A Note on Gaussian Estimation of the CKLS and CIR Models with Feedback Effects for Japan

In this note we extend the Gaussian estimation of two factor CKLS and CIR models recently considered in Nowman, K. B. (2001, Gaussian estimation and forecasting of multi-factor term structure models with an application to Japan and the United Kingdom, Asia Pacif. Financ. Markets 8, 23–34) to include feedback effects in the conditional mean as was originally formulated in general continuous time models by Bergstrom, A. R. (1966, Non-recursive models as discrete approximations to systems of stochastic differential equations, Econometrica 34, 173–182) with constant volatility. We use the exact discrete model of Bergstrom, A. R. (1966, Non-recursive models as discrete approximations to systems of stochastic differential equations, Econometrica 34, 173–182) to estimate the parameters which was first used by Brennan, M. J. and Schwartz, E. S. (1979, A continuous time approach to the pricing of bonds, J. Bank. Financ. 3, 133–155) to estimate their two factor interest model but incorporating the assumption of Nowman, K. B. (1997, Gaussian estimation of single-factor continuous time models of the term structure of interest rates, J. Financ. 52, 1695–1706; 2001, Gaussian estimation and forecasting of multi-factor term structure models with an application to Japan and the United Kingdom, Asia Pacif. Financ. Markets 8, 23–34). An application to monthly Japanese Euro currency rates indicates some evidence of feedback from the 1-year rate to the 1-month rate in both the CKLS and CIR models. We also find a low level-volatility effect supporting Nowman, K. B. (2001, Gaussian estimation and forecasting of multi-factor term structure models with an application to Japan and the United Kingdom, Asia Pacif. Financ. Markets 8, 23–34).     

The survival probability of the SABR model: asymptotics and application

The stochastic-alpha-beta-rho (SABR) model is widely used by practitioners in interest rate and foreign exchange markets. The probability of hitting zero sheds light on the arbitrage-free small strike implied volatility of the SABR model (see, e.g. De Marco et al. [SIAM J. Financ. Math., 2017, 8(1), 709–737], Gulisashvili [Int. J. Theor. Appl. Financ., 2015, 18, 1550013], Gulisashvili et al. [Mass at zero in the uncorrelated SABR modeland implied volatility asymptotics, 2016b]), and the survival probability is also closely related to binary knock-out options. Besides, the study of the survival probability is mathematically challenging. This paper provides novel asymptotic formulas for the survival probability of the SABR model as well as error estimates. The formulas give the probability that the forward price does not hit a nonnegative lower boundary before a fixed time horizon.     

A comparison of nearest neighbours,discriminant and logit models for auditing decisions

This study investigates the efficiency of k-nearest neighbours (k-NN) in developing models for estimating auditors' opinions, as opposed to models developed with discriminant and logit analyses. The sample consists of 5276 financial statements, out of which 980 received a qualified audit opinion, obtained from 1455 private and public UK companies operating in the manufacturing and trade sectors. We develop two industry-specific models and a general one using data from the period 1998–2001, which are then tested over the period 2002–2003. In each case, two versions of the models are developed. The first includes only financial variables. The second includes both financial and non-financial variables. The results indicate that the inclusion of credit rating in the models results in a considerable increase both in terms of goodness of fit and classification accuracies. The comparison of the methods reveals that the k-NN models can be more efficient, in terms of average classification accuracy, than the discriminant and logit models. Finally, the results are mixed concerning the development of industry-specific models, as opposed to general models. Copyright © 2007 John Wiley & Sons, Ltd.     

Estimation for factor models of term structure of interest rates with jumps: the case of the Taiwanese government bond market

This paper examines the Ornstein–Uhlenbeck (O–U) process used by Vasicek, J. Financial Econ. 5 (1977) 177, and a jump-diffusion process used by Baz and Das, J. Fixed Income (Jnue, 1996) 78, for the Taiwanese Government Bond (TGB) term structure of interest rates. We first obtain the TGB term structures by applying the B-spline approximation, and then use the estimated interest rates to estimate parameters for the one-factor and two-factor Vasicek and jump-diffusion models. The results show that both the one-factor and two-factor Vasicek and jump-diffusion models are statistically significant, with the two-factor models fitting better. For two-factor models, compared with the second factor, the first factor exhibits characteristics of stronger mean reversion, higher volatility, and more frequent and significant jumps in the case of the jump-diffusion process. This is because the first factor is more associated with short-term interest rates, and the second factor is associated with both short-term and long-term interest rates. The jump-diffusion model, which can incorporate jump risks, provides more insight in explaining the term structure as well as the pricing of interest rate derivatives.     

Selecting credit rating models: a cross-validation-based comparison of discriminatory power

In commercial banking, various statistical models for corporate credit rating have been theoretically promoted and applied to bank-specific credit portfolios. In this paper, we empirically compare and test the performance of a wide range of parametric and nonparametric credit rating model approaches in a statistically coherent way, based on a ‘real-world’ data set. We repetitively (k times) split a large sample of industrial firms’ default data into disjoint training and validation subsamples. For all model types, we estimate k out-of-sample discriminatory power measures, allowing us to compare the models coherently. We observe that more complex and nonparametric approaches, such as random forest, neural networks, and generalized additive models, perform best in-sample. However, comparing k out-of-sample cross-validation results, these models overfit and lose some of their predictive power. Rather than improving discriminatory power, we perceive their major contribution to be their usefulness as diagnostic tools for the selection of rating factors and the development of simpler, parametric models.

The implied intra-day probability of informed trading

The paper develops a methodology for estimating the intra-day probability of informed trading for NYSE stocks, implied by the specialist’s quotes and depths. The time series pattern of our measure (PROBINF) in an intra-day analysis around earnings announcements is consistent with previous findings and with expectations regarding informed trading. Moreover, we find that PROBINF exhibits a strong and robust relationship with PIN, the level of insider trading and with measures of the price impact of trades. Our methodology complements the one developed in Easley et al. (J Financ 51(3):811–833, 1996a, J Financ 51(4):1405–1436, b), as it can be used to measure short term changes in informed trading and information asymmetry around events such as merger and acquisition announcements, share repurchases, stock splits, dividend announcements and index additions and deletions.     

Hedging jump risk,expected returns and risk premia in jump-diffusion economies

This article presents a pure exchange economy that extends Rubinstein [Bell J. Econ. Manage. Sci., 1976, 7, 407–425] to show how the jump-diffusion option pricing model of Black and Scholes [J. Political Econ., 1973, 81, 637–654] and Merton [J. Financ. Econ., 1976, 4, 125–144] evolves in gamma jumping economies. From empirical analysis and theoretical study, both the aggregate consumption and the stock price are unknown in determining jumping times. By using the pricing kernel, we determine both the aggregate consumption jump time and the stock price jump time from the equilibrium interest rate and CCAPM (Consumption Capital Asset Pricing Model). Our general jump-diffusion option pricing model gives an explicit formula for how the jump process and the jump times alter the pricing. This innovation with predictable jump times enhances our analysis of the expected stock return in equilibrium and of hedging jump risks for jump-diffusion economies.     

Normality tests of option-implied risk-neutral densities: evidence from the small Finnish market

This study provides an empirical analysis of option-implied risk-neutral densities. The normality of the risk-neutral density is statistically assessed testing restrictions regarding the skewness and kurtosis of the implied distribution and by applying the traditional test approach involving a comparison of the pricing errors calculated using alternative models. It is found that both the approaches give similar results, whereas the former method has the advantage that the significance of the estimated parameters can be statistically tested. Using data from the small Finnish market, the normality of the distributions is soundly rejected as expected based on the theoretical framework by Damodaran [J. Financ. Quant. Anal. 20 (1985) 423].     

Practitioners' Corner

The first 150 words of the full text of this article appear below. In our discussion in the last issue of Journal of FinancialEconometrics (JFEC) of the nonparametric methods developed byBarndorff-Nielsen and Shephard (2006) to detect jumps in thelocal behavior of the continuous time path of a price process,we observed these tests were not designed to detect major pricediscontinuity events such as the 1987 crash, since the testingmethodology precludes jumps in adjacent time intervals. Indeed,a major event such as Black Monday is characterized by a sequenceof jumps in consecutive time intervals throughout the day. Inthe interest of thematic continuity, let’s pursue thematter of jumps further. The first article in the current issue by Hossein Asgharianand Chistoffer Bengtsson addresses directly the detection ofbig events in stock prices. More particularly, the authors analyzethe spillover of jumps across international stock markets. Tomeasure jumps, the authors formulate a parametric model in . . . [Full Text of this Article]     

A comparison of inflation forecasts

Interest rate models provide slightly better monthly forecasts and substantially better eight- and fourteen-month forecasts of inflation than a univariate time series model. The Livingston surveys underestimate eight- and fourteen-month inflation rates, especially during the high inflation period of 1978–81. In contrast, eight- and fourteen-month inflation forecasts extrapolated from one-month interest rates show little bias and track ex post eight- and fourteen-month inflation rates better than the survey forecasts.     

Risk-managed industry momentum and momentum crashes

This paper investigates Barroso and Santa-Clara’s [J. Financ. Econ., 2008, 116, 111–120] risk-managed momentum strategy in an industry momentum setting. We investigate several traditional momentum strategies including that recently proposed by Novy-Marx [J. Financ. Econ., 2012, 103, 429–453]. We moreover examine the impact of different variance forecast horizons on average pay-offs and also Daniel and Moskowitz’s [J. Financ. Econ., 2016, 122, 221–247] optionality effects. Our results show in general that neither plain industry momentum strategies nor the risk-managed industry momentum strategies are subject to optionality effects, implying that these strategies have no time-varying beta. Moreover, the benefits of risk management are robust across volatility estimators, momentum strategies and subsamples. Finally, the ‘echo effect’ in industries is not robust in subsamples as the strategy works only during the most recent subsample.     

Nonparametric density estimation and tests of continuous time interest rate models

I study the finite sample distribution of one of Ait-Sahalia's(1996c) nonparametric tests of continuous-time models of theshort-term riskless rate. The test rejects true models too oftenbecause interest rate data are highly persistent but the asymptoticdistribution of the test (and of the kernel density estimatoron which the test is based) treats the data as if it were independentlyand identically distributed. To attain the accuracy of the kerneldensity estimator implied by its asymptotic distribution with22 years of data generated from the Vasicek model in fact requires2755 years of data.     

The use of stand alone warrants as unique capital raising instruments

This study documents a significant positive announcement effect for a unique capital raising tool, stand alone warrants, in the Australian market. The result is consistent with the models of Schultz [J. Financ. Econom. 34 (1993) 109] and Mayers [J. Financ. Econom. 47 (1998) 83] where a warrant is viewed positively by the market. The results of the model developed to analyse the determinants of the announcement effect, support variants of the information asymmetry hypothesis (proxied by major shareholder pre-commitment and issue size).     

Local risk-minimization for Barndorff-Nielsen and Shephard models

We obtain explicit representations of locally risk-minimizing strategies for call and put options in Barndorff-Nielsen and Shephard models, which are Ornstein–Uhlenbeck-type stochastic volatility models. Using Malliavin calculus for Lévy processes, Arai and Suzuki (Int. J. Financ. Eng. 2:1550015, 2015) obtained a formula for locally risk-minimizing strategies for Lévy markets under many additional conditions. Supposing mild conditions, we make sure that the Barndorff-Nielsen and Shephard models satisfy all the conditions imposed in (Arai and Suzuki in Int. J. Financ. Eng. 2:1550015, 2015). Among others, we investigate the Malliavin differentiability of the density of the minimal martingale measure. Moreover, we introduce some numerical experiments for locally risk-minimizing strategies.     

Dynamic optimal capital structure with regime switching

We investigate the optimal capital structure of a corporate when the dynamics of the assets (both growth rate and volatility) change following different states of the economy. Two structural models are examined in the paper. The first considers the case when the firm is not facing tax benefit and bankruptcy costs with a regime switching dynamics. This model extends the Black and Cox (J Financ 31:351–367, 1976) model to allow for regime switching risk. The second model incorporates both tax benefit and bankruptcy costs with a regime switching dynamics. This is is more realistic, and is an extension of the Leland (J Financ 49(4):1213–1252, 1994) model with regime switching risk. We obtain closed-form analytic solutions for the optimal capital structure and default barrier for both models.     

An Empirical Comparison of Asset-Pricing Models in the Shanghai A-Share Exchange Market

This paper evaluates and compares the performance of three-asset pricing models—the capital asset pricing model of Sharpe (J Finance 19:425–442, 1964), the three-factor model of Fama and French (J Financ Econ 33:3–56, 1993), and the five-factor model (Fama and French in J Financ Econ 123:1–22, 2015)—in the Shanghai A-share exchange market. Our results do not support the superiority of the five-factor model and show that the three-factor model outperforms the other models. We also verify the redundancy of the book-to-market factor and confirm the findings of Fama and French (2015).     

An empirical investigation of asset pricing models under divergent lending and borrowing rates

Asset pricing theory implies that the estimate of the zero-beta rate should fall between divergent lending and borrowing rates. This paper proposes a formal test of this restriction using the difference between the prime loan rate and the 1-month Treasury bill rate as a proxy for the difference between borrowing and lending rates. Based on simulations, this paper shows that in the ordinary least squares case, the Fama and MacBeth (J Pol Econ 81:607–636, 1973) t-statistic has high power against a general alternative, which is not true of the Shanken (Rev Financ Stud 5:1–33, 1992) and Kan et al. (J Financ doi:10.1111/jofi.12035, 2013) t-statistics. In the generalized least squares case, all three t-statistics have high power. The empirical investigation highlights that only the intertemporal capital asset pricing model reasonably prices the zero-beta portfolio. Other models, such as the Fama and French (J Financ Econ 33:3–56, 1993) model, do not assign the correct value to the zero-beta rate.     

The price of risk and ambiguity in an intertemporal general equilibrium model of asset prices

We consider a version of the intertemporal general equilibrium model of Cox et?al. (Econometrica 53:363–384, 1985) with a single production process and two correlated state variables. It is assumed that only one of them, Y ₂, has shocks correlated with those of the economy’s output rate and, simultaneously, that the representative agent is ambiguous about its stochastic process. This implies that changes in Y ₂ should be hedged and its uncertainty priced, with this price containing risk and ambiguity components. Ambiguity impacts asset pricing through two channels: the price of uncertainty associated with the ambiguous state variable, Y ₂, and the interest rate. With ambiguity, the equilibrium price of uncertainty associated with Y ₂ and the equilibrium interest rate can increase or decrease, depending on: (i) the correlations between the shocks in Y ₂ and those in the output rate and in the other state variable; (ii) the diffusion functions of the stochastic processes for Y ₂ and for the output rate; and (iii) the gradient of the value function with respect to Y ₂. As applications of our generic setting, we deduct the model of Longstaff and Schwartz (J Financ 47:1259–1282, 1992) for interest-rate-sensitive contingent claim pricing and the variance-risk price specification in the option pricing model of Heston (Rev Financ Stud 6:327–343, 1993). Additionally, it is obtained a variance-uncertainty price specification that can be used to obtain a closed-form solution for option pricing with ambiguity about stochastic variance.     

American-style options in jump-diffusion models: estimation and evaluation

We propose dynamic programming coupled with finite elements for valuing American-style options under Gaussian and double exponential jumps à la Merton [J. Financ. Econ., 1976, 3, 125–144] and Kou [Manage. Sci., 2002, 48, 1086–1101], and we provide a proof of uniform convergence. Our numerical experiments confirm this convergence result and show the efficiency of the proposed methodology. We also address the estimation problem and report an empirical investigation based on Home Depot. Jump-diffusion models outperform their pure-diffusion counterparts.     

Weighing asset pricing factors: a least squares model averaging approach

Empirical evidence has demonstrated that certain factors in asset pricing models are more important than others for explaining specific portfolio returns. We propose a technique that evaluates the factors included in popular linear asset pricing models. Our method has the advantage of simultaneously ranking the relative importance of those pricing factors through comparing their model weights. As an empirical verification, we apply our method to portfolios formed following Fama and French [A five-factor asset pricing model. J. Financ. Econ., 2015, 116, 1–22] and demonstrate that models accommodated to our factor rankings do improve their explanatory power in both in-sample and out-of-sample analyses.