PORTFOLIO RE-BALANCING

Product Overview          Features/Benefits         Technical Architecture         Client Profiles         Quantal Risk Estimates

 

Our core financial technology consists of global "hybrid" multi-factor models for stocks and Government bond returns. The hybrid model combines the accuracy of an implicit factor specification -- where common risk factors that cause stocks to move together are inferred from those stock co-movements -- with the explanatory power of an explicit model in which risk exposures are attributed to cross-sectional characteristics. Quantal's tried and tested risk forecasts allow users to solve a wide range of portfolio and basket trading objectives. Unlike explicit factor models or two-step hybrid models, the implicit factor based risk and returns models are especially responsive to structural shifts in the marketplace, and we are able to provide accurate forecasts of risk exposure to investment managers over their portfolio rebalance horizons.

Quantal PRO (Portfolio Risk and Optimization)
Combines our proprietary global risk estimates with a flexible portfolio optimizer and a specialized report generator, to provide a complete portfolio management solution for financial institutions, high net worth money managers, fund of funds managers, and long-short equity hedge fund managers. Already in its third generation, Quantal PRO has a proven track record in the portfolio analytics industry and is known as the leading offering for up-to-date reliable factor risk estimates. Our professional services organization complements the Quantal PRO solution by providing on-going support and consulting services to clients.

Quantal PRO's strengths lie in up-to-date multifactor risk models that quickly respond to shifts in factor structure, thus providing investors with accurate forecasts over their portfolio rebalance horizons. The globally integrated model for conditional equity portfolio risk enables users to reliably predict, analyze, and control risk as the market evolves over time. The model can be used to provide estimates of tracking error relative to benchmark indexes, to reliably attribute portfolio risk to security characteristics (industry/sector, value/growth, style, size, etc.), to correctly incorporate baskets like ETFs into portfolios, and to take into account other objectives and constraints (trading costs, turnover, daily volume constraints, etc.) in rebalancing portfolios. The model works equally well in long-short and long-only portfolio applications.

The built in optimizer can easily be configured to incorporate user-defined objectives, allowing investment managers to evaluate and implement unique portfolio strategies.

An integrated suite of tools for viewing, analysis, risk attribution, charting, audit trailing, and report generation allows investment managers to efficiently perform their portfolio management tasks and generate up-to-date reports for their clients.

The implicit factor based model is capable of adapting to structural shifts as they occur, or even to market-level behavioral swings in the market, so ensuring that forecasts capture the dynamics of the underlying factor structure. By contrast, explicit factor models require a revision in the model specification to capture these changes. The ability to adapt to structural shifts in the factor structure allows the implicit factor-based model to protect investors from being surprised by new sources of risk.

Structural models, where all the emphasis is put on explicit factors that may have been incorrectly specified to begin with, or become out-of-date due to changes in companies' competitive products, positions and strategies, changes in management, etc. cannot protect clients from such shifts in these factors. Given an accurate estimation of the implicit factor structure, the investment manager is then able to accurately relate factor risk to meaningful explicit characteristics, in essence a hybrid model approach. The approach is more reliable than so-called two-step hybrid models, where an explicit factor approach is applied first, and then an implicit factor approach is applied to capture the remaining "residual" factors. This two-step approach is fundamentally misconceived: if the explicit factor structure in the first step of the two-step model is properly specified, the second implicit factor step is redundant; alternatively, if the explicit factor structure in the first step of the two-step model is incorrectly specified, the exposures fitted to the explicit factors are just as incorrect as they are sans the second step, nor are they corrected in the second step.

 

Features/Benefits

Highly flexible portfolio management environment includes consistent framework for domestic and international securities.

  • Investment managers can manage their global portfolios according to their individual investment styles and security holding preferences.

  • Daily-updated, forward-looking conditional risk estimates of securities, and combinations of securities, that adapt optimally to unforeseen market shocks.

  • Protects investment managers from being surprised by new sources of risk in their portfolios. "Fat-tailed" unconditional distribution of market returns.

  • Provides more realistic estimation of market risk and returns.

  • Reliable and efficient procedures for measuring portfolio exposures to characteristics such as industry/sector, size, momentum, P/E, dividend yield, price-to-book, style, etc.

  • Investments managers can easily and flexibly take into account the drivers behind the performance of their portfolios.

  • Easy to model and control partial and total exposure to user defined characteristics and/or user defined portfolios.

  • Investment managers can tailor their risk exposure profiles and choose how to benchmark their portfolios against established indices or customized portfolios.

  • Integrated specialized optimizer with broad set of tunable and user-defined parameter inputs, including trading costs.

  • Simplifies what-if scenario analysis and implementation of unique investment strategies, while taking into consideration the impact of trading costs.

  • User-friendly graphical interface, desktop folders and broad set of utilities that provide optimized portfolio viewing, universal analysis, charting, audit trailing and report generation capabilities.

  • Useful for both "bottom up" or "top down" up-to-date portfolio management and external client reporting purposes.

  • Simultaneous optimization of both total portfolio risk and tracking error.

  • International portfolios can be chosen to take advantage of "alphas" stemming from the average investor's home-country bias (this bias makes passive index strategies inefficient)

  • Easy to incorporate user specific valuation estimates of individual securities, while taking into account total portfolio impact

  • Innovative investment strategies for clients. Examples include: Buy-write/Volatility arbitrage strategies; "Alpha Transport" Structures.

Quantl PRO Platform

Technical Architecture

Quantal PRO system is based upon an advanced scalable clustered Multi-Tier Client/Server software architecture that integrates open standard software, a reliable database and Quantal's proprietary financial algorithms.

 

Client Tier: Quantal PRO Client
The Quantal PRO client is a high standard Java Application based on the extensible framework of XML and SWING classes using Java Technology. The dynamic Graphical User Interface (GUI) can be easily be customized to meet individual client preferences. We also provide the Quantal API (Application Programming Interface) for other proprietary or third party systems to directly interface to our servers. Direct access to our servers through the Quantal API can significantly reduce server throughput time for high volume users.

Server Tier: Quantal PRO Server
The Quantal PRO server is built around the Apache Web Server and JBoss Application Server embedded with Tomcat servlet container. JBoss is an open source J2EE based application server, which is also certified as J2EE compliant by Oracle. The JBoss server is deployed in a scalable clustered configuration that provides high availability and load-balancing to the Quantal PRO clients. Primary and secondary server co-location centers guarantee maximum system up time.
The connection between the Quantal PRO Client and the Quantal PRO Contact Server is built on top industry standard choice of protocols: HA-RMI, HTTP and SSL (RSA, RC4, DES 128 bit encryption).

Application Tier: Quantal PRO Optimization Server
The Quantal PRO Optimization Server is a standard Web Service Server that uses SOAP (Simple Object Access Protocol) Protocol for communication. The Quantal PRO Optimization Server wraps Quantal's proprietary optimization algorithm. The Optimization Server takes requests from the Quantal PRO Contact server and performs the optimization based upon the portfolio parameters. The Quantal PRO Optimization Server is also designed with high availability and load-balancing capability to meet growing client demands. The protocol between the Quantal PRO Application Server and Optimization Server is based on industry standard SOAP.

Benefits of Quantal PRO's System Architecture:

- High-Availability - Front-end server availability is 99.9%

- Hosted Operation - Zero maintenance for Users.

- Automatic Updates - Users always receive the latest version of software.

- Industry Standard 128 bit encryption - High security and privacy when transporting portfolios.

- Multiplatform Support - Users can choose to run Quantal PRO in Windows, OS X, and Linux environment.

 

Client Profiles


Our clients include enhanced index and index-tracking fund managers, domestic U.S. and international long-short equity hedge funds, investment advisors, equity derivatives traders, companies taking correlation into account in CDO ratings, and funds involved in PIPES transactions.

Quantal Risk Estimates


This product delivers daily updates of our global conditional volatility and correlation estimates for direct input into users' risk management systems, derivatives pricing models, and basket trading models. Our global risk estimate adapts itself quickly to structural shifts in the securities universe by placing more emphasis on the recent past and by using reliable daily data and stable procedures that estimate the factor structure implicit in security "returns" (Why the quotes? ) behavior. Our global securities universe includes all traded equity securities worldwide.


On a daily basis, the internal team of experts and automated control processes consistently monitor the quality of the securities data in order to provide highly reliable and stable risk forecasts to our customers and partners.