Zeal Asset Management selects TS Imagine for real-time portfolio and risk management for quantitative investment strategy
TS Imagine, a leader in trading, portfolio and risk management solutions for capital markets, has been selected by Zeal Asset Management, as the platform to run their quantitative investment strategy.
Broker-dealers understand the importance of producing accurate margin calculations for their clients’ accounts, but they need to know more than just how much margin each client must post; they need to know why the margin system came up with a given result.
In times of stress in the markets, not only does volatility increase for individual assets, cross-asset correlations can increase dramatically as well. This results in a “double whammy” for a typical portfolio because the portfolio’s volatility increases due to both effects.
Those responsible for maintaining a margin system often feel that they are drowning in data management issues. In part two of this series we discuss ways to make margin calculations far more efficient and meet the firm’s need for answers in real-time.
Computing, optimizing and monitoring real-time margin requirements across a multitude of instruments and customer accounts is a Herculean task. In this article, Imagine discusses the key challenges in this arena and will dive deeper into the specifics of solving its challenges.
Global cloud-based portfolio, risk and margin solutions provider Imagine Software has announced the expansion of its asset class offering to structured product issuers and traders.
Imagine Software Expands Asset-Class Coverage and Delivers Cloud-Based Solution for Structured Products
New models and workflows support structured products combined with cost and operational efficiencies of Imagine’s cloud-based solution.
When newcomers to the field of quantitative finance are assigned the task of writing up an analysis, they will often show numbers using five, six or even more digits to the right of the decimal point. This may be driven by the part of the brain that craves precision and exactness. Given the unstable nature of financial data, does that mean it is a fool’s errand to try to estimate risk?