- April 17th, 2004, 11:55 pm
- Forum: The Quantitative Finance FAQs Project
- Topic: How do GARCH processes work?
- Replies:
**56** - Views:
**268083**

<t>The long memory property of S&P 500 daily returns has been documented in Ding and Granger (1996). Long memory Garch models include PARCH (Ding, Granger and Engle (1993)) and FIGARCH/FIEGARCH (Baillie, Bollerslev and Mikkelsen(1996)). There might be others as well. PARCH seems to be easier to ...

- January 6th, 2004, 12:01 am
- Forum: The Quantitative Finance FAQs Project
- Topic: How do GARCH processes work?
- Replies:
**56** - Views:
**268083**

<t>Exotiq,If the data is skewed you are going have a hard time fitting a square into a round hole (i.e. a skewed distribution into a normal distribution). You are assuming that the GARCH parameters will somehow able to explain way the skewness. It might, but then again it probably will not. I don't ...

- December 28th, 2003, 5:27 pm
- Forum: The Quantitative Finance FAQs Project
- Topic: How do GARCH processes work?
- Replies:
**56** - Views:
**268083**

<t>Exotiq, Two strends of not-so-developed literature out there ... One estimates the skewness and kurtosis a la GARCH style, done in additional to variance estimation. The kurtosis and skewnes is, if memory is correct, time varying. The results are not very statisfactory. The other estimates the ga...

- December 9th, 2003, 4:06 pm
- Forum: The Quantitative Finance FAQs Project
- Topic: How do GARCH processes work?
- Replies:
**56** - Views:
**268083**

<t>Lees, See #2, #3 and #5 below for possible reasons for your problem.Reasons for "badly behaved" parameters:1) bad starting values (ex. starting values where loglikelihood is undefined or close to undefined, value too far from the optimum value, etc.)2) sample too small -- not enough data points t...

- November 21st, 2003, 1:37 pm
- Forum: The Quantitative Finance FAQs Project
- Topic: How do GARCH processes work?
- Replies:
**56** - Views:
**268083**

<t>Muzzex,1) Does these packages offer the ability of variance targetting? If GARCH's volatility is too high and you do not have large enough sample, the constant in the volatility equation might be important. Usually people estimate that constant. However, another way is to use variance targeting. ...

- November 21st, 2003, 4:13 am
- Forum: The Quantitative Finance FAQs Project
- Topic: How do GARCH processes work?
- Replies:
**56** - Views:
**268083**

<t>Habib, In general you'll like to have more observations than less. A report Engle and I prepared a while back indicates that parameters estimated from small sample such as 500 observations tend to be unstable. 1000 or more would be better. Anyway, it's a good question. I think the best way to mea...

- November 19th, 2003, 1:12 pm
- Forum: The Quantitative Finance FAQs Project
- Topic: How do GARCH processes work?
- Replies:
**56** - Views:
**268083**

<t>MAE and RMSE might not be the best criteria to use. The distribution of squared returns (sq'd rt) is quite non-normal. I suspect, don't know for sure, that these forecasting criteria might best be used if data is close to normal. One idea might be to use the log of sq'd rt vs. log of the forecast...

- November 18th, 2003, 7:06 pm
- Forum: The Quantitative Finance FAQs Project
- Topic: How do GARCH processes work?
- Replies:
**56** - Views:
**268083**

<t>Remember the squared returns are just a proxy for the realized and unobservable variance. You'll have to define "perform very bad." What criteria are you using? Are you sure you moving average has the same informationally content as your GARCH model? That is you are not using information at time ...

- November 12th, 2003, 1:00 pm
- Forum: Technical Forum
- Topic: Justification for MLE
- Replies:
**26** - Views:
**190533**

<t>Criteria are created because we don’t live in asymptopia. They are small sample corrections, as you term it ad hoc. Theories do not tell you which one is the most reasonable. If the theory doesn't show you the way, then what do you have left to go on? Schwarz criterion (BIC) is usually more restr...

- November 12th, 2003, 5:12 am
- Forum: The Quantitative Finance FAQs Project
- Topic: How can I simulate correlated random numbers?
- Replies:
**34** - Views:
**296483**

<t>QuoteOriginally posted by: blueseasearching choleskey decomposition in google lead me to this page.I have such topic this quarter and what my instructor`s equation is X=chol(cov())*randn()+Mu()I have no idea why it is the product of chol, not directly of covariance? Cholesky decoposition remain t...

- November 12th, 2003, 4:55 am
- Forum: The Quantitative Finance FAQs Project
- Topic: How do GARCH processes work?
- Replies:
**56** - Views:
**268083**

<t>QuoteOriginally posted by: mrbadguy2.Could be interesting comparing Black-Scholes versus GARCH option pricing models given following process for conditional variance in Garch(1,1): h(t+1)=w+alfa*epsilon(t)*h(t)+beta*h(t) any ideas?Thanks.There are two published papers on GARCH option pricing. One...

- November 12th, 2003, 3:33 am
- Forum: Technical Forum
- Topic: Justification for MLE
- Replies:
**26** - Views:
**190533**

<t>adannenberg, they don't teach this in grad school, huh. When it comes down to it there is no easy answer. There is no magic bullet that will work in all situations. A method that works for one set of models might not work for another. As you have alluded, nothing replaces real world human experie...

- November 10th, 2003, 6:31 pm
- Forum: Technical Forum
- Topic: High-multivariate correlation forecasting
- Replies:
**6** - Views:
**189785**

<t>There are three methods that I am aware of that might make this problem tractable. Riskmetric uses exponential moving average to estimate correlation between assets. It's not too difficult to implement. Robert Engle's new DCC (Dynamic Conditional Correlation) model is able to estimate large corre...

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