Faculty of Business

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Browsing by Institution Author "ÇAĞLAYAN, Mustafa Onur"

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    ArticlePublicationOpen Access
    Development and calibration of a currency trading strategy using global optimization
    (Springer Science+Business Media, 2013-06) Çağlayan, Mustafa Onur; Pinter, Janos D.; Economics; Industrial Engineering; ÇAĞLAYAN, Mustafa Onur; PINTER, Janos
    We have developed a new financial indicator—called the Interest Rate Differentials Adjusted for Volatility (IRDAV) measure—to assist investors in currency markets. On a monthly basis, we rank currency pairs according to this measure and then select a basket of pairs with the highest IRDAV values. Under positive market conditions, an IRDAV based investment strategy (buying a currency with high interest rate and simultaneously selling a currency with low interest rate, after adjusting for volatility of the currency pairs in question) can generate significant returns. However, when the markets turn for the worse and crisis situations evolve, investors exit such money-making strategies suddenly, and—as a result—significant losses can occur. In an effort to minimize these potential losses, we also propose an aggregated Risk Metric that estimates the total risk by looking at various financial indicators across different markets. These risk indicators are used to get timely signals of evolving crises and to flip the strategy from long to short in a timely fashion, to prevent losses and make further gains even during crisis periods. Since our proprietary model is implemented in Excel as a highly nonlinear “black box” computational procedure, we use suitable global optimization methodology and software—the Lipschitz Global Optimizer solver suite linked to Excel—to maximize the performance of the currency basket, based on our selection of key decision variables. After the introduction of the new currency trading model and its implementation, we present numerical results based on actual market data. Our results clearly show the advantages of using global optimization based parameter settings, compared to the typically used “expert estimates” of the key model parameters.
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    Do hedge funds’ exposures to risk factors predict their future returns?
    (Elsevier, 2011-07) Bali, T. G.; Brown, S.; Çağlayan, Mustafa Onur; Economics; ÇAĞLAYAN, Mustafa Onur
    This paper investigates hedge funds’ exposures to various financial and macroeconomic risk factors through alternative measures of factor betas and examines their performance in predicting the crosssectional variation in hedge fund returns. Both parametric and nonparametric tests indicate a significantly positive (negative) link between default premium beta (inflation beta) and future hedge fund returns. The results are robust across different subsample periods and states of the economy, and after controlling for market, size, book-to-market, and momentum factors as well as the trendfollowing factors in stocks, short-term interest rates, currencies, bonds, and commodities. The paper also provides macro and micro level explanations of our findings.
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    Emerging market exposures and the predictability of hedge fund returns
    (Wiley, 2014) Çağlayan, Mustafa Onur; Ulutaş, Sevan; Economics; ÇAĞLAYAN, Mustafa Onur
    We examine emerging market and global macro hedge funds and find a significant positive relation between hedge funds' future returns and their exposure to both emerging market equities and emerging market currencies. We present evidence that the strong predictive power of emerging market betas is related to the superior market-timing ability of these fund managers. Results are robust after controlling for commonly used hedge fund factors, the emerging market equity index, lagged fund returns, liquidity risk, and fund characteristics. Our results suggest that hedge funds can earn positive excess returns by timing their exposure to emerging market securities.
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    Macroeconomic risk and hedge fund returns
    (Elsevier, 2014-10) Bali, T. G.; Brown, S. J.; Çağlayan, Mustafa Onur; Economics; ÇAĞLAYAN, Mustafa Onur
    This paper estimates hedge fund and mutual fund exposure to newly proposed measures of macroeconomic risk that are interpreted as measures of economic uncertainty. We find that the resulting uncertainty betas explain a significant proportion of the cross-sectional dispersion in hedge fund returns. However, the same is not true for mutual funds, for which there is no significant relationship. After controlling for a large set of fund characteristics and risk factors, the positive relation between uncertainty betas and future hedge fund returns remains economically and statistically significant. Hence, we argue that macroeconomic risk is a powerful determinant of cross-sectional differences in hedge fund returns.
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    Conference ObjectPublicationOpen Access
    Optimized calibration of currency market strategies
    (2010) Çağlayan, Mustafa Onur; Pinter, Janos D.; Economics; Industrial Engineering; ÇAĞLAYAN, Mustafa Onur; PINTER, Janos
    We propose a new financial indicator and risk metric embedded in a currency trading model to assist investors in currency markets. Since our model is highly nonlinear, we utilize global optimization technology to maximize the performance of the currency basket, based on our selection of key decision variables. We introduce the model and present numerical results based on actual market data.
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    Systematic risk and the cross section of hedge fund returns
    (Elsevier, 2012-10) Bali, T. G.; Brown, S. J.; Çağlayan, Mustafa Onur; Economics; ÇAĞLAYAN, Mustafa Onur
    This paper investigates the extent to which market risk, residual risk, and tail risk explain the cross-sectional dispersion in hedge fund returns. The paper introduces a comprehensive measure of systematic risk (SR) for individual hedge funds by breaking up total risk into systematic and fund-specific or residual risk components. Contrary to the popular understanding that hedge funds are market neutral, we find that systematic risk is a highly significant factor explaining the dispersion of cross-sectional returns while at the same time measures of residual risk and tail risk seem to have little explanatory power. Funds in the highest SR quintile generate 6% more average annual returns compared with funds in the lowest SR quintile. After controlling for a large set of fund characteristics and risk factors, systematic risk remains positive and highly significant, whereas the relation between residual risk and future fund returns continues to be insignificant. Hence, systematic risk is a powerful determinant of the cross-sectional differences in hedge fund returns.