The main problem of electronic-stores is to resolve the obstacles of visitors as potential customers. In this paper the relationship between the experience of online customers, perceived value, satisfaction, and the loyalty is investigated. The main hypotheses of this study are analyzed using...

This paper uncovers and explains the emergence of cycles of intraday declines and overnight reversals in the U.S. stock market in the 21st century. Using quote midpoints for the past 24 years of common stocks traded in the three main exchanges, I show that the cross-sectional association between...

We propose the "President reacts to news" channel of stock returns by studying the financial market impact of the Twitter account of the 45th president of the United States, Donald Trump. We use machine learning algorithms to classify topic and textual sentiment of 1,400 economy-related tweets...

The present study proposes a Customer Behavior Mining Framework on the basis of data mining techniques in a telecom company. This framework takes into account the customers' behavior patterns and predicts the way they may act in the future. Firstly, clustering technique is used to implement...

This supplemental appendix extends the main paper by presenting additional analyses and robustness checks. It also describes the procedure to construct the Monthly TAQ effective spread benchmark.The paper "A Simple Estimation of Bid-Ask Spreads from Daily Close, High, and Low Prices" to which...

We propose a new method to estimate the bid-ask spread when quote data are not available. Compared to other low-frequency estimates, this method utilizes a wider information set, namely, readily available close, high, and low prices. In the absence of end-of-day quote data, this method generally...

We propose the "President reacts to news" channel of stock returns by studying the financial market impact of the Twitter account of the 45th president of the United States, Donald Trump. We use machine learning algorithms to classify topic and textual sentiment of 1,400 economy-related tweets...