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Quant Concept FAQs Print E-mail


By combining the latest studies in the areas of hedge fund risk management and asset allocation with the best industry practices, Quant framework delivers a comprehensive yet easily accessible system designed to address the practitioner needs. In a way it changes the entire canvas of investing into hedge funds, thus arousing many questions of "how" and "why".

What is the main difference between Quant and the traditional frameworks?

The most distinctive features can be summarized as follows:

  • Analyzing distribution based metrics (ex. high moments, VaR or CVaR) rather than mean-variance indicators
  • Taking into account nonnormality of hedge funds' distributions of returns
  • Using high moment statistics
  • Discounting formal and shallow labeling of manager styles according to the index categorization
  • Identifying a real manager style drift based on multi factor analysis
  • Fund of funds portfolio optimization routines based on non-linear and global optimization
  • Using distribution fitting to replicate hedge fund distributions of returns and address short series problems
  • Employing unique proprietary frameworks of Trend Segmentation™ and FlexiRank™

Can Quant platform be used by "non-quant" people?

Yes, by all means. Quant framework was designed not for quant geeks but for any hedge fund investors demanding robust risk tools:

  • The system is extremely easy to use and requires just a basic investment expertise
  • Our latest macroeconoimic scenario screening was designed for senior management and investment desision makers, who require screening investment vehicles based on macroeconomic views
  • Quant framework and applications fill the gap between the advanced analytical models and practical applicatoins that can be effectively digested by any hedge fund investor

What is wrong with the classic CAPM and mean-variance frameworks?

Distributions of hedge funds’ returns exhibit a high extent of nonnormalities. Therefore, the commonly used mean-variance methodology is not applicable. Using the standard deviation and its derived statistics, as measures of risk, is highly misleading, when it comes to hedge funds.

Why are you using genetic optimization algorithms?

Applying distribution based metrics entails analysis and optimization of multi extreme functions. In turn, this leads to inapplicability of the classic quadratic optimization methods and requires deploying the global optimization framework. From the practitioner’s point of view, this means that most commonly used software applications for the asset portfolio analysis and risk assessment are inapplicable, because of incorporating the quadratic optimization methods.

Genetic algorithms present one of the most powerful methods of global optimization allowing optimization of nonlinear multi extreme functions. This makes them a powerful tool to address the complexity of hedge fund portfolio optimization.

Does Quant system use the TAA framework?

No. The TAA (Tactical Asset Allocation) framework implies constructing fund portfolios based on their labeled strategy and a pattern behavior of the corresponding indices or benchmarks. Unfortunately, it suffers from numerous drawbacks when it comes to hedge funds:

  • Fund managers may use multiple strategies, which makes it difficult to categorize
  • The whole TAA concept relies on the style-weighted allocation (read index-weighted allocation) that predetermines allocation across individual funds. Since the majority of hedge funds are not correlated with their corresponding indices, the applicability of TAA becomes questionable

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Is Quant a pure quantitative framework?

No. We fully understand the drawbacks and pitfalls of a "pure data mining" approach and do not think any risk assessment can be done blindly based on numbers and figures. Quant framework is built on a sensible balance between the quantitative and qualitative methods. In fact, sophisticated quantitative risk assessment should help identifying potential bottlenecks of the applied trading strategy and, as such, should be enhanced by deep qualitative analysis.

Are the methods and techniques used in Quant completely new?

No. Not at all. The methods of stochastic modeling, distribution analysis and multi-extreme optimization have been developing for years (if not centuries). Quant framework combines and integrates the most suitable techniques to address hedge fund return peculiarities and irregularities. Trend Segmentation™ and Flexirank™ techniques (patent pending) are new.

What is Trend Segmentation™ technique?

Trend Segmentation™ (TS) technique is a proprietary method of screening and analyzing underlying assets based on different ‘trend conditions’ of the driving economic factors (or benchmarks). It is based on an assumption that managers tend to exploit the same strategies and make the same mistakes during similar market conditions. The TS engine analyzes factor (or benchmark) returns and divides its series into a several groups of similar market conditions. Then it calculates the risk-return metrics of the analyzed assets over the identified time segments.

Could Quant framework be applied to any non-linear assets?

While many Quant analytical methods and techniques can be effectively used for analyzing a broad range of instruments (for example, distributions analysis, style valuation, performance attribution analysis, VaR analysis or Trend Segmentation™ could be used for equity evaluation), the framework has been designed to address specific hedge fund issues. It has never been intended to be fully applicable to any financial instruments.

Could Quant help in identifying hedge fund fraud?

Yes, many Quant techniques can help you in exposing return anomalies and discrepancies in strategy descriptions. One of our case studies, The Madoff's Fraud Exposure, illustrates how easily one could spot Bernard Madoff's fraud using Quant Suite applications. Contact us to get access to Quant video library and case studies.

Could Quant help me to avoid the losses of 2008 crash?

Yes, using Quant techniques you may easily expose funds with inappropriate hedging strategies that are exposed to excessive risk during certain market conditions. Quant Platform can identify these devastating markets and find bottlenecks in manager trading strategies. We have numerous case studies illustrating how Quant approaches can spot hidden-risk managers that show no alarming signs when using traditional risk evaluation. Contact us to get access to Quant video library and case studies