Presentation on theme: "Structural Models of Credit Risk are Useful: Evidence from Hedge Ratios on Corporate Bonds Stephen M. Schaefer London Business School International Financial."— Presentation transcript:
Structural Models of Credit Risk are Useful: Evidence from Hedge Ratios on Corporate Bonds Stephen M. Schaefer London Business School International Financial Research Forum Financial Risks New Developments in Structured Products and Credit Derivatives Paris, 27-28 March 2008
Structural Models are UsefulPage 2 Joint work with: Ilya A. Strebulaev Stanford University
Structural Models are UsefulPage 3 Structural Models Structural models of credit risk represent default in terms of the value of the firms assets (that collateralise the debt): falling short of the face value of the debt at maturity (Merton model); or hitting a lower threshold representing (e.g.) the point at which lenders will intervene and liquidate the firm (second generation models – e.g., Leland) Structural models represent the best framework currently available to analyse fundamental value in credit setting BUT …..
Structural Models are UsefulPage 4 Introduction Structural models fail to explain size of yield spreads on corporate bonds e.g. Huang and Huang (2003) - 5 models: ModelActual Data A14-39123 BBB39-59194
Structural Models are UsefulPage 5 What do credit spreads in structural models represent? The credit spread in a structural model is approximately: So possible reasons for underestimating spreads: underestimating default probability (or LGD) underestimating hedge ratio (beta) of debt to equity (or equity risk premium) or.. impact of other variables (liquidity etc.)
Structural Models are UsefulPage 6 Source: Huang & Huang Yield Spread, Default Loss Rate and Calculated Credit Spread (10-year bonds)
Structural Models are UsefulPage 7 So, is it all bad news?
Structural Models are UsefulPage 8 Structural Models and Default Probabilities Actually structural models appear to provide reasonably good (or at least not bad) estimates of default probabilities Leland (2002), Huang and Huang (2003) Moodys KMV
Structural Models are UsefulPage 9 Lelands Estimates of Default Probabilities Leland uses default boundary model with realistic input parameters to calculate default probabilities A-rated bonds; asset volatility is 23% (Base case). B-rated bonds; asset volatility is 32% Dotted line is actual. Source: Leland, H. Predictions of Expected Default Frequencies in Structural Models of Debt, Working Paper, Univ. of California, Berkeley, September 2002.
Structural Models are UsefulPage 10 Short-Term vs. Long-Term Default Probabilities Long-term (7-8 years and longer) default frequencies fit quite well Short-term (1-6 years and below) default frequencies are too low
Structural Models are UsefulPage 11 What do we do in this paper? Existing research: default probabilities – (partial) success spreads – failure (i.e., so far – no success for variable that depends on prices) This paper: perhaps the risk premium component is underestimated do structural models predict hedge ratios of corporate debt to equity?
Structural Models are UsefulPage 12 Why are hedge ratios important - I? Determine risk premia In all structural models the bond value is determined as the price of the replicating portfolio in theory portfolio and equity and riskless debt replicates payoff on bond composition of the replicating portfolio is determined by the hedge ratios so bond price is determined by the hedge ratios If observed hedge ratios consistent with those predicted by models, then that failure of models to predict spreads likely to be due to non credit risk factors
Structural Models are UsefulPage 13 Why are hedge ratios important - II? Hedge ratio: measures exposure of debt value to value of collateralising assets hedge ratio High => high credit risk hedge ratio low => low credit risk high hedge ratio (slope) = credit exposure low hedge ratio (slope) = low credit exposure
Structural Models are UsefulPage 14 Focus of Paper Estimate hedge ratio regressions: In a world governed by structural models, hedge ratio regressions would produce coefficients j,E close to one high explanatory power (R 2 close to 1)... but not exactly as a result of (a) non-linearity; (b) discreteness We show that (a) and ( b) are not important and test hypothesis that j,E = 1 Consider other systematic factors (a la Collin-Dufresne) and examine their relation to underlying credit risk
Structural Models are UsefulPage 15 Main Findings - 1 Simple structural model (Merton, 1974) provides reasonably good estimates of hedge ratios of corporate debt to equity BUT returns on corporate bonds also strongly related to: SMB and HML (Fama-French factors).. But NOT in a way that is related to exposure to underlying equity and NOT in a way that appears linked to credit exposure S&P (or VIX).. but NOT in way that is linked to credit risk Thus these factors seem to have significant effects on prices / returns but not via credit risk channel Another puzzle: structural (Merton) model fails to explain LOW empirical hedge ratios of debt to riskless bonds (duration)
Structural Models are UsefulPage 16 Main Findings - 2 While it is true that structural models underestimate corporate yield spreads.. if spreads reflected credit risk alone then the sensitivity of bond returns to equity would be higher to be consistent with reasonable estimates of the equity risk premium in fact.. empirical sensitivities correspond quite well to predictions of simple structural model.
Structural Models are UsefulPage 17 Data Merrill Lynch: Corporate Master Index and Corporate High Yield Index covers nearly all corporate bond issues in the U.S. (2114 issuers; 10370 issues) Monthly price data from 12.1996–12.2003 (388,000 bond- month observations) final sample satisfies additional standard criteria (only US bonds, matching with CRSP/COMPUSTAT, no financials, only straight bonds) Entire and final sample: Entire SampleFinal Sample Bonds10,3701360 Issuers2,114396
Structural Models are UsefulPage 18 Descriptive Statistics: Final Dataset
Structural Models are UsefulPage 19 A Simple Time-Series Hedging Regression We run the following regression : Results: : estimated hedge ratios – small (0.006 – 0.04 for IG) but highly (statistically) significant R 2 much less than 100% sensitivity to Treasury returns (duration) low
Structural Models are UsefulPage 20 Hedge Ratios Are these hedge ratios reasonable? compare with hedge ratios implied by Merton model In one-factor structural models the hedge ratio, E, is: where E is the delta of equity to the firms asset value and L is the debt-to-asset value ratio
Structural Models are UsefulPage 21 Hedge Ratios from the Merton Model Asset Volatility Leverage10152025304050 100.00 0.040.582.539.2517.19 200.000.030.702.634.8013.5221.39 300.000.863.424.6013.6015.3129.03 400.101.426.8810.4116.4423.7331.58 500.4953.198.0511.8817.5024.1729.68 602.064.4713.25516.6019.5324.7934.08 703.207.9815.2514.7321.7927.8329.87
Structural Models are UsefulPage 22 The Volatility of Corporate Assets
Structural Models are UsefulPage 23 Testing the Merton Models Hedge Ratio Predictions Estimates of individual hedge ratios are very noisy: calculate as mean hedge ratio within sub-rating :
Structural Models are UsefulPage 24 Using the Merton Model to Predict Hedge Ratios Source: Schaefer / Strebulaev
Structural Models are UsefulPage 25 Explaining Structural Model Spreads with Empirical Betas Implies default-boundary structural models produce very similar hedge ratios to Merton
Structural Models are UsefulPage 26 The story so far Merton model produces hedge ratios in line with empirical estimates so, structural models appear to capture credit exposure quite well But the R 2 are lower than the model predicts equity and risk-free debt should account for large fraction (80% plus) of debt return variation BUT we find R 2 ~ 50% – 70% for investment grade bonds and R 2 ~ 30 – 40% for non-investment grade What other factors influence corporate bond returns? Inside the model: stochastic interest rates Outside the model: other systematic factors
Structural Models are UsefulPage 27 Stochastic Interest Rates In Merton model ( effectively, Black-Scholes) riskless interest rates are fixed formally, need model that allows for uncertainty in riskless rate Also, puzzle of low interest rate sensitivity of corporate debt
Structural Models are UsefulPage 28 Low Duration Puzzle: Regressions on riskless bonds only
Structural Models are UsefulPage 29 Including Stochastic Interest Rates Merton (1974) with affine interest rates (Shimko et. al. (1993), Lando (2004)) For simplicity, consider one-factor Vasicek model Results on hedge ratios unchanged
Structural Models are UsefulPage 30 Other Factors: Running a kitchen sink regression Hedge ratios for equity and riskless debt are not much changed
Structural Models are UsefulPage 31 Sensitivity to SMB Sensitivity to corporate debt returns to SMB: not result of sensitivity of underlying assets to SMB not strongly connected to credit exposure (!!)
Structural Models are UsefulPage 32 Conclusion 1 Hedge ratios provide a good measure of credit exposure and, in this sense, structural models seem to capture credit exposure better than commonly supposed: But do NOT explain level of credit spreads
Structural Models are UsefulPage 33 Conclusion 2 Understanding identity and role of non credit risk related factors: still incomplete liquidity taxes: ?? imperfect substitution between equity, riskless bonds and corporate bonds fluctuations in capital allocated to credit risky instruments