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…
☆52Updated 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.☆70Updated 2 years ago
- Trend Prediction for High Frequency Trading☆43Updated 2 years ago
- High Frequency Pairs Trading Based on Statistical Arbitrage (Python)☆103Updated 6 years ago
- Pairs Trading with Machine Learning on Distributed Python Platform☆122Updated 3 years ago
- ☆25Updated 7 years ago
- Machine learning trading method using meta-labeling. You can see the details in 'Advances in Financial Machine Learning' by Lopez de Prad…☆15Updated 4 years ago
- Quantopian Pairs Trading algorithm implementation.☆64Updated 8 years ago
- Backtest result archive for Momentum Trading Strategies☆64Updated 6 years ago
- This project is to apply Copula Function to pair trading strategy both in American stock market.☆29Updated 7 years ago
- Find trading pairs with Machine Learning☆41Updated 4 years ago
- The Implied Volatility Smirk of Individual Option in S&P 500 Shows its Underlying Asset’s Return☆38Updated 5 years ago
- ☆77Updated last year
- 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…☆69Updated 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
- Pair Trading - Reinforcement Learning - with Oanda Trading API☆65Updated 5 years ago
- This project used GARCH type models to estimate volatility and used delta hedging method to make a profit.☆68Updated 5 years ago
- Statistical arbitrage of cointegrating currencies with pair trading where the signal for the next day is predicted using LSTM☆56Updated 5 years ago
- The notebook with the experiments to replicate and enhance the stock clustering proposed by Han(2022) for alogtrading, with KMeans Optimi…☆21Updated last year
- Deep q learning on determining buy/sell signal and placing orders☆50Updated 6 years ago
- High Frequency Trading (HFT) done using the Alpaca Trade API and Python.☆24Updated 6 years ago
- Design your own Trading Strategy☆39Updated last year
- stock-pairs-trading is a python library for backtest with stock pairs trading using kalman filter on Python 3.8 and above.☆37Updated 2 years ago
- Build a statistical risk model using PCA. Optimize the portfolio using the risk model and factors using multiple optimization formulation…☆134Updated 6 years ago
- Example of order book modeling.☆57Updated 6 years ago
- Algorithmic Portfolio Hedging. Black-Scholes Pricing for Dynamic Hedges to produce a Dynamic multi-asset Portfolio Hedging with the usage…☆56Updated 4 years ago
- The random forest, FFNN, CNN and RNN models are developed to predict the movement of future trading price of Netflix (NFLX) stock using t…☆61Updated 4 years ago
- A statistical arbitrage strategy on treasury futures using mean-reversion property and meanwhile insensitive to the yield change☆79Updated 7 years ago
- • Conducted a volatility study to develop pairs trading strategy by writing web crawlers that automated extracting 30 equity and ETF spot…☆48Updated 4 years ago
- keywords - Kmeans Clustering, Tsne, PCA, Indian Stocks, Johansen test☆32Updated 7 years ago