by GCBC Ventures | Jul 23, 2023 | Finance, Machine Learning, Papers
Quantocracy: This is a curated mashup of quantitative trading links. Reinforcement Learning for Credit Index Option Hedging – Francesco Mandelli, Marco Pinciroli, Michele Trapletti, Edoardo Vittori In this paper, we focus on finding the optimal hedging strategy...
by GCBC Ventures | Jul 21, 2023 | Finance
Dynamic Time Warping (DTW) We apply Dynamic Time Warping (DTW) to transformed time series of prices, as explained below, to find nearest neighbors for current stocks and ETFs. DTW can be defined as: In time series analysis, dynamic time warping (DTW) is...
by GCBC Ventures | Jul 18, 2023 | Finance, Uncategorized
Standard Deviation – For N=21, 42, …, 231, 252 days, we compute the standard deviation of the adjusted close prices. Slopes – For N=21, 42, …, 231, 252 days, we compute slopes for data as described below. After the data has been transformed, we...
by GCBC Ventures | Jul 16, 2023 | Finance, Machine Learning, Papers
Quantocracy: This is a curated mashup of quantitative trading links. Financial Machine Learning – Bryan T. Kelly, Dacheng Xiu We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line...
by GCBC Ventures | Nov 11, 2021 | Finance, Machine Learning
Introduction In this article, we cluster stock price time series with hierarchical clustering and Euclidean, correlation, and Jensen-Shannon distances to answer two questions regarding portfolio diversification. How diversified is a given portfolio? How can a...
by GCBC Ventures | Nov 4, 2021 | Finance, Machine Learning
Introduction We use the K-means algorithm to answer two questions regarding portfolio diversification. How diversified is a given portfolio? How can a diversified portfolio be constructed? Additionally, we use the multidimensional scaling (MDS) algorithm to visualize...
