Bitcoin Returns and the Frequency of Daily Abnormal Returns

Multiples Valuation and Abnormal Returns

Chaotic 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...

Rationalizing Trading Frequency and Returns

Barber and Odean (2000) study the relationship between trading frequency and returns. They find that households who trade more frequently have a lower net return than other households. But all households have about the same gross return. They argue that these results cannot emerge from a model with rational traders and instead attribute these findings to overconfidence. Using a dynamic optimiza...

Predicting Daily Returns for the IBM Stock

The goal of the work described in this paper is to predict the daily returns of the closing prices for the IBM stock. From the original data of IBM daily quotes a new data set was built using technical indicators as predictor variables. Using this new data set, two modelling approaches were tried: regression and classification. Early analysis and experiments suggested that this prediction probl...

Can Short-sellers Predict Returns? Daily Evidence

We test whether short-sellers in U.S. stocks are able to predict future returns based on new SEC-mandated data for 2005. There is a tremendous amount of short-selling activity during the sample: Short-sales represent 24 percent of NYSE and 32 percent of Nasdaq share volume. Our analysis shows that short-sellers primarily target short-term overreaction in stock prices, but they are also able to ...