by GCBC Ventures | Apr 26, 2023 | Finance, Machine Learning
1. Introduction We use machine learning algorithms to match current input data with historical data. As we know the future prices for past prices, we use these matched future prices to form percent returns, zscore (standard deviation units) returns and up/down...
by GCBC Ventures | Apr 26, 2023 | Finance
Calendar returns is an analysis of close-to-close returns for specific calendar periods: year, quarter, month, and week. Results are computed for: Minimum, 25th Percentile, Median, 75th Percentile, and Maximum. They are available as CSV files and for each asset there...
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...
by GCBC Ventures | Oct 27, 2021 | Finance
Introduction In this article, we present a mechanical trading system that is a generalization of a dual moving average cross over system with a fixed time period for exits. Array Of Dual Moving Averages In canonical dual moving average (DMA) systems, a long entry...
by GCBC Ventures | Dec 21, 2020 | Finance
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Using daily adjusted close data from 20201118 to 20201218 for Dow 30 stocks, we compute correlation coefficients, apply a threshold of...
