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The first yet most important step in a hedge fund portfolio construction involves screening and filtering funds from the hedge fund universe. With over 8,000 funds in a typical database, this task may become hardly doable unless robust quantitative filtering tools are applied. Quant Screen component incorporates a set of software tools providing fund screening and hedge fund universe truncating according to the defined selection criteria.

Structure

Typical Tasks

  • Selecting fund subsets satisfying the given risk/return profiles
  • Screening funds exhibiting high/low correlations with the given benchmarks
  • Macroeconomic Screening: selecting funds the provide a given risk/return profile under a certain Macro model
  • Identifying funds driven by user-defined economic factors
  • Selecting funds with defined beta and alpha to any factor (benchmark)
  • Identifying trend followers and trend neutral funds
  • Creating fund subsets (wallets) with different filters for further portfolio construction
  • Deselecting "red flag" funds to minimize the qualitative due diligence subset
  • and many more...

Features

  • Native screening of VaR-based metrics (VaR, CVaR and MVaR)
  • Multiple screening filters
  • Embedded Macroeconomic Scenario Builder
  • alpha and beta filtering against 2,300+ factors
  • cross-vendor screening (Global Universe search)
  • Taking into account market factors and benchmarks (ex. correlation to benchmarks)
  • Identifying trend followers and market neutral funds
  • Creating an unlimited number of screened subsets (wallets) for further analysis
  • Adding custom factors and benchmarks

Why It Matters

Quality. The investment quality and risk assessment accuracy of the selected funds determine overall quality of the assembled portfolio. Quant Screen provides the most accurate framework for a fund risk valuation taking into account nonnormality of their distributions of returns by applying downside risk metrics (ex. ETL, LPM, Omega, MVaR etc.). Using the common measures like the standard deviation for the screening purpose leads to unpredictable results and, strictly speaking, is hardly applicable for hedge funds.

Exposure. The larger the size of the fund universe, the better investment opportunities of constructing a perfect portfolio. In practice, many bad investment decisions are derived from the limited choice of investment candidates resulting in cross investments and, in turn, poor asset diversification. Quant Screen tools offer a powerful solution to minimize the fund pre-selection time regardless of the size of the database.

Filters. Quant screening engine goes far beyond the common fund filtering criteria based on the standard deviation and mean return. It offers a broad choice of the advanced filters including correlations to the given factors (benchmarks), market neutrality, skewness, kurtosis and many more.

Screen Filters

  • VaR, MVaR and CVaR
  • Mean return
  • Max drawdown
  • Skewness and kurtosis
  • Alphas to market factors
  • VaR ratios
  • Trend segmentation
  • Betas to market factors
  • Hurst Exponent
  • Correlation to benchmarks
  • AUM
  • and many more...

Trend Segmentation

Trend Segmentation™ Screening is a proprietary routine of measuring fund’s performance relative to different market cycles. This technique takes into account the direction of the established market trend, while its concept is based on a simple consideration. Each fund manager has certain strong and weak skill points and, therefore, cannot perform equally across any market conditions. Furthermore, managers tend to employ similar trading tactics over recognizable market patterns.

The output of Trend Segmentation™ engine presents three fund subsets (bins) ranking managers across all market conditions: uptrend, downtrend and trendless. Knowing the tendency of the underlying funds’ performance during different market cycles and ranking the styles accordingly, a practitioner may greatly enhance portfolio performance, since it gives a clue to constructing dynamically trend-adjusted portfolios.