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5
votes
2answers
438 views

How to use a realized kernel?

I've read that realized kernels are the thing to use for calculating daily volatility from high-frequency data. So I've got minute data, how do I actually use such a kernel? Will it give me minute-ly ...
5
votes
2answers
665 views

How do you synthesize a probability density function (pdf) from equally weighted price data?

What I'm working with: I have a collection of prices that has very few to no repeating values (depending on the look back period) ie each price value is unique, some prices are clustered and some can ...
4
votes
1answer
145 views

Estimating investor's utility from the trades data

Is it possible to infer investor's utility function from the set of decisions she is making? Let's assume for simplicity that the market consists of a single traded asset whose return distribution is ...
3
votes
1answer
147 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 ...
2
votes
1answer
47 views

Data Selection for Empirical Pricing Kernel Estimation (Stochastic Discount Factor)

I want to estimate an empirical pricing kernel for an index. Hence, I need to estimate a physical and risk neutral density. For estimating the physical density, only the index data in an observed time ...
1
vote
0answers
105 views

Pricing binary options with kernel density estimation

Suppose I have a large enough set of prices of an asset, from which I can extract the following function: $f:T\to\mathcal{D}$, where $T$ is a fixed finite set of time intervals (say, 1 minute, 2 ...