BessieChen / Algorithmic-Portfolio-Management-in-R-programming-language
The course, authored by Prof. Jerzy in NYU, applies the R programming language to momentum trading, statistical arbitrage (pairs trading), and other active portfolio management strategies. The course implements volatility and price forecasting models, asset pricing and factor models, and portfolio optimization. The course will apply machine lear…
☆13Updated 6 years ago
Alternatives and similar repositories for Algorithmic-Portfolio-Management-in-R-programming-language:
Users that are interested in Algorithmic-Portfolio-Management-in-R-programming-language are comparing it to the libraries listed below
- Implied volatility surface interpolation with shape-constrained bayesian neural network.☆15Updated 3 years ago
- Short-term momentum trading strategy implemented for the lecture "Systematic risk premia strategies traded at hedge funds" at University …☆41Updated 3 years ago
- Code repository for demos of the article 'Arbitrage-Free Implied Volatility Surface Generation with Variational Autoencoders'.☆31Updated 2 years ago
- ☆17Updated 7 years ago
- ☆19Updated 4 years ago
- A low frequency statistical arbitrage strategy☆20Updated 6 years ago
- A 50ETF Option Volatility Arbitrage Strategy Based on SABR Model☆23Updated 2 years ago
- A dynamic factor model to forecasts inflation, i.e. CPI, PPI. WindAPI is required to extract vintages.☆14Updated 4 years ago
- Machine learning trading method using meta-labeling. You can see the details in 'Advances in Financial Machine Learning' by Lopez de Prad…☆13Updated 3 years ago
- By means of stochastic volatility models☆44Updated 5 years ago
- Project description: https://medium.com/@tzhangwps/measuring-financial-turbulence-and-systemic-risk-9d9688f6eec1?source=friends_link&sk=1…☆26Updated 2 months ago
- ☆24Updated 6 years ago
- SABR Implied volatility asymptotics☆22Updated 4 years ago
- In this project, I explore various machine learning techniques including Principal Component Analysis (PCA), Support Vector Machines (SVM…☆10Updated 2 years ago
- Mock pairs trading strategy and backtesting with Kalman iltering and pair selection using clustering and cointegration.☆11Updated 2 years ago
- Implementation of option pricing models using Numba that performs better. This entire project has utilized as little libraries as possibl…☆16Updated 2 years ago
- Algorithmic multi-greek hedges using Python☆19Updated 4 years ago
- This repository provides the implementation of a handful of forecasting methods in yield curve modelling.☆24Updated 4 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
- Basic Limit Order Book functions☆21Updated 7 years ago
- Fama-French models, idiosyncratic volatility, event study☆31Updated 2 years ago
- Development space for PhD in Finance☆33Updated 5 years ago
- FactorLab is a python library which enables the transformation of raw data into informative alpha and risk factors used in the investment…☆19Updated 3 years ago
- Covariance Matrix Estimation via Factor Models☆33Updated 6 years ago
- A financial trading method using machine learning.☆60Updated 2 years ago
- Contains detailed and extensive notes on quantitative trading, leveraging NLP for finance, backtesting, alpha factor research, portfolio …☆44Updated 2 years ago
- A Long/Short Global Macro Strategy based on French Fama 3-Factor Model with a target beta term. We evaluate its sensitivity to variation …☆8Updated 3 years ago
- Factor Investing Library☆26Updated 2 years ago
- Construction of local volatility surface by using SABR☆29Updated 7 years ago
- • Visualised trend and seasonality & conducted tests for checking stationarity of Time series for predicting volatility using GARCH Model…☆15Updated 2 years ago