Over the course of its many years of involvement in investment
research, design and management, ZCM has developed a variety of
software products in the financial field. These products are available
as turn-key packages, as customized software, or as consulting or
Over the course of its many years of involvement in investment research, design and management, ZCM has developed a variety of software products in the financial field. These products are available as turn-key packages, as customized software, or as consulting or joint-venture projects.
For all processing-intensive research tasks, ZCM utilizes high-performance IBM RS6000TM workstations (See About ZCM's Technology) using the SpeakeasyTM high-level computer language as a front end.
Some time ago, Speakasy Corporation approached ZCM about the possibility of creating a "Trader Workstation" for the IBM RS6000 machines as a value-added package to Speakeasy.
ZCM thus created EZ-MarketsTM, a sophisticated trader workstation package. The package incorporates a well-stocked trading toolbox of technical indicators and other technical and mathematical analyses with versatile graphics functions. A unique feature of EZ-Markets is that, because it is written in Speakeasy, it is very easy to customize the tool set as per client requirements.
The sophisticated functionality of the package includes: all the major technical indicators; basic and advanced charting capabilities; basic and advanced mathematical operators; forecasting modules, and much more.
EZ-MarketsTM is available as a value-added software add-on to the SpeakeasyTM high-level computer language. Please contact Speakeasy Corporation directly for more information on ordering this software.
In early 1999 ZCM started research and development for the Tick-Based SMP Program, a high-frequency trading version of ZCM's SMP (Statistical Multi-Pattern) trading methodology. The Tick-Based SMP Program uses real-time transaction, or "tick" market data as input.
In order to implement this approach, since all data manipulations at ZCM are carried out using the SpeakeasyTM high-level computer language as a front end, a real-time data feed capability had to incorporated into the Speakeasy language.
With the help of Speakeasy Corp., ZCM created this value-added capability. While the application of interest was market transaction data, the real-time datafeed Speakeasy capability is completely general. Thus, applications can be envisaged for unattended data collection procedures, remote log-in and session intervention, and more.
In the financial datafeed application, the data stream is received by the workstation, the data is filtered for the desired market symbols, and the filtered data is fed into the Speakeasy processor as it arrives real time. Once there, the data can be added to, and processed as regular Speakeasy objects.
The basic modules of the Real-Time Datafeed capability for Speakeasy are available as part of the standard Speakeasy package. The additional modules dealing specifically with financial real-time data applications are available from ZCM as custom software.
ZCM has developed a powerful statistical tool to analyze the quality of the performance of portfolio managers, based on the application of powerful game theory concepts. The technique goes beyond simple profit/loss analysis, and can be applied to any asset class (We consider portfolios invested in any instrument that requires asset turnover a "trading" portfolio.) The methodology used to buy and sell the assets in the portfolio is irrelevant, as are the specific instruments involved. In particular, the Analyzer works equally as well on Systematic or Discretionary methods.
With the advent of cheap powerful computers in the 1990s, computerized trading methodologies became very popular. In the typical development of computerized trading techniques, certain trading rules are coded and applied to a certain database of past market data. The parameters of the encoded trading rules are then optimized to generate the best risk/reward profile for the hypothetical portfolio.
While this procedure is a very powerful selection process for profitable trading strategies, it has one potentially huge drawback: the scourge of "overfitting", or "curve-fitting." Since the rules and parameters are self-selected to give the best possible profile for the past, it is quite possible that the model has been "overfitted," to the past data, and the same rules and parameters will be useless in generating profitable trades in real time.
Even if the trading model has not been overfitted, it frequently happens that a model that was "in synchronicity" with the markets for a certain period, becomes gradually -or suddenly- "out of sync" with the markets, and starts behaving in an undesirable manner: most commonly, it starts incurring losses heavier than expected from the simulations with the past data. The usual reason for this to happen is that, after the model has been in "real-life" use for some time, a market scenario is encountered which was not present in the past data used to develop the model. As the financial markets are constantly in flux, this is not an uncommon occurrence.
The development of computerized trading strategies being one of the core activities of ZCM, it became clear that a tool was needed to monitor the behavior of trading models, and if possible get an early warning of the model becoming out of sync with the markets.
The Trading Portfolio Risk Analyzer was created with this goal in mind.
With discretionary trading, the problem of overfitting of the trading model does not exist, since the trader is generally not rigidly enslaved to the behavior of past data as a systematic model would be; however, the phenomenon of getting "out of synchronicity" with the markets remains very much a problem. Discretionary portfolio managers may become "out-of-sync" due to an inability to evolve with changing market conditions, to personal life difficulties, to burn-out, or to many other individual factors.
Although ZCM's trading methodologies are all systematic, it became clear, after some experience with using the Trading Portfolio Risk Analyzer, that it could be applied as successfully to discretionary trading techniques as to the computerized methodologies it was originally designed for.
Since the seminal and revolutionary work by Markowitz in the 1950s, "efficient frontier" analyses of mixed portfolios have become commonplace.
Markowitz-type analyses have three drawbacks: One, the definition of risk; two, that they admit only a single objective function; three, that it is difficult to introduce constraints.
In the Markowitz approach, in order to generate a solution to the problem, "risk" has to be equated to "asset variance." In simple terms, risk is equated to the volatility of the portfolio components. That is, the more volatile the asset class the more risk it supposedly brings to the portfolio. With this assumption, the problem is reduced to a quadratic level, and is easily solvable.
Nevertheless, in terms of actual portfolio management, most managers are aware that portfolio risk is not equal to asset volatility. Portfolio risk is best described by the statistical distribution of drawdowns1 that is likely to occur for a given investment strategy. While volatility and portfolio correlation may be large contributors, the Markowitz approach leaves out two even more important contributors to drawdowns: Sequential loss and event confluence. Thus, for instance, a volatile asset class used with a strategy that generates small probabilities for large sequential losses may introduce only small drawdowns, while a low-volatility one may do quite the opposite. Unfortunately, the drawdowns distribution is a highly nonlinear function of the portfolio weights, so that, if this definition of risk is used, the Markowitz approach becomes useless.
The second drawback is that the analysis only allows for optimization of a single objective function: Minimize the risk, or maximize the return, but not both at once. As for the third, it restricts the applicability of the approach, since in most real life cases managers want to have very strong constraints in their portfolio construction.
Because of these limitations, ZCM engaged in an effort to find a more useful solution. Fortunately, ZCM research was able to generate a computer solution to the general portfolio optimization problem: Multiple fully-nonlinear objective functions with multiple fully-nonlinear constraints.
With this general solution, ZCM has applied the algorithm to the specification of an optimal portfolio allocation to multiple markets, using the worst drawdown 2 as the measure of risk, and maximizing returns and minimizing drawdowns simultaneously.
The technique can, and has been, applied also to optimization of the allocation of equity to multiple investment managers, with constraints tailored to the "manager of managers" requirements. Furthermore, the general nature of the algorithm allows application to a very wide range of constrained nonlinear optimization problems.
The Fully-Nonlinear Asset Allocator is available through an ASP (Application Service Provider) arrangement with ZCM, as a custom software package, or for consulting or joint-venture projects.
(1) A peak-to-valley drop -an equity loss- observed in the portfolio's cumulative profit/loss curve, or "equity line."
(2) An extreme in the distribution of drawdowns.