<t>QuoteOriginally posted by: jfuquaQuoteOriginally posted by: APSMore importantly, Econometrica or Journal of Finance generally publish articles that are meant to increase our understanding of the people's decisions in the world around us. They're not meant to be Financial Engineering or Mathematic...

<t>More importantly, Econometrica or Journal of Finance generally publish articles that are meant to increase our understanding of the people's decisions in the world around us. They're not meant to be Financial Engineering or Mathematics journals. If you use a continuous time model of utility maxim...

<t>Or, use large sample theory to obtain the standard errors. There exists large sample theory of maximum likelihood estimators, OLS, the method of moments, GMM, etc. Bootstrap is also good, but as soon as you try to analyze time series data, you have to be careful about using bootstrap. You can't j...

<t>A lot of the time people just estimate a GARCH(1,1) model and ignore other possibilities, perhaps following the reasoning that a very simple but possibly misspecified model is better than a complex misspecified model to avoid overfitting. There are probably some formal papers on p,q selection in ...

You can learn how to do useful things in MATLAB within a day. You can learn enough to be an expert within a few days or weeks. Given this consideration, there is no need to insist on using the exclusive OR in the statement about learning MATLAB OR ..

<t>You're right about the X\y trick, but that just solves the OLS problem. It would also solve the GLS problem after the X and y matrices are pre-multiplied by a Cholesky or some other factor of inv(G). It turns out there is no point in doing that as MATLAB has the lscov function for GLS in the pres...

<t>If I'd try to list all of them, I'd probably run out of blackboard space.. so I just said (BEKK, O-GARCH, DCC, etc). In think only in the last 10 years people have come up with more than a dozen interesting MGARCH models and their extensions. So, I am curious if anyone actually successfully appli...

I just posted a link to a (likely) relevant paper on the technical forum where you asked the same question.

<t>MATLAB is generally pretty weak when it comes to providing canned routines. If you want software that would solve your problem with a single command, look into something like gretl, STATA, or EVIEWS. As you know, the formula for GLS is trivial: B = inv(X'inv(G)X)X'inv(G)yPerhaps Matlab has it bui...

<t>I think you just opened a big can of worms here because how to actually apply the modern portfolio theory to find mean-variance efficient portfolios has been a research topic for a long time. Of course, the most simple way to do it is to use the historic mean vector and the sample covariance matr...

Most of us have studied the Markowitz portfolio theory. I am curious about its relevance in practical applications. Does anyone use this framework for portfolio management?

I am curious. What are the typical uses of Multivariate GARCH models (BEKK, O-GARCH, DCC, etc) in practical finance applications?

<t>I never looked into forecasting using GARCH, but I remember reading a paper that mentions that multi-step volatility forecasting is hard due to non-linear nature of GARCH, and that it's easier to do a multi-step forecast if you use something called AGARCH(p,q) model instead. AGARCH is like GARCH,...

<t>I am trying to understand what you're trying to do here. If you're trying to extract the white noise shocks (that is, the residuals) that are driving your model, then you can certainly do this for an ARMA-GARCH model. For an AR(1) model: y_t = B*y_t-1 + e_t, it's just e_t = y_t - B*y_t-1If you ha...

<r>I'd chip in with some obvious suggestions. First, you should know how to write R code efficiently (well, many R users know this, but I mention this just in case). There are three important optimization tricks (which are the same as for MATLAB).1) Do not grow arrays dynamically. If you need to fil...