國立虎尾科技大學 |

Essays in Risk Management and Financial Econometrics.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Essays in Risk Management and Financial Econometrics./
Author:	Liu, Haoyang.
Description:	1 online resource (96 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-08(E), Section: A.
Contained By:	Dissertation Abstracts International79-08A(E).
Subject:	Finance. -
Online resource:	click for full text (PQDT)
ISBN:	9780355831351

Essays in Risk Management and Financial Econometrics.
Liu, Haoyang.

Essays in Risk Management and Financial Econometrics. - 1 online resource (96 pages)

Source: Dissertation Abstracts International, Volume: 79-08(E), Section: A.

Thesis (Ph.D.)--University of California, Berkeley, 2017.

Includes bibliographical references

This dissertation consists of three chapters that concern risk management and financial econometrics. Fannie Mae and Freddie Mac's implicit government guarantee is widely argued to cause irresponsible risk taking. Despite moral-hazard concerns, this paper presents evidence that Fannie Mae and Freddie Mac (the GSEs) more effectively managed home price risks during the 2000-2006 housing boom than private insurers. Mortgage origination data reveal that the GSEs were selecting loans with increasingly higher percentage of down payments, or lower loan to value ratios (LTVs), in boom areas than in other areas. Furthermore, the decline of LTVs in boom areas stems entirely from the segment insured by the GSEs only, and none of the decline stems from the segment co-insured by private mortgage insurers. Private mortgage insurers also did not lower their exposure to home price risks along other dimensions, including the percentage of high LTV GSE loans they insured. To quantify how the GSEs' portfolios would have performed under alternative home price scenarios, I build an insurance valuation model based on competing-risk hazard regressions, calibrated Hull and White term-structure model, and forecasting prepayment and default speeds. I find that the GSEs' risk management would have been sufficient for the historically average 32% mean reversion but insufficient for the realized 95% mean reversion between 2006 and 2011. My results highlight that post-crisis reform of the mortgage insurance industry should carefully consider additional factors besides moral hazard, such as mortgage insurers' future home price assumptions.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355831351Subjects--Topical Terms:

559073
Finance.
Index Terms--Genre/Form:

554714
Electronic books.

Essays in Risk Management and Financial Econometrics.
LDR:04819ntm a2200349Ki 4500 001 918471
005 20181026115416.5
006 m o u
007 cr mn||||a|a||
008 190606s2017 xx obm 000 0 eng d
020 $a 9780355831351
035 $a (MiAaPQ)AAI10280857
035 $a (MiAaPQ)berkeley:16902
035 $a AAI10280857
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Liu, Haoyang. $3 1192801
245 1 0 $a Essays in Risk Management and Financial Econometrics.
264 0 $c 2017
300 $a 1 online resource (96 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertation Abstracts International, Volume: 79-08(E), Section: A.
500 $a Advisers: Nancy Wallace; Christopher Palmer.
502 $a Thesis (Ph.D.)--University of California, Berkeley, 2017.
504 $a Includes bibliographical references
520 $a This dissertation consists of three chapters that concern risk management and financial econometrics. Fannie Mae and Freddie Mac's implicit government guarantee is widely argued to cause irresponsible risk taking. Despite moral-hazard concerns, this paper presents evidence that Fannie Mae and Freddie Mac (the GSEs) more effectively managed home price risks during the 2000-2006 housing boom than private insurers. Mortgage origination data reveal that the GSEs were selecting loans with increasingly higher percentage of down payments, or lower loan to value ratios (LTVs), in boom areas than in other areas. Furthermore, the decline of LTVs in boom areas stems entirely from the segment insured by the GSEs only, and none of the decline stems from the segment co-insured by private mortgage insurers. Private mortgage insurers also did not lower their exposure to home price risks along other dimensions, including the percentage of high LTV GSE loans they insured. To quantify how the GSEs' portfolios would have performed under alternative home price scenarios, I build an insurance valuation model based on competing-risk hazard regressions, calibrated Hull and White term-structure model, and forecasting prepayment and default speeds. I find that the GSEs' risk management would have been sufficient for the historically average 32% mean reversion but insufficient for the realized 95% mean reversion between 2006 and 2011. My results highlight that post-crisis reform of the mortgage insurance industry should carefully consider additional factors besides moral hazard, such as mortgage insurers' future home price assumptions.
520 $a The second chapter studies high dimensional time series, with application to estimating the mean variance frontier. One persistent challenge in macroeconmics and finance is how to draw inference from data with a large cross section but short time series. Financial econometric techniques all are designed for large time series and small cross-sections. However, financial data typically has a large cross section and short time series (large-N small-T). One particular large-N small-T impact is the underestimation of risk in the mean variance frontier. We propose a correction for the finite sample bias when the underlying returns are high dimensional linear time series. Our algorithm first corrects for the bias in eigenvalues of the asset return covariance matrix, and then estimate the contribution of each leading factor to the mean variance frontier. A cross validation method is employed to select the optimal number of leading factors. Performance of the proposed methods is examined through extensive simulation studies.
520 $a The third chapter studies how expected home prices affect borrowers' default behavior. One of the penalties mortgage defaulters face is being locked out of the mortgage market and missing the home price appreciation. I find that this penalty deters some borrowers from defaulting. A higher future home price growth implies a lower ex-ante default probability. Furthermore, high credit score borrowers react more to past home price declines and future home price appreciation than low credit score borrowers. This suggests that high credit score borrowers are more likely to be strategic defaulters. A model is built to study the effect of changing the cooling off period. In high expected home price appreciation areas, a longer cooling-off period amplifies the impact of each foreclosure. In low expected home price appreciation areas, a longer cooling-off period reduces the number of foreclosures.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Finance. $3 559073
655 7 $a Electronic books. $2 local $3 554714
690 $a 0508
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of California, Berkeley. $b Business Administration, Ph.D. Program. $3 1180579
773 0 $t Dissertation Abstracts International $g 79-08A(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10280857 $z click for full text (PQDT)