{'fraction_non_alphanumeric': 0.02511415525114155, 'fraction_numerical': 0.0, 'mean_word_length': 5.54228855721393, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Examining financial puzzles from an evolutionary perspective

In this thesis, we examine some puzzles in finance from an evolutionary perspective. We first provide a literature review of evolutionary psychology, and discuss three main findings; the frequentist hypothesis, applications from risk-sensitive optimal foraging theory, and the cheater detection hypothesis. Next we introduce some of the most-researched puzzles in the finance literature. Examples include overreaction, loss aversion, and the equity premium puzzle. Following this, we discuss risk-sensitive optimal foraging theory further and examine some of the financial puzzles using the framework of risk-sensitive foraging. Finally, we develop a dynamic patch selection model which gives the patch selection strategy that maximizes an organism's long-run probability of survival. It is from this optimal patch strategy that we observe loss aversion. Throughout the thesis, we stress the following: humans' behavior in financial markets is neither inherently irrational, nor is it rational. Rather the puzzles occur as a consequence of evolutionarily-optimal cognitive mechanisms being utilized in environments other than the ancestral domain in which they evolved to adapt in. Thesis Supervisor: Andrew W. Lo Title: Harris & Harris Group Professor