asaficontact / learning_to_beat_the_random_walkLinks
In this project, I explore various machine learning techniques including Principal Component Analysis (PCA), Support Vector Machines (SVM), Artificial Neural Networks (ANN), and Sentiment Analysis in an effort to predict the directional changes in exchange rates for a list of developed and developing countries.
☆10Updated 2 years ago
Alternatives and similar repositories for learning_to_beat_the_random_walk
Users that are interested in learning_to_beat_the_random_walk are comparing it to the libraries listed below
Sorting:
- Semi-automatic analysis of a financial series using Python.☆13Updated 3 years ago
- The course, authored by Prof. Jerzy in NYU, applies the R programming language to momentum trading, statistical arbitrage (pairs trading)…☆13Updated 6 years ago
- Foreign Exchange Forecasting Model created for the paper "Can Interest Rate Factors Explain Rate Fluctuations?"☆31Updated 2 years ago
- Allows the generation of optimal portfolios with CoIn, Gumbel, and no copula constraint for the stochastic interest rate - constant elast…☆13Updated last year
- By means of stochastic volatility models☆44Updated 5 years ago
- Portfolio optimization with cvxopt☆38Updated 4 months ago
- ☆41Updated 2 years ago
- Visualising correlations between different ETFs using network analytics and Plotly☆34Updated 3 years ago
- Projects are developed for implementing the knowledge gained in the courses studied at World Quant University and meeting the requirement…☆28Updated 5 years ago
- This repo is for my articles published on Medium.com☆16Updated 2 years ago
- Mean Reversion Trading Strategy☆25Updated 4 years ago
- ☆19Updated 5 years ago
- ☆26Updated 9 months ago
- Algorithmic multi-greek hedges using Python☆20Updated 4 years ago
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆64Updated 2 years ago
- detecting regime of financial market☆36Updated 2 years ago
- Project description: https://medium.com/@tzhangwps/measuring-financial-turbulence-and-systemic-risk-9d9688f6eec1?source=friends_link&sk=1…☆25Updated 3 months ago
- ☆24Updated 2 years ago
- Portfolio Construction Utilizing Lead-Lag Relationship Discovery: Identify leaders and followers in financial markets to inform strategic…☆19Updated last year
- ☆23Updated 5 years ago
- Basic Limit Order Book functions☆21Updated 7 years ago
- A cursory look at the dynamics of zero coupon bond yield curves.☆13Updated 2 years ago
- Code repository for demos of the article 'Arbitrage-Free Implied Volatility Surface Generation with Variational Autoencoders'.☆33Updated 2 years ago
- Mock pairs trading strategy and backtesting with Kalman iltering and pair selection using clustering and cointegration.☆11Updated 2 years ago
- Statistical tests for Value at Risk (VaR) Models.☆14Updated last year
- KAIST(Korea Advanced Institute of Science and Technology) Financial Engineering( Derivatives) Course Code+@☆27Updated 3 years ago
- The "Python Machine Learning (2nd edition)" book code repository and info resource☆14Updated 6 years ago
- Value and Momentum Using Machine Learning☆11Updated 4 years ago
- Implementation of code snippets and exercises in the book Machine Learning for Asset Managers written by Prof. Marcos López de Prado.☆16Updated 4 years ago
- ☆19Updated last year