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Mean-variance approaches to risk-return relationships in strategy: paradox lost

Article Abstract:

An analysis of corporate strategic management was conducted to examine mean-variance relationships and to counter previous research findings which have suggested that negative associations exist between the levels of risk and return. The current analysis suggests that the existence of negative associations between the levels of return and risk in mean-variance terms is not verifiable. This suggestion infers that findings obtained by using variance and mean of return are specific to the information and time period analyzed and may not be generalizable. In addition, because mean and variance are mathematically connected, enhancing the system with more equations will not generate the data necessary to establish validity of statements addressing the mean-variance relationship. An empirical example of the US airline industry is presented to supplement analytic proofs.

Author: Ruefli, Timothy W.
Publisher: Institute for Operations Research and the Management Sciences
Publication Name: Management Science
Subject: Business, general
ISSN: 0025-1909
Year: 1990
Research, Analysis of variance

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Ordinal time series methodology for industry and competitive analysis

Article Abstract:

Ordinal time series analysis along longitudinal, multidimensional performance lines can be used for industry and competitive analysis. Ordinal data use eliminates the need found in cardinal analysis for additional assumptions and calculations concerning appropriate discount rates, model specifications, and data re-scaling. The strategy analyst can develop empirical measures of volatility, position, movement direction, and relative industrial or firm uncertainty by using longitudinal data. Industrial and firm groups can be identified using these statistical industry behavior patterns, key strategic dimensions, and relationships among and across performance measures. Published data on large transportation industry firms over the last 25 years is used to illustrate the methodology by performing a comparative ordinal time series analysis.

Author: Ruefli, Timothy W., Wilson, Chester L.
Publisher: Institute for Operations Research and the Management Sciences
Publication Name: Management Science
Subject: Business, general
ISSN: 0025-1909
Year: 1987
Analysis, Management, Usage, Railroads, Trucking, Airlines, Multivariate analysis, Business planning, Railroad management, Time-series analysis, Time series analysis

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Strategic risk: an ordinal approach

Article Abstract:

An ordinal measure of risk is constructed that represents risk at the strategic level. Risk in this context refers to the probability that a firm may lose its position relative to the positions of other firms in the same set. A model is proposed that represents such a strategic risk by using partitionable information from probability distributions of relative firm positions over time. This analysis derives a newmeasure of individual firms' risk on the basis of firm identity and position losses or gains, while disaggregating risk hierarchially according to industry,group and individual companies. Both hypothetical data and actual data from theUS airline industry are used to illustrate the application of the ordinal risk measure.

Author: Ruefli, Timothy W., Collins, James M.
Publisher: Institute for Operations Research and the Management Sciences
Publication Name: Management Science
Subject: Business, general
ISSN: 0025-1909
Year: 1992
Models

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Subjects list: Risk management, Strategic planning (Business)
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