Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...
This article ( original research paper) proposes a systematic regression-based fundamental equity valuation model that can potentially be applied in areas such as quantitative finance and machine ...
This article considers a regression model on a Lexis diagram of an a × p table with a single response in each cell following a distribution in the exponential family. A regression model on the fixed ...
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the gradient boosting regression technique, where the goal is to predict a single numeric value. Compared to ...
In this paper we propose a semi-parametric, parsimonious value-at-risk forecasting model based on quantile regression and readily available market prices of option contracts from the over-the-counter ...
A tool called AI-Newton can derive scientific laws from raw data, but is some way from developing human-like reasoning.
It can be highly beneficial for companies to develop a forecast of the future values of some important metrics, such as demand for its product or variables that describe the economic climate. There ...
The Income Tax department is exploring usage of artificial intelligence (AI) to build regression models to identify deviations and errors in tax filing and separate those deviations for further ...
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