SSRN Author: Robert A. JarrowRobert A. Jarrow SSRN Content
https://www.ssrn.com/author=16130
https://www.ssrn.com/rss/en-usThu, 06 Jan 2022 01:25:15 GMTeditor@ssrn.com (Editor)Thu, 06 Jan 2022 01:25:15 GMTwebmaster@ssrn.com (WebMaster)SSRN RSS Generator 1.0REVISION: The Valuation of Corporate Coupon BondsThis paper shows that, for a sample of corporate bond prices, credit spreads and therefore discount rates of promised coupons and principal differ substantially. To better fit this stylized fact we propose and estimate a tractable, arbitrage-free valuation model for corporate bonds that includes a more realistic recovery rate process. Existing spread calculations assume that coupons and principal have the same seniority. Thus, these spread calculations are misspecified because they include recovery rates for coupons due after default. Misspecification errors resulting from such a coupon recovery assumption depend on recovery rates, coupons, maturity, and default probabilities and can be substantial in size. We provide two pieces of evidence in support of the no-coupon recovery model: (i) for a large sample of bond market transactions our model has lower pricing errors than one assuming recovery on all coupons, and (ii) the model's outperformance magnitude is closely linked to model ...
https://www.ssrn.com/abstract=3277092
https://www.ssrn.com/2090304.htmlWed, 05 Jan 2022 00:54:33 GMTREVISION: The Valuation of Corporate Coupon BondsThis paper shows that, for a sample of corporate bond prices, credit spreads and therefore discount rates of promised coupons and principal differ substantially. To better fit this stylized fact we propose and estimate a tractable, arbitrage-free valuation model for corporate bonds that includes a more realistic recovery rate process. Existing spread calculations assume that coupons and principal have the same seniority. Thus, these spread calculations are misspecified because they include recovery rates for coupons due after default. Misspecification errors resulting from such a coupon recovery assumption depend on recovery rates, coupons, maturity, and default probabilities and can be substantial in size. We provide two pieces of evidence in support of the no-coupon recovery model: (i) for a large sample of bond market transactions our model has lower pricing errors than one assuming recovery on all coupons, and (ii) the model's outperformance magnitude is closely linked to model ...
https://www.ssrn.com/abstract=3277092
https://www.ssrn.com/2081699.htmlFri, 03 Dec 2021 02:15:01 GMTREVISION: Computing the Probability of a Financial Market Failure: A New Measure of Systemic RiskThis paper characterizes the probability of a market failure defined as the default of two or more globally systemically important banks (G-SIBs) in a small interval of time. The default probabilities of the G-SIBs are correlated through the possible existence of a market-wide stress event. The characterization employs a multivariate Cox process across the G-SIBs, which allows us to relate our work to the existing literature on intensity-based models. Various theorems related to market failure probabilities are derived, including the probability of a market failure due to two banks defaulting over the next infinitesimal interval, the probability of a catastrophic market failure, the impact of increasing the number of G-SIBs in an economy, and the impact of changing the initial conditions of the economy's state variables. We also show that if there are too many G-SIBs, a market failure is inevitable, i.e., the probability of a market failure tends to 1.
https://www.ssrn.com/abstract=3946914
https://www.ssrn.com/2078806.htmlMon, 22 Nov 2021 01:13:06 GMTREVISION: The Valuation of Corporate Coupon BondsThis paper shows that, for a sample of corporate bond prices, credit spreads and therefore discount rates of promised coupons and principal differ substantially. To better fit this stylized fact we propose and estimate a tractable, arbitrage-free valuation model for corporate bonds that includes a more realistic recovery rate process. Existing spread calculations assume that coupons and principal have the same seniority. Thus, these spread calculations are misspecified because they include recovery rates for coupons due after default. Misspecification errors resulting from such a coupon recovery assumption depend on recovery rates, coupons, maturity, and default probabilities and can be substantial in size. We provide two pieces of evidence in support of the no-coupon recovery model: (i) for a large sample of bond market transactions our model has lower pricing errors than one assuming recovery on all coupons, and (ii) the model's outperformance magnitude is closely linked to model ...
https://www.ssrn.com/abstract=3277092
https://www.ssrn.com/2075521.htmlTue, 09 Nov 2021 22:05:50 GMTNew: The Economics of Insurance: A Derivatives-Based ApproachThis article revisits the economics of insurance using insights from derivatives pricing and hedging. Applying this perspective, I emphasize the following insights applicable to insurance. First, I provide a valid justification for the use of arbitrage-free insurance premiums. This justification applies in both complete and incomplete markets. Second, I demonstrate the importance of diversifiable idiosyncratic risk for the determination of insurance premiums. And third, analyzing the insurance industry using the functional approach, I show the importance of derivatives and the synthetic construction of derivatives for reducing an insurance company's insolvency risk.
https://www.ssrn.com/abstract=3957018
https://www.ssrn.com/2075128.htmlTue, 09 Nov 2021 10:21:50 GMTREVISION: The Low-volatility Anomaly and the Adaptive Multi-Factor ModelThe paper provides a new explanation of the low-volatility anomaly. We use the Adaptive Multi-Factor (AMF) model estimated by the Groupwise Interpretable Basis Selection (GIBS) algorithm to find those basis assets significantly related to low and high volatility portfolios. These two portfolios load on very different factors, indicating that volatility is not an independent risk, but that it's related to existing risk factors. The out-performance of the low-volatility portfolio is due to the (equilibrium) performance of these loaded risk factors. The practical insight is that the long and short legs of a portfolio are with different risks and need to be modeled separately. Our methodology is applicable to any long-short anomaly but we focus on the low-volatility anomaly since it is formed explicitly on the risk characteristic rather than on embedded risks of other anomalies. The AMF model outperforms the Fama-French 5-factor model significantly both in-sample and out-of-sample.
https://www.ssrn.com/abstract=3834026
https://www.ssrn.com/2073747.htmlWed, 03 Nov 2021 00:51:48 GMTREVISION: Time-Invariance Coefficients Tests with the Adaptive Multi-Factor ModelThe purpose of this paper is to test the time-invariance of the beta coefficients estimated by the Adaptive Multi-Factor (AMF) model. The AMF model is implied by the generalized arbitrage pricing theory (GAPT), which implies constant beta coefficients. The AMF model utilizes a Groupwise Interpretable Basis Selection (GIBS) algorithm to identify the relevant factors from among all traded ETFs. We compare the AMF model with the Fama-French 5-factor (FF5) model. We show that for nearly all time periods with length less than 6 years, the beta coefficients are time-invariant for the AMF model, but not for the FF5 model. This implies that the AMF model with a rolling window (such as 5 years) is more consistent with realized asset returns than is the FF5 model.
https://www.ssrn.com/abstract=3834053
https://www.ssrn.com/2073746.htmlWed, 03 Nov 2021 00:51:32 GMTREVISION: The Low-volatility Anomaly and the Adaptive Multi-Factor ModelThe paper provides a new explanation of the low-volatility anomaly. We use the Adaptive Multi-Factor (AMF) model estimated by the Groupwise Interpretable Basis Selection (GIBS) algorithm to find those basis assets significantly related to low and high volatility portfolios. These two portfolios load on very different factors, indicating that volatility is not an independent risk, but that it's related to existing risk factors. The out-performance of the low-volatility portfolio is due to the (equilibrium) performance of these loaded risk factors. The practical insight is that the long and short legs of a portfolio are with different risks and need to be modeled separately. Our methodology is applicable to any long-short anomaly but we focus on the low-volatility anomaly since it is formed explicitly on the risk characteristic rather than on embedded risks of other anomalies. The AMF model outperforms the Fama-French 5-factor model significantly both in-sample and out-of-sample.
https://www.ssrn.com/abstract=3834026
https://www.ssrn.com/2059531.htmlTue, 14 Sep 2021 00:29:36 GMTREVISION: The Low-volatility Anomaly and the Adaptive Multi-Factor ModelThe paper provides a new explanation of the low-volatility anomaly. We use the Adaptive Multi-Factor (AMF) model estimated by the Groupwise Interpretable Basis Selection (GIBS) algorithm to find those basis assets significantly related to low and high volatility portfolios. These two portfolios load on very different factors, indicating that volatility is not an independent risk, but that it's related to existing risk factors. The out-performance of the low-volatility portfolio is due to the (equilibrium) performance of these loaded risk factors. The AMF model outperforms the Fama-French 5-factor model both in-sample and out-of-sample.
https://www.ssrn.com/abstract=3834026
https://www.ssrn.com/2043587.htmlTue, 20 Jul 2021 16:23:06 GMTREVISION: Time-Invariance Coefficients Tests with the Adaptive Multi-Factor ModelThe purpose of this paper is to test the time-invariance of the beta coefficients estimated by the Adaptive Multi-Factor (AMF) model. The AMF model is implied by the generalized arbitrage pricing theory (GAPT), which implies constant beta coefficients. The AMF model utilizes a Groupwise Interpretable Basis Selection (GIBS) algorithm to identify the relevant factors from among all traded ETFs. We compare the AMF model with the Fama-French 5-factor (FF5) model. We show that for nearly all time periods with length less than 6 years, the beta coefficients are time-invariant for the AMF model, but not for the FF5 model. This implies that the AMF model with a rolling window (such as 5 years) is more consistent with realized asset returns than is the FF5 model.
https://www.ssrn.com/abstract=3834053
https://www.ssrn.com/2043583.htmlTue, 20 Jul 2021 16:21:37 GMTREVISION: The Low-volatility Anomaly and the Adaptive Multi-Factor ModelThe paper provides a new explanation of the low-volatility anomaly. We use the Adaptive Multi-Factor (AMF) model estimated by the Groupwise Interpretable Basis Selection (GIBS) algorithm to find those basis assets significantly related to low and high volatility portfolios. These two portfolios load on very different factors, indicating that volatility is not an independent risk, but that it's related to existing risk factors. The out-performance of the low-volatility portfolio is due to the (equilibrium) performance of these loaded risk factors. The AMF model outperforms the Fama-French 5-factor model both in-sample and out-of-sample.
https://www.ssrn.com/abstract=3834026
https://www.ssrn.com/2020738.htmlMon, 03 May 2021 20:55:04 GMTREVISION: High-Dimensional Estimation, Basis Assets, and the Adaptive Multi-Factor ModelThe paper proposes a new algorithm for the high-dimensional financial data -- the Groupwise Interpretable Basis Selection (GIBS) algorithm, to estimate a new Adaptive Multi-Factor (AMF) asset pricing model, implied by the recently developed Generalized Arbitrage Pricing Theory, which relaxes the convention that the number of risk-factors is small. We first obtain an adaptive collection of basis assets and then simultaneously test which basis assets correspond to which securities, using high-dimensional methods. The AMF model, along with the GIBS algorithm, is shown to have a significantly better fitting and prediction power than the Fama-French 5-factor model.
https://www.ssrn.com/abstract=3169905
https://www.ssrn.com/2017923.htmlMon, 26 Apr 2021 09:03:05 GMT