How to simplify risk management, asset allocation and options trading through volatility and GARCH forecasting

(Last Updated On: June 19, 2012)

How to simplify risk management, asset allocation and options trading through volatility and GARCH forecasting

 

Hi there,

Want a better idea of how everything in the quant forest fits together?

A number of you have asked me to briefly explain quant algos and ideas at a basic level so you can understand their benefits more clearly. I’m happy to accommodate you. I enjoy teaching, and this also gives me the opportunity to demonstrate why a Quantlabs.net Premium membership is an exceptional value for you.

Today’s topic is about forecasting volatility. There are 3 main reasons you’d want to do this: risk management, asset allocation, and options speculation.

1. You can’t manage risk without an accurate measure of potential losses which themselves are based on future volatilities and their correlations.

2. Assets can’t be allocated sensibly without minimizing risk relative to expected return — again, you need an accurate way to estimate the variance-covariance matrix.

3. As for options trading, you’re no doubt well aware that options prices are highly correlated to volatility.

Now GARCH (Generalized Auto Regressive Conditional Heteroskedactic) is all about predicting future volatility. It models data series that exhibit periods of crazy swings followed by periods of relative calm, which is exactly what interests us as traders. Key ideas behind GARCH modeling:

* If an asset price made a big move yesterday, it’s more likely to make a big move again today

* Volatility not only spikes during crises, but it eventually drops back to approximately the same level of volatility as before

* Graphs of post-crisis volatility exhibit kurtosis (fatter tails) before they drop back to “normal” levels

The various iterations of GARCH capture all these points and more with complex equations forming each model.

And the good news is that, I cover GARCH in-depth in my Algorithm, Modelling, and Strategy Development course. It’s one of the many, many tools for which I provide the source code in R, tutorial videos, and everything you need to know to use it correctly and profitably.

Get everything now:

–>http://quantlabs.net/dlg/sell.php?prodData=m%2C3 <–

Learn about the rest of Premium benefits including our HFT and Algo Development courses, software tool kits, and more!

–> http://quantlabs.net/quant-member-benefits/ <–

Good trading,

Bryan

P.S. Risk management and asset allocation are key principles for any serious quant trader. And if you’re interested in any kind of options trading — many quant traders are! — GARCH’s volatility forecasting is absolutely essential.

I’m also providing source code for pairs trading, cointegration, estimating, simulation, and much more. It’s all coming ASAP!

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NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!
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About caustic

Hi i there My name is Bryan Downing. I am part of a company called QuantLabs.Net This is specifically a company with a high profile blog about technology, trading, financial, investment, quant, etc. It posts things on how to do job interviews with large companies like Morgan Stanley, Bloomberg, Citibank, and IBM. It also posts different unique tips and tricks on Java, C++, or C programming. It posts about different techniques in learning about Matlab and building models or strategies. There is a lot here if you are into venturing into the financial world like quant or technical analysis. It also discusses the future generation of trading and programming Specialties: C++, Java, C#, Matlab, quant, models, strategies, technical analysis, linux, windows P.S. I have been known to be the worst typist. Do not be offended by it as I like to bang stuff out and put priorty of what I do over typing. Maybe one day I can get a full time copy editor to help out. Do note I prefer videos as they are much easier to produce so check out my many video at youtube.com/quantlabs