The objective of this paper is to combine a real options framework with portfolio optimization techniques and to apply this new framework to investments in the electricity sector. In particular, a real options model is used to assess the adoption decision of particular technologies under uncertainty. These technologies are coal-fired power plants, biomassfired power plants and onshore wind mills, and they are representative of technologies based on fossil fuels, biomass and renewables, respectively. The return distributions resulting from this analysis are then used as an input to a portfolio optimization, where the measure of risk is the Conditional Value-at-Risk (CVaR).
The empirical joint distribution of return-pairs on stock indices displays high tail-dependence in the lower tail and low tail-dependence in the upper tail. The presence of tail-dependence is not compatible with the assumption of (conditional) j oint normality. The presence of asymmetric-tail dependence is not compatible with the assumption of a joint student -t distribution. A general test for one dependence structure versus another via the profilelikelihood is described and employed in a bivariate GARCH model, where the joint distribution of the disturbances is split into its marginals and its copula. The copula used is such that it allows for the presence of lower tail-dependence and for asymmetric taildependence, and that it encompasses the normal or t-copula. The model is estimated using bivariate data on a set of European stock indices. We find that the assumption of normal or student-t dependence is easily rejected in favour of an asymmetrically tail-dependent distribution. KeywordsValue-at-Risk, copula, non-normal bivariate GARCH, asymmetric dependence, profile likelihood-ratio test JEL ClassificationsC12, C32, C52, C51, G15 CommentsThe authors would like to thank Paul Embrechts, Andrew Harvey, Steve Satchell, three anonymous referees, and particularly Alessio Sancetta for helpful comments and suggestions.
Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThis study extends the literature on portfolio choice under prospect theory preferences by introducing a two-period life cycle model, where the household decides on optimal consumption and investment in a portfolio with one risk-free and one risky asset. The optimal solution depends primarily on the household's choice of the present value of the consumption reference levels relative to the present value of its endowment income. If the present value of the consumption reference levels is set below the present value of endowment income, then the household behaves in such a way to avoid relative losses in consumption in any present or future state of nature (good or bad). As a result the degree of loss aversion does not directly affect optimal consumption and risk taking activity. However, it must be sufficiently high in order to rule out outcomes with relative losses. On the other hand, if the present value of the consumption reference levels is set exactly equal to the present value of the endowment income, i.e., the household sets its reference levels such that they are in balance with its income, then the household's optimal consumption is the reference consumption in both periods and the household will not invest in the risky asset. Finally, if the present value of the household's consumption reference levels is set above the present value of its endowment income, then the household cannot avoid experiencing a relative loss in consumption, either now or in the future. As a result, loss aversion directly affects consumption and risky investment. Reference levels play a significant role in consumption and risk taking activity. In most cases the household will "follow the Joneses" if the reference levels are set equal to the consumption levels of the Joneses. Independent of how consumption reference levels are set, being more ambitious, i.e., increasing one's reference levels, will result in less happiness. The only case when this is not true is when reference levels increase with growing income (and the present value of reference levels is set below the present value of endowment income).
Growing experimental evidence suggests that loss aversion plays an important role in asset allocation decisions. We study the asset allocation of a linear loss-averse (LA) investor and compare the optimal LA portfolio to the more traditional optimal mean-variance (MV) and conditional value-at-risk (CVaR) portfolios. First we derive conditions under which the LA problem is equivalent to the MV and CVaR problems. Then we analytically solve the twoasset problem, where one asset is risk-free, assuming binomial or normal asset returns. In addition we run simulation experiments to study LA investment under more realistic assumptions. In particular, we investigate the impact of different dependence structures, which can be of symmetric (Gaussian copula) or asymmetric (Clayton copula) type. Finally, using 13 EU and US assets, we implement the trading strategy of an LA investor assuming assets are reallocated on a monthly basis and find that LA portfolios clearly outperform MV and CVaR portfolios.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.