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5

I would create categories, and work on risk parity among the categories. Otherwise, variance is not really a good measure of downside risk: Change your risk measure, use a rolling window historical VaR or Expected Shortfall at some horizon that matches your investment style. downside semi-variance could do the trick too if don't want to change your algo ...


5

You can find an exact algorithm with a step-by-step explanation here: https://www.dropbox.com/s/t4fq067kzx26mhw/project_paper.pdf As you can see from the URL it is an archived document because the original site is unfortunately long gone and the tool referenced in the paper with it :-( But it should be helpful anyway to understand what is going on. Notice ...


3

Assume $p_i(x)$ is a payoff of one particular option. You can try to reproduce the diagram using a bunch of options with strikes on the breakpoints (underlying is useless, because its payoff can always be modelled by buy&sell of a certain call and put). Then you can create a system of k equations with n unknowns (number of each kind of option). All other ...


2

I have experience of C# as a strategy client at the end of a VB .Net ticker plant. The latency fluctuations caused by the garbage collection could be in the order of seconds! And occurred every four or five minutes with a stream of a 1000-ish ticks a second. I was the first engineer to test our trading system in this way, it was a shock to all concerned and ...


2

I'd recommend M. Joshi and T. Leung "Using Monte Carlo simulation and importance sampling to rapidly obtain jump-diffusion prices of continuous barrier options". Though it assumes jump-diffusion process for the returns it is straightforward to obtain the scheme for a diffusion process. Also Paul Glasserman's [book][2] [2]: ...


1

Are you working with futures data (mixing rate futures with equity futures) OR allocating between macro instruments? If so, using non-linear variants of GARCH (GJR-GARCH, TGARCH etc.) are common way to solve your risk parity allocation issue that you might be facing. One common related issue is not that the volatility to a couple of instruments drop ...


1

I know this is a really old question but here is something I ran into while trying to do essentially the same thing. One of the problems that you face when trying to detect patterns using (say) k means clustering is how do you encapsulate a pattern. For example, suppose on a certain day the index goes up 2% over a minute and then goes down 1% over the next ...


1

Hello people. This is quite a complex problem if you want to solve this in a computationally efficient way for a rolling window. I have gone ahead and written a solution to this in C#. I want to share this as the effort required to replicate this work is quite high. First, here are the results: here we take a simple drawdown implementation and ...



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