توضیح 1
The live starter code is self-contained and uses only runner-compatible functions.
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درس 16 از 22
Advanced Topic – Optional. Compare sign-sensitive GJR, EGARCH, APARCH, GARCH-M, and stochastic-volatility ideas.
Advanced Topic – Optional
This chapter extends the core pathway. Complete Chapters 1–14 first, then use this material when your question and data justify the added model complexity.
Motivation
Equal positive and negative return shocks can have unequal volatility effects; asymmetric recursions expose that assumption.
Why this matters
Compare sign-sensitive GJR, EGARCH, APARCH, GARCH-M, and stochastic-volatility ideas.
Packages and data
Base-R mechanics; rugarch and stochvol are optional production tools.
توضیح 1
The live starter code is self-contained and uses only runner-compatible functions.
توضیح 2
Book-only outputs are labelled when the separate source dataset or advanced package was not supplied.
توضیح 3
R code, paths, function names, and formulas remain left-to-right in every locale.
اصطلاحات
Maps the prior innovation to next conditional variance with other inputs held fixed.
Visualize sign effects
Adds gamma for negative innovations.
alpha+gamma response below zero
Latent log variance has its own innovation.
Not deterministic from past returns
نمادگذاری و فرمولها
sigma_t^2 = omega + alpha e^2 + gamma I(e<0)e^2 + beta sigma_(t-1)^2
Under symmetric innovations, a common covariance-stationarity condition is alpha + gamma/2 + beta < 1.
مثال حلشده
سناریو
How much larger is next variance after a -3% shock than a +3% shock?
بررسی با R
shock <- c(-.03,.03)
base <- .000004 + .88*.0002
next_var <- base + (.06 + .10*(shock<0))*shock^2
print(data.frame(shock,next_var))
print(next_var[1]/next_var[2])
print(.06+.10/2+.82)Holding prior variance fixed isolates the specification's sign-sensitive response. Limitation: The curve is a model implication, not an observed causal law or investment signal.
Visual
Negative and positive shocks of equal magnitude imply different next variance.
ارتباط با R
Run the self-contained starter code in the protected STATLAB R runner. The code prints an auditable result and avoids network or unrestricted file access.
Live R Lab
Run a self-contained example, verify its output, and explain one limitation for asymmetric and extended volatility models.
Ready to run
Common mistake
Do not transfer stationarity constraints across EGARCH, GJR, and APARCH; parameters differ.
STATLAB Tip
Plot the news-impact curve beside standardized-residual diagnostics.
تمرین هدایتشده
سناریو
Vary gamma from 0 to 0.2 and compare both sides of the news-impact curve.
Compare your result with the definition, units, and model assumptions—not only with a target number.
Exercises
Complete these without looking at the selected solutions. More than one defensible program may exist.
توضیح 1
Calculate next variance for ±2% shocks.
توضیح 2
Explain EGARCH positivity.
توضیح 3
Contrast response after an isolated extreme return.
Selected solutions
These are compact solution routes. Confirm dimensions, units, and any changed modelling choices.
توضیح 1
Evaluate the recursion twice with indicator zero and one.
توضیح 2
Exponentiating any real log variance yields a positive variance.
توضیح 3
Stochastic volatility includes a separate latent shock; observation-driven GARCH does not.
Chapter summary
Compare sign-sensitive GJR, EGARCH, APARCH, GARCH-M, and stochastic-volatility ideas.
توضیح 1
News-impact curves expose asymmetry.
توضیح 2
GJR adds a negative-shock indicator.
توضیح 3
Extensions target different model components.
توضیح 4
Stochastic volatility has its own innovation.
اصطلاحات
GJR
Use in Asymmetric and Extended Volatility Models.
EGARCH
Use in Asymmetric and Extended Volatility Models.
APARCH
Use in Asymmetric and Extended Volatility Models.
impact curve
Use in Asymmetric and Extended Volatility Models.
References and provenance
Nelson (1991); Glosten, Jagannathan & Runkle (1993); Safavi (2026), Chapter 16. Student notes: Mohammad Safavi, Ph.D., STATLAB Academy, Version 1.0.
منبع
The authoritative 125-page English PDF accompanies this native lesson.
دریافتبازاندیشی
Name the assumption, evidence you would seek, and how the recommendation might change.
ارزیابی پایانی