Please use this identifier to cite or link to this item:
Title: Essays on behavioral and experimental finance
Authors: Zhu, Jiahua
Keywords: Social sciences::Economic theory::Microeconomics
Issue Date: 2020
Publisher: Nanyang Technological University
Source: Zhu, J. (2020). Essays on behavioral and experimental finance. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: Behavioral finance has become a prevalent research area to investigate the bounded rationality of investors and inefficiency of the financial market, which is different from the traditional economic and financial theory that assumes the agents are rational, self-controlled, and are not confused by behavioral bias or information processing errors. This thesis contains three essays that revolve around the topic of behavioral and experimental financial, which aims to provide new insight to the ongoing growth of behavioral finance literature and possible policies to maintain the stability of the market. Chapter 1 provides two explanations for the findings found by Bao et al. (2017) that bubbles are less likely to emerge in experimental asset markets when subjects make price forecasts only (Learning to Forecast treatment, LtF) than when they make trading quantity decisions (Learning to Optimize treatment, LtO) or both price forecasts and quantity decisions (mixed treatment). First, the subjects in the LtO and mixed treatment usually have a high intensity of choice parameter, which leads them to switch faster between the decision rules and a greater fraction of the population to choose the destabilizing strong trend-following rule. Second, the actual quantity decision may deviate substantially and persistently from the conditionally optimal level given the price forecasts in the mixed treatment, which amplifies the price deviation from the fundamental value. Our findings are helpful for understanding the root of financial bubbles and financial crisis, and designing policies to stabilize the market. Chapter 2 explores how ambiguous signals and ambiguity aversion influence individuals' expectations and the pricing of asset in experimental financial markets. In line with the theory of Epstein and Schneider (2008), we find that subjects' degree of ambiguity aversion is positively correlated with their expectations about the variance of ambiguous signals. These signals matter for the determination of asset prices. We find that the distribution of the excess return of the asset exhibits negative skewness, and that price volatility is significantly larger under ambiguous signals. Our findings provide evidence in support of the idea that ambiguous information and ambiguity aversion may be a source of negative skewness and excess volatility in financial markets. Chapter 3, following Bloomfield and Hales (2002), investigates how individuals use measures of apparent predictability from the price chart to predict future market prices. Our findings are as follows: first, we confirm the experimental findings by Bloomfield and Hales (2002) that people use the number of reversals as a proxy for the predictability. Their predicted price changes are smaller when there are fewer reversals. Second, people also use the volatility of the price as a measure of predictability. Third, social intelligence and cognitive ability do not seem to influence people's predicting ability or their perceived predictability of asset prices. In summary, these three chapters investigate expectation formation and belief updating in financial markets, find that behavioral bias affects individuals' expectations and market efficiency. These findings provide informative suggestions for designing financial education and regulation program to stabilize the financial market.
DOI: 10.32657/10356/144057
Schools: School of Social Sciences 
Rights: This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SSS Theses

Files in This Item:
File Description SizeFormat 
NTU_THESIS_JH.pdf3.04 MBAdobe PDFThumbnail

Page view(s) 50

Updated on Sep 26, 2023

Download(s) 20

Updated on Sep 26, 2023

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.