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Mehmet Bayraktar

Mehmet Bayraktar
Head of Multi Asset Class Research

About the Contributor

As Head of Multi-Asset Class Research, Mehmet is responsible for driving the research agenda for MSCI’s multi-asset class portfolio and risk management analytics. A managing director, Mehmet previously was Head of Research & Chief Economist for the largest asset management firm in Turkey, Is Asset Management. Mehmet received his MBA from University of Chicago and his MSc in Finance & Economics from London School of Economics. He graduated with a B.A. in Economics from Bogazici University in Istanbul.

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Contributions by Mehmet Bayraktar

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  1. Many institutional investors develop proprietary return forecasting models, but use third-party/alternative models such as the MSCI Global Equity Total Market Model to measure risk and transaction costs. While there may be a significant overlap between the factors used in alpha and risk models, at times they may be misaligned. For managers who optimize their portfolios, the optimizer will tend to amplify the component of alpha that is not aligned with the risk model; this may lead to unintended portfolio exposures and unnecessary trading. This Research insight describes a practical process for detecting and addressing misalignment between alpha and risk factors.

  2. BLOG

    Are Your Factors Aligned? 

    Mar 10, 2016 Mehmet Bayraktar

    Integrated Risk Management

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    Many institutional investors develop proprietary return forecasting models, but use third-party/alternative models to measure risk and transaction costs.

  3. Heading into 2016, MSCI examined 12 stress points globally to be used in quantifying the effect on portfolios of a range of shifts in markets, liquidity and the macroeconomy. These stress points include the prospect of additional interest-rate hikes by the Federal Reserve, weakness in the eurozone and a deceleration in Chinese economic growth.

  4. PAPER

    Research Spotlight - Lost in the Crowd? Identifying and Measuring Crowded Strategies and Trades 

    Jun 26, 2015 Stan Radchenko , Stuart Doole , Mehmet Bayraktar , Altaf Kassam

    Factor and Risk Modeling , Investing (Investment Management) , Portfolio Construction and Optimization , Risk Management , Asset Pricing and Valuation

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    The “quant meltdown” of 2007 and the subsequent global financial crisis highlighted the risks of crowded investment strategies. The recent growth of “smart beta” indexes and their use in ETFs has added to concerns about crowding. In this Research Spotlight, we explore the risks posed by crowded strategies and explain how the MSCI Crowding Scorecard enables asset managers to assess these risks as they exist in today’s markets. The Scorecard employs four metrics that can help managers understand the risks of overlapping trading strategies, which may not be apparent by focusing on a single metric alone.

  5. AUTHORS: Mehmet K. Bayraktar, Stuart Doole, Altaf Kassam, Stan Radchenko

    The “quant meltdown” of August 2007 and the subsequent unfolding of the global financial crisis highlighted the risks of crowded investment strategies. The rapid growth of smart beta indexes and their use in ETFs has added to the need for scrutiny. In this Research Insight, we propose a set of four key metrics (our “Crowding Scorecard”) for monitoring and detecting the crowding risk of any particular investment strategy, building on our innovative analysis of historical behaviors of investment strategies and the MSCI equity risk models incorporating Systematic Equity Strategies (SES).
     

  6. BLOG

    USING SYSTEMATIC EQUITY STRATEGIES TO BUILD BETTER PORTFOLIOS 

    Apr 23, 2015 Mehmet Bayraktar

    Factor Investing

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    Systematic Equity Strategies, when represented as factors in risk models, allow investment managers to better monitor the sources of risk and return in equity portfolios. We believe that they also improve forecast accuracy and help construction of portfolios that tilt towards (or away from) these strategies, which are rules-based or computer-based implementations.

  7. BLOG

    U.S. MARKET BRIEF- MOMENTUM STRATEGIES OUTPERFORMED IN A VOLATILE MONTH 

    Feb 2, 2015 Mehmet Bayraktar

    Factors

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    January saw the return of volatility to the U.S. equity market. A confluence of factors led to this uncertainty: Investors were faced with the influence of a stronger dollar and the effect of lower oil prices on corporate earnings growth.

  8. PAPER

    Market Insight - Historic Drawdowns - A review of recent mutual fund active performance - July 2014 

    Jul 31, 2014 Mehmet Bayraktar , Stan Radchenko

    Performance Analysis , Risk Management

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    Actively managed large cap mutual funds have significantly underperformed their benchmarks from March 1 through April 30 this year, which has raised questions among investors since this happened during a flat stock market with volatility levels at historically low levels. In this paper, we demonstrate the significance of this recent performance, measure mutual fund tilts on investment styles and analyze the impact of these styles by calculating contributions of tilts to the performance of funds. We also compare the best- and worst-performing mutual funds and identify the key drivers of performance.

  9. PAPER

    Market Spin Cycle - The Rotation Continues... 

    Jul 14, 2014 Ting Fang , Mehmet Bayraktar , Stan Radchenko

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    In "Market Spin-cycle: Uncovering Style and Sector Rotation in a Flat Market", we investigated the sector and investment style rotations in the US market from March 1st through May 8th, 2014. In particular, we identified declining performance in growth-oriented styles associated with risk-taking behavior, such as Beta, Growth, and Momentum, with improving performance in Value, Profitability, and Size suggesting rotation in investment styles.

    In this follow-up paper, we extend this analysis through the end of June 30th, 2014 and observe a significant reversal in the rotation in investment styles seen between March 1st and May 8th, 2014. Using MSCI Barra models, we identify a decline in performance of quality-oriented investment styles that appeal to risk-averse investors, such as Asset Turnover, Profitability, Earnings Quality, Value and Size[1] and an outperformance of Beta, Growth, Momentum, and Residual Volatility, growth-oriented investment styles that are associated with risk-taking behavior.

  10. BLOG

    THE ROOTS OF ACTIVE MANAGERS’ UNDERPERFORMANCE IN MARCH AND APRIL 

    Jul 7, 2014 Mehmet Bayraktar

    Models/Client Cases

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    March and April of this year saw one of the worst periods of active performance over the past 10 years for actively managed portfolios. And this happened, despite a flat stock market and historically low volatility levels.

  11. PAPER

    Model Insight - Barra South Africa Equity Model (ZAE4) Empirical Notes - June 2014 

    Jun 12, 2014 Mehmet Bayraktar , Jay Yao , Jun Wang

    Factor and Risk Modeling

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    This Model Insight summarizes the methodology and empirical results for the fourth-generation Barra South Africa Equity Model (ZAE4). This paper includes extensive information on factor structure, commentary on the performance of select factors, an analysis of the explanatory power of the model, and an examination of its effectiveness in portfolio construction using minimum volatility and index tracking portfolios. It also includes a side-by-side comparison of the forecasting accuracy and backtesting performance of the ZAE4 Model and its predecessor, the Barra SAE3 Model.  The new Barra South Africa Equity Model captures the dynamics of the South African market through the latest advances in MSCI research methodology and a comprehensive factor set, including the expanded Systematic Equity Strategy (SES) factors.

  12. PAPER

    The Market Spin Cycle: Uncovering Style and Sector Rotation in a Flat Market 

    May 23, 2014 Stan Radchenko , Vikas Kalra , Philippe Durand , Mehmet Bayraktar

    Investing (Investment Management)

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    Recent U.S. equity market performance, driven by a significant decline in glamour (high-growth, high-momentum) names, has attracted a lot of attention from market analysts. By now it is well publicized that, despite the range-bound performance of the US equity market since March, there have been significant differences among the performance of various sectors of the economy.

    We contribute to this discussion by focusing on what we view as a rotation in investment styles. This rotation has been observed within majority of GICS® sectors, but it has been most pronounced in Health Care, Information Technology, and Consumer Discretionary, the three sectors with the weakest performance from March 1 to May 15, 2014.

    Using MSCI Barra models, in this paper we identify a rotation in investment styles highlighted by declining performance in growth-oriented styles currently associated with risk-taking behavior, such as Beta, Growth, and Momentum, and improving performance in Value, Profitability, and Size, styles appealing to more risk-averse investors focused on valuations.

  13. This Research Insight, second in a series, introduces the Seasonality factor in our equity models; this factor was identified as part of MSCI's Systematic Equity Strategies (SES) research program. Seasonal behavior of stock returns is widely discussed in finance literature. The most prominent is the "January Effect," where prices tend to rise during January after stock sell-offs in December. In this paper, we examine how the SES Seasonality factor identifies seasonal pricing patterns for US equities, and how the Seasonality factor can help capture risk associated with manager crowding.

  14. PAPER

    Model Insight - The Barra Emerging Markets Model Empirical Notes - February 2014 

    Feb 25, 2014 Andrei Morozov , Paul Ward , Imre Balint , Mehmet Bayraktar , Laszlo Borda

    Factor and Risk Modeling , Portfolio Construction and Optimization , Risk Management

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    This Model Insight provides empirical results for the new Barra Emerging Markets Model, including detailed information on the structure, the performance, and the explanatory power of the factors. Furthermore, these notes also include backtesting results and a thorough side-by-side comparison of the forecasting accuracy of the new Emerging Markets Model and the Global Equity Model (GEM3).

  15. PAPER

    Research Insight - Introducing the Prospect Factor - December 2013 

    Dec 5, 2013 Igor Mashtaler , Nicolas Meng , Mehmet Bayraktar , Stan Radchenko

    Factor and Risk Modeling , Portfolio Construction and Optimization , Risk Management

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    In this Research Insight, we introduce the Prospect factor. Systematic implementation of Prospect theory may be thought of as a contrarian investment strategy that takes long positions in stocks with poor historical performance and short positions in stocks with historical good performance. We find that the Prospect factor is significant in explaining risk and return characteristics of Japanese and US securities. The Prospect factor was identified as part of our Systematic Equity Strategies (SES) research program.

  16. PAPER

    Model Insight - The Barra US Small Cap Equity Model Empirical Notes - December 2013 

    Dec 4, 2013 Igor Mashtaler , Mehmet Bayraktar , Nicolas Meng

    Factor and Risk Modeling , Portfolio Construction and Optimization , Risk Management

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    This Model Insight provides empirical results for the new Barra US Small Cap Model, including detailed information on the structure, the performance, and the explanatory power of the factors. Furthermore, these notes also include backtesting results and a thorough side-by-side comparison of the forecasting accuracy of the new model and its predecessor.

  17. PAPER

    Model Insight - The Barra US Sector Equity Model Methodology and Empirical Notes - December 2013 

    Dec 4, 2013 Mehmet Bayraktar , Stan Radchenko

    Factor and Risk Modeling , Portfolio Construction and Optimization , Risk Management

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    This Model Insight explains MSCI's motivation for building the Barra US Sector Equity Models, describes the methodology and factor structure, and provides empirical results for the US Sector model family, which includes 10 individual sector models and a fully integrated model.

  18. PAPER

    Model Insight - Barra Korea Equity Model (KRE3) Empirical Notes - November 2013 

    Nov 1, 2013 Jun Wang , Mehmet Bayraktar , Jay Yao

    Factor and Risk Modeling

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    This Model Insight provides empirical results for the new Barra Korea Equity Model (KRE3), including detailed information about the structure, the performance, and the explanatory power of the factors. Furthermore, these notes also include backtesting results and a side-by-side comparison of the forecasting accuracy of the KRE3 Model and the KRE2 Model, its predecessor.

  19. In this Research Insight, we introduce “Systematic Equity Strategies” (SES), which refers to a rules-based implementation of investment strategies and anomalies.  Our research finds that SES, when used as factors in risk models, can help predict both expected and abnormal stock returns, thus improving forecast accuracy. Some Systematic Equity Strategies may lead to crowding risk as large pools of capital pursue shared strategies; by using SES factors, investors can monitor their exposures and predict crowding risk. Incorporating SES factors in risk models can help investors diagnose the sensitivity of their portfolios to potentially crowded investment trends, helping users make better trade-off decisions between risk and return.

  20. PAPER

    Research Insight - Systematic Equity Strategies - A Test Case Using Empirical Results from the Japan Equity Market - June 2013 

    Jun 19, 2013 Jun Wang , Jay Yao , Jyh-huei Lee , Mehmet Bayraktar , Igor Mashtaler , Nicolas Meng

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    In an introductory paper, we explained Systematic Equity Strategies (SES) and how they can be used as factors in a risk model.  In this paper, we use data from the Japan equity markets to define seven new SES factors and study their empirical behavior.  Our findings illustrate the important role that these factors play in portfolio construction and risk management. Our study also shows problems associated with omitting these factors from a risk model, and explain why models that include SES risk factors should lead to improved portfolio risk forecasts.

  21. PAPER

    Model Insight - Barra Japan Equity Model (JPE4) Empirical Notes - October 2013 

    Jun 18, 2013 Jun Wang , Jay Yao , Mehmet Bayraktar , Igor Mashtaler , Nicolas Meng

    Factor and Risk Modeling

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    This Model Insight provides empirical results for the new Barra Japan Equity Model (JPE4), including detailed information on the structure, the performance, and the explanatory power of the factors. Furthermore, these notes also include backtesting results and a thorough side-by-side comparison of the forecasting accuracy of the JPE4 Model and the JPE3 Model, its predecessor.

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