Topic: volatility-modeling Goto Github
Some thing interesting about volatility-modeling
Some thing interesting about volatility-modeling
volatility-modeling,Python wrappers around QuantLib and Pandas to easily generate volatility surfaces
User: aaronsmith1234
volatility-modeling,Algoritmos en R para las volatilidades propuestas en el Capitulo 9 del libro Paul Wilmott Introduces Quantitative Finance.
User: aguumg
volatility-modeling,
User: aguumg
volatility-modeling,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. Itβs evident that Bitcoin functions as a central node, which means it has the highest likelihood of appearing on a random path in the graph.
User: amalsebastian7
volatility-modeling,Public repo of some of my options modeling projects
User: antek0308
volatility-modeling,Implement pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, Heston
User: artursepp
volatility-modeling,Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.
User: bottama
volatility-modeling,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.
User: boyla950
volatility-modeling,Stock Market Data - Correlations/Visualizations/Calculations
User: cgowda337
volatility-modeling,GARCH and Multivariate LSTM forecasting models for Bitcoin realized volatility with potential applications in crypto options trading, hedging, portfolio management, and risk management
User: chibui191
volatility-modeling,Traditionally, volatility is modeled using parametric models. This project focuses on predicting EUR/USD volatility using more flexible, machine-learning methods.
User: csatzky
volatility-modeling,Repository for code used in my bachelor-thesis with the title: "Analyse der Prediction-Power von Recurrent Neural Networks am Beispiel von Finanzmarktdaten"
User: estrixds
volatility-modeling,Market Data & Derivatives Pricing Tutorial based on Jupyter notebooks
Organization: frontmark
volatility-modeling,Collection of numerical methods for high frequency data, in Python notebooks
User: gaelwjl
volatility-modeling,Contains financial studies work, including capital markets, corporate finance and other topics.
User: garthmortensen
volatility-modeling,Predicting Market Volatility
User: gaurav7888
volatility-modeling,GARCH models to forecast time-varying volatility and value-at-risk in R
User: ggstream12
volatility-modeling,This repository includes the scripts to replicate the results of my paper entitled "A False Discovery Rate Approach to Optimal Volatility Forecasting Model Selection".
User: hkalager
Home Page: https://doi.org/10.1016/j.ijforecast.2023.07.003
volatility-modeling,computes Volatility Spillover between Cryptocurrency (BTC/USD) and S&P 500 index
User: hobinkwak
volatility-modeling,Topological Tail Dependence: Evidence from Forecasting Realized Volatility
User: ibaris
volatility-modeling,IBOVESPA volatility forecasting
User: imsanjoykb
Home Page: https://imsanjoykb.github.io/
volatility-modeling,Dashboard for return, volatility and correlation analysis for the NAFTRAC IPC. Mexican Stock Exchange (BMV).
User: israelcastilloh
volatility-modeling,SABR Implied volatility asymptotics
User: jackjacquier
volatility-modeling,I investigate the Asymmetric Volatility Spillover Effects within and across six major International stock markets. United States, Canada, France, Germany, Italy & Japan
User: jolly-io
volatility-modeling,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.
User: kedarghule
volatility-modeling,Toolbox for time series modelling
User: lkamocsai
volatility-modeling,Predicted Volatility: Applying Predicted Volatility to Determine Profitability of Cyclical and Defensive ETFs
User: lrb924
volatility-modeling,Undergraduate thesis, Seoul National University Dept. of Economics β "Modeling Volatility and Risk Spillover Between the Financial Markets of US and China Using GARCH Value-at-Risk Forecasting and Granger Causality."
User: majorlift
volatility-modeling,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.
User: maltseva88
volatility-modeling,A vectorized implementation of py_vollib, that supports numpy arrays and pandas Series and DataFrames.
User: marcdemers
volatility-modeling,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.
User: martinmashalov
volatility-modeling,Analyze a personal portfolio of stock's past performance and forecast future performance to optimize daily positional adjustments to create a 20% monthly return
User: maurolp15
volatility-modeling,Quant finance notebooks from PQN course
User: mikewenner
volatility-modeling,Implementation with a Jupyter Notebook of the VIX index modelization provided in its CBOE white paper.
User: qlero
volatility-modeling,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.
User: quant-tradingco
Home Page: https://github.com/Quant-TradingCO
volatility-modeling,The workings for a very interesting exercise from the Econometrics of Financial Markets module of the MSc Quantitative Finance 2023/24 course at Bayes Business School (formerly Cass).
User: radusbriciu
volatility-modeling,Model which predicts the volatility of a company's stock based on the shareholder meeting transcripts over the years for the Fortune 500 companies. This model is based on BERT and GPT-3 LLMs to summarize and predict the volatility.
User: raghuram-veeramallu
volatility-modeling,Code for the paper "Realized Semi(Co)Variation: Signs that All Volatilities are Not Created Equal"
User: sakethaleti
volatility-modeling,Study on volatility transmission and protuberance among developed and developing stock markets using multivariate GARCH
User: sam14032000
Home Page: https://sam14032000.github.io/research/1/
volatility-modeling,Portfolio Performance Analysis
User: sashaflores
volatility-modeling,Machine learning for financial risk management
User: siruiji
Home Page: https://www.oreilly.com/library/view/machine-learning-for/9781492085249/
volatility-modeling,Financial time series forecasting using R
User: vladonmyown
volatility-modeling,This repo is about forecasting the Yen movements in order to know whether to be long or short.
User: vmieres
volatility-modeling,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.
User: white07s
volatility-modeling,Implementing Bitcoin futures' strike prices and time-to-maturity to construct a volatility surface for potential profit opportunities. Utilizing time series and the GARCH model for volatility forecasting and Long Short-Term Memory (LSTM) for bitcoin futures' price forecasting in Python.
User: xli253
volatility-modeling,Measure market risk by CAViaR model
User: yatshunlee
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