New Methods for the Cross-Section of Returns

on the comparison of keyword and semantic-context methods of learning new vocabulary meaning

the rationale behind the present study is that particular learning strategies produce more effective results when applied together. the present study tried to investigate the efficiency of the semantic-context strategy alone with a technique called, keyword method. to clarify the point, the current study seeked to find answer to the following question: are the keyword and semantic-context metho...

The Cross - Section of Stock Returns :

Deep Learning for Forecasting Stock Returns in the Cross-Section

Many studies have been undertaken by using machine learning techniques, including neural networks, to predict stock returns. Recently, a method known as deep learning, which achieves high performance mainly in image recognition and speech recognition, has attracted attention in the machine learning field. This paper implements deep learning to predict one-month-ahead stock returns in the cross-...

Inflation Risk and the Cross Section of Stock Returns

I establish that inflation risk is priced in the cross section of stock returns: Stocks that have low returns during inflationary times command a risk premium. I estimate a market price of inflation risk that is comparable in magnitude to the price of risk for the aggregate market. Inflation is therefore a key determinant of risk in the cross section of stocks. The inflation premium cannot be e...

Capital, Contracts and the Cross Section of Stock Returns∗

We present a tractable, static, general equilibrium model with multiple sectors in which firms offer workers incentive contracts and simultaneously raise capital in stock markets. Workers optimally invest in the stock market and at the same time hedge labor income risk. Firms rationally take agents’ portfolio decisions into account. In equilibrium, the cost of capital of each sector is endogeno...