Open Data, more than 50 financial data. 提供超過 50 個金融資料(台股為主),每天更新 https://finmind.github.io/
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Updated
Apr 21, 2026 - Jupyter Notebook
Open Data, more than 50 financial data. 提供超過 50 個金融資料(台股為主),每天更新 https://finmind.github.io/
Crack spread is the price differential between crude oils and refined products. "Crack" refers to the catalyzing and heating process that results in the breaking down of the carbon bonds, hence the name "cracking". The spreads represent industry refining margins and lend insight into economic activities. The spreads are thought to be seasonal. T…
LLM-assisted options trading system for crude oil futures with rules-based exits, five-tier strategy promotion, and human-in-the-loop safety gates
Methods for Identification - academic project
Group Project: we intend to develop a robust machine learning model that will deliver a one-year projection for the price of West Texas Intermediate (WTI) Crude Oil.
Code and walkthrough for reproducibility of the Case Study (Crude Oil Price Prediction using Artificial Neural Network) presented in class.
Quantitative Analysis of Strait of Hormuz Disruption on Global Capital Markets & Commodity Trades
React-based dashboard for real-time crude oil price forecasting powered by a hybrid ARIMA | GRU | XGBoost backend with live news sentiment integration.
🚀 AI Forex Trend Pullback EA 2026 - High Sharpe Ratio Strategy ⚡
Adams Resources & Energy is a diversified energy company engaged in the marketing, transportation, terminalling, and storage of crude oil and other related petroleum products in select markets across the United States. Through its subsidiaries GulfMark Energy, Firebird Bulk Carriers, Phoenix Oil, and Victoria Express Pipeline, the company purcha...
Accurate crude oil prices with full historical data. Integrate in under 10 minutes.
This repository contains the analysis and results of a study on the estimation of Value at Risk (VaR) for Brent crude oil. The analysis compares classical VaR methods with advanced Machine Learning models based on Quantile Regression, aiming to evaluate the risk associated with this highly volatile and globally significant commodity.
This repository contains three machine learning projects examining price forecasting across different asset classes. Each project isolates a specific question: Which models work best under different market regimes?
Crude Oil trend pullback algorithmic trading system— EMA crossover, ATR-based stops, 5.2x return/drawdon ratio
VECM analysis of the 3-2-1 crack spread: demand-pull and cost-push price transmission between crude oil, gasoline, and heating oil (BENV0122 UCL)
SMS alerts for ±5% Brent crude oil price movements
Crude oil market analysis and forecasting experiments using Python notebooks.
Crude oil chart
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