This paper compares various machine learning models to predict the cross-section of emerging market stock returns. We document that allowing for non-linearities and interactions leads to economically and statistically superior out-of-sample returns compared to traditional linear models. Although...

Financial institutions have witnessed numerous episodes of financial crises all over the world during the last four decades. The researchers, academicians and policy makers in the field of finance studied these episodes extensively and to mitigate the risk involved in these crises have proposed...

The investment choices of large asset owners such as pension funds, sovereign wealth funds and endowments, are, to a large extent ‘guided’ and pre-determined by the systematic use of old- fashioned indices or benchmarks designed by a small set of Anglo- American ‘index providers’ –...

We examine the F score in global emerging markets and show there is a meaningful premium attached to high F score stocks which is unrelated to the size, value and momentum premiums. It is larger for high value stocks, moderately higher for high momentum stocks and unrelated to stock size. This...

In almost all stages of forecasting volatility, certain subjective decisions need to be made. Despite of an enormous literature in the area, these subjectivities are hindrances to reaching an overall conclusion on the performances of the models. In order to find out outperforming model in...

We develop a classification methodology for the context and content of news articles to predict risk and return in stock markets in 51 developed and emerging economies. A parsimonious summary of news, including topic-specific sentiment, frequency, and unusualness (entropy) of word flow, predicts...

We propose a coherent framework using support vector regression (SRV) for generating and ranking a set of high quality models for predicting emerging market sovereign credit spreads. Our framework adapts a global optimization algorithm employing an hv-block cross-validation metric, pertinent for...

This paper examines the quarter-ahead out-of-sample predictability of Brazil, Mexico, the Philippines and Turkey credit spreads before and after the Lehman Brothers' default. A model based on the country-specific credit spread curve factors predicts no better than the random walk and slope...

This study employs the DCC-GARCH model to investigate the dynamic connectedness between the Indian stock market and major global stock markets. Specifically, we examine daily log returns data of the National Stock Exchange (NSE) index and several international indices, including the United...

In this paper, we confirm cross-sectional reversals in intraday returns in China's A-share market. Intraday reversals are shown to be robust with respect to seasonality, alternative samples, and the daily price-limit rule. To investigate the potential drivers, trade volumes and order imbalances...