A Robust Analysis of the Risk-Structure of Equilibrium Term Structures of Bond Yields

期限(时间) 债券 经济 计量经济学 物理 财务 量子力学
作者
Anh Le,Kenneth J. Singleton
出处
期刊:Social Science Research Network [RELX Group (Netherlands)]
被引量:4
标识
DOI:10.2139/ssrn.2024222
摘要

Many prominent equilibrium term structure models (ETSMs) in which the state of the economy zt follows an affine process imply that the variation in expected excess returns on bond portfolio positions is fully spanned by the set of conditional variances ςt2 of zt. We show that these two assumptions alone – spanning of excess returns by the variances ςt2 of affine processes zt – are sufficient to econometrically identify the quantities of risk that span risk premiums from the term structure of bond yields. Using this result we derive maximum likelihood estimates of ςt2 and evaluate the goodness-of-fit of the family of affine ETSMs that imply this tight link between premiums and quantities of risk. These assessments are fully robust to the values of the parameters governing preferences and the evolution of the state zt, and to whether or not the economy is arbitrage free. Our findings suggest that, to be consistent with U.S. macroeconomic and Treasury yield data, affine ETSMs should have the features that: the fundamental sources of risks, including consumption growth, inflation, and yield volatilities are driven by distinct economic shocks; consumption growth risk alone is unlikely to fully account for the predictability of excess returns on bonds; and inflation risk, and not long-run risks or variation in risk premiums arising from habit-based preferences, is likely to be the dominant risk underlying risk premiums in U.S. Treasury markets.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
3秒前
Mansis发布了新的文献求助10
4秒前
YifanWang应助瘦瘦冬寒采纳,获得10
4秒前
ZHAO应助瘦瘦冬寒采纳,获得10
4秒前
4秒前
GE发布了新的文献求助10
4秒前
活泼的枕头完成签到,获得积分10
5秒前
5秒前
Fan发布了新的文献求助10
5秒前
6秒前
7秒前
赘婿应助tianmaobo采纳,获得10
7秒前
星辰大海发布了新的文献求助10
8秒前
8秒前
yu关注了科研通微信公众号
8秒前
11秒前
小马甲应助hh采纳,获得10
12秒前
科研浦东发布了新的文献求助10
12秒前
13秒前
123额发布了新的文献求助10
14秒前
李李完成签到,获得积分10
15秒前
七田皿发布了新的文献求助10
16秒前
纯情的阁发布了新的文献求助10
16秒前
小轩子完成签到 ,获得积分20
16秒前
华仔应助荔枝铎采纳,获得30
17秒前
pumpkin发布了新的文献求助10
17秒前
希哩哩完成签到 ,获得积分10
17秒前
18秒前
19秒前
123完成签到,获得积分10
20秒前
20秒前
思源应助Jinyang采纳,获得10
20秒前
dhfify完成签到,获得积分10
21秒前
22秒前
CodeCraft应助嘎嘎采纳,获得30
22秒前
章英健发布了新的文献求助50
23秒前
cjl完成签到,获得积分10
24秒前
七田皿完成签到,获得积分10
24秒前
希望天下0贩的0应助123额采纳,获得10
24秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
核安全综合知识2024版 500
Photothermal Science and Techniques 500
The Effective Clinical Neurologist 3ed 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7715295
求助须知:如何正确求助?哪些是违规求助? 9270476
关于积分的说明 20082239
捐赠科研通 7291644
什么是DOI,文献DOI怎么找? 3298452
关于科研通互助平台的介绍 2452617
邀请新用户注册赠送积分活动 2305889