Time-Varying Risk and Risk Premiums in Frontier Markets

2011 ◽  
Author(s):  
Galin Todorov ◽  
Prasad V. Bidarkota
Keyword(s):  
Time Varying ◽  
Risk Premiums

Tests of Asset Pricing with Time-Varying Expected Risk Premiums and Market Betas

1987 ◽  
Vol 42 (2) ◽  
pp. 201-220 ◽  
Author(s):  
WAYNE E. FERSON ◽  
SHMUEL KANDEL ◽  
ROBERT F. STAMBAUGH
Keyword(s):  
Asset Pricing ◽  
Time Varying ◽  
Risk Premiums

Bond Risk Premiums with Machine Learning

2020 ◽  
Author(s):  
Daniele Bianchi ◽  
Matthias Büchner ◽  
Andrea Tamoni
Keyword(s):  
Machine Learning ◽  
Yield Curve ◽  
Return Predictability ◽  
Time Varying ◽  
Short Term ◽  
Risk Premiums ◽  
Machine Learning Methods ◽  
Yield Information ◽  
Bond Return ◽  
Bond Risk

Abstract We show that machine learning methods, in particular, extreme trees and neural networks (NNs), provide strong statistical evidence in favor of bond return predictability. NN forecasts based on macroeconomic and yield information translate into economic gains that are larger than those obtained using yields alone. Interestingly, the nature of unspanned factors changes along the yield curve: stock- and labor-market-related variables are more relevant for short-term maturities, whereas output and income variables matter more for longer maturities. Finally, NN forecasts correlate with proxies for time-varying risk aversion and uncertainty, lending support to models featuring both channels.

Industry Characteristics, Risk Premiums, and Debt Pricing

2016 ◽  
Vol 92 (1) ◽  
pp. 1-27 ◽  
Author(s):  
Dan Amiram ◽  
Alon Kalay ◽  
Gil Sadka
Keyword(s):  
Industry Structure ◽  
Empirical Literature ◽  
Time Varying ◽  
External Shocks ◽  
Expected Loss ◽  
Firm Level ◽  
Risk Premiums ◽  
Industry Level ◽  
Debt Pricing ◽  
Loan Portfolios

ABSTRACT Despite theoretical and anecdotal evidence highlighting the importance of industry-level analyses to lenders, the empirical literature on debt pricing has focused almost exclusively on firm-level forces that affect expected loss. This paper provides empirical evidence that industry-level characteristics relate to debt pricing through risk premiums. We address the empirical challenges that arise when testing these theories by using a proprietary dataset of time-varying and forward-looking measures of industry characteristics. These characteristics include growth, sensitivity to external shocks, and industry structure, all measured at the six-digit NAICS level. Our results show that lenders demand higher spreads to bear industry-level risk. The relation exists within subsamples with constant credit ratings, and strengthens when lenders' loan portfolios are less diversified and during periods when diversification is difficult. Therefore, our results suggest that industry characteristics relate to debt pricing by informing lenders not only about expected loss, but also about risk premiums. JEL Classifications: G31; G32; G33; M21.

Do time-varying risk premiums explain labor market performance?

2011 ◽  
Vol 99 (2) ◽  
pp. 385-399 ◽  
Author(s):  
Long Chen ◽  
Lu Zhang
Keyword(s):  
Labor Market ◽  
Market Performance ◽  
Time Varying ◽  
Risk Premiums

scholarly journals Hedge Funds, Arbitrage, and Timing

2020 ◽  
Vol 13 (1) ◽  
pp. 45
Author(s):  
Daniel T. Lawson ◽  
Robert L. Schwartz ◽  
Seth D. Thomas
Keyword(s):  
Hedge Funds ◽  
Small Firms ◽  
Hedge Fund ◽  
Time Varying ◽  
Risk Premiums ◽  
Growth Anomaly ◽  
Asset Pricing Anomalies ◽  
Pricing Anomalies ◽  
Asset Growth ◽  
Abnormal Profits

This paper is an extension of the work of Lawson and Schwartz (2018) which analyzes the risk-adjusted performance of hedge funds by employing a collection of four, five, seven, and eight-factor models. The purpose is to evaluate how well the top and bottom performing subset of hedge fund strategies have profited on known asset pricing anomalies during two unique time periods, 1994 to 2000 and 2001 to 2008. The bifurcation of the data into two distinct periods allows for a deeper exploration of the potential time-varying significance of estimated factor arbitrage. Our empirical testing suggests that both the top and bottom performing funds did utilize the asset growth anomaly to generate abnormal profits. Top performers tended to invest with a long emphasis on low asset growth, value firms while the bottom-five performing hedge fund strategies tested positive for a predilection towards going long small firms with low asset growth characteristics. Arguably, these outcomes probably align with the nature of the investment philosophy of each fund strategy. Interestingly, however, the time-varying significance of estimated coefficients for the value and returns momentum factors between the two distinct timeframes suggests either intentional or unintentional rotation between the use of available pricing anomalies and risk premiums.

scholarly journals The Volatility of Long-Term Bond Returns: Persistent Interest Shocks and Time-Varying Risk Premiums

2017 ◽  
Vol 99 (5) ◽  
pp. 884-895
Author(s):  
Daniela Osterrieder ◽  
Peter C. Schotman
Keyword(s):  
Time Varying ◽  
Risk Premiums ◽  
Bond Returns

Time-Varying Predictability of Consumption Growth, Macro-Uncertainty, and Risk Premiums

2017 ◽  
Author(s):  
Pedro Barroso ◽  
Martijn Boons ◽  
Paul Karehnke
Keyword(s):  
Time Varying ◽  
Consumption Growth ◽  
Risk Premiums

Expected prices, futures prices and time-varying risk premiums: The case of copper

2020 ◽  
Vol 69 ◽  
pp. 101825 ◽  
Author(s):  
Sebastián Cifuentes ◽  
Gonzalo Cortazar ◽  
Hector Ortega ◽  
Eduardo S. Schwartz
Keyword(s):  
Time Varying ◽  
Futures Prices ◽  
Risk Premiums

Time-Varying Risk Premiums and Term Premiums in Commodity Futures

2017 ◽  
Vol 19 (4) ◽  
pp. 39-52 ◽  
Author(s):  
Denis B. Chaves
Keyword(s):  
Commodity Futures ◽  
Time Varying ◽  
Risk Premiums
Sign in / Sign up

Export Citation Format

Share Document