Yvaine-Zhang / Models-for-Intraday-Trading-Volume-PredictionLinks
Having effective intraday forecast for the level of trading volume is of vital importance to algorithmic trading and portfolio management since it attempts to minimize transaction costs by optimally scheduling and placing. The purpose of this project is to create dynamic statistical models of intraday trading volume prediction (in Python). By as…
☆48Updated 5 years ago
Alternatives and similar repositories for Models-for-Intraday-Trading-Volume-Prediction
Users that are interested in Models-for-Intraday-Trading-Volume-Prediction are comparing it to the libraries listed below
Sorting:
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆66Updated 2 years ago
- Trend Prediction for High Frequency Trading☆42Updated 2 years ago
- High Frequency Pairs Trading Based on Statistical Arbitrage (Python)☆105Updated 6 years ago
- Find trading pairs with Machine Learning☆41Updated 4 years ago
- Quantopian Pairs Trading algorithm implementation.☆63Updated 7 years ago
- Backtest result archive for Momentum Trading Strategies☆61Updated 6 years ago
- High Frequency Trading (HFT) done using the Alpaca Trade API and Python.☆25Updated 5 years ago
- This project is to apply Copula Function to pair trading strategy both in American stock market.☆28Updated 6 years ago
- ☆25Updated 6 years ago
- Pair Trading Strategy using Machine Learning written in Python☆119Updated 3 years ago
- Alpaca-based Order Book Inbalace Algorithm.☆12Updated 5 years ago
- Machine learning trading method using meta-labeling. You can see the details in 'Advances in Financial Machine Learning' by Lopez de Prad…☆14Updated 4 years ago
- A low frequency statistical arbitrage strategy☆20Updated 6 years ago
- This repository stores the implementation of the paper "DETECTING DATA-DRIVEN ROBUST STATISTICAL ARBITRAGE STRATEGIES WITH DEEP NEURAL NE…☆66Updated last year
- Statistical arbitrage of cointegrating currencies with pair trading where the signal for the next day is predicted using LSTM☆53Updated 4 years ago
- Deep q learning on determining buy/sell signal and placing orders☆49Updated 6 years ago
- Example of order book modeling.☆58Updated 6 years ago
- High Frequency Trading bot for 2019 Traders at MIT, HFT Case. I placed 4th in the HFT competition (2nd overall) out of 120.☆19Updated 5 years ago
- A statistical arbitrage strategy on treasury futures using mean-reversion property and meanwhile insensitive to the yield change☆77Updated 6 years ago
- stock-pairs-trading is a python library for backtest with stock pairs trading using kalman filter on Python 3.8 and above.☆38Updated last year
- ☆75Updated last year
- The Implied Volatility Smirk of Individual Option in S&P 500 Shows its Underlying Asset’s Return☆37Updated 4 years ago
- Algorithmic Portfolio Hedging. Black-Scholes Pricing for Dynamic Hedges to produce a Dynamic multi-asset Portfolio Hedging with the usage…☆55Updated 4 years ago
- Different quantitative trading models research☆53Updated 7 months ago
- Collection of indicators that I used in my strategies.☆56Updated 4 months ago
- This project used GARCH type models to estimate volatility and used delta hedging method to make a profit.☆64Updated 5 years ago
- Intraday momentum strategy that buys (sells) leveraged ETFs late in the trading session following a significant intraday gain (loss) and …☆26Updated last year
- Pairs trading strategy that includes a research pipeline for identifying and selecting pairs. Tests all possible pairs in a universe for …☆35Updated last year
- Bitmex orderbooks saving + (neural) trading signal generator + backtesting etc.☆35Updated 2 years ago
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆84Updated 2 years ago