Master Volatility with ARCH & GARCH Models скачать в хорошем качестве

Master Volatility with ARCH & GARCH Models

🚀 Master Quantitative Skills with Quant Guild https://quantguild.com 📈 Interactive Brokers for Algorithmic Trading https://www.interactivebrokers.com/mk... 👾 Join the Quant Guild Discord server here   / discord   ___________________________________________ 🪐 Jupyter Notebook https://github.com/romanmichaelpaoluc... TL;DW Executive Summary Volatility is an unobservable measure of variability in the return space We can proxy for volatility in a backward looking sense (historic or realized volatility) or in a forward looking sense (implied volatility) There are many stylized facts about volatility including the leverage effect, volatility clustering, excess kurtosis (fat tails, leptokurtic return distributions) Naïve parametric models fail to capture these dynamics and severely underestimate tail risk - a big problem! Engle proposed ARCH, an autoregressive conditionally heteroskedastic model capable of modeling these dynamics improving forecasts! Bollerslev proposed a generalized ARCH model (GARCH) which is an infinite order ARCH model, thus a more parsimonious version GARCH can capture richer dynamics with fewer lags, impressive! These volatility models outperform other models that do not account for dynamics especially in the context of risk modelling as we saw in our VaR example in this video I hope you enjoyed! Roman ___________________________________________ 📖 Chapters: 00:00 - Introduction 04:00 - What is Volatility? 05:17 - Realized or Historic Volatility 09:07 - Implied Volatility 12:05 - Volatility Risk Premium 15:01 - Which Volatility Does ARCH/GARCH Model? 16:38 - Kurtosis and Excess Kurtosis in Returns 21:23 - Stylized Facts of Volatility to Model 25:38 - Modeling Volatility in a Pre-ARCH World 26:16 - ARCH Models 30:15 - Example: EWMA vs. ARCH for Volatility Forecasting 32:35 - Dynamics of Volatility the ARCH Model Captures 36:01 - GARCH Models 40:52 - Applications of ARCH/GARCH Models 43:43 - TL;DW Executive Summary ___________________________________________ 🗣️ Shout Outs A special thank you to my members on YouTube for supporting my channel and enabling me to continue to create videos just like this one! ⭐ Quant Guild Directors Dr. Jason Pirozzolo ___________________________________________ ▶️ Related Videos Quant Builds 🔨 How to Build a Volatility Trading Dashboard in Python with Interactive Brokers    • How to Build a Volatility Trading Dashboar...   Statistics and Trading Profitability Over Time (Edge) 📈 Expected Stock Returns Don't Exist    • Expected Stock Returns Don't Exist   How to Trade    • How to Trade   How to Trade Option Implied Volatility    • How to Trade Option Implied Volatility   How to Trade with an Edge    • How to Trade with an Edge   How to Trade with the Kelly Criterion    • How to Trade with the Kelly Criterion   Quant Trader on Retail vs Institutional Trading    • Quant Trader on Retail vs. Institutional T...   Quant on Trading and Investing    • Quant on Trading and Investing   ___________________________________________ 🗂️ Resources 📚 Quant Guild Library: https://github.com/romanmichaelpaoluc... 🌎 GitHub: https://github.com/RomanMichaelPaolucci https://github.com/Quant-Guild 📝 Medium (Blog):   / quantguild     / quant   ___________________________________________ 🛠️ Projects The Gaussian Cookbook: https://gaussiancookbook.com Recipes for simulating stochastic processes: https://papers.ssrn.com/sol3/papers.c... ___________________________________________ 💬 Socials TikTok:   / quantguild   Instagram:   / quantguild   X/Twitter: https://x.com/quantguild/ LinkedIn (personal):   / rmp99   LinkedIn (company):   / quant-guild   ___________________________________________