Off-campus UMass Amherst users: To download campus access dissertations, please use the following link to log into our proxy server with your UMass Amherst user name and password.

Non-UMass Amherst users: Please talk to your librarian about requesting this dissertation through interlibrary loan.

Dissertations that have an embargo placed on them will not be available to anyone until the embargo expires.

Author ORCID Identifier

N/A

AccessType

Open Access Dissertation

Document Type

dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Management

Year Degree Awarded

2018

Month Degree Awarded

September

First Advisor

essor Hossein B. Kazemi (Chair)

Second Advisor

essor Benjamin Branch

Third Advisor

essor Sanjay Nawalkha

Fourth Advisor

essor Manhaz Madavi (Smith College)

Subject Categories

Applied Statistics | Econometrics | Finance | Finance and Financial Management | Macroeconomics | Statistical Models

Abstract

ABSTRACT

ESSAYS IN FINANCIAL ECONOMICS: ANNOUNCEMENT EFFECTS IN FIXED INCOME MARKETS

PHD IN FINANCE MAY 2018

JAMES J FOREST

B.A., FRAMINGHAM STATE UNIVERSITY

M.S., NORTHEASTERN UNIVERSITY

Ph.D., UNIVERSITY OF MASSACHUSETTS – AMHERST

Directed by: Professor Hossein B. Kazemi

This dissertation demonstrates the use of empirical techniques for dealing with modeling issues that arise when analyzing announcement effects in fixed income markets. It describes empirical challenges in achieving unbiased and efficient parameter estimates and shows the importance of modelling a wide range of macroeconomic announcement effects to avoid omitted variable bias. Employing techniques common in Macroeconomics, financial market researchers are better able to provide meaningful results.

In “The Effect of Macroeconomic Announcements on Credit Markets: An Autometric General-to-Specific Analysis of the Greenspan Era,” I show that a congruent, parsimonious, encompassing model discovered using David Hendry’s econometric modelling approach overcomes the many inadequacies of the typical static models of US Treasury returns. The typical specification tends to fail most specification tests. Results suggest a place for general-to-specific modelling in financial economics, a place where it has only recently been employed.

In “A High-Frequency Analysis of Trading Activity in the Corporate Bond Market: Macro Announcements or Seasonality?” Here we explore whether factors that drive trading activity of US corporate bond market. Our main findings are that the thinly-traded market for corporate bonds is less affected by surprises in individual economic reports and that the market is dominated by day-of-week and time-of-day affects. We find that, unlike daily returns on the S&P 500, corporate bonds are sensitive to surprises in both labor market and inflation data. Trading activity is affected by absolute surprises in core CPI and nonfarm payrolls, but neither core PPI nor jobless claims affect order flow. Perhaps most interesting, however, is the presence of “behavioral seasonal” effects associated with the onset and incidence of seasonal affective disorder. This “winter blues” effect has been seen affecting activity in equity markets by Kamstra, M. J., L. A. Kramer and M. D. Levi (American Economic Review; 2000, 2003).

In “The Effect of Treasury Auction Results on Interest Rates: The 1990s Experience,” I examine the response of U.S. Treasury returns to auction announcements. Rate changes differ significantly on auction days for one-year bills. Surprises in the release of bid-to-cover ratios and noncompetitive bidding affect Treasury 30-year returns significantly. Other maturities, however, are relatively unaffected. The results complement the study by Lou, Yan and Zhang (2013) and show the benefits of controlling macroeconomic announcements when analyzing market responses to auctions.

DOI

https://doi.org/10.7275/12736173

Download

Share

COinS