Prediction of stock prices has become an important area of research in the field of financial analytics and has garnered a lot of attention among academicians. Drawing on the literature on application of econometric tools and also machine learning techniques, this paper presents a framework for...

Volatility in stock markets evokes varying responses from market participants. While some perceive it as opportunity to make money, others perceive it as a threat and start unwinding their positions. In today's globalized environment, increased volatility reflects not only the domestic...

The paper examines the pattern of stock returns of mid cap Indian companies over a period of time and proposes frameworks for predictive modelling. Ten features are identified as predictors of stock returns. Subsequently two Machine Learning models, Random Forest and Dynamic Neural Fuzzy...

The paper applies machine learning tools in pairs trading. Three different algorithms, namely, Support Vector Machine (SVM), Random Forest (RF) and Adaptive Neuro Fuzzy Inference System (ANFIS), have been used for predictive modeling of the value of the ratio of share prices of pairs of...