نوع مقاله : علمی - پژوهشی
نویسندگان
1 گروه مهندسی مالی، دانشکده حسابداری و علوم مالی، دانشکدگان مدیریت، دانشگاه تهران، تهران، ایران
2 دانشکده اقتصاد، دانشگاه تهران، تهران، ایران
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Introduction: This study aims to develop and evaluate a novel portfolio optimization framework for enhanced index tracking. Enhanced index tracking is an intermediate strategy between active and passive portfolio management, in which the goal is to construct a portfolio from the constituents of a benchmark index so as to closely follow the index while achieving returns above the benchmark. The main objective is to jointly pursue “return enhancement” and “strict control of tail risk” in financial markets where returns may exhibit skewness, excess kurtosis, and extreme events. In such environments, relying solely on conventional variance-based risk measures may underestimate downside risks and thereby expose portfolio-weighting decisions to substantial losses. The proposed framework employs the Omega ratio as a distribution-based performance measure and Conditional Value at Risk (CVaR) as a downside risk control metric, with the aim of generating excess returns over the benchmark while enhancing the portfolio’s resilience to severe losses.
Methods: The proposed framework is formulated as an Omega–CVaR optimization problem. The objective function maximizes the Omega ratio of the tracking portfolio in order to improve the ratio of returns above a specified threshold to losses below that threshold. Simultaneously, CVaR is imposed as a constraint to control downside risk by limiting the mean of large losses in the tail of the return distribution. Operational constraints include full investment, minimum/maximum weight bounds of 0% and 50% to prevent excessive concentration, and asset selection restricted to the constituents of the benchmark index. The empirical assessment is conducted using 30 rolling time windows; in each iteration, 52 weeks of in-sample data are used for estimation and 12 weeks of out-of-sample data are used for performance evaluation. The study period spans approximately eight years (from late January 2018 to late December 2025), and the results are compared with those of the Tehran Exchange Price Index (TEPIX) and a competing model based on conventional constraints/objectives.
Finding: The results indicate that the Omega–CVaR framework delivers a substantial long-term advantage in terms of cumulative returns relative to both the TEPIX and the competing model. The cumulative return of the proposed portfolio is reported at 2,546%, compared with 1,350% for the TEPIX. Analyzing the time path of performance across rolling windows shows that the primary advantage of the model does not necessarily stem from “persistent weekly outperformance,” but rather from two complementary mechanisms. First, the CVaR constraint, by limiting the average losses beyond the confidence level, reduces the depth of drawdowns during bearish phases. Second, maximizing the Omega ratio leads to a weight allocation that increases the share of desirable returns relative to undesirable losses, enabling the portfolio to better exploit the “compounding effect” during recovery periods following downturns. Nonetheless, statistical tests reveal that at weekly horizons, the model’s outperformance relative to the TEPIX and competing models is not consistently and significantly confirmed. This pattern is consistent with the defensive nature of the portfolio, as evidenced by an average beta of about 0.43, indicating lower sensitivity to market fluctuations than the TEPIX.
Conclusions: The findings suggest that the Omega–CVaR framework is an effective tool for enhanced index tracking in volatile markets characterized by extreme risks. Although statistically significant short-term outperformance is not observed, effective control of severe losses and reinforcement of the compounding effect can ultimately lead to higher cumulative returns over the long run. This strategy is particularly recommended for investors seeking lower risk and greater stability in their portfolios, especially in markets with non-normal return distributions.
کلیدواژهها [English]
)