A master thesis from Aalborg University
Index Tracking and Basket-Adjusted Integrated Covariance Estimation
Author(s)
Term
4. term
Education
Publication year
2025
Submitted on
2025-05-28
Pages
54 pages
Abstract
This thesis investigates the efficacy of using the ETF basket-adjusted covariance (BAC) estimator for improving the positive semidefinite covariation estimates of the mrcCholCov -estimator. The estimators are applied and compared in an index tracking setup. For index tracking, a framework consisting of two parts is established. The first part picks an appropriate subset of component stocks from the index wished to be tracked, and the second part determines appropriate weights for the tracking portfolio. A simulation study investigates the rate, G , at which BAC-based tracking is beneficial to vanilla mrcCholCov -based tracking across varying ETF and stock liquidities as well as for varying sizes of the tracking portfolio. The results suggest that G is independent from the tracking portfolio size and the ETF-liquidity. The latter is, however, argued to be due to limitations of the simulation. Additionally, it is concluded that G is higher for stock baskets, where many stocks are illiquid and few stocks have a high liquidity. Finally, an empirical study, using 55 S&P 500 component stocks, compares the tracking performance of the two estimators for index fund sizes of q = 10, 20, and 30. Overall, the BAC yields the best performance, and this effect is mostly profound for q > 10.
Keywords
Documents
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