کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5098923 | 1376970 | 2012 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A Krylov subspace approach to large portfolio optimization
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
کنترل و بهینه سازی
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چکیده انگلیسی
With a large number of securities (N) and fewer observations (T), deriving the global minimum variance portfolio requires the inversion of the singular sample covariance matrix of security returns. We introduce the Break-Down Free Generalized Minimum RESidual (BFGMRES), a Krylov subspaces method, as a fully automated approach for deriving the minimum variance portfolio. BFGMRES is a numerical algorithm that provides solutions to singular linear systems without requiring ex-ante assumptions on the covariance structure. Moreover, it is robust to illiquidity and potentially faulty data. US and international stock data are used to demonstrate the relative robustness of BFGMRES to illiquidity when compared to the “shrinkage to market” methodology developed by Ledoit and Wolf (2003). The two methods have similar performance as assessed by the Sharpe ratios and standard deviations for filtered data. In a simulation study, we show that BFGMRES is more robust than shrinkage to market in the presence of data irregularities. Indeed, when there is an illiquid stock shrinkage to market allocates almost 100% of the portfolio weights to this stock, whereas BFGMRES does not. In further simulations, we also show that when there is no illiquidity, BFGMRES exhibits superior performance than shrinkage to market when the number of stocks is high and the sample covariance matrix is highly singular.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Economic Dynamics and Control - Volume 36, Issue 11, November 2012, Pages 1688-1699
Journal: Journal of Economic Dynamics and Control - Volume 36, Issue 11, November 2012, Pages 1688-1699
نویسندگان
Isabelle Bajeux-Besnainou, Wachindra Bandara, Efstathia Bura,