"QSG has built its reputation on building customized stock selection models tailored to a client's unique strategy and goals," stated Tim Sargent, CFA, President and founder of QSG. âThe release of VRA v4.0 is testament to our commitment to providing our clients with the most innovative quant analysis tools while making their lives easier. Our goal is to narrow the gap between quantitative and fundamental managers and help both to make better investment decisions.â
âQSGâs Virtual Research Analyst v4.0 provides investment managers and research analysts a flexible platform to quickly create, backtest and put into daily production their stock selection strategies without worrying about the hassles of database managementâ, added Bola Olusanya, Managing Director. âBy handling these issues, we provide our clients with more time to focus on building and implementing more profitable strategies.â
New/Updated features in VRA v4.0 include the following:
â¢ Advanced Filtering & Screening
o QSG Research has shown that parameter changes are an often-ignored source of alpha. With VRA v4.0âs new filtering tool, users can create and save multiple filters based on absolute and change parameters.
o Filter based on multiple company attributes including stock and benchmark total returns over user-specified lookback horizons.
o On-the-fly Attribution of Sector/Industry/Size/Style of Client Portfolios, Universes, and dynamic Filters.
â¢ Easy Creation of User-Defined, Multi-Factor Models
o Leveraging QSGâs US and International Factor libraries of 600+ proven stock selection global indicators, users can instantly create their own unique multi-factor models.
o Easily share user-defined models across clientâs entire organization.
â¢ Automatic Email Alerts
o VRA v4.0 automatically sends users emails of daily, weekly and/or monthly changes in their dynamic screens and filters, allowing users to easily monitor changes in their Stock Selection models and enhance timely buy/sell decisions.
â¢ Enhanced Stock Level Drilldown
o Compare a stockâs total return to its Sector, Industry Group, Industry and Sub-Industry averages over multiple custom universes.
o Compare a stockâs historical rank time series over various equal- and value-weighted benchmarks.
o Easily view detailed Factor & Model definitions.