Portfolio allocation and asset demand with mean-variance preferences

Eichner, Thomas; Wagener, Andreas

doi:10.1007/s11238-010-9217-4

Cited by 16 publications

(17 citation statements)

References 20 publications

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“…Lajeri and Nielsen (2000) and Eichner and Wagener (2003, 2005) have developed a

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‐equivalent for Kimball's (1990) notion of decreasing absolute prudence. Contributions toward modeling risk preferences (e.g., Eichner, 2008; Eichner & Wagener, 2009, 2011, 2012; Epstein, 1985; Guo et al., 2018; Ormiston & Schlee, 2001) have demonstrated analogues of the EU properties like “risk vulnerability,” “temperance,” “properness,” and “standardness” in terms of the relative willingness to pay for a change in risk, which falls under the ambit of mean–variance preference–theoretic analysis.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The second and third questions are answered by developing a two‐moment decision‐theoretic model following the approaches used by Eichner (2008), and Eichner and Wagener (2003, 2009, 2011, 2012). The model considers the risks perceived by a risk‐averse buyer due to the uncertainty associated with supply disruptions, for making an optimal portfolio choice to split orders between the primary supplier and the backup supplier.…”

Section: Introductionmentioning

confidence: 99%

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Optimal portfolio choices to split orders during supply disruptions: An application of sport's principle for routine sourcing

Padhi¹,

Mukherjee

2021

Decision Sciences

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Sourcing in the face of supply chain disruptions has been one of the most challenging tasks in supply chain management, particularly when such disruptions occur due to natural calamities, such as flood, fire, and earthquake, affecting both the primary and the backup suppliers. Invariably, such disruptions lead to reduced supply from the primary supplier, encouraging the supplier to place fresh orders with the backup suppliers. In order to mitigate the adverse effect of supply disruption, in this article we use the concepts underlying the well-known Duckworth-Lewis-Stern method, used in cricket, to revise the supply target of the primary supplier and to decide a target for the backup supplier. We simulated the supply disruption scenarios in an experimental setting by conducting a two-round questionnaire survey among 300 purchase managers. The means and variances of the participants' estimates of probabilities of meeting the revised targets within the scheduled time for various model-generated supply scenarios were used to find the participants' risk preferences. In the second-round survey, the participants, clustered in groups of 10, ranked their own risk preferences. These ranks were used to find the optimal portfolio choices. Finally, we validated the theoretical predictions for the risk options using two approaches-one, at the group level by estimating the within-and the between-group risk preferences of buyers, and, two, at the aggregate level, by considering all the participants, fitting quantile regression model to the experimental results, and estimating the risk preference structures for different quantiles of the relative risk-return trade-off distributions. K E Y W O R D SDuckworth-Lewis-Stern method, mean-variance decision-theoretic model, portfolio of risky options, risk preference structures, supply disruption 1 1 https://shodhganga.inflibnet.ac.in/bitstream/10603/147247/14/14%20leather% 20craftsmanship-sustainable%20livelihood.pdf 2 https://www.automotivelogistics.media/flooding-in-chennai-causes-plant-closuresand-supply-disruption/14135.article (accessed 4 June 2019).

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“…Lajeri and Nielsen (2000) and Eichner and Wagener (2003, 2005) have developed a

( {{{\mu}},{{\sigma}}} )

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal portfolio choices to split orders during supply disruptions: An application of sport's principle for routine sourcing

Padhi¹,

Mukherjee

2021

Decision Sciences

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“…Wagener [29], and Eichner and Wagener [18] [30] carried out some compara- 1 See, for example, Battermann, Broll and Wahl [19], Broll, Wahl and Wong [20], Wong and Ma [17], and Eichner and Wagener [24].…”

Section: The Modelmentioning

confidence: 99%

The Impacts of Joint Energy and Output Prices Uncertainties in a Mean-Variance Framework

Alghalith¹,

Niu²,

Wong³

2017

TEL

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In this paper, we analyze the impacts of joint energy and output prices uncertainties on the inputs demands in a mean-variance framework. We find that the concepts of elasticities and variance vulnerability play important roles in the comparative statics analysis. If the firms' preferences exhibit variance vulnerability, increasing the variance of energy price will necessarily cause the risk averse firm to decrease the demands for the non-risky inputs. Further, we investigate two special cases with only uncertain energy price and only uncertain output price. In the case with only uncertain energy price, we find that the uncertain energy price has no impact on the demands for the non-risky inputs. Besides, if the firms' preferences exhibit variance vulnerability, increasing the variance of energy price will surely cause the risk averse firm to decrease the demand for energy.

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“…Inspired by studies on the effects of (additive) background risks on risktaking under the EU-hypothesis (see, e.g., Eeckhoudt et al, 1996;Caballé and Pomansky, 1997), Wong and Ma (2008) or Eichner and Wagener (2003b;2009) analyze quasi-linear decision problems where the MV-decision maker has faced both a direct, controllable risk and an exogenous background risk. Eichner and Wagener (2011) study linear portfolio choices with several risky assets. In these studies, the different risks are additive, i.e., final wealth or consumption emerges as a linear combination of multiple random variables.…”

Section: Introductionmentioning

confidence: 99%