evidence of the leverage effect in the unconditional volatility is proposed that volatility in negative shocks is considerably higher than that of positive shocks across examined stock indices. This phenomenon is more conspicuous in mature stock indices compared to emerging indices. The positive connection between the leverage effect and stock market volatility is propositioned as diminishing magnitude of this effect during the stable market condition after the GFC. Our findings lend reinforcement to the conclusion that some Asia Pacific stock markets satisfy the weak form of the EMH.","PeriodicalId":198417,"journal":{"name":"DecisionSciRN: Stock Market Decision-Making (Sub-Topic)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115296265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Horses for Courses: Mean-Variance for Asset Allocation and 1/N for Stock Selection","authors":"Emmanouil Platanakis, C. Sutcliffe, Xiaoxia Ye","doi":"10.2139/ssrn.3372334","DOIUrl":"https://doi.org/10.2139/ssrn.3372334","url":null,"abstract":"For various organizational reasons, large investors typically split their portfolio decision into two stages - asset allocation and stock selection. We hypothesise that mean-variance models are superior to equal weighting for asset allocation, while the reverse applies for stock selection, as estimation errors are less of a problem for mean-variance models when used for asset allocation than for stock selection. We confirm this hypothesis for US data using Bayes-Stein with no short sales and variance based constraints. Robustness checks with four other types of mean-variance model (Black-Litterman with three different reference portfolios, minimum variance, Bayes diffuse prior and Markowitz), and a wide range of parameter settings support our conclusions. We also replicate our core results using Japanese data, with additional replications using the Fama-French 5, 10, 12 and 17 industry portfolios and equities from seven countries. In contrast to previous results, but consistent with our empirical results, we show analytically that the superiority of mean-variance over 1/N is increased when the assets have a lower cross-sectional idiosyncratic volatility, which we also confirm in a simulation analysis calibrated to US data.","PeriodicalId":198417,"journal":{"name":"DecisionSciRN: Stock Market Decision-Making (Sub-Topic)","volume":"8 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115013964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Real-Time Stock Trend Prediction via Sentiment Analysis of News Article","authors":"Sanmoy Paul, S. Vishnoi","doi":"10.2139/ssrn.3753015","DOIUrl":"https://doi.org/10.2139/ssrn.3753015","url":null,"abstract":"The stock market is volatile and volatility occurs in clusters, price fluctuations based on sentiment and news reports are common. A trader uses a wide variety of publicly available information to forecast the marketing decision. This paper proposes an advice to traders for stock trading using sentimental analysis of publically available news reports. It is based on a hypothesis, that news articles have an impact on the stock market, with this hypothesis we study the relationship between news and stock trend and also proved that negative news has a persistent effect on the stock market. In order to prove this assumption semi-supervised learning technique is being used to build the final model of news classification. This research shows that SVM with TF-IDF as feature performs well in further analysis. The accuracy of the prediction model is more than 90% having 52% correlation with the return label of a stock. This paper also proposes a real-time system which fetches news of any company on a real-time basis and displays its top five news and also predicts the adjusted close price of the next seven days. Keywords: Text Mining, Human Sentiments, KNN, Random Forest, Multinomial Naive Bayes, linear SVM, News.","PeriodicalId":198417,"journal":{"name":"DecisionSciRN: Stock Market Decision-Making (Sub-Topic)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131082635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Patrick Schotanus, Ron Chrisley, A. Clark, D. Pritchard, Aaron Schurger
{"title":"Reflexivity and the Market Mind Hypothesis: Why George Soros is Not a Failed Philosopher (and What it Means for Economics, the Economy, and Investing)","authors":"Patrick Schotanus, Ron Chrisley, A. Clark, D. Pritchard, Aaron Schurger","doi":"10.2139/ssrn.3939493","DOIUrl":"https://doi.org/10.2139/ssrn.3939493","url":null,"abstract":"George Soros is one of the best traders of all time. That is the general consensus. While Soros gladly accepts that compliment he frequently also expressed his frustration that he failed as a philosopher. Specifically, he admits that he was unable to formulate his philosophy of reflexivity from its original abstractions. More importantly, reflexivity—which informed his successful trading—did not get the academic recognition that Soros’s track record suggests it deserves. This paper will discuss the reasons for this, the key one being that reflexivity points to the elephant in economics’s room. This will be highlighted by explaining reflexivity, from its original abstractions, in novel terms provided by cognitive science. In particular, via philosophy of mind this paper will argue why Soros is not a failed philosopher. This leads to the submission that reflexivity deserves proper recognition as an early contribution to the emerging field of cognitive economics, for which the Market Mind Hypothesis is a standard bearer. Moreover, the issues discussed are relevant in the wider context of our economic predicament.","PeriodicalId":198417,"journal":{"name":"DecisionSciRN: Stock Market Decision-Making (Sub-Topic)","volume":"2004 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127331375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Option Momentum","authors":"S. Heston, Shuaiqi Li","doi":"10.2139/ssrn.3705573","DOIUrl":"https://doi.org/10.2139/ssrn.3705573","url":null,"abstract":"This paper improves continuous-time variance swap approximation formulas to derive exact returns on benchmark VIX option portfolios. The new methodology preserves the variance swap interpretation that decomposes returns into realized variance and option implied-variance.<br><br>We apply this new methodology to explore return momentum on option portfolios across different S&P 500 stocks. We find that stock options with high historical returns continue to outperform options with low returns. This predictability has a quarterly pattern, resembling the pattern of stock momentum found by Heston and Sadka (2008). In contrast to stock momentum, option momentum lasts for up to five years, and does not reverse.<br>","PeriodicalId":198417,"journal":{"name":"DecisionSciRN: Stock Market Decision-Making (Sub-Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131226392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Reddit Sentiment Analysis","authors":"Sebastian Lindskog, J. A. Serur","doi":"10.2139/ssrn.3887779","DOIUrl":"https://doi.org/10.2139/ssrn.3887779","url":null,"abstract":"It has never been easier for individual investors to get started trading stocks or options. Companies like Robinhood and Webull even offer zero commission trades, no account minimum size, and incentives like a free stock if a user creates an account. Recently, there has been a huge increase in the growth of users of these types of platforms. The combination of many people out of work because of the coronavirus and the US government stimulus package appears to have sparked this. This surge in new investors has sparked tons of activity on popular social media websites like Reddit. There users regularly post stock recommendations and trading strategies. It appears that many Reddit traders are grouping together and causing irrational stock market moves. Panic buying stocks for companies that just declared bankruptcy, betting against Warren Buffet, and ignoring the impact of the coronavirus on airlines and cruise ships are a few of the unusual market moves lately. The purpose of this project is to identify if there is a relationship between the Reddit sentiment on stocks and performance.","PeriodicalId":198417,"journal":{"name":"DecisionSciRN: Stock Market Decision-Making (Sub-Topic)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129951611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analytic Value Function for Pairs Trading Strategy With a Levy-Driven Ornstein-Uhlenbeck Process","authors":"Lan Wu, Xin Zang, Hongxin Zhao","doi":"10.2139/ssrn.3553064","DOIUrl":"https://doi.org/10.2139/ssrn.3553064","url":null,"abstract":"This paper studies the performance of pairs trading strategy under a specific spread model. Based on the empirical evidence of mean reversion and jumps in the spread between pairs of stocks, we assume that the spread follows a Levy-driven Ornstein-Uhlenbeck process with twosided jumps. To evaluate the performance of a pairs trading strategy, we propose the expected return per unit time as the value function of the strategy. Significantly different from the current related works, we incorporate an excess jump component into the calculation of return and time cost. Further, we obtain the analytic expression of strategy value function, where we solve out the probabilities of crossing thresholds via the Laplace transform of first passage time of the Levy driven Ornstein-Uhlenbeck process in one-sided and two-sided exit problems. Through numerical illustrations, we calculate the value function and optimal thresholds for a spread model with symmetric jumps, reveal the non-negligible contribution of incorporating the excess jumps into the value function, and analyze the impact of model parameters on the strategy performance.","PeriodicalId":198417,"journal":{"name":"DecisionSciRN: Stock Market Decision-Making (Sub-Topic)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127236981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}