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Purpose – The purpose of this chapter is to investigate the relationship between emotion and European energy forward prices of oil, gas, coal and electricity during normal times and periods of extreme price movements.

Methodology/Approach – We use a biorhythm approach characterized by the seasonal affective disorder (SAD) variable to study the impact of emotion on energy markets. Normal times and periods of extreme price movements are approximated by OLS and quantile estimations, respectively.

Findings – We use European energy forward prices of oil, gas, coal, and electricity. European equity future index (Dow Jones Euro Stoxx 50) and euro/dollar US exchange rate are used as control variables for economic and financial environment. Estimating OLS and quantile regressions, we find that seasonal patterns have a significant impact during extreme volatility periods only. Further investigations reveal that the SAD effect is significant during periods of price decrease, but insignificant during price increase times. The out-of-sample predictive ability properties show that our “SAD model” outperforms significantly the pure “macroeconomic” one.

Originality/Value of chapter – This topic is novel in energy finance since I use psychological background theory to understand energy price dynamics. I illustrate the relevance of our approach by comparing the out-of-sample predictive ability of our model against macroeconomic one. My results could be considered to improve energy porfolio allocation.

This paper aims to give a brief review on behavioral economics and behavioral finance and discusses some of the previous research on agents' utility functions, applicable risk measures, diversification strategies and portfolio optimization.

The authors also cover related disciplines such as trading rules, contagion and various econometric aspects.

While scholars could first develop theoretical models in behavioral economics and behavioral finance, they subsequently may develop corresponding statistical and econometric models, this finally includes simulation studies to examine whether the estimators or statistics have good power and size. This all helps us to better understand financial and economic decision-making from a descriptive standpoint.

The research paper is original.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.