Risk lovers, mixed risk loving and the preference to combine good with good

Jokung, O. and Mitra, S. 2019. Risk lovers, mixed risk loving and the preference to combine good with good. International Journal of Management and Applied Science. 11 (4), pp. 295-313.

TitleRisk lovers, mixed risk loving and the preference to combine good with good
TypeJournal article
AuthorsJokung, O. and Mitra, S.
Abstract

This paper examines the concept of 'risk loving' (that is risk seeking, intemperance, edginess, etc.), which can be characterised by preferences over simple lotteries. This paper analyses the notion of preferring to combine good with good, and bad with bad, as opposed to combining good with bad as usual. The significance of such preferences has implications on utility functions and are analysed in the paper. This paper extends Eeckhoudt and Schlesinger (2006) results to risk lovers, the results from Crainich et al. (2013) are also generalised to higher orders. We also generalise to higher orders the concept of bivariate risk seeking, introduced by Richard (1975) and called correlation loving by Epstein and Tanny (1980). In the expected utility framework, risk loving of order (N, M) coincides with the non-negativity of the (N, M)th partial derivative of the utility function. In dealing with mixed risk loving utility functions, we give several useful properties, for example, mixed risk loving is consistent with the mixture of positive exponential utilities and with non-increasing coefficients of absolute risk aversion at any order.

JournalInternational Journal of Management and Applied Science
Journal citation11 (4), pp. 295-313
ISSN2394-7926
Year2019
PublisherInderscience Publishers
Publication dates
Published21 Nov 2019

Related outputs

Catastrophe Bond Pricing In The Primary Market: The Issuer Effect And Pricing Factors
Chatoro, M, Mitra, S., Pantelous, A.A. and Shao, J. 2023. Catastrophe Bond Pricing In The Primary Market: The Issuer Effect And Pricing Factors. International Review of Financial Analysis. 85 102431. https://doi.org/10.1016/j.irfa.2022.102431

A Real Options Approach To Measuring Freedom In Sen’s Capabilities Approach
Mitra, S. 2022. A Real Options Approach To Measuring Freedom In Sen’s Capabilities Approach. International Journal of Sustainable Economy. 14 (1), pp. 98-110. https://doi.org/10.1504/IJSE.2022.119716

Optimal Feedback Control of Stock Prices Under Credit Risk Dynamics
Mitra, S., Jinghai Shao and Karathanasopoulos, Andreas 2022. Optimal Feedback Control of Stock Prices Under Credit Risk Dynamics. Annals of Operations Research. 313, pp. 1285-1318. https://doi.org/10.1007/s10479-021-04002-6

Keynesian Resurgence: Financial Stimulus And Contingent Claims Modelling
Clark, E., Mitra, S. and Jokung, O. 2020. Keynesian Resurgence: Financial Stimulus And Contingent Claims Modelling. International Journal of Mathematics in Operational Research. 17 (2), pp. 199-232. https://doi.org/10.1504/IJMOR.2020.109701

Downside risk measurement in regime switching stochastic volatility
Mitra, S. 2020. Downside risk measurement in regime switching stochastic volatility. Journal of Computational and Applied Mathematics. 378 112845. https://doi.org/10.1016/j.cam.2020.112845

Health Care Investment: The Case of Multiple Sources of Risk
Jokung, O. and Mitra, S. 2020. Health Care Investment: The Case of Multiple Sources of Risk. Asia-Pacific Financial Markets. 27, pp. 231-255. https://doi.org/10.1007/s10690-019-09291-3

An analysis of dollar cost averaging and market timing investment strategies
Lars Kirkby, J., Mitra, S. and Nguyen, D. 2020. An analysis of dollar cost averaging and market timing investment strategies. European Journal of Operational Research. 286 (3), pp. 1168-1186. https://doi.org/10.1016/j.ejor.2020.04.055

FinTech revolution: the impact of management information systems upon relative firm value and risk
Mitra, S. and Karathanasopoulos, A. 2020. FinTech revolution: the impact of management information systems upon relative firm value and risk. Journal of Banking and Financial Technology. 4, p. 175–187. https://doi.org/10.1007/s42786-020-00023-0

Ensemble Models in Forecasting Financial Markets
Karathanasopoulos, A., Mitra, S., Lo, C.C., Zaremba, A. and Osman, M. 2019. Ensemble Models in Forecasting Financial Markets. Journal of Computational Finance. 23 (3), pp. 101-119. https://doi.org/10.21314/JCF.2019.374

Big Data And PAC Learning In The Presence Of Noise: Implications For Financial Risk Management
Chinthalapati, V.L.R., Mitra, S. and Serguieva, A. 2019. Big Data And PAC Learning In The Presence Of Noise: Implications For Financial Risk Management. International Journal of Artificial Intelligence. 17 (1), pp. 34-56.

Post Global Financial Crisis Modelling: Credit Risk For Firms That Are Too Big To Fail
Clark, E., Mitra, S. and Jokung, O. 2019. Post Global Financial Crisis Modelling: Credit Risk For Firms That Are Too Big To Fail. International Journal of Financial Markets and Derivatives. 7 (1), pp. 15-39. https://doi.org/10.1504/IJFMD.2019.101235

Political Risk Modelling and Measurement From Stochastic Volatility Models
Mitra, S. 2019. Political Risk Modelling and Measurement From Stochastic Volatility Models. International Journal of Sustainable Economy. 11 (2), pp. 184-218. https://doi.org/10.1504/IJSE.2019.099064

Regression Based Scenario Generation: Applications For Performance Management
Mitra, S., Lim, S. and Karathanasopoulos, A. 2019. Regression Based Scenario Generation: Applications For Performance Management. Operations Research Perspectives. 6 100095. https://doi.org/10.1016/j.orp.2018.100095

Firm Value And The Impact of Operational Management
Mitra, S. and Karathanasopoulos, A. 2019. Firm Value And The Impact of Operational Management. Asia-Pacific Financial Markets. 26, pp. 61-85. https://doi.org/10.1007/s10690-018-9258-1

Stock-ADR Arbitrage: Microstructure Risk
Mitra, S. 2019. Stock-ADR Arbitrage: Microstructure Risk. Journal of International Financial Markets, Institutions and Money. 63 101132. https://doi.org/10.1016/j.intfin.2019.08.004

Efficient Option Risk Measurement With Reduced Model Risk
Mitra, S. 2017. Efficient Option Risk Measurement With Reduced Model Risk. Insurance: Mathematics and Economics. 72, pp. 163-174. https://doi.org/10.1016/j.insmatheco.2016.09.006

Stock Market Prediction Using Evolutionary Support Vector Machines: An Application To The ASE20 Index
Karathanasopoulos, A., Theofilatos, K.A., Sermpinis, D., Dunis, C., Mitra, S. and Stasinakis, C. 2016. Stock Market Prediction Using Evolutionary Support Vector Machines: An Application To The ASE20 Index. European Journal of Finance. 22 (12), pp. 1145-1163. https://doi.org/10.1080/1351847X.2015.1040167

Operational Risk: Emerging Markets, Sectors and Measurement
Mitra, S., Karathanasopoulos, A., Sermpinis, G., Dunis, C. and Hood, J. 2015. Operational Risk: Emerging Markets, Sectors and Measurement . European Journal of Operational Research. 241 (1), pp. 122-132. https://doi.org/10.1016/j.ejor.2014.08.021

Permalink - https://westminsterresearch.westminster.ac.uk/item/w3qw8/risk-lovers-mixed-risk-loving-and-the-preference-to-combine-good-with-good


Share this

Usage statistics

6 total views
0 total downloads
These values cover views and downloads from WestminsterResearch and are for the period from September 2nd 2018, when this repository was created.