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Balazs Szekely

Research and Insights

Articles by Balazs Szekely

    Adaptive Backtest for Expected Shortfall

    Research Report | Oct 18, 2017 | Carlo Acerbi, Balazs Szekely

    Expected Shortfall (ES) replaced Value at Risk (VaR) under the Basel Committee’s Minimum Capital Requirements for Market Risk in 2016. However, whether ES can be backtested is still an open and critical question. We have recently shown that ES can be only approximately backtested, because any ES backtest is sensitive to VaR predictions. This paper proposes a new ES backtest that has the minimum possible sensitivity to VaR predictions, which makes it an appropriate validation tool for ES-based...

    Keeping Indexes Investable in Evolving Markets

    Research Report | Mar 24, 2017 | Pavlo Taranenko, Carlo Acerbi, Sebastien Lieblich, Balazs Szekely

    Market liquidity around the globe has changed drastically over the past decade, due to a combination of regulatory, technological and investment changes. Relative trading volumes on many primary trading venues have dropped by about 50% since their peak in 2009. To ensure the investability and replicability of MSCI equity indexes, we regularly monitor the liquidity of index constituents, apply liquidity screening criteria and review index construction rules and liquidity measures. Methodology...

    Backtesting Year in Review - A look at 2016

    Research Report | Mar 3, 2017 | Carlo Acerbi, Thomas Verbraken, Balazs Szekely

    For the year ending December 31, 2016, we analyzed the 12-month risk forecast accuracy of four categories of simulation models available in RiskMetrics RiskManager: Monte Carlo, historical, filtered historical and weighted historical.

    Stress Testing Portfolios: Best Practices for Shockwave Propagation

    Research Report | Sep 19, 2016 | Carlo Acerbi, Thomas Verbraken, Zsolt Simon, Balazs Szekely

    Scenario propagation is the second stage of predictive stress testing practices, following scenario definition. This paper illustrates common pitfalls and suggests best practices for a robust propagation of the shockwave of a prospective scenario onto all relevant risk factors of a financial portfolio. The central observation: Risk managers must guard against “noise” in the predictions. Diagnostic statistics can reduce noise and ensure meaningful predictions. Key best practices include: the...

    Backtesting Risk Models - August 2016

    Research Report | Aug 26, 2016 | Carlo Acerbi, Thomas Verbraken, Balazs Szekely

    For the July 2016 backtesting review, MSCI began by analyzing how each of four types of simulation models available in RiskMetrics RiskManager—Monte Carlo, historical, filtered historical and weighted historical—performed over the year ended June 30, 2016.

    Backtesting Year in Review - A Look at 2015

    Research Report | Feb 12, 2016 | Carlo Acerbi, Thomas Verbraken, Balazs Szekely

    For this year’s backtesting review, MSCI began by analyzing how each of four types of simulation models available in RiskMetrics RiskManager—Monte Carlo, historical, filtered historical and weighted historical—performed over the year ended December 31, 2015.

    Backtesting Risk Models - Mid-Year

    Research Report | Sep 2, 2015 | Carlo Acerbi, Thomas Verbraken, Balazs Szekely

    Risk measures, such as Expected Shortfall and Value at Risk, are designed to calculate the risk of a portfolio. But different risk models may work better than others for different asset classes and in varying time horizons. The MSCI Model Scorecard provides an innovative tool designed to help select the best risk model in terms of Expected Shortfall (ES) and Value at Risk (VaR) predictivity.

    Backtesting Expected Shortfall - A Practical Guide

    Research Report | Jul 22, 2015 | Carlo Acerbi, Thomas Verbraken, Balazs Szekely

    Expected shortfall (ES) has attracted controversy as a measure of a portfolio’s risk since it was introduced in 2001. One reason for this was that some critics suggested ES could not be backtested. Last year, however, MSCI proposed a way of backtesting expected shortfall. This development is especially important in the light of the Basel Committee on Banking Supervision’s recent decision to adopt ES in place of VaR. The ability to backtest expected shortfall also has broader...

    Research Insight - Backtesting Expected Shortfall - December 2014

    Research Report | Dec 2, 2014 | Carlo Acerbi, Balazs Szekely

    In this white paper, we join the debate over Expected Shortfall versus VaR by introducing three model-independent, nonparametric back-test methodologies for Expected Shortfall, which we find more powerful than today's standard Basel VaR test. Our three Expected Shortfall back-test's generally require the storage of more information, but we find no conceptual limitations nor computational difficulties. In fact, one of the proposed back tests does not require any additional storage of data from...