nitintonypaul/garch

Generalized AutoRegressive Conditional Heteroskedasticity (1,1). Built from scratch.

Language: C++ - Size: 107 KB - Last synced at: about 6 hours ago - Pushed at: about 7 hours ago - Stars: 0 - Forks: 0

ferrangarciarovira/VaR-Volatility-Models

Comparative analysis of Value at Risk (VaR) measures using Black-Scholes pricing under different volatility models: jump diffusion and rough volatility.

Language: Jupyter Notebook - Size: 35 MB - Last synced at: 10 days ago - Pushed at: 10 days ago - Stars: 1 - Forks: 0

manuelmusngi/volatility_smile_trading_analysis

a C++ framework

Language: C++ - Size: 61.5 KB - Last synced at: 16 days ago - Pushed at: 16 days ago - Stars: 0 - Forks: 0

Kaylieo/Monte-Carlo-for-Crude-Oil-Stocks

A Monte Carlo simulation project for financial risk analysis of Crude Oil Stocks.

Language: Python - Size: 8.38 MB - Last synced at: 17 days ago - Pushed at: 17 days ago - Stars: 0 - Forks: 0

HugzGJ9/Quantitative_Finance

Quantitative Finance Library & Option Trading Tool

Language: Python - Size: 43.5 MB - Last synced at: 21 days ago - Pushed at: 21 days ago - Stars: 4 - Forks: 1

marcdemers/py_vollib_vectorized

A vectorized implementation of py_vollib, that supports numpy arrays and pandas Series and DataFrames.

Language: Python - Size: 281 KB - Last synced at: 20 days ago - Pushed at: 6 months ago - Stars: 132 - Forks: 33

mbhadriraju/IVSurface

User-specified asset, strike price range, and time range for volatility surface construction. Interactive UI built using React.

Language: JavaScript - Size: 5.55 MB - Last synced at: 23 days ago - Pushed at: 23 days ago - Stars: 1 - Forks: 0

ted-love/py_vol_surface

A package that utilises QT and OpenGL graphics to visualise realtime 3D volatility surfaces and analytics.

Language: Python - Size: 1.2 MB - Last synced at: 11 days ago - Pushed at: 2 months ago - Stars: 2 - Forks: 0

DavideDevetak24/Black_Scholes_Volatility_Surfaces

Implied volatility surfaces from SPX option chains data (both calls and puts), interpolation for continuous querying, and GUI to visualize surfaces and calculate Black-Scholes prices and IVs

Language: Python - Size: 379 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

aaronsmith1234/volatilipy

Python wrappers around QuantLib and Pandas to easily generate volatility surfaces

Language: Python - Size: 280 KB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 17 - Forks: 7

Beliavsky/GARCH

Simulation and estimation of ARCH and GARCH processes, used to model the time-varying standard deviation (volatility) of asset returns, with conditional distributions such as the normal, Laplace, and Student t.

Language: Fortran - Size: 687 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0

cgowda337/Financial-Markets-EDA

Financial Markets EDA

Language: Jupyter Notebook - Size: 1.66 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

chicago-joe/Risk-Modeling-for-Volatility-Dispersion-Trades

Language: R - Size: 8.87 MB - Last synced at: about 23 hours ago - Pushed at: over 2 years ago - Stars: 13 - Forks: 9

ArturSepp/StochVolModels

Python implementation of pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, Heston

Language: Python - Size: 10.1 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 157 - Forks: 32

Beliavsky/GARCH-BHHH

Estimate GARCH models using the BHHH algorithm

Language: Python - Size: 0 Bytes - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

diaabraham/algorithmic-trading-strategy

A Python-based backtesting engine that implements a volatility regime-based mean reversion trading strategy. The strategy dynamically adjusts risk exposure based on rolling volatility bands and capitalizes on mean-reversion opportunities in high-volatility environments.

Language: Jupyter Notebook - Size: 0 Bytes - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

chibui191/bitcoin_volatility_forecasting

GARCH and Multivariate LSTM forecasting models for Bitcoin realized volatility with potential applications in crypto options trading, hedging, portfolio management, and risk management

Language: Jupyter Notebook - Size: 105 MB - Last synced at: about 2 months ago - Pushed at: over 3 years ago - Stars: 250 - Forks: 74

MajorLift/volatility-modeling-python-datasci

Undergraduate thesis, Seoul National University Dept. of Economics — "Modeling Volatility and Risk Spillover Between the Financial Markets of US and China Using GARCH Value-at-Risk Forecasting and Granger Causality."

Language: HTML - Size: 4.08 MB - Last synced at: about 1 month ago - Pushed at: 5 months ago - Stars: 21 - Forks: 4

ErikssonWilliam/Financial-Risk-Management

Estimation and forecasting of volatility using financial timeseries. Includes models like GARCH, EWMA, EqWMA and Rolling Window. Portfolio management using CVaR, EVT and Monte Carlo Simulation.

Language: MATLAB - Size: 1.27 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

ThecoderPinar/big-tech-financial-insights

🚀 A comprehensive project analyzing Big Tech stock prices using time series analysis, volatility modeling, and macroeconomic indicators. Featuring interactive dashboards and automated reporting! 📈💼

Language: HTML - Size: 19.9 MB - Last synced at: 2 months ago - Pushed at: 11 months ago - Stars: 9 - Forks: 1

Quant-TradingCO/Volatility-and-options

In this repo you will find some tools related to pricing and risk measurement of options. You can find tools to calculate the price of an option like de Black-Scholes or Heston Model, or to get implied volatilities.

Language: Jupyter Notebook - Size: 213 KB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 5 - Forks: 1

sjdKRM/EPAT

Executive Programme in Algorithmic Trading by QuantInsti

Language: Jupyter Notebook - Size: 3.68 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

AxelMunguiaQuintero/Trading-Cuantitativo-en-Python

Curso diseñado para proporcionar una comprensión muy profunda del Trading Cuantitativo, fusionando los principios de Ingeniería Financiera con el poder de la Inteligencia Artificial, todo implementado en Python. Desarrollarás algoritmos y estrategias avanzadas que aprovechan datos financieros y técnicas de Inteligencia Artificial.

Language: Jupyter Notebook - Size: 5.76 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 7 - Forks: 7

YOLOWinnnn/Code-for-fitting-the-GARCH-family-model-to-the-volatility-of-Mainland-China-Low-Carbon-Stocks

项目主要构建了多混频Realized GARCH-MIDAS-X模型，结合社交媒体情绪和高频数据，与 不加社交媒体情绪指标的模型相比，加入后的模型显著提升了内地低碳市场波动预测的准确性。通过稳健 性检验，证明了研究结果的可靠性。该研究丰富了市场波动模型，并为低碳投资和宏观调控提供了参考。

Language: Python - Size: 110 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 0

yatshunlee/CAViaR

Measure market risk by CAViaR model

Language: Jupyter Notebook - Size: 30.2 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 11 - Forks: 2

lrb924/Predicted_Volatility

Predicted Volatility: Applying Predicted Volatility to Determine Profitability of Cyclical and Defensive ETFs

Language: Jupyter Notebook - Size: 10.3 MB - Last synced at: 4 months ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 6

csatzky/forecasting-realized-volatility-using-supervised-learning

Traditionally, volatility is modeled using parametric models. This project focuses on predicting EUR/USD volatility using more flexible, machine-learning methods.

Language: R - Size: 2.21 MB - Last synced at: 5 months ago - Pushed at: over 3 years ago - Stars: 22 - Forks: 5

ibaris/finance-tda

Topological Tail Dependence: Evidence from Forecasting Realized Volatility

Language: Jupyter Notebook - Size: 766 KB - Last synced at: 30 days ago - Pushed at: about 1 year ago - Stars: 3 - Forks: 1

kelvinkissi/Quantitative-Analysis-With-Pandas

Language: Jupyter Notebook - Size: 2.86 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

imsanjoykb/IBOVESPA-volatility-forecasting

IBOVESPA volatility forecasting

Language: R - Size: 747 KB - Last synced at: about 2 months ago - Pushed at: almost 4 years ago - Stars: 9 - Forks: 1

avsayapin/NewsSentimentMOEX

Sentiment analysis of financial news in Russian and application of it's results in volatility modeling

Language: Jupyter Notebook - Size: 2.26 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

Yosri-Ben-Halima/GARCH-Models-Hyperparameter-Optimizer

In this project, I develop an optimization tool for GARCH model parameters using Optuna. This project automates the hyperparameter tuning process to enhance model performance by selecting optimal values for parameters. It supports various volatility models and error distributions, with a focus on minimizing a composite score.

Language: Jupyter Notebook - Size: 421 KB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 1 - Forks: 0

frankieycy/option-pricing

C++ option pricing library on vanillas & exotics, Python volatility calibration library

Language: Jupyter Notebook - Size: 251 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 17 - Forks: 1

MunumButt/Fast-BSM-Python

Fast black-scholes-merton option pricing model in Python

Language: Jupyter Notebook - Size: 1.77 MB - Last synced at: 10 months ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

jojo142/Stress-Testing-Financial-Portfolios

Stress Testing Financial Portfolios using S&P 500 Stock Data from Kaggle.

Language: Jupyter Notebook - Size: 1.15 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

hobinkwak/Volatility-Spillover

computes Volatility Spillover between Cryptocurrency (BTC/USD) and S&P 500 index

Language: Python - Size: 11.7 KB - Last synced at: 12 months ago - Pushed at: over 3 years ago - Stars: 4 - Forks: 1

SakethAleti/PresAddress-SoFiE2021

Code for the paper "Realized Semi(Co)Variation: Signs that All Volatilities are Not Created Equal"

Language: Jupyter Notebook - Size: 58.5 MB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 5 - Forks: 4

jolly-io/Stock_Markets_Assymetric_Volatility_Spillover_Effects

I investigate the Asymmetric Volatility Spillover Effects within and across six major International stock markets. United States, Canada, France, Germany, Italy & Japan

Language: R - Size: 2.31 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 0

JackJacquier/SABR-Implied-Volatility

SABR Implied volatility asymptotics

Language: Jupyter Notebook - Size: 140 KB - Last synced at: over 1 year ago - Pushed at: about 5 years ago - Stars: 18 - Forks: 9

Avinash793/time-series-analysis-examples

Detailed implementation of various time series analysis models and concepts on real datasets.

Language: Jupyter Notebook - Size: 3.15 MB - Last synced at: 23 days ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

AlexanderShulzhenko/Short-term-Volatility-Prediction

Framework with implemented LightGBM model and feature engineering scripts to predict short-term volatility fluctuations of financial assets

Language: Jupyter Notebook - Size: 23.1 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 1

SiruiJi/ml4frm

Machine learning for financial risk management

Language: Python - Size: 82 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

antek0308/Volatility_notebooks

Public repo of some of my options modeling projects

Language: Jupyter Notebook - Size: 3.84 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

Rafaelll92/Modelos_Heterocedasticos_Multivariados_Econometria_Mercado_a_Vista

Análise da série histórica Dados Históricos Petrobras Ações Ordinárias - PETR3_SA 2020-10-07 00:00:00 até 2023-10-06 00:00:00

Size: 2.93 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

SarcasticMatrix/Stochastic-Volatility-with-particle-filtering

Language: Python - Size: 7.71 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 1

boyla950/predicting-the-pound

MSc Finance dissertation project at Newcastle University. This project focused on forecasting the volatility of exchange rates involving the Great British Pound using EWMA, GARCH-type and Implied Volatility models.

Language: Python - Size: 2.16 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 3 - Forks: 0

yulu0131/VolaDocs

Volatility Model Documentation

Size: 11.1 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

kedarghule/Stock-Portfolio-Diversification-Using-Clustering-and-Volatility-Prediction

The project aims to profile stocks with similar weekly percentage returns using K-Means Clustering. The project calculates realized volatility for each stock and predicts realized volatility for each stock using classical volatility models and machine learning models and comparing their performance. This is a capstone project for CIVE 7100 Time Series and Geospatial Data Sciences.

Language: Jupyter Notebook - Size: 50.5 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 3 - Forks: 3

SashaFlores/WhaleOffPortfolio

Portfolio Performance Analysis

Language: Jupyter Notebook - Size: 5.14 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

MartinMashalov/ImpliedVolatilityAnalysis

Predicting asset prices' directional movements based on implied volatility of price action. This experiment was performed on SPX index fund with VIX as implied volatility reference.

Language: Python - Size: 94.7 KB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 1

qlero/vix_index_modelization 📦

Implementation with a Jupyter Notebook of the VIX index modelization provided in its CBOE white paper.

Language: Jupyter Notebook - Size: 310 KB - Last synced at: almost 2 years ago - Pushed at: almost 6 years ago - Stars: 16 - Forks: 13

frontmark/jupyter-notebooks

Market Data & Derivatives Pricing Tutorial based on Jupyter notebooks

Language: Jupyter Notebook - Size: 1.45 MB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 34 - Forks: 7

aguumg/Volatility-Calculators-Cryptocurrencies

Language: Jupyter Notebook - Size: 238 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

gaelwjl/ML_Optimal_Trading

Collection of numerical methods for high frequency data, in Python notebooks

Language: Jupyter Notebook - Size: 2.45 MB - Last synced at: about 2 years ago - Pushed at: about 4 years ago - Stars: 8 - Forks: 2

mikewenner/PyQuant_Lab

Quant finance notebooks from PQN course

Language: Jupyter Notebook - Size: 1.98 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

white07S/Pricing-Models

Implementation of option pricing models using Numba that performs better. This entire project has utilized as little libraries as possible, even though certain models have their own Machine Learning Model with assessment and performance.

Language: Python - Size: 206 KB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 3

Maurolp15/JMB_Portfolio_Project

Analyze a personal portfolio of stock's past performance and forecast future performance to optimize daily positional adjustments to create a 20% monthly return

Language: Jupyter Notebook - Size: 15.6 MB - Last synced at: over 2 years ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 1

MartinMashalov/VIXFuturePrediction Fork of maylathant/VIXFuturePrediction

Predicting future VIX movements using forked repository from @maylathant. Investigation on VIX price action and predictive modeling in order to aid in risk management on SPX index fund.

Size: 50.8 KB - Last synced at: about 1 year ago - Pushed at: about 4 years ago - Stars: 0 - Forks: 0

hkalager/FDR_buckets

This repository includes the scripts to replicate the results of my WORKING paper entitled "A False Discovery Rate Approach to Optimal Volatility Forecasting Model Selection". Access the article here https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3737477

Language: MATLAB - Size: 6.88 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

VladOnMyOwn/ForecastingWithRandPython

Financial time series forecasting using R

Language: Jupyter Notebook - Size: 12.4 MB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

coren-frankel/VolatilitySurf

Java Spring Collaborative Project built by Erik van Erp, David Moore, & Coren Frankel

Language: Java - Size: 7.38 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

vmieres/Predicting-Currency-Movements

This repo is about forecasting the Yen movements in order to know whether to be long or short.

Language: Jupyter Notebook - Size: 1.05 MB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0

amalsebastian7/NETWORK-OF-INFLUENCE-ON-THE-STOCK-MARKET-AND-ITS-IMPACT-ON-RISK-ANALYSIS

The goal of this research is to better understand the relationships between cryptocurrencies and stock indexes, including how cryptocurrencies are interconnected. Preliminary visualization revealed a trend of market movement across all cryptocurrencies, indicating a substantial correlation. Initial analysis focusses on finding the correlation between the stock indexes and cryptocurrencies value returns. Another objective is to study the volatility of the asset value measured by standard deviation of each asset for a short period and to further calculate the correlation between them. In order to express relationships between assets in a pictorial format, graphs are used. The assets are represented by the graph vertices, and the relationships between them are shown by edges in the graph. Further, centrality is crucial in identifying important nodes. Two measures will be considered, Eigen-vector centrality (measuring likelihood of visitation to a node) and betweenness centrality (counting the instance in which counts the instances in which a node acts as a bridge facilitating the quickest and shortest route between two nodes). The tests were carried out on four indexes (three stock indexes and one crypto index) and six well-known cryptocurrencies based on the quantity and accessibility of historical trading data. The results of the research based on the time series of price returns, points to a strong relationship between Ethereum and Bitcoin in cryptocurrencies, but Dow Jones and S&P 500 have the strongest correlation when it comes to stock indices. The moving average of volatility showed that cci30 is highly volatile compared to other stock indexes and all six crypto currencies are highly volatile. The network graph demonstrates the interconnectedness and clustering of the selected cryptocurrency currencies. It’s evident that Bitcoin functions as a central node, which means it has the highest likelihood of appearing on a random path in the graph.

Language: Mathematica - Size: 3.03 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

garthmortensen/finance

Contains financial studies work, including capital markets, corporate finance and other topics.

Language: MATLAB - Size: 17.6 MB - Last synced at: about 2 years ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 1

sam14032000/market_linkages_mgarch-bekk

Study on volatility transmission and protuberance among developed and developing stock markets using multivariate GARCH

Language: Jupyter Notebook - Size: 160 KB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 3 - Forks: 0

israelcastilloh/mx-stocks-analyzer

Dashboard for return, volatility and correlation analysis for the NAFTRAC IPC. Mexican Stock Exchange (BMV).

Language: Python - Size: 4.17 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 1

aguumg/Calculo-de-Volatilidades-en-R

Algoritmos en R para las volatilidades propuestas en el Capitulo 9 del libro Paul Wilmott Introduces Quantitative Finance.

Size: 5.7 MB - Last synced at: about 2 years ago - Pushed at: almost 4 years ago - Stars: 0 - Forks: 0

maltseva88/Times-Series-Analysis

In this notebook, I've loaded historical Dollar-Yen exchange rate futures data. I've applied time series analysis and modeling to determine whether there is any predictable behavior.

Size: 5.49 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 1