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3
votes
3answers
111 views

What is the rationale behind using SV models with 2 distinct volatility processes?

In the Double Heston model, there are 2 distinct volatility processes. The SDEs read \begin{align} & d{{S}_{t}}=r{{S}_{t}}dt+\sqrt{{{v}_{1}}(t)}{{S}_{t}}d{{W}_{1}}(t)+\sqrt{{{v}_{2}}(t)}{{S}_{t}}...
0
votes
0answers
32 views

In what situations would cross validations scores be inaccurate?

I'm trying to fit a SVM model on times series stock return data, predicting a buy, hold, or sell signal of the stock. I'm using 10-fold cross validation (using the R package ...
5
votes
2answers
196 views

How does the number of free dimensions of a model affect its required size of sample?

Adding more variables to a model usually increases its accuracy. However, without adequate analysis it could also lead to curve fitting. Another question (How much data is needed to validate a short-...
1
vote
2answers
352 views

Choosing attributes for SVM classification?

Let's assume I am classifying every trading day as a 1 or a 0. Exactly what I am classifying doesn't matter, but for the sake of this question let's say I am predicting direction of price change. So, ...
4
votes
1answer
175 views

How to properly cross-validate when optimizing SVM classification?

I'm using SVM binary classification to predict movement of NASDAQ stock prices. My question is regarding cross-validation. I will divide the training data into V subsets. Training will be performed on ...