Hot answers tagged kernel
First, I assume that your price data are all from the same asset but spread over a certain time range. If you are looking for the distribution of the price of this asset on the real axis, you have plenty of methods (several fields in mathematics and statistics deal with this topic). As a first step you could make a histogram of your data. There you can see ...
The problem is to find the best functional form of the utility function plus estimate its parameters. A good starting point is the following draft chapter from an upcoming book which gives a good intuition and many examples: Preferences by Andrew Ang
One simple approach is Construct the cumulative probability function (CDF), which will be a step-function. Smooth the CDF; for example, by using splines or a kernel smoothing function. Calculate the slope of the smoothed CDF, giving a curvy linear PDF. In R, this could be done using the ecdf function and one of the kernel smoothers. Again, as vanguard2k ...
The cross-validation procedure does not turn on the choice of algorithm. Yes - calculate the prediction error of the fitted models when predicting the V'th part of the data. Combine the V estimates of prediction average using a simple average. Subsets should be randomly sampled (roughly equally sized). 2a. Subsets should not overlap. No. As long as the ...
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