Everything You Need to Know About GARCH for Your Thesis
CrunchEconometrix
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Everything You Need to Know About GARCH for Your Thesis
19 236 просмотров · 6 лет назад
CrunchEconometrix
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19 236 просмотров · 6 лет назад
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Basics of GARCH Modelling in EViews - Volatility Tutorial for Finance Dissertation | UK, US, Canada
Are you writing your MSc Finance, Financial Economics, Banking, Risk Management dissertation on volatility modelling and new to GARCH? Your supervisor said ""model volatility using GARCH and you don't know where to start? This video covers basics of GARCH modelling in EViews - foundation before you estimate.
This is essential foundation for finance dissertations - 90% of volatility dissertations use GARCH family.
WHAT YOU WILL LEARN:
✓ What is volatility modelling - why volatility matters in finance - risk management, option pricing, portfolio allocation, Value at Risk
✓ What is ARCH model - Engle 1982 - conditional heteroskedasticity - foundation
✓ What is GARCH model - Bollerslev 1986 - generalized - more parsimonious - most popular
✓ Basics of GARCH modelling steps: Step 1 - Estimate mean equation (e.g., returns = c + AR(1)), Step 2 - Test for ARCH effects using ARCH LM test, Step 3 - Estimate GARCH(p,q) if ARCH effect exists, Step 4 - Diagnostics - standardized residuals white noise and no ARCH
✓ How to choose GARCH order - GARCH(1,1) most popular for MSc - why - captures most volatility clustering with few parameters
✓ What are extensions of GARCH: EGARCH, TGARCH, GARCH-M, IGARCH - when to use which - brief overview for literature review
✓ How to interpret basic GARCH output - ARCH coefficient (alpha) and GARCH coefficient (beta) - persistence = alpha + beta - should be less than 1
✓ What is unconditional vs conditional variance - difference - why conditional matters for forecasting
✓ How to explain GARCH modelling in dissertation Chapter 3 methodology - academic writing tips for UK/US universities
✓ Common mistakes MSc Finance students make: Not testing ARCH effects before GARCH, choosing high orders without justification, not checking persistence less than 1, not doing diagnostics
✓ What next after basics - how to estimate GARCH(1,1) in EViews - link to next videos in playlist
WHO THIS IS FOR:
MSc Finance, Financial Economics, Banking, Risk Management, Investment, Financial Engineering students in UK (LSE, Imperial, Warwick Business School, Manchester Business School, Cass, Birmingham, Leeds, Glasgow, Edinburgh), US, Canada, Australia, EU studying volatility. If your dissertation deals with stock returns, exchange rates, crypto, oil prices, this basics video is essential.
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WHAT IS COVERED IN THIS VIDEO:
What is volatility modelling and why it matters in finance - risk, VaR, options
ARCH model basics - Engle - foundation
GARCH model basics - Bollerslev - why more popular
Steps of GARCH modelling - mean equation, ARCH LM test, GARCH estimation, diagnostics
Choosing GARCH order - why GARCH(1,1) most popular for MSc
Extensions - EGARCH, TGARCH, GARCH-M, IGARCH - overview
Interpreting basic GARCH output - alpha, beta, persistence
Unconditional vs conditional variance
How to write GARCH methodology for UK dissertation
Common mistakes and what next
If this helped, LIKE, COMMENT your volatility topic and country, SHARE with classmates.
FAQ:
Q: What is difference between ARCH and GARCH? A: ARCH - conditional variance depends only on past squared errors. GARCH - depends on past squared errors AND past variances. GARCH more parsimonious.
Q: Why GARCH(1,1) most popular? A: Captures volatility clustering with just 2 parameters - parsimonious - sufficient for most finance data - less overfitting.
#GARCH #ARCH #VolatilityModelling #FinanceDissertation #MScFinance #EViews #TimeSeries #Econometrics #UKUniversities #RiskManagement #GARCHModelling #Volatility #FinancialEconometrics #EViewsTutorial #DissertationHelp #PhDResearch #GARCHBasics"
0:00 Foundations of GARCH Modeling
1:20 Generalizing the GARCH PQ Model
3:11 Why GARCH Models Outperform ARCH
4:17 Stylized Facts of Financial Time Series