As times change, so does the paradigm that we operate in. These are new times. These are “fat-failed” times requiring a new set of risk analytics tools. Our aim is to provide fresh and evolving risk management software solutions that enable practitioners to tackle the investment challenges they face in this new reality.
We at FinAnalytica draw on our core strengths and commitment to risk analytics sound research and risk management software development practices in all publications, presentations and product releases. We are dedicated to sharing our knowledge and expertise with the highest possible transparency. We strive to provide the most innovative and relevant risk analytics methodology. Our goal is to remain at the forefront of current and future risk management and portfolio construction issues by collaborating with our customers and our extensive academic network.
Latest Article and Case Study
17 Nov, 2011
Pensions and Investments: Standard risk measurement not enough: Eurozone crisis deconstructed
Taking a view on the sovereign debt crisis, Michael Palmieri and Svetoslav Delev, disucss how the most widely used risk measures lead institutional investors astray prior to market shocks.
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Latest White Paper
Broad Market Risk for Sector Fund of Funds: A Copula-Based Dependence Approach
Michael Stein, Svetlozar T. Rachev, Stoyan V. Stoyanov, Frank J. Fabozzi
We use a combination of sophisticated methods to measure the dependence of a sector FoF on the broad stock market, thereby modeling the univariate randomness of the variables adequately as well. A very parsimonious approach is used to allow for updating in high frequencies and on a regular basis using only recent information and therefore small data sets. This allows for a large variety of applications, from risk management and measurement, portfolio optimizations and scenario analyses to investment selection and hedging purposes as examples, the latter being critical for sector FoFs when adequate hedging tools are unavailable.
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Latest Book
Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization: The Ideal Risk, Uncertainty, and Performance Measures
Svetlozar T. Rachev, Stoyan V. Stoyanov, Frank J. Fabozzi
Wiley, February 2008
Version 4.0 offers enhanced ‘Tempered' Stable Distributions modelling and increased performance through new scenario caching. Users have access to expanded upside tail returns analytics and enhanced tail risk hedging models
FinAnalytica President Dr. Boryana Racheva-Iotova discusses how tail risk management can be a key source of added value in long horizon portfolio allocation and optimization.
Joel Nadelman of FinAnalytica and Randy Jones of PerTrac review the challenges that institutional investors face in selecting alternative investment managers and constructing resilient portfolios that balance risk and reward.
Accounting for fat tails of individual instruments is not the same as managing those tails at portfolio level. Svetlozar (Zari) Rachev and Georgi Mitov explore how advanced copulas might address the problem of fat tails, dependence models and portfolio risk.