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Title: Challenges to rationality : an examination on the influence of environmental conditions on decision making in real-world financial markets
Author: Costa Sperb, Luis Felipe
ISNI:       0000 0004 7960 7728
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2019
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This thesis, which is divided into three papers, investigates the influence of weather and other atmospheric conditions on decision making in naturalistic environments and its implications for market efficiency and forecasting. The decision setting chosen is the UK horserace betting market. The distinctive features of this setting which enables to investigate behaviour more clearly than in other financial markets is the generation of an unequivocal outcome (a winner) within a finite time frame, thus offering an objective benchmark to inspect decision making anomalies and factors which may have caused them. The first paper investigates the influence of weather and other atmospheric factors on the performance of horses and jockeys, and the extent to which probability estimates derived from betting markets odds can be improved by incorporating this influence. The findings suggest that bettors do not fully account for such influence on horserace performance, and by correcting such inefficiency in odds, forecasting power was significantly improved. It was also demonstrated that substantial economic gains were attainable when adopting forecasts that make full use of information related to the influence of weather and other atmospheric conditions on the performance of horses and jockeys. The findings of this paper have important implications as they may suggest that in a far wider variety of naturalistic contexts, decision makers may not be making full use of relevant information that is publicly available. This is likely to lead to sub-optimal decisions and, in particular reduce forecasting performance, leading to misleading forecasts. The second paper explores whether the calibration of probabilistic forecasts derived from betting odds are affected by weather and other atmospheric conditions, via misattribution of mood, as well as the extent to which these probability estimates can be improved by correcting for any misattribution of mood detected. This paper shows that after discounting the effects of the prevailing weather and other atmospheric conditions on the performance of horses and jockeys, the accuracy of probabilistic forecasts derived from betting odds are systematically affected by the same conditions. By correcting for misattribution of mood, this paper shows that significantly better forecasts can be derived from betting odds, and that these have substantial economic value. The principal conclusion from this paper is that when the purpose of a financial market is to derive accurate probabilistic estimates from final contract prices, forecast accuracy can be substantially improved by understanding and correcting for situations where markets systematically under-perform. The third paper addresses the conflicting and inconclusive evidence of the existence of weather effects, via misattribution of mood, on market efficiency in naturalistic financial markets. A review on research on weather-induced misattribution of mood in naturalistic financial markets indicates that shortcomings in previous research may be the foundation to these conflicting and inconclusive results. This paper then proposes that investigating the influence of weather-induced misattribution of mood on the level of favourite-longshot bias (FLB) (a phenomenon whereby favourites/longshots are under-/over-bet) displayed in horserace betting markets addresses all shortcomings identified in previous research. The results show that under weather conditions when individuals are expected to experience good mood (cf. bad mood), they over-/underestimate the winning probabilities of longshot/favourite contestants at a greater extent, and that such effect inflict substantial economic cost on decision makers. Remarkably, these results remain significant when controlling for various factors known to influence the FLB, hence providing robust evidence to support the conclusions that weather-induced misattribution of mood can significantly affect decision making in a naturalistic financial market, and that (in horserace markets) it is weather conditions associated with good mood which damage decision quality. Importantly, the results of this paper suggest that decision anomalies may be innate to the human decision making process.
Supervisor: Johnson, Johnnie Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available