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I have re-read this thread and have some final comments. To me position/risk management can be grouped into: 1. Growth optimal position sizing under risk constraints and the assumption that your trading systems work (i.e. have an edge) and that future returns will be drawn from a distribution...

As always when you rely on historical relationships the warnings above are valid. Common sense should always be used. If your position sizing system comes up with a leverage of 800% then maybe you should think again before using it. Even if Ralph Vince among others (I think I have a reasearch...

As you say above, building the scenarios from historical data is the most crucial part of the LSP method. I guess it will always be hard to create a good, statistically valid method if you have little data. In that case you probably will have to work with some parametric method with the problems...

We’re currently using LSP so I might have some input. First some clarifications on what LSP does. The goal of LSP is to find the allocation among assets that gives maximum growth of capital given a drawdown constraint. It is not a mean-variance method (Ralph Vince seems to hate those). It uses...

I also like the work of Ralph Vince. His writing style and the fact that some of his definitions are different from those used by others mean that it may require some effort to understand the text, but once you get used to it there's a lot to learn from him.

Comparing GDP figures to determine standard of living is always tricky (even when using PPP). I remember reading an article about it in The Economist. One reason that GDP is higher in the US is that you work many more hours than we do in most countries in Europe, so you've really earned the...

For anyone new to system verification it is actually a good suggestion to use some silly ideas like the ones above in order to put together a systematic approach to verification. It can be psychologically easier to develop your methods if you investigate an idea you don't really believe in...

Be prepared that correlations will vary over time. So be very careful in your interpretations. Look e.g. at the 2009 rally in almost all asset classes. And the break-down of historically well-established covariances during 2008 that helped wipe out a large number of hedge funds. Beware that...

Congratulations and good luck trading with the big guys! /Hugin

These are interesting questions and I believe addressing them is required in order to have a working trading strategy. If the system generates long signals for 42 stocks in a 50 stock universe this is definitely something to look at. During back-testing such clustering of trades will mean...

I'm no FPGA expert but from what I've heard the solution Mitrionics provides is to convert code written in a variant of C into something that can be loaded into the FPGA. This should make it easier both to find developers and to verify the code provided that the platform includes some test...

About two years ago I heard about some guys that looked at implementing high frequency algorithms for a small hedge fund using tools from http://www.mitrionics.com/. Not certain if they did target Xilinx FPGA though. Haven't heard about them since. Maybe they're still in the lab...

I would consider anything that can affect the trading system's ability to generalize well to be a parameter. Apart from the explicit parameters of the model, this would include the selection of symbols, the range of dates for training/back tests etc. We rely heavily on optimization methods...

For a trade indicator to be useful I believe it should be consistent and not signal a trend if the underlying price generating process does not include one. The problem is that even if you construct a time series with no trend component, an increase in volatility may make some trend indicators...

I use an adaptive, rather short, window of up to 40 days. The main benefit over most other standard trend indicators is that it addresses fake trends due to volatility changes. I've done some tests on various time series in Excel with various volatility and most time my eyes agree with the...

We have used a trend indicator based on regression. The basic input is the steepness of the regression line using the price data. One problem with trend indicators is that a change in volatility may be interpreted as a trend which results in false indications. To handle this the slope is...

I like Ralph Vince's Leverage Space Portfolio model. Implementing his principles requires you to know about optimization (e.g. Genetic Algorithms) and requires a bit of coding, so it may not be for everyone. What I find especially interesting is that he address geometric growth under the...

We coded the one we use, so I'm not familiar with the capabilities of standard software tools, like TS, Ninja, etc. Maybe someone on ET knows more about the support of portfolio level testing in these tools. If not, then this would be nice feature to implement as part of a portfolio test function.

Depends on what you trade, but for stocks I suggest a Monte Carlo simulation comparing the result from your system with a large (>10000) number of random "systems" that just randomly selects symbols and dates. The random trades should be the same number and length as the trades from your...

As I understand from a quick look is that they instead of looking at the log of close to close returns use the log of the high to low ratio as the "return" in the calculation of the volatility estimate. So its not just the high to low over the entire window which, as you say, would become a...