Robust pricing–hedging dualities in continuous time

We pursue a robust approach to pricing and hedging in mathematical finance. We consider a continuous-time setting in which some underlying assets and options, with continuous price paths, are available for dynamic trading and a further set of European options, possibly with varying maturities, is available for static trading. Motivated by the notion of prediction set in Mykland (Ann. Stat. 31:1413–1438, 2003), we include in our setup modelling beliefs by allowing to specify a set of paths to be considered, e.g. superreplication of a contingent claim is required only for paths falling in the given set. Our framework thus interpolates between model-independent and model-specific settings and allows us to quantify the impact of making assumptions or gaining information. We obtain a general pricing–hedging duality result: the infimum over superhedging prices of an exotic option with payoff \(G\) is equal to the supremum of expectations of \(G\) under calibrated martingale measures. Our results include in particular the martingale optimal transport duality of Dolinsky and Soner (Probab. Theory Relat. Fields 160:391–427, 2014) and extend it to multiple dimensions, multiple maturities and beliefs which are invariant under time-changes. In a general setting with arbitrary beliefs and for a uniformly continuous \(G\), the asserted duality holds between limiting values of perturbed problems.     

Prognose des Abwicklungsergebnisses mittels Chain-Ladder-Verfahren für abhängige Run-Off-Portfolios

In the present paper we analyse how the estimators from Merz u. Wüthrich (2007) could be generalised to the case of N correlated run-off triangles. The simultaneous view on N correlated subportfolios is motivated by the fact, that in practice a run-off portfolio often has to be divided in subportfolios, so that the homogeneity assumption of the claims reserving method on each subportfolio is satisfied. We derive an explicit formula for the process-variance, the estimation-error and the prediction error made by the forecast for the claims development result with the Chain-Ladder method. We illustrate the results by an example.     

A note on the valuation of asset management firms

Market capitalization relative to assets under management is often used to value asset management firms. Huberman’s (2004) dividend discount model implies that cross-sectional variations in this metric are explained by cross-sectional differences in operating margins, and yet we find no evidence of this in our data set. We show that a superior model—inspired by the work of Berk and Green (2004)—includes also the level of fees as an explanatory variable. This approach dramatically increases the fit of our valuation model and casts doubt on the relevance of the so-called Huberman puzzle.     

Episodes of Exuberance in Housing Markets: In Search of the Smoking Gun

In this paper, we examine changes in the time series properties of three widely used housing market indicators (real house prices, price-to-income ratios, and price-to-rent ratios) for a large set of countries to detect episodes of explosive dynamics. Dating such episodes of exuberance in housing markets provides a timeline as well as empirical content to the narrative connecting housing exuberance to the global 2008 ?09 recession. For our empirical analysis, we employ two recursive univariate unit root tests recently developed by Phillips and Yu (International Economic Review 52(1):201–226, 2011) and Phillips et al. (2015). We also propose a novel extension of the test developed by Phillips et al. (2015) to a panel setting in order to exploit the large cross-sectional dimension of our international dataset. Statistically significant periods of exuberance are found in most countries. Moreover, we find strong evidence of the emergence of an unprecedented period of exuberance in the early 2000s that eventually collapsed around 2006 ?07, preceding the 2008 ?09 global recession. We examine whether macro and financial variables help to predict (in-sample) episodes of exuberance in housing markets. Long-term interest rates, credit growth and global economic conditions are found to be among the best predictors. We conclude that global factors (partly) explain the synchronization of exuberance episodes that we detect in the data in the 2000s.     

Effects of Jumps and Small Noise in High-Frequency Financial Econometrics

Several new statistical procedures for high-frequency financial data analysis have been developed to estimate risk quantities and test the presence of jumps in the underlying continuous-time financial processes. Although the role of micro-market noise is important in high-frequency financial data, there are some basic questions on the effects of presence of noise and jump in the underlying stochastic processes. When there can be jumps and (micro-market) noise at the same time, it is not obvious whether the existing statistical methods are reliable for applications in actual data analysis. We investigate the misspecification effects of jumps and noise on some basic statistics and the testing procedures for jumps proposed by Ait-Sahalia and Jacod (Ann Stat 37–1:184–222 2009; 38–5:3093–3123 2010) as an illustration. We find that their first test (testing the presence of jumps as a null-hypothesis) is asymptotically robust in the small-noise asymptotic sense against possible misspecifications while their second test (testing no-jumps as a null-hypothesis) is quite sensitive to the presence of noise.     

The SIML Estimation of Integrated Covariance and Hedging Coefficient Under Round-off Errors,Micro-market Price Adjustments and Random Sampling

For estimating the integrated volatility and covariance by using high frequency data, Kunitomo and Sato (Math Comput Simul 81:1272–1289, 2011; N Am J Econ Finance 26:289–309, 2013) have proposed the separating information maximum likelihood (SIML) method when there are micro-market noises. The SIML estimator has reasonable finite sample properties and asymptotic properties when the sample size is large when the hidden efficient price process follows a Brownian semi-martingale. We shall show that the SIML estimation is useful for estimating the integrated covariance and hedging coefficient when we have round-off errors, micro-market price adjustments and noises, and when the high-frequency data are randomly sampled. The SIML estimation is consistent, asymptotically normal in the stable convergence sense under a set of reasonable assumptions and it has reasonable finite sample properties with these effects.     

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.

An Empirical Investigation of the Option-Adjusted Realized Return

The issue of meaningful evaluation of professionally managed portfolios remains to be resolved satisfactorily within the investment community. The fact that many of the current procedures for evaluating portfolio performance are deeply rooted in conventional mean-variance (M-V) analysis raises serious concerns from a theoretical perspective. The primary objective of this paper is an empirical investigation (as differentiated from a thorough empirical test) of an ordinal portfolio performance measure, called the Option-adjusted Realized (average rate of) Return or ORR, developed recently by Smith and Kokoska (1998). The ORR is a leverage- and risk-adjusted average realized rate of return that can be used directly in evaluating portfolio performance.Using returns data for June 1992 to May 1998, we estimate ORRs for two portfolios—the CREF Stock Fund and a hypothetical market index portfolio whose composition is identical to that of the S&P 500 Index. Also, we estimate Sharpe and Treynor ratio values for each portfolio and compare rankings provided by these methods for the two portfolios with rankings provided by the ORR method. For the interval of time from June 1995 to May 1998, the rankings provided by the three methods are not consistent. The ORR rankings for this time period indicate the CREF Fund underperformed the S&P Index on a risk-adjusted basis. Additional partitioning of the data creates other multiple intervals or holding periods for which the evaluation results (ex post) support at least moderate likelihood of unambiguous inconsistency ex ante. We argue that, given our set of assumptions, the ORR rankings, founded in option-pricing theory, are more reliable than the others that are M-V based.     

On time-heterogeneous credibility estimation

Abstract

Let χ_i be the total claim amount of an insurance policy in calendar year i. We assume that the χ_i's are conditionally independent given an unknown random parameter ø, and that for all i. In the present paper it is under these assumptions shown how to calculate the credibility estimator of m(ø) by recursive updating. We also give estimators for the unknown parameters α_i, β_i, and ?_i based on portfolio data. Finally we mention some related models.     

Land as Production Input and Collateral: Land Investment by Japanese Firms

Is the collateral role an empirically important determinant of investment in land? We study what has determined the land investment by Japanese firms since the 1990s, after the collapse of the asset-price bubble. With a large panel data set, we estimate nonlinear land-investment functions and calculate q for land assets. The estimates confirm the dual roles of land assets: production inputs and collateral. Firms sold land assets in response to the decline in their sales and the deterioration in financial conditions. Partial q for land assets was generally below one during the period.     

Alpha-CIR model with branching processes in sovereign interest rate modeling

We introduce a class of interest rate models, called the \(\alpha\)-CIR model, which is a natural extension of the standard CIR model by adding a jump part driven by \(\alpha\)-stable Lévy processes with index \(\alpha\in(1,2]\). We deduce an explicit expression for the bond price by using the fact that the model belongs to the family of CBI and affine processes, and analyze the bond price and bond yield behaviors. The \(\alpha\)-CIR model allows us to describe in a unified and parsimonious way several recent observations on the sovereign bond market such as the persistency of low interest rates together with the presence of large jumps. Finally, we provide a thorough analysis of the jumps, and in particular the large jumps.     

Predicting premiums for the market, size, value, and momentum factors

This paper investigates the out-of-sample predictability of monthly market as well as size, value, and momentum premiums. We use a sample from each of the US and the Swiss stock markets between 1989 and 2007. Using the Swiss sample provides an important new perspective as the repeated evaluation of the same (US) data set leads to data mining problems. To avoid data mining in our predictability study, we test both statistical significance and robustness in the two samples. Our key results are as follows. We find no robust indication that the market premium is predictable, which is also true for the momentum and value premiums. It cannot be excluded that the results from the US may be caused by data mining in light of the results from the Swiss sample. However, the size premium seems to be somewhat predictable, due to the credit spread. We theorize that there are three possible reasons for this rare evidence for predictability. First, predictability may have disappeared over the last decade, as academic research made the respective information public. Second, predictability seems, as we demonstrate, not to be robust to the choice of methodology. Third, robustness tests in the Swiss sample reveal that many of the supposedly statistically significant interrelations from the US sample may be attributed to randomness, which, in that case, would be data mining. Therefore, we think that future discussions of predictability should address the issue of data mining by applying robustness tests.

Credit Risk and the Term Structure of Lease Rates: A Reduced Form Approach

Previous research either assumes default free leases or leases subject to default risk using a structural approach. However, structural credit risk models suffer from a common criticism that the firm’s asset value process is unobservable. We develop a reduced form credit risk model for leases that avoids making assumptions regarding unobservable asset valuation processes. Furthermore, we assume a correlated market and credit risk that provides us with a simple analytic formula for valuing defaultable lease contracts. Numerical analysis reveals that tenant credit risk can have a substantial impact on the term structure of leases. Finally, we use the model to demonstrate the implied lease term structure for a set of retail and financial firms in the Fall of 2000.

On a risk model with dependence between interclaim arrivals and claim sizes

We consider an extension to the classical compound Poisson risk model for which the increments of the aggregate claim amount process are independent. In Albrecher and Teugels (2006 Albrecher, H. and Teugels, J. 2006. Exponential behavior in the presence of dependence in risk theory. Journal of Applied Probability, 43(1): 257–273. [Crossref], [Web of Science ®] , [Google Scholar]), an arbitrary dependence structure among the interclaim time and the subsequent claim size expressed through a copula is considered and they derived asymptotic results for both the finite and infinite-time ruin probabilities. In this paper, we consider a particular dependence structure among the interclaim time and the subsequent claim size and we derive the defective renewal equation satisfied by the expected discounted penalty function. Based on the compound geometric tail representation of the Laplace transform of the time to ruin, we also obtain an explicit expression for this Laplace transform for a large class of claim size distributions. The ruin probability being a special case of the Laplace transform of the time to ruin, explicit expressions are therefore obtained for this particular ruin related quantity. Finally, we measure the impact of the various dependence structures in the risk model on the ruin probability via the comparison of their Lundberg coefficients.     

Pricing a contingent claim liability with transaction costs using asymptotic analysis for optimal investment

We price a contingent claim liability (claim for short) using a utility indifference argument. We consider an agent with exponential utility, who invests in a stock and a money market account with the goal of maximizing the utility of his investment at the final time T in the presence of a proportional transaction cost ε>0 in two cases: with and without a claim. Using the heuristic computations of Whalley and Wilmott (Math. Finance 7:307–324, 1997), under suitable technical conditions, we provide a rigorous derivation of the asymptotic expansion of the value function in powers of \(\varepsilon^{\frac{1}{3}}\) in both cases with and without a claim. Additionally, using the utility indifference method, we derive the price of the claim at the leading order of \(\varepsilon^{\frac{2}{3}}\) . In both cases, we also obtain a “nearly optimal” strategy, whose expected utility asymptotically matches the leading terms of the value function. We also present an example of how this methodology can be used to price more exotic barrier-type contingent claims.     

Using Google Scholar citations to rank accounting programs: a global perspective

We conduct an assessment on accounting program research performance based on Google Scholar citations for all articles from a set of 23 quality accounting journals during 1991–2010. Our work is a new approach in accounting by directly measuring the impact of the faculty research in accounting programs. We find that the top-5 accounting programs are the University of Pennsylvania, the University of Chicago, Stanford University, the University of Michigan, and Harvard University. These top programs produce a large number of high impact articles. In addition, using the mean citations from all articles in a journal, we find that the Review of Accounting Studies (RAST) is a top-5 journal, replacing Contemporary Accounting Research (CAR).     

An explicit martingale version of the one-dimensional Brenier theorem

By investigating model-independent bounds for exotic options in financial mathematics, a martingale version of the Monge–Kantorovich mass transport problem was introduced in (Beiglböck et al. in Finance Stoch. 17:477–501, 2013; Galichon et al. in Ann. Appl. Probab. 24:312–336, 2014). Further, by suitable adaptation of the notion of cyclical monotonicity, Beiglböck and Juillet (Ann. Probab. 44:42–106, 2016) obtained an extension of the one-dimensional Brenier theorem to the present martingale version. In this paper, we complement the previous work by extending the so-called Spence–Mirrlees condition to the case of martingale optimal transport. Under some technical conditions on the starting and the target measures, we provide an explicit characterization of the corresponding optimal martingale transference plans both for the lower and upper bounds. These explicit extremal probability measures coincide with the unique left- and right-monotone martingale transference plans introduced in (Beiglböck and Juillet in Ann. Probab. 44:42–106, 2016). Our approach relies on the (weak) duality result stated in (Beiglböck et al. in Finance Stoch. 17:477–501, 2013), and provides as a by-product an explicit expression for the corresponding optimal semi-static hedging strategies. We finally provide an extension to the multiple marginals case.