Small transformer model for stock market intraday forecasting
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Updated
Nov 3, 2025 - Python
Small transformer model for stock market intraday forecasting
Based on the concepts in "CIMTR" and others, swing trading
Liferay 7 plataform to add a custom product to host trading strategies
In this project, I generated investing insights by applying sentiment analysis on financial news headlines from Finviz.
Open-source market structure analysis terminal for day traders | 开源K线结构分析交易终端 | 0DTE options, support/resistance zones, pluggable strategies
This repository contains code, information, and resources developed and used for the Stevens Algorithmic Trading Competition Spring 2019. For questions about the competition itself, please contact algotrading@stevens.edu.
Risk Management & Position Sizing Calculator for traders. Calculates real post-tax Risk:Reward, position size, and brokerage costs using Dhan charges.
🔋 Optimize battery dispatch using a rainflow-aware DQN that tracks degradation and enhances performance with advanced features for reliable results.
OHLCV Ethereum data is transformed using an encoder-decoder network. The transformed data is input into an LSTM model that predicts the asset price in 24 hours. These forecasts are used to create buy and sell signals which were back-tested producing a Sharpe ratio of 1.45. The code was run various times end-to-end producing similar results.
Minute-level intraday spike detection — identifies optimal trading windows and day-of-week patterns using Polygon.io data.
Rainflow‑aware DQN for battery dispatch (arbitrage + FR/reserves): Gymnasium env with safety layer, exact cycle‑based degradation, time features & stacked observations; SB3 training.
📊 Calculate your true risk and position size accurately for trading, factoring in all fees for better risk management and profitability.
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