Daniel P. Palomar
Daniel P. Palomar
This is related to @yihui comment in Issue #422 : > @dataopt [Algorithms](https://en.wikibooks.org/wiki/LaTeX/Algorithms) are different with theorems in LaTeX, so they cannot be implemented as easily as theorems. The major...
Thanks for writing pseudocode.js. It looks quite amazing. By default, pseudocode.js does an automatic numbering starting at 1. I am personally trying to use it in a book, so I...
### Description One of the great advantages of `xts` is its flexibility in indexing the observations with dates and so. However, I found a strange behaviour after I change the...
Implement a risk parity portfolio to equalize the risk factors. Basic reference is: T. Roncalli and G. Weisang, “Risk parity portfolios with risk factors,” SSRN 2155159, 2012.
When generating a pdf book (via latex), the references are included at the end of the book. I wonder how one could include the references on a chapter basis, i.e.,...
- Obviously, revise the existing code and vignette. - Allow for box constraints (not allowed already?) - Include optional mean and variance terms in the objective apart from the tracking...
List of things to implement: (@dppalomar, @mirca) 1. Compare our method with the nonlinear solver optim() in the vignette. 2. Try using the QP solver solve.QP() after the first majorization...
Due to volatility clustering, the variance changes over time and it might be more realistic to implement a rollowing-window approach to fitting+imputation.
Version 0.1.1 can deal with outliers in the price time series. However, it cannot deal with price jumps where the outlier is persistent.
In the current package version, one can specify every how many days the portfolio needs to be rebalanced/reoptimized (with the arguments `optimize_every` and `rebalance_every`. However, one may want to specify...