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Textual analysis in empirical asset pricing
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Nguyen, My Tra (2022) Textual analysis in empirical asset pricing. PhD thesis, University of Warwick.
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Official URL: http://webcat.warwick.ac.uk/record=b3795658
Abstract
This thesis consists of three chapters, in which I discuss how textual analysis can contribute to the area of empirical asset pricing. In Chapter 2, I implement textual analysis based on newspapers articles and develop a novel measure of U.S. populist rhetoric. Aggregate Populist Rhetoric (APR) Index spikes around populist events. I decompose the APR Index into sub-indices. I show that APR Index and International Relations sub-index are negatively priced in the cross-section of currency excess returns. Currencies that perform well (badly) when U.S. populist rhetoric is high yield low (high) expected excess returns. Investors require high risk premium for holding currencies which underperform in times of rising U.S. populist rhetoric, especially in the post-crisis period. A long-short strategy that buys (sells) currencies with high (low) exposure to U.S. populism offers diversification benefits.
In Chapter 3, I use textual analysis to identify the set of Trump tweets that contain information on macroeconomic policy, trade or exchange rate content. I then analyse the effects of Trump tweets on the intraday trading activity of foreign exchange markets, such as trading volume, volatility and FX spot returns. I find that Trump tweets reduce speculative trading, with a corresponding decline in trading volume and volatility, and induce a bias reflecting Trump’s (optimistic) views on the U.S. economy. I rationalise these results within a model of Trump tweets revealing economic content as a public signal that reduces disagreement among speculators.
In Chapter 4, I apply textual analysis to construct the Fiscal News Index based on a large sample of U.S. Presidential Speeches between February 1929 and December 2020. The Fiscal News Index is a priced risk factor in the cross-section of stock returns. Investors demand higher expected returns for holding stocks with high exposure to Fiscal News Index. A long short trading strategy based on this risk factor generates an average excess returns of 8.2% annually with a Sharpe ratio of 0.86.
Item Type: | Thesis (PhD) | ||||
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Subjects: | H Social Sciences > HB Economic Theory H Social Sciences > HC Economic History and Conditions H Social Sciences > HG Finance J Political Science > JK Political institutions (United States) |
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Library of Congress Subject Headings (LCSH): | Capital assets pricing model, Discourse analysis, Trump, Donald, 1946- -- Language, Twitter, Communication in politics -- United States -- History -- 21st century, United States -- Economic conditions -- 21st century, Investments -- Management -- 21st century, Macroeconomics -- United States, Speculation, Stocks | ||||
Official Date: | February 2022 | ||||
Dates: |
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Institution: | University of Warwick | ||||
Theses Department: | Warwick Business School | ||||
Thesis Type: | PhD | ||||
Publication Status: | Unpublished | ||||
Supervisor(s)/Advisor: | Gozluklu, Arie ; Filippou, Ilias ; Viswanath-Natraj, Ganesh | ||||
Format of File: | |||||
Extent: | xi, 208 leaves : illustrations, charts | ||||
Language: | eng |
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