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Trading System Development

Often, trading model developers “spoil” the eventual results of their model by making errors early in the process. These errors could be using poorly-collected data, not accounting for survivorship bias, or testing too many specifications of a similar model. Data snooping such as that can be particularly costly in that it is an error that cannot be reversed. Therefore, if you haven’t yet begun the active work of acquiring data, specifying a model, or backtesting, then you have the opportunity to conduct the testing and development process optimally.

Initial Review

For clients coming to us for trading model development, we find it efficient to first step back and begin with a broad discussion so that we can acquire a conceptual understanding of your idea and examine the strategy for face validity. Once comfortable with your hypothesis, we would begin the specifcation of a model meeting that investment thesis. During this early phase of developing the model, we would ensure that the model doesn’t suffer from any biases that are standard in finance or portfolio theory, such as data snooping bias or survivorship bias. We would do this by not testing too many models, using robust strategies that are not overspecified, and considering the effect of non-survivors in our datasets.

From there, we briefly discuss the means of trade execution that you will use in your system, which could be manual trade execution, automated trading, or a combination of both. We also discuss whether absolute return or risk-adjusted return will be the objective of the trading model, and the availability of the data needed to backtest and to trade the system in real time.

Once we feel comfortable that we understand the core goal of your trading model, and before we begin working on the formal quantitative analysis, we outline for you qualitatively what we believe to be the most effective way to develop the model. We also provide you with a brief report on the quantitative methodologies that we will use, based on the particular needs of your model.

Data Considerations

Our clients come to us requesting trading systems in various forms. We can develop models which can be traded in a trading software package such as Tradestation, Metastock, or E-Signal. We could give you results in a statistical programming language such as R or SAS, or in a standard programming language such as C++.

As most trading systems involve robust backtesting and sensitivity analyses, having a reliable and cleaned data set is of extreme importance. Many of our clients use external data feeds which provide real-time data for trading, but do not have historical databases included. In these circumstances, we often have the data needed to do more extensive backtesting, and/or can acquire it at a reasonable cost. If the data is in a difficult to use format, we have a data cleaning team who can convert the data set into something more useful. If you are working on a system that is dependent upon relatively new securities, the data may not exist. In this case, we would work with you to construct representative return streams that can be used to back-test your system through a wider variety of economic and trading environments than may currently be available.

Backtesting and Developing the Trading Model

Back-testing is one of the most important steps in model development. A positive result from the testing procedure is not a guarantee of future success, but it does indicate that sufficient evidence exists of the indicator’s success to include it in the final signal. We of course take into account commissions, bid/ask spreads, volume, and other trading costs and limitations during our testing procedures.

Our primary objective is that all of our work be both robust and fully replicable. We don’t help you to make trading profits by creating overspecified versions of a model, by testing dozens of indicators, or by testing multiple variations of the same core model until we find something that “looks good”. Our consulting team has wide experience in testing and optimizing trading systems, both academically and on WallSreet. They often confer over academic work that they are publishing, about the cutting edge strategies being developed every day in academia, or over their own models. Every member of our team knows that strategies need to be clearly specified beforehand in order to be robust, that multiple optimization attempts cannot be attempted on the same data set, and that violation of principles such as these will render valueless any predictions on the future performance of the model. This problem (data snooping resulting in non-robust results) is the issue that comes up the most for us when discussing with clients our plans to develop their trading model. Many of our clients come to us not fully understanding the biases that can be present in financial market data. We consider ourselves to be teachers and not just doers, and we will remain with you via phone, email, or in-person until you are completely comfortable with your understanding of these issues. The worst thing that can happen to a trading model developer is for he or she to inaccurately conclude that they have a profitable model, and to then lose both time and money trading that system until abandoning it for lack of success. Trading models that are created properly work in real-time, and not just in the past.

We use every tool in the portfolio theorists toolbox in order to optimally analyze (and revise if needed) your trading model. Due to our Wall Street and academic experience (every member of our team was at one point a professor of statistics, econometrics, economic theory, or finance), we are knowledgeable in almost every quantitative technique that is commonly used (and not so commonly used) in trading model validation and optimization, including but not limited to:

  • Time Series Analysis
  • Kalman filtering
  • Principal Components Analysis
  • Monte Carlo Simulation
  • Jackknife/Bootstrapping Techniques
  • General Autoregressive Conditional Heteroskedasticity
  • Black-Scholes Option Pricing
  • Simulation Based Option Pricing
  • Advanced Derivative Valuation
  • Path Dependent Security Pricing
  • Brownian Motion and Geometric Brownian Motion
  • Interest Rate Term Structure Modeling
  • Genetic Programming
  • Spot Rate and Overall Volatility Term Structure Modeling
  • Single-Factor Markovian Short-Rate Modeling
  • Time Varying Volatility Analysis
  • Securitization Analysis, Pricing, and Valuation (ABS, MBS, CDS)
  • CDS Pricing and Valuation
  • Steepest Ascent Optimization
  • Ito calculus
  • Simulated Annealing
  • Exhaustive (“Brute-Force”) Optimization
  • Covariance Matrix Adaptation-Evolution Strategy

Deliverables and After-Support

When your model is fully developed, we ordinarily send a final deliverable report which includes the entirety of our analyses, results, syntax code to replicate the analyses, and of course a full recomenndation. We will also continue to work with you on that model as you begin trading it, so that we can make any adjustments needed going forward, use more data from the new trading to confirm that our assumptions have proven accurate, run a power analysis in continuous time to ensure that we have sufficient sample size to validate the model in real time, and suggest other models that may work well in concert with your current model(s). We also would provide you with a risk-management review and further implementation recommendations.

Risk management is one of the most important aspects of trading system development. Even an ideal signal-generating procedure can produce negative results if position sizing, entries, exits, and/or leverage are suboptimally applied. We realize that every trader has a unique risk tolerance, and we work with you to ensure that you completely understand the risk-management process. We run your system through proprietary testing procedures designed to match the system’s risk to your risk tolerance. Our process minimizes or eliminates the risk of losing more than you are comfortable with. Our experienced programmers and analysts estimate conservative, realistic, and optimistic scenarios for the statistical distribution of each variable in the signal development process. These variables are then simulated millions of times across the entire range of their distributions, providing a clear conception of the maximum gains and losses of the system in a given unit of time. Further, maximum drawdown statistics are calculated and graphically displayed for the system across the same range of simulated histories. After discussing the results of our analysis, we consider your risk tolerance and provide you with advice on position sizing and the use of leverage.

Of course, we remain available for consultation on any of these issues, either at that time or in the future. Trading models can’t be carried out by rote (this is true of even automated trading systems), they need to be understood conceptually. We will remain with you, in a professorial role that is still familiar to many of us, until you have that conceptual understanding.

The final stage of the development of a trading model is execution. We can help you select the ideal platform with manual or automated execution. Manual trading is typically reserved for medium- to long-term systems, as it requires regular and extensive human intervention; in contrast, short-term systems require rarer interventions, as automated trading systems handle most of the trading. There are various trading software packages, not all of which support automated trading. The ones that do may not be suitable for your specific system. Moreover, some packages may require in-depth programming before automated trading is possible. We can help you discover precisely the service your new model requires and help you integrate your selection with your current systems and operations. Here is a selection of services in which we are proficient:

  • Alaron
  • AmiBroker
  • Bright Trading
  • FXCM
  • GAIN Capital /
  • Gateway Capital
  • Infinity Futures
  • Interactive Brokers
  • IntesaTrade
  • JPR Capital
  • Lind-Waldock
  • MB Trading
  • OptionsXpress
  • Patsystems
  • REDIPlus
  • Tradecision
  • TradeStation
  • Trading Technologies
  • WealthLab


We understand the importance and necessity of confidentiality when dealing with any trading model or idea, and provide all of our prospective clients with a Non-Disclosure Agreement immediately upon contact. This ensures you that your idea and/or existing model will not be shared with any third parties, and your consultation with us is completely confidential.

Please click here to read our Data Security Policy.