vincent27hugh / Time_Series_ARIMA-GARCH
In this project, this research generally investigates the financial time series such as the price & return of NASDAQ Composite Index using ARIMA and GARCH methods.
☆12Updated 6 years ago
Alternatives and similar repositories for Time_Series_ARIMA-GARCH:
Users that are interested in Time_Series_ARIMA-GARCH are comparing it to the libraries listed below
- Codes for the paper 'Clustering Approaches for Global Minimum Variance Portfolio'☆23Updated 2 years ago
- Randomly partitions time series segments into train, development, and test sets; Trains multiple models optimizing parameters for develo…☆11Updated 4 years ago
- The course, authored by Prof. Jerzy in NYU, applies the R programming language to momentum trading, statistical arbitrage (pairs trading)…☆14Updated 6 years ago
- ☆12Updated 5 years ago
- The major goal of this project is to predict financial re- cession given the frequencies of the top 500 word stems in the reports of fina…☆15Updated 9 years ago
- Python code for dynamic facctor model. (Preliminary and in progress)☆22Updated 7 years ago
- Development space for PhD in Finance☆33Updated 4 years ago
- (Work In Progress) Implementation of "Financial Time Series Prediction Using Deep Learning"☆15Updated 7 years ago
- Project description: https://medium.com/@tzhangwps/measuring-financial-turbulence-and-systemic-risk-9d9688f6eec1?source=friends_link&sk=1…☆26Updated last month
- A public available dataset for using market sentiment for financial asset allocation.☆23Updated 6 years ago
- This project is to practice applying Long Short-Term Memory network in deep learning to predict time series financial data. I selected Am…☆15Updated 7 years ago
- UCLA Master of Applied Economics Capstone Research☆11Updated 6 years ago
- CVXPY Portfolio Optimization Sample☆45Updated 8 years ago
- Using Extreme Value Theory (EVT) to Estimate Value-at-Risk (VaR) and Expected shortfall (ES)☆10Updated 3 years ago
- Covariance Matrix Estimation via Factor Models☆32Updated 6 years ago
- Portfolio optimization package in Python.☆16Updated 5 years ago
- Implementations of the graphical lasso method to estimation of covariance matrices in finance.☆36Updated 12 years ago
- Bayer, Friz, Gulisashvili, Horvath, Stemper (2017). Short-time near-the-money skew in rough fractional volatility models.☆12Updated 8 years ago
- Inspired by Hillebrand & Medeiros (2009) and Corsi (2009), I put neural networks in a High frequency environment, and tested the performa…☆18Updated 4 years ago
- Comparison of Markov-Switching GARCH models, namely symmetric GARCH, EGARCH, GJR-GARCH, performances in Value-at-Risk forecasting.☆25Updated 7 years ago
- Python package for generating Directional Changes - a technical analysis indicator - from time series.☆20Updated 6 years ago
- Non-Linear Covariance Shrinkage☆14Updated 3 years ago
- Forecasting Macroeconomic Parameters with Deep Learning Neural Networks - Final Year Peoject☆13Updated 6 years ago
- ☆16Updated 4 years ago
- Market Risk Management with Time Series Prediction of Stock Market Trends using ARMA, ARIMA, GARCH regression models and RNN for time ser…☆21Updated 7 years ago
- NYU Tandon lecture slides☆31Updated last week
- Stock Price prediction using news data. The datasets used consists news and stock price data from 2008 to 2016. The polarity(Subjectivity…☆48Updated 7 years ago
- keywords - Kmeans Clustering, Tsne, PCA, Indian Stocks, Johansen test☆31Updated 6 years ago
- Estimation of the Covariance Matrix - linear and nonlinear shrinkage☆22Updated 2 years ago
- Machine Learning for Financial Market Prediction☆58Updated 6 years ago