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Gergana Jostova's
Scholarly Papers
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Total Downloads
5,882 |
Total
Citations
74 |
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1.
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Doron Avramov Hebrew University of Jerusalem Gergana Jostova George Washington University - Department of Finance Alexander Philipov George Mason University - Finance Area
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17 Mar 04
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03 Dec 06
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1,251 (3,558)
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11
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Abstract:
This paper provides new evidence on the empirical success of structural models in explaining corporate credit risk changes. A parsimonious set of common factors and firm-level fundamentals, inspired by structural models, explains more than 54% (67%) of the variation in credit spread changes for medium (low) grade bonds. No dominant latent factor is present in the unexplained variation. While our set of variables has lower explanatory power among high-grade bonds, it does capture most of the systematic variation of credit spread changes in that category as well. It also subsumes the explanatory power of the Fama and French (1993) factors among all grade classes.
Credit spread changes, corporate bonds, structural models of default, default risk
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2.
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Momentum and Credit Rating
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Doron Avramov Hebrew University of Jerusalem Tarun Chordia Emory University - Department of Finance Gergana Jostova George Washington University - Department of Finance Alexander Philipov George Mason University - Finance Area
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Posted:
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09 Jun 05
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Last Revised:
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26 Feb 08
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1,190 ( 3,885) |
16
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Doron Avramov Hebrew University of Jerusalem Tarun Chordia Emory University - Department of Finance Gergana Jostova George Washington University - Department of Finance Alexander Philipov George Mason University - Finance Area
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20 Jan 07
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26 Feb 08
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This paper establishes a robust link between momentum and credit rating. Momentum profitability is large and significant among low-grade firms, but it is nonexistent among high-grade firms. The momentum payoffs documented in the literature are generated by low-grade firms that account for less than 4% of the overall market capitalization of rated firms. The momentum payoff differential across credit rating groups is unexplained by firm size, firm age, analyst forecast dispersion, leverage, return volatility, and cash flow volatility.
Momentum, asset-pricing anomalies, credit risk
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Doron Avramov Hebrew University of Jerusalem Tarun Chordia Emory University - Department of Finance Gergana Jostova George Washington University - Department of Finance Alexander Philipov George Mason University - Finance Area
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09 Jun 05
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Last Revised:
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26 Jul 06
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1,190
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Abstract:
This paper establishes a robust link between momentum and credit rating. Momentum profitability is large and significant among low-grade firms, but it is nonexistent among high-grade firms. The momentum payoffs documented in the literature are generated by low-grade firms that account for less than 4% of the overall market capitalization of rated firms. The momentum payoff differential across credit rating groups is unexplained by firm size, firm age, analyst forecast dispersion, leverage, return volatility, and cash flow volatility.
momentum, credit risk, credit rating
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Doron Avramov Hebrew University of Jerusalem Tarun Chordia Emory University - Department of Finance Gergana Jostova George Washington University - Department of Finance Alexander Philipov George Mason University - Finance Area
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06 Mar 08
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Last Revised:
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08 Feb 09
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833 (7,077)
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8
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Low credit risk firms realize higher returns than high credit risk firms. This effect is puzzling because investors seem to pay a premium for bearing credit risk. This paper shows that the credit risk effect manifests itself due to the poor performance of low-rated stocks during periods of financial distress at least three months before and after credit rating downgrades. Around downgrades, low-rated firms experience considerable negative returns amid strong institutional selling, whereas returns do not differ across credit risk groups in stable or improving credit conditions. Remarkably, the group of low-rated stocks driving the credit risk effect accounts for about 4.2% of the total market capitalization. Isolating the credit risk effect to a limited number of firms in a specific set of circumstance allows us to distinguish between its potential explanations. Our evidence points away from risk-based explanations, and towards mispricing generated by retail investors and sustained by illiquidity and short sell constraints.
credit risk effect, credit rating, asset-pricing anomalies
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4.
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Dispersion in Analysts' Earnings Forecasts and Credit Rating
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Doron Avramov Hebrew University of Jerusalem Tarun Chordia Emory University - Department of Finance Gergana Jostova George Washington University - Department of Finance Alexander Philipov George Mason University - Finance Area
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Posted:
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21 Mar 07
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Last Revised:
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19 Mar 09
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790 ( 7,676) |
8
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Doron Avramov Hebrew University of Jerusalem Tarun Chordia Emory University - Department of Finance Gergana Jostova George Washington University - Department of Finance Alexander Philipov George Mason University - Finance Area
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26 Feb 08
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19 Mar 09
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8
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Abstract:
This paper shows that the puzzling negative cross-sectional relation between dispersion in analysts' earnings forecasts and future stock returns may be explained by financial distress, as proxied by credit rating downgrades. Focusing on a sample of firms rated by S&P, we show that the profitability of dispersion-based trading strategies concentrates in a small number of the worst-rated firms and is significant only during periods of deteriorating credit conditions. In such periods, the negative dispersion-return relation emerges as low-rated firms experience substantial price drop along with considerable increase in forecast dispersion. Moreover, even for this small universe of worst-rated firms, the dispersion-return relation is nonexistent when either the dispersion measure or return is adjusted by credit risk. The results are robust to previously proposed explanations for the dispersion effect such as short-sale constraints and leverage.
Dispersion in analyst forecasts, asset-pricing anomalies, credit risk, credit rating
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Doron Avramov Hebrew University of Jerusalem Tarun Chordia Emory University - Department of Finance Gergana Jostova George Washington University - Department of Finance Alexander Philipov George Mason University - Finance Area
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21 Mar 07
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Last Revised:
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09 Jan 08
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790
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Abstract:
This paper shows that the puzzling negative cross-sectional relation between dispersion in analysts' earnings forecasts and future stock returns is a manifestation of financial distress, as proxied by credit rating downgrades. Focusing on a sample of firms rated by S&P, we show that the profitability of dispersion based trading strategies concentrates in a small number of the worst-rated firms and is significant only during periods of deteriorating credit conditions. In such periods, the negative dispersion-return relation emerges as low-rated firms experience substantial price drop along with considerable increase in forecast dispersion. Moreover, even for this small universe of worst-rated firms, the dispersion-return relation is nonexistent when either the dispersion measure or return is adjusted by credit risk. The results are robust to previously proposed explanations for the dispersion effect such as short-sale constraints, illiquidity, and leverage.
Dispersion in analyst forecasts, asset-pricing anomalies, credit risk, credit rating
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5.
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Predictability in Emerging Sovereign Debt Markets
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Gergana Jostova George Washington University - Department of Finance
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Posted:
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11 Jul 01
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Last Revised:
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15 Mar 07
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709 ( 9,125) |
2
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Gergana Jostova George Washington University - Department of Finance
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23 Feb 04
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02 Jun 06
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This paper finds strong evidence of predictability in Brady bonds, the most liquid emerging debt market, by implementing a new model for credit spreads. Predictability is economically and statistically significant and robust to various considerations. Active management provides US investors in emerging markets with double the buy-and-hold returns at lower risk and the equivalent of free options on Brady bonds. Our analysis suggests that predictability is primarily driven by credit spread deviations from fundamentals, rather than time-varying risk or risk premia. We believe this inefficiency is the result of the restrictions of a non-transparent, institutionally dominated, dealer market and the lack of a well developed derivatives market for emerging country credit risk.
predictability, credit risk, credit spreads, emerging debt markets, Brady bonds, inefficiency
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Gergana Jostova George Washington University - Department of Finance
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11 Jul 01
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Last Revised:
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15 Mar 07
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709
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2
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Abstract:
This paper finds strong evidence of predictability in Brady bonds, the most liquid emerging debt market, by implementing a new model for credit spreads. Predictability is economically and statistically significant and robust to various considerations. Active management provides US investors in emerging markets with double the buy-and-hold returns at lower risk and the equivalent of free options on Brady bonds. Our analysis suggests that predictability is primarily driven by credit spread deviations from fundamentals, rather than time-varying risk or risk premia. We believe this inefficiency is the result of the restrictions of a non-transparent, institutionally dominated, dealer market and the lack of a well developed derivatives market for emerging country credit risk.
Predictability, credit risk, credit spreads, emerging debt markets, Brady bonds, efficiency
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6.
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Bayesian Analysis of Stochastic Betas
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Gergana Jostova George Washington University - Department of Finance Alexander Philipov George Mason University - Finance Area
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Posted:
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26 Apr 04
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Last Revised:
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02 Jun 06
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665 ( 9,984) |
21
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Gergana Jostova George Washington University - Department of Finance Alexander Philipov George Mason University - Finance Area
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08 Dec 04
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Last Revised:
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02 Jun 06
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0
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Abstract:
We propose a mean-reverting stochastic process for the market beta. In a simulation study, the proposed model generates significantly more precise beta estimates than GARCH betas, betas conditioned on aggregate or firm-level variables, and rolling-regression betas, even when the true betas are generated based on these competing specifications. Our model significantly improves out-of-sample hedging effectiveness. In asset-pricing tests, our model provides substantially stronger support for the conditional CAPM relative to competing beta models and helps resolve asset-pricing anomalies such as the size, book-to-market, and idiosyncratic volatility effects in the cross-section of stock returns.
Stochastic betas, mean-reverting systematic risk, size effect, book-to-market effect
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Gergana Jostova George Washington University - Department of Finance Alexander Philipov George Mason University - Finance Area
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26 Apr 04
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Last Revised:
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27 Sep 05
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665
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21
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Abstract:
We propose a mean-reverting stochastic process for the market beta. In a simulation study, the proposed model generates significantly more precise beta estimates than GARCH betas, betas conditioned on aggregate or firm-level variables, and rolling-regression betas, even when the true betas are generated based on these competing specifications. Our model significantly improves out-of-sample hedging effectiveness. In asset-pricing tests, our model provides substantially stronger support for the conditional CAPM relative to competing beta models and helps resolve asset-pricing anomalies such as the size, book-to-market, and idiosyncratic volatility effects in the cross-section of stock returns.
Stochastic beta, time-varying systematic risk, asset-pricing anomalies, hedging
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7.
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Edith S. Hotchkiss Boston College - Wallace E. Carroll School of Management Gergana Jostova George Washington University - Department of Finance
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19 Jul 07
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Last Revised:
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14 Sep 07
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421 (19,026)
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10
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Abstract:
This paper studies the determinants of trading volume and liquidity of corporate bonds. Using transactions data from a comprehensive dataset of insurance company trades, our analysis covers more than 17,000 US corporate bonds of 4,151 companies over a five year period. The availability of transactions data allows us to study the effect of a variety of issue- and issuer-specific characteristics on liquidity. We find that the most economically important determinants of bond trading volume are the bond's issue size and age; trading volume declines substantially as bonds become seasoned and are absorbed into less active portfolios. We also examine the relationship between bond trading volume and activity in the issuer's stock. Our results show that bonds of companies with publicly traded equity are more likely to trade than those with private equity. Further, public companies with more active stocks have more actively traded bonds. Finally, we show that while the liquidity of high-yield bonds is more affected by credit risk, interest-rate risk is more important in determining the liquidity of investment-grade bonds.
Institutional trading, liquidity, corporate bonds, NAIC
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Tarun Chordia Emory University - Department of Finance Doron Avramov Hebrew University of Jerusalem Gergana Jostova George Washington University - Department of Finance Alexander Philipov George Mason University - Finance Area
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23 Aug 07
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Last Revised:
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26 May 09
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23 (165,362)
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Abstract:
While working on our forthcoming Journal of Finance paper entitled "Momentum and Credit Rating," we found that the dispersion effect where high dispersion stocks earn lower returns is related to the credit ratings of the companies. Moreover, the profitability of dispersion based trading strategies is concentrated in a small number of the worst-rated firms and is significant only during periods of deteriorating credit conditions. Thus, it is the financial distress related to deteriorating credit conditions that drives the dispersion effect.
dispersion in analyst forecasts, abnormal returns, credit ratings
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9.
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Doron Avramov Hebrew University of Jerusalem Gergana Jostova George Washington University - Department of Finance Alexander Philipov George Mason University - Finance Area
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18 Apr 07
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Last Revised:
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18 Apr 07
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0 (0)
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Abstract:
New evidence is reported on the empirical success of structural models in explaining changes in corporate credit risk. A parsimonious set of common factors and company-level fundamentals, inspired by structural models, was found to explain more than 54 percent (67 percent) of the variation in credit-spread changes for medium-grade (low-grade) bonds. No dominant latent factor was present in the unexplained variation. Although this set of factors had lower explanatory power among high-grade bonds, it did capture most of the systematic variation in credit-spread changes in that category. It also subsumed the explanatory power of the Fama and French factors among all grade classes.
Debt Investments, Credit Analysis, Portfolio Management, Debt Strategies
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