7 citations · 8 across the 9 of their papers we have counts for
4 papers · 1 filter
Optimizing Stock Option Forecasting with the Assembly of Machine Learning Models and Improved Trading Strategies
Zheng Cao, Raymond Guo, Wenyu Du +2
This paper introduced key aspects of applying Machine Learning (ML) models, improved trading strategies, and the Quasi-Reversibility Method (QRM) to optimize stock option forecasti…
Solving the Stock Option Forecast problem by a numerical method for the Black-Scholes Equation with Machine Learning Classification Model
Benjamin Jiang, Matthieu Durieux, Kirill V. Golubnichiy
We proposed classification models that utilize the result from the Quasi-Reversibility Method, which solves the Black-Scholes equation to forecast the option prices one day in adva…
Application of Convolutional Neural Networks with Quasi-Reversibility Method Results for Option Forecasting
Zheng Cao, Wenyu Du, Kirill V. Golubnichiy
This paper presents a novel way to apply mathematical finance and machine learning (ML) to forecast stock options prices. Following results from the paper Quasi-Reversibility Metho…
Forecasting Stock Options Prices via the Solution of an Ill-Posed Problem for the Black-Scholes Equation
Michael V. Klibanov, Aleksander A. Shananin, Kirill V. Golubnichiy +1
In the previous paper (Inverse Problems, 32, 015010, 2016), a new heuristic mathematical model was proposed for accurate forecasting of prices of stock options for 1-2 trading days…