Days to Cover and Stock Returns∗
نویسندگان
چکیده
A crowded trade problem emerges when speculators’ positions are large relative to the liquidity of the asset, thereby making exit difficult. We study this problem, which has been a point of concern in the Dodd Frank Financial Reforms regarding systemic risk, through the lens of short-selling. We show in a simple model that days to cover (DTC), the ratio of short interest to trading volume, measures the costliness of exiting crowded trades. We find that arbitrageurs are worried about the crowding problem as short-sellers avoid illiquid stocks and require a significant premium to enter into such positions. A strategy shorting high DTC stocks and buying low DTC stocks generates a 1.2% monthly return. We show that there is a comparably large days-to-cover effect on the long positions of levered hedge funds. ∗We thank Jeremy Stein, Charles Lee and seminar participants at European Finance Association, Seoul National University, Hong Kong University of Science and Technology, Baruch College, and Princeton University for helpful comments. †Princeton University and NBER. ‡Hong Kong University of Science and Technology. §Hong Kong University of Science and Technology. ¶Columbia University, Princeton University, and NBER. ‖Goldman Sachs.
منابع مشابه
Days- of- Week Effect on Tehran Stok Exchange Returns: An Empirical Analysis
The purpose of this study is to concentrate on the investigation of days-of-week effect on Tehran Stock Exchange and its comparison with other emerging markets. Using Classical Linear Regression (CLR) as well as Autoregressive Conditional Heteroskedasticity (ARCH) models it in indicated has indicated that there is significantly positive total return on Saturdays and significantly negative total...
متن کاملEffect of Oil Price Volatility and Petroleum Bloomberg Index on Stock Market Returns of Tehran Stock Exchange Using EGARCH Model
The present research aims to evaluate impacts of crude oil price return index, Bloomberg Petroleum Index and Bloomberg energy index on stock market returns of 121 companies listed in Tehran stock exchange in a 10 years' period from early 2006 to April 2016. First, explanatory variables were aligned with petroleum products index mostly due to application of dollar data. Subsequently, to check va...
متن کاملImpact of Speculative Bubble on Stock Returns in Companies Listed on Tehran Stock Exchange
Recent studies show that individual investors tend to speculate on stock markets and hold shares with a lottery-like return. For this speculation of people have a significant impact on stock returns, individual investors must trade the same shares with the same time. The purpose of this study was to investigate the effect of the speculative bubble on the stock returns of companies in Iran. Foll...
متن کاملChaotic Test and Non-Linearity of Abnormal Stock Returns: Selecting an Optimal Chaos Model in Explaining Abnormal Stock Returns around the Release Date of Annual Financial Statements
For many investors, it is important to predict the future trend of abnormal stock returns. Thus, in this research, the abnormal stock returns of the listed companies in Tehran Stock Exchange were tested since 2008- 2017 using three hypotheses. The first and second hypotheses examined the non-linearity and non-randomness of the abnormal stock returns ′ trend around the release date of annual fin...
متن کاملInvestigating the effect of volume shock on abnormal stock returns of companies listed on the Tehran Stock Exchange
The aim of this study was to investigate the effect of volume shock on abnormal stock returns. In terms of research method, this research is in the category of descriptive-correlational research and in terms of research purpose, it is in the category of applied research. The statistical population in this study is all companies listed on the stock exchange that 120 companies were selected as a ...
متن کاملThe relationship between Neural Networks and DEA-R (Case Study: Companies Stock Exchange)
Evaluate the performance of companies on the Stock Exchange using non-parametric methods is very important. DEA and DEA-R with the strategies for piecewise linear frontier production function and use of available data, assess the stock company. In this study, using a neural network algorithm DEA and DEA-R is suggested to classify the first companies in the stock exchange; Secondly, using the...
متن کامل