Abstract
We make an attempt to examine the performance of portfolios formulated on the basis of Mean–Variance approach . For the analysis, monthly adjusted opening and closing prices of composite portfolio of BSE 100 companies have been taken for the period ranging from June 1996 to May 2005. The study has wide-ranging implications for finance professionals and policy makers. Ten portfolios have, first, been formulated and then evaluated by using Sharpe’s excess return to beta approach. Nine portfolios’ expected returns out of ten are significant at 5% level of significance. A cross-sectional analysis of the same set of ten portfolios carried out for three non-overlapping sub-periods (June 1996–December 1999, Jan 2000–December 2002, and Jan 2003–May 2005). The three sub-periods exhibit successive different economic conditions in the Indian economy, viz. decline , recession and growth , respectively. The results so obtained exhibit that portfolio -expected return of all ten portfolios, in three different economic conditions, are optimal.
How many millionaires do you know who have become wealthy by investing in savings accounts? I rest my case.
Robert G. Allen
This chapter draws from the author’s previous publication (Dhankar & Kumar, 2006) Rakesh Kumar, Assistant Professor in the Department of Business Studies, Deen Dayal Upadhyaya College, University of Delhi, New Delhi, and re-used here with permission.
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Appendices
Appendix 1
List of companies of BSE 100
Code | Company | Code | Company | Code | Company | Code | Company |
---|---|---|---|---|---|---|---|
c1 | ABB Ltd. | c20 | Colgate Pamolive Ltd. | c39 | ICICI Bank | c58 | Lupin Ltd. |
c2 | Andhra Bank | c21 | Container Corporation | c40 | I-Flex Solution | c59 | Patni Computers |
c3 | Arvind Mill | c22 | Corporation Bank | c41 | Kochi Refinery | c60 | Pfizer Ltd. |
c4 | Ashok Leyland | c23 | Cummins Ltd. | c42 | Kotak Mahindra Bank | c61 | Polaris Software Ltd. |
c5 | Asian Paints | c24 | Divi’s Laboratory | c43 | Larsen & Turbo | c62 | Punjab National Bank |
c6 | ACC | c25 | Dr. Reddy Lab | c44 | MTNL | c63 | Ranbaxy Ltd. |
c7 | Bajaj Auto Ltd. | c26 | GAIL | c45 | Mahindra & Mahindra | c64 | Rashtriya Chemical |
c8 | Bank of Baroda | c27 | Glaxosmithkline | c46 | Mangalore Refinery | c65 | Raymond Ltd. |
c9 | Bank of India | c28 | Grasim Industries Ltd. | c47 | Maruti Udoyg Ltd. | c66 | Reliance Capital |
c10 | Bharat Electronics | c29 | Great Eastern shipping Ltd. | c48 | Matrix Laboratory | c67 | Reliance Energy Ltd. |
c11 | Bharat Forge Ltd. | c30 | Gujarat Ambuja Cement | c49 | Moser Baer | c68 | Reliance Industries |
c12 | BHEL | c31 | HCL Infosystem | c50 | MICO | c69 | Satyam Computers |
c13 | Bharat Petroleum | c32 | HCL Technologies | c51 | National Aluminium | c70 | Shipping Corporation |
c14 | Bharati Televenture | c33 | HDFC Bank | c52 | Nestle India | c71 | Siemens Ltd. |
c15 | Biocon Ltd. | c34 | Hero Honda | c53 | Neyveli Lignite | c72 | State Bank of India |
c16 | Cadila Health care Ltd. | c35 | Hindalco | c54 | Nicholas Piramal | c73 | SAIL |
c17 | Canara Bank | c36 | Hindustan Lever Ltd. | c55 | Novartis India | c74 | Sterlite Industries Ltd. |
c18 | Chennai Petroleum Ltd. | c37 | Hindustan Petroleum | c56 | ONGC | c75 | Sun Pharmaceuticals |
c19 | Cipla Ltd. | c38 | HDFC | c57 | Oriental Bank of Commerce | c76 | Tata Chemicals |
c77 | Tata Iron & Steel | c83 | Indian Hotels | c89 | Jaiprakash Associate | c96 | VSNL |
c78 | Tata Motor | c84 | Indian Oil Corporation | c90 | Jammu & Kashmir Bank | c97 | Vijaya Bank |
c79 | Tata Power | c85 | Indian Overseas Bank | c91 | TVS Motors | c98 | Wipro Ltd. |
c80 | Tata Tea Ltd. | c86 | Indian Petrochemicals | c92 | Tata Teleservices | c99 | Wockhardt |
c81 | Indian Rayon Ltd. | c87 | IDBI c93 UTI Bank | c94 | Union Bank of India | c100 | Zee Telefilm |
c82 | ITC Ltd. | c88 | Infosys Technologies | c95 | United Phosphorus Ltd. |
Appendix 2
Correlation Matrix for Portfolio 1
-
c95c42 = 0.18, c95c88 = 0.24, c95c54 = 0.12, c95c1 = 0.1, c95c100 = 0.12, c95c0.05 = –0.01, c95c98 = 0.13, c95c89 = 0.16, c95c31 = 0.14
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c42c88 = 0.58, c42c54 = –0.28, c42c1 = 0.08, c42c100 = 0.05 c42c69 = 0.34, c42c98 = 0.08, c42c89 = –0.03, c42c31 = 0.17
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c88c54 = –0.28, c88c1 = 0.08, c88c100 = 0.05, c88c69 = –0.13, c88c98 = 0.33, c88c89 = 0.08, c88c31 = –0.11
-
c54c1 = 0.17, c54c100 = 0.22, c54c69 = 0.18, c54c98 = 0.10, c54c89 = 0.18, c54c31 = 0.27
-
c1c100 = 0.25, c1c69 = 0.23, c1c98 = 0.24, c1c89 = 0.19, c1c31 = 0.23
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c100c69 = 0.29, c100c98 = 0.02, c100c89 = 0.16, c100c31 = 0.36
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c69c98 = –0.02, c69c89 = 0.08, c69c31 = 0.35
-
c98c89 = 0.15, c98c31 = 0.16
-
c89c31 = 0.32
Correlation Matrix for Portfolio 2
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c33c71 = 0.13, c33c68 = 0.18, c33c52 = 0.12, c33c19 = 0.12, c33c47 = 0.25, c33c45 = 0.10, c33c50 = 0.21, c33c27 = 0.11, c33c7 = 0.18
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c71c68 = 0.34, c71c52 = 0.10, c71c19 = 0.24, c71c47 = 0.30, c71c45 = 0.61, c71c50 = 0.13, c71c27 = 0.29, c71c7 = 25
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c68c52 = 0.18, c68c19 = 0.41, c68c47 = 0.29, c68c45 = 0.37, c68c50 = 0.21, c68c27 = 0.38, c68c7 = 0.43
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c52c19 = 0.24, c52c47 = 0.1, c52c45 = 0.09, c52c50 = 0.19, c52c27 = 0.35, c52c7 = 0.26
-
c19c47 = 0.35, c19c45 = 0.36, c19c50 = 0.09, c19c27 = 0.4, c19c7 = 0.29
-
c47c45 = 0.61, c47c50 = 0.09, c47c27 = 0.05, c47c7 = 0.13
-
c45c50 = 0.06, c45c27 = 0.05, c45c7 = 0.29
-
c50c27 = 0.24, c50c7 = 0.16
-
c27c7 = 0.39
Correlation Matrix for Portfolio 3
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c77c44 = 0.31, c77c28 = 0.48, c77c61 = 0.06, c77c36 = 0.12, c77c32 = 0.28, c77c24 = 0.04, c77c25 = 0.41, c77c6 = 0.43, c77c63 = 0.27
-
c44c28 = 0.31, c44c61 = 0.19, c44c36 = 0.14, c44c32 = 0.33, c44c24 = –0.33, c44c25 = 0.19, c44c6 = 0.52, c44c63 = 0.28
-
c28c61 = 0.27, c28c36 = 0.22, c28c32 = 0.50, c28c24 = –0.04, c28c25 = 0.35, c28c6 = 0.51, c28c63 = 0.39
-
c61c36 = 0.28, c61c32 = 0.53, c61c24 = 0.35, c61c25 = 0.20, c61c6 = 0.28, c61c63 = 0.31
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c36c32 = 0.34, c36c24 = 0.14, c36c25 = 0.28, c36c6 = 0.14, c36c63 = 0.33
-
c32c24 = 0.27, c32c25 = 0.36, c32c6 = 0.43, c32c63 = 0.32
-
c24c25 = 0.41, c24c6 = 0.18, c24c63 = 0.40
-
c25c6 = 0.37, c25c63 = 0.54
-
c6c63 = 0.43
Correlation Matrix for Portfolio 4
-
c82c74 = 0.01, c82c62 = -0.06, c82c43 = 0.23, c82c94 = 0.31, c82c10 = 0.28, c82c30 = 0.21, c82c26 = 0.12, c82c34 = 0.06, c82c35 = 0.27
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c74c62 = 0.12, c74c43 = 0.33, c74c94 = 0.03, c74c10 = 0.25, c74c30 = 0.29, c74c26 = 0.13, c74c34 = 0.20, c74c35 = 0.34
-
c62c43 = 0.37, c62c94 = 0.07, c62c10 = 0.24, c62c30 = 0.10, c62c26 = 0.16, c62c34 = 0.20, c62c35 = 0.15
-
c43c94 = 0.12, c43c10 = 0.41, c43c30 = 0.41, c43c26 = 0.38, c43c34 = 0.26, c43c35 = 0.36
-
c94c10 = 0.22, c94c30 = 0.16, c94c26 = 0.-0.05, c94c34 = –0.03, c94c35 = 0.16
-
c10c30 = 0.36, c10c26 = 0.35, c10c34 = 0.24, c10c35 = 0.38
-
c30c26 = 0.24, c30c34 = 0.21, c30c35 = 0.32
-
c26c34 = 0.27, c26c35 = 0.16
-
c34 c35 = 0.16
Correlation Matrix for Portfolio 5
-
c72c86 = 0.21, c72c78 = 0.51, c72c80 = 0.02, c72c14 = 0.50, c72c23 = 0.31, c72c11 = 0.28, c72c55 = 0.45, c72c91 = 0.44, c72c81 = 0.18
-
c86c78 = 0.05, c86c80 = 0.08, c86c14 = 0, c86c23 = –0.02, c86c11 = 0.03, c86c55 = 0.12, c86c91 = –-0.12, c86c81 = 0.18
-
c78c80 = 0.27, c78c14 = 0.41, c78c23 = 0.30, c78c11 = 0.08, c78c55 = 0.28, c78c91 = 0.21, c78c81 = 0.31
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c80c14 = 0.01, c80c23 = 0.12, c80c11 = 0.11, c80c55 = 0.09, c80c91 = –0.05, c80c28 = 0.28
-
c14c23 = 0.12, c14c11 = 0.15, c14c55 = 0.43, c14c91 = 0.51, c14c81 = –0.36
-
c23c11 = 0.18, c14c55 = 0.17, c23c91 = 0.20, c23c81 = 0.10
-
c11c55 = 0.23, c11c91 = 0.23, c11c81 = 0
-
c55c91 = 0.44, c55c81 = 0.20
-
c91c81 = –0.26
Correlation Matrix for Portfolio 6
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c83c57 = –0.08, c83c53 = 0.10, c83c22 = 0.10, c83c56 = 0.26, c83c8 = 0.23, c83c38 = 0.16, c83c51 = 0.14, c83c17 = 0.26, c83c90 = 0.06
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c57c53 = 0.18, c57c22 = 0.24, c57c56 = 0.21, c57c8 = 0.41, c57c38 = 0.22, c57c51 = 0.19, c57c17 = 0.29, c57c90 = 0.37
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c53c22 = 0.15, c53c56 = 0.36, c53c8 = 0.27, c53c38 = 0.10, c53c51 = 0.07, c53c17 = –0.11, c53c90 = 0.35
-
c22c56 = 0.07, c22c8 = 0.53, c22c38 = 0.09, c22c51 = 0.30, c22c17 = 0.44, c22c90 = 0.38
-
c56c8 = 0.32, c56c38 = 0.20, c56c51 = 0.22, c56c17 = 0.42, c56c90 = 0.16
-
c8c38 = 0.31, c8c51 = 0.21, c8c17 = 0.63, c8c90 = 0.24
-
c38c51 = 0.12, c38c17 = 0.42, c38c90 = 0.22
-
c51c17 = 0.32, c51c90 = 0.18
-
c17c90 = 0.39
Correlation Matrix for Portfolio 7
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c67c65 = 0.28, c67c39 = 0.14, c67c9 = 0.27, c67c2 = 0.46, c67c75 = 0.29, c67c13 = 0.22, c67c37 = 0.31, c67c40 = 0.02, c67c84 = –0.11
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c5c39 = 0.05, c5c9 = 0, c5c2 = –0.08, c5c75 = 0.27, c5c13 = 0.16, c5c37 = 0.26, c5c40 = –0.14, c5c84 = –0.28
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c39c9 = 0.38, c39c2 = 0.18, c39c75 = 0.13, c39c13 = 0.33, c39c37 = 0.22, c39c40 = 0.23, c39c84 = –0.18
-
c9c2 = 0.58, c9c75 = 0.32, c9c13 = 0.36, c9c37 = 0.24, c9c40 = 0.12, c9c84 = 0.43
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c2c75 = 0.14, c2c13 = 0.23, c2c37 = 0.18, c2c40 = –0.06, c2c84 = 0.30
-
c75c13 = 0.24, c75c37 = 0.23, c75c40 = 0.32, c75c84 = –0.13
-
c13c37 = 0.69, c13c40 = –0.09, c13c84 = 0.15
-
c37c40 = –0.05, c37c84 = 0.03
-
c40c84 = 0.28
Correlation Matrix of Portfolio 8
-
c12c79 = 0.22, c12c49 = 0.28, c12c20 = 0.51, c12c18 = 0.33, c12c48 = 0.33, c12c93 = 0.50, c12c70 = 0.42, c12c73 = 0.29, c12c3 = 0.17
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c79c49 = 0.35, c79c20 = 0.36, c79c18 = 0.08, c79c48 = 0.35, c79c93 = 0.06, c79c70 = –0.12, c79c73 = 0.14, c79c3 = 0.31
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c49c20 = 0.32, c49c18 = 0.21, c49c48 = 0.10, c49c93 = 0.06, c49c70 = –0.013, c49c73 = 0.10, c49c3 = 0.18
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c20c18 = 0.29, c20c48 = 0.05, c20c93 = –0.15, c20c70 = 0.19, c20c73 = 0.35, c20c3 = 0.36
-
c18c48 = 0.17, c18c93 = 0.21, c20c70 = 0.07, c18c73 = 0.43, c18c3 = 0.27
-
c48c93 = 0.26, c48c70 = 0.02, c48c73 = 0.14, c48c3 = –0.01
-
c93c70 = 0.18, c93c73 = 0.22, c93c3 = 0.28
-
c70c73 = 0.16, c70c3 = 0.22
-
c73c3 = 0.37
Correlation Matrix of Portfolio 9
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c58c41 = 0.01, c58c60 = 0.15, c58c76 = 0.18, c58c59 = 0.41, c58c96 = 0.09, c58c64 = 0.29, c58c4 = 0.21, c58c29 = 0.41, c58c29 = 0.22
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c41c60 = 0.09, c41c76 = 0.43, c41c59 = –0.05, c41c96 = 0.18, c41c64 = 0.21, c41c4 = 0.36, c41c29 = 0.29, c41c92 = 0.30
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c60c76 = 0.22, c60c59 = –0.25, c60c96 = –0.03, c60c64 = 0.03, c60c4 = 0.08, c64c29 = –0.01, c60c92 = –0.04
-
c76c59 = 0.04, c76c96 = 0.19, c76c64 = 0.20, c76c4 = 0.34, c76c29 = 0.37, c76c92 = 0.19
-
c59c96 = 0.40, c59c64 = –0.35, c59c4 = –0.48, c59c29 = 0.08, c59c92 = –0.51
-
c96c64 = 0.03, c96c4 = 0.15, c96c29 = 0.21, c96c92 = 0.58
-
c64c4 = 0.02, c64c29 = 0.15, c64c92 = 0.08
-
c4c29 = 0.35, c4c92 = 0.30
-
c29c92 = 0.43
Correlation Matrix of Portfolio 10
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c65c15 = 0.47, c65c99 = 0.09, c65c16 = 0.20, c65c21 = –0.06, c65c85 = 0.39, c65c46 = 0.04, c65c87 = 0.13, c65c97 = 0.14, c65c66 = 0.46
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c15c99 = –0.20, c15c16 = 0.01, c15c21 = –0.40, c15c85 = 0.26, c15c46 = 0.56, c15c87 = –0.15, c15c97 = 0.00, c15c66 = 0.61
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c99c16 = 0.01, c99c21 = 0.05c61, c99c85 = 0.22, c99c46 = 0.0, c99c87 = 0.48, c99c97 = 0.45, c99c66 = 0.33
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c16c21 = 0.26, c16c85 = 0.16, c16c46 = –0.13, c16c87 = 0.07, c16c97 = 0.33, c16c66 = 0.20
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c21c85 = 0.04, c21c46 = 0.08, c21c87 = 0.11, c21c97 = 0.23, c21c66 = 0.20
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c85c46 = 0.35, c85c87 = 0.16, c85c97 = 0.19, c85c66 = 0.32
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c46c87 = -0.06, c46c97 = 0.02, c46c66 = 0.29
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c87c97 = 0.56, c87c66 = 0.35
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c97c66 = 0.
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Dhankar, R.S. (2019). Mean–Variance Approach and Portfolio Selection. In: Risk-Return Relationship and Portfolio Management. India Studies in Business and Economics. Springer, New Delhi. https://doi.org/10.1007/978-81-322-3950-5_16
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