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Essays on Asset Pricing.
~
Columbia University.
Essays on Asset Pricing.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Essays on Asset Pricing.
作者:
Tomunen, Tuomas.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, 2020
面頁冊數:
147 p.
附註:
Source: Dissertations Abstracts International, Volume: 81-11, Section: A.
附註:
Advisor: Tetlock, Paul C.
Contained By:
Dissertations Abstracts International81-11A.
標題:
Finance.
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27956509
ISBN:
9798641900421
Essays on Asset Pricing.
Tomunen, Tuomas.
Essays on Asset Pricing.
- Ann Arbor : ProQuest Dissertations & Theses, 2020 - 147 p.
Source: Dissertations Abstracts International, Volume: 81-11, Section: A.
Thesis (Ph.D.)--Columbia University, 2020.
This item must not be sold to any third party vendors.
How are the prices of financial assets determined? In this dissertation, I test various theories empirically, focusing on several classes of bonds. In the first chapter, I test whether asset prices reflect the risk-exposures of financial intermediaries in a setting that is well suited to tackling concerns about omitted risk factors. I analyze catastrophe bonds whose cash flows are linked to the occurrence of natural disasters and find that 71% of the variation in their expected returns can be explained by a theoretically-motivated measure of financial intermediaries’ marginal rate of substitution. Assuming that natural disasters are independent of aggregate wealth, this pricing result is inconsistent with any explanation based on macroeconomic risk factors. However, the result is consistent with intermediary asset pricing models that suggest that financial intermediaries are marginal investors in capital markets. I also show that the premium on natural disaster risk has decreased significantly in recent years and has become less responsive to the occurrence of disasters, suggesting that intermediaries’ access to outside capital has improved over time. In the second chapter, which is coauthored with Robert J. Hodrick, we examine the statistical term structure model of Cochrane and Piazzesi (2005) and its affine counterpart, developed in Cochrane and Piazzesi (2008), in several out-of-sample analyzes. The model’s one-factor forecasting structure across bonds with two, three, four, and five years to maturity characterizes the term structures of additional major currencies in samples ending in 2003. In post-2003 data such one-factor structures again characterize each currency’s term structure, but we reject equality of the coefficients across the two samples. We derive currency return forecasting implications from the Cochrane and Piazzesi (2008) affine model showing that the term structure forecasting variables in each currency should predict cross-currency investments, but we find no support for these predictions in either pre-2004 or post-2003 data, whereas the interest differentials do predict currency returns. Here too, though, we find strong evidence of parameter instability as the parameter estimates on the interest differentials change sign. In recursive out-of-sample forecasts of excess rates of return on bonds in each currency, the Cochrane and Piazzesi (2008) term structure forecasting models fail to beat forecasts from the historical average excess rates of return. Graphical analysis indicates that the instability in the forecasting models’ parameters begins in the global financial crisis.
ISBN: 9798641900421Subjects--Topical Terms:
183252
Finance.
Subjects--Index Terms:
Affine term structure models
Essays on Asset Pricing.
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How are the prices of financial assets determined? In this dissertation, I test various theories empirically, focusing on several classes of bonds. In the first chapter, I test whether asset prices reflect the risk-exposures of financial intermediaries in a setting that is well suited to tackling concerns about omitted risk factors. I analyze catastrophe bonds whose cash flows are linked to the occurrence of natural disasters and find that 71% of the variation in their expected returns can be explained by a theoretically-motivated measure of financial intermediaries’ marginal rate of substitution. Assuming that natural disasters are independent of aggregate wealth, this pricing result is inconsistent with any explanation based on macroeconomic risk factors. However, the result is consistent with intermediary asset pricing models that suggest that financial intermediaries are marginal investors in capital markets. I also show that the premium on natural disaster risk has decreased significantly in recent years and has become less responsive to the occurrence of disasters, suggesting that intermediaries’ access to outside capital has improved over time. In the second chapter, which is coauthored with Robert J. Hodrick, we examine the statistical term structure model of Cochrane and Piazzesi (2005) and its affine counterpart, developed in Cochrane and Piazzesi (2008), in several out-of-sample analyzes. The model’s one-factor forecasting structure across bonds with two, three, four, and five years to maturity characterizes the term structures of additional major currencies in samples ending in 2003. In post-2003 data such one-factor structures again characterize each currency’s term structure, but we reject equality of the coefficients across the two samples. We derive currency return forecasting implications from the Cochrane and Piazzesi (2008) affine model showing that the term structure forecasting variables in each currency should predict cross-currency investments, but we find no support for these predictions in either pre-2004 or post-2003 data, whereas the interest differentials do predict currency returns. Here too, though, we find strong evidence of parameter instability as the parameter estimates on the interest differentials change sign. In recursive out-of-sample forecasts of excess rates of return on bonds in each currency, the Cochrane and Piazzesi (2008) term structure forecasting models fail to beat forecasts from the historical average excess rates of return. Graphical analysis indicates that the instability in the forecasting models’ parameters begins in the global financial crisis.
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