In the first post of the DVI series, we concluded with a simple system that performed pretty well in a 26 diverse ETF universe. In the past I have found more strategies with similar or performances, and then the real challenge (and fun) for me starts. How do we trade this strategy?
To further pounder this, I guess I have spent +90% of my research time to find nice strategies. At the beginning of this year I forced myself to stop searching and to start trading based on the 3-5 most promising strategies. I am glad I did as I learned a lot about trade execution, setting up my infrastructure, the discipline of trading etc. Today I still trading with a relatively modest account of 25k$ (more will added when I feel I have mastered the routine), but I still do not have a framework telling me how to should split my money and divide across strategies, how many strategies etc.
My objectives aim to generate 10-15% uncompounded a year with ~10% DD. As a consequence of the ~10%MaxDD requirement, most investors will agree to diversify their investments to reduce risk. This comes straight from the text books on Modern Portfolio Theory (MPT). But how does this diversification work with mechanical strategies? Can we treat mechanical strategies as individual assets as described in MPT? And if so, what would be a good way to select and combine mechanical strategies into a portfolio of strategies? How do we decide to activate and deactivate strategies?
Maybe these questions are all very easy to answer for people with more financial education/investor/trading experience but I have not sorted them out yet (I hold an MSc degree in Mech Engineering and an MBA). So I invite all readers to help me sort these out, please comment!
In the mean time, I am reading and experimenting to deepen my understanding. Some interesting topics I have found are the developments around the Adaptive Time Machine by David Varadi, the latest book by Ralph Vince (The Leverage Space Model – LSPM) and it’s implementation in R discussed over at FOSStrading.
Here is what my current line of thinking is.I am going to try to validate this in the coming weeks and see if I can work this out into a workable setup for my own trading.
- when taking a position, one should never trade below a certain minimum value because of transaction costs. Let´s say 2500$.
- returns coming from trading strategies behave like returns from individual assets and so MPT or LSPM models hold for them
- define the tools to be used to experiment
- use MPT or LSPM to find an optimum allocation of money to trading strategies maximizing reward vs risk of drawdown
a) experiment with number of strategies added and their correlations
b) investigate the difference when applying a strategy vs individual ETF’s or applying a strategy vs a universe of ETF’s and threat the return stream as an individual stream
c) investigate on/off switching of strategies based on their historical performance
- translate into a practical setup
I started off on the 2nd post on the DVI system, but I felt that I had to clear this out of my system first. I will post the 2nd part on the DVI system pretty soon.