Publication Date

2018

Document Type

Dissertation/Thesis

First Advisor

Anderson, Evan W.

Degree Name

Ph.D. (Doctor of Philosophy)

Legacy Department

Department of Economics

LCSH

Economics; Finance

Abstract

The ability of sentiments to impact macroeconomic activity and financial markets is unequivocally recognized. Economists and policymakers alike, agree that the extended periods of pessimistic sentiments impeded the economic recovery after the Great Recession. Despite this knowledge, there is still much more to know about the mechanisms by which these unpredictable changes in confidence perpetuate in economic and financial systems. It is also imperative to learn how to measure the exogenous shifts in the market sentiments and the sensitivity of asset prices and macroeconomic variables to them. This dissertation examines the sentiments in two ways. Using social network data, this work presents methods to identify sentiments of influential investors and highlight the effects of the stated opinions on the broader stock market and on individual securities. This paper concludes that these high-frequency sentiments influence prices and there are incremental benefits of recognizing investor heterogeneity in such analyses. The other research presents a production economy asset pricing model and elaborates on the interplay of macroeconomic and asset market observations with the changes in consumer preferences. The results reveal significant and persistent risks to the changes in market sentiments and simultaneously explain major moments of economic and financial series.

Comments

Advisors: Evan Anderson; Ai-ru Cheng.||Committee members: Alexander Garivaltis; George Slotsve.||Includes illustrations.||Includes bibliographical references.

Extent

147 pages

Language

eng

Publisher

Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type

Text

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