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On Trading of Equities: A Robust Control Paradigm


Abstract: The objective of this paper is describe a new paradigm for the trading of equities. In our formulation, the control corresponds to a feedback law which modulates the amount invested I(t) in stock over time. The controller also includes a saturation limit Imax corresponding to a limit on the value at risk. The admissible stock price evolution p(t) over time is modelled as a family P of uncertain inputs against which we seek robust returns. Motivated by the fact that back-testing of candidate trading strategies involves significant cost and effort associated with computational simulation over sufficiently diverse markets, our paradigm involves the notion of synthetic prices and some idealizations involving the volatility of prices and trading liquidity. Our point of view is that a robust performance certification in this somewhat idealized market setting serves as a filter to determine if a trading strategy is worthy of the considerable time and expense associated with full-scale back-testing. The paper also includes a description of a so-called saturation reset controller. This controller is used to illustrate how the model works in practice and the attainment of robustness objectives over various sub-classes of P.

Author: B. Ross Barmish


  • JohnLast 2690 days ago

    Check this artcilce it is quite interesting by offering an independant validation tool for trading system.

    Here I can just summarize the common basic tools for validation of trading systems.

    -Sinple Back Testing with or without Out of Sample Validation

    -Walk Forward Testing

    -Monte Carlo analysis

    -Bootstrapping procedures 

    Here on this article a different paradigm is offered related with the Robust Control. It is worth to have a look at it.  

    Here is a video of the author


  • JohnLast 2688 days ago

    Guys you could really  watch this video the week - end, the video and sound quality is poor but content is king. I am analysing it.

  • JohnLast 2687 days ago

    The real problem is that the application of data mining on trading may be a wrong paradigm.

    Check was an experienced trader has to say on the topic.


    So I can add:

    data - mining + back - testing  =  tools for fools.

    In fact you can come out in the back - test pretty easily with nice looking equity curves.

    You can ask why a simple moving average cross over system with extensive search (brute force search) on all parameters has to be outperformed by any complex data mining algorythm?

    Theoretically both approaches should work.

    The problem with the market is that it is self reacting to itself. If the market was a mere physical process every data mining routine would work. But the market reacts to itself. That is why HFT was so profitable there, the first players in their time horizon were faced to a market that did not react to their strategies. And by doing so it was regarding to them a physical process that can be predicted. 

    This is a simple question but the answer is not obvious.

    Another remark is also very intereesting

    " Backtesting is the method of choice for destroying your career and your firm, if you own it. Backtesting is toxic to quants. there is only one possibly useful alternative. backtest once with a well defined prior."  Richard Michaud

    I think the robust control is the way to go. In that way everything mathces into mucch more complex paradigm. Data - mining and back - testing needed to be related with robust control. Otherwize it is toxic.