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.     

A BSDE approach to fair bilateral pricing under endogenous collateralization

Nie and Rutkowski (Int. J. Theor. Appl. Finance 18:1550048, 2015; Math. Finance, 2016, to appear) examined fair bilateral pricing in models with funding costs and an exogenously given collateral. The main goal of this work is to extend results from Nie and Rutkowski (Int. J. Theor. Appl. Finance 18:1550048, 2015; Math. Finance, 2016, to appear) to the case of an endogenous margin account depending on the contract’s value for the hedger and/or the counterparty. Comparison theorems for BSDEs from Nie and Rutkowski (Theory Probab. Appl., 2016, forthcoming) are used to derive bounds for unilateral prices and to study the range for fair bilateral prices in a general semimartingale model. The backward stochastic viability property, introduced by Buckdahn et al. (Probab. Theory Relat. Fields 116:485–504, 2000), is employed to examine the bounds for fair bilateral prices for European claims with a negotiated collateral in a diffusion-type model. We also generalize in several respects the option pricing results from Bergman (Rev. Financ. Stud. 8:475–500, 1995), Mercurio (Actuarial Sciences and Quantitative Finance, pp. 65–95, 2015) and Piterbarg (Risk 23(2):97–102, 2010) by considering contracts with cash-flow streams and allowing for idiosyncratic funding costs for risky assets.     

Business cycles,financial cycles and capital structure

We perform peridogram based cycle analysis of firm capital structure and find evidence that firms’ leverage is both persistent and cyclical. The cyclicality of leverage is supported by the trade-off, pecking order and market timing capital structure theories (Korajczyk and Levy in J Financ Econ 68:75–109, 2003; Bhamra et al. in Rev Financ Stud 23:645–703, 2010). Although market timing theory research supports persistence, previous literature dictates that the trade-off and pecking order theories may predict either persistent or mean reverting leverage. Our tests reject mean reversion in favor of persistent and cyclical leverage. We corroborate pecking order theory literature that predicts leverage is persistent. In these models, when firms’ investment spending is below earnings, leverage decreases. In addition, we examine whether firms change their capital structure as a result of business and financial cycles. Since financial cycles last longer than business cycles, financial cycles should have a long term effect on leverage. Our findings confirm the persistent leverage business cycle models that suggest firms change their capital structure due to financial and credit cycles (Jermann and Quadrini in Am Econ Rev 102:238–271, 2012; Azariadis et al. in Rev Econ Stud 83:1364–1405, 2016). We conclude that leverage is persistent due to the cyclicality of the financing decision.     

Corporate bankruptcy prediction: a high dimensional analysis

Much bankruptcy research has relied on parametric models, such as multiple discriminant analysis and logit, which can only handle a finite number of predictors (Altman in The Journal of Finance 23 (4), 589–609, 1968; Ohlson in Journal of Accounting Research 18 (1), 109–131, 1980). The gradient boosting model is a statistical learning method that overcomes this limitation. The model accommodates very large numbers of predictors which can be rank ordered, from best to worst, based on their overall predictive power (Friedman in The Annals of Statistics 29 (5), 1189–1232, 2001; Hastie et al. 2009). Using a sample of 1115 US bankruptcy filings and 91 predictor variables, the study finds that non-traditional variables, such as ownership structure/concentration and CEO compensation are among the strongest predictors overall. The next best predictors are unscaled market and accounting variables that proxy for size effects. This is followed by market-price measures and financial ratios. The weakest predictors overall included macro-economic variables, analyst recommendations/forecasts and industry variables.     

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 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.     

Jump-robust estimation of volatility with simultaneous presence of microstructure noise and multiple observations

In this paper, we develop the multipower estimators for the integrated volatility in (Barndorff-Nielsen and Shephard in J. Financ. Econom. 2:1–37, 2004); these estimators allow the presence of jumps in the underlying driving process and the simultaneous presence of microstructure noise and multiple records of observations. By multiple records we mean more than one observation recorded on a single time stamp, as often seen in stock markets, in particular, for heavily traded securities, for a data set with even millisecond frequency. We establish the consistency and asymptotic normality of the estimators for both noise-free and noise-present cases. Simulation studies confirm our theoretical results. We apply the estimators to a real high-frequency data set.     

Change of numeraire in the two-marginals martingale transport problem

In this paper, we apply change of numeraire techniques to the optimal transport approach for computing model-free prices of derivatives in a two-period setting. In particular, we consider the optimal transport plan constructed in Hobson and Klimmek (Finance Stoch. 19:189–214, 2015) as well as the one introduced in Beiglböck and Juillet (Ann. Probab. 44:42–106, 2016) and further studied in Henry-Labordère and Touzi (Finance Stoch. 20:635–668, 2016). We show that in the case of positive martingales, a suitable change of numeraire applied to Hobson and Klimmek (Finance Stoch. 19:189–214, 2015) exchanges forward start straddles of type I and type II, so that the optimal transport plan in the subhedging problems is the same for both types of options. Moreover, for Henry-Labordère and Touzi’s (Finance Stoch. 20:635–668, 2016) construction, the right-monotone transference plan can be viewed as a mirror coupling of its left counterpart under the change of numeraire.     

Pricing currency options under double exponential jump diffusion in a Markov-modulated HJM economy

Extending the framework of Amin and Jarrow (J Int Money Financ 10:310–329, 1991) and Bo et al. (Insur Math Econ 46:461–469, 2010), this study provides a theoretical exploration of currency options pricing under the presence of interest-rate regime shifts and exchange-rate asymmetric jumps. Evidence of interest-rate regime shifts inferred from UK and US zero coupon bond yields provides support for the regime-switching specifications which we reflect upon the domestic and foreign forward rates. Results of statistical tests conducted on JPY/USD and EUR/USD FX rates provide further support the rationale behind using a double exponential jump diffusion process within a Markov modulated Heath–Jarrow–Morton economy. Our numerical results suggest that, the pricing performance of our model is closely comparable to the Bo-Wang-Yang model for at-the-money options, yet yields improvements in percentage root mean errors for in-the-money options.     

The dispersion anomaly and analyst recommendations

The main objective of this study is to distinguish whether the forecast dispersion anomaly is due to Miller’s (J Finance 32(4):1151–1168, 1977) overpricing hypothesis or idiosyncratic risk, by conditioning the sample on “buy” and “sell” consensus recommendations. Observations on the long and short possibilities provided to the investors by the analyst stock recommendations can help us infer on the impact of short sale constraints even though they are not directly observed. This study provides strong evidence that the impact of analyst forecast dispersion is more pronounced in the group of stocks that receive the least favorable recommendations in a given period, even after controlling for the idiosyncratic risk, Fama–French factors (J Financ Econ 33(1):3–56, 1993; J Financ Econ 116(1):1–22, 2015) and even short-sale constraints. These results are consistent with Miller’s (1977) hypothesis, according to which if short-sale constraints bind, high opinion divergence stocks become overpriced and hence have low subsequent returns.     

Service quality in the private banking business

This paper examines the concept of service quality in private banking theoretically and empirically and identifies factors which contribute to service quality. A multidimensional and hierarchical model is developed based on the work of Rust and Oliver (in Service Quality, pp. 1–20, 1994) and Brady and Cronin (in J. Mark. 65(3):34–49, 2001). The model is then empirically tested among private banking providers with the partial least squares method. Furthermore, the developed model is compared to other approaches, including Grönroos (in Eur. J. Mark. 18(4):36–44, 1984). Another model for comparison excludes the indirect effects of Grönroos (in Eur. J. Mark. 18(4):36–44, 1984) and focuses on the direct effects on service quality. We can conclude that the model based on Rust and Oliver (in Service Quality, pp. 1–20, 1994) and Brady and Cronin (in J. Mark. 65(3):34–49, 2001) produces the best results and can best explain service quality in private banking. Finally, an analysis of various provider groups is conducted in order to identify differences between private banking providers in Germany, Switzerland, Austria and Liechtenstein and between providers with various minimum investment requirements.     

Indirect tax reform and the specification of demand: the case of Ireland

This paper examines the sensitivity of marginal tax reform analysis to changes in the underlying demand system. In particular, we analyse the sensitivity of results from Ahmad and Stern’s (J Publ Econ 25(3):259–298, 1984) marginal tax reform model to different specifications of Deaton and Muellbauer’s (Am Econ Rev 70(3):312–326, 1980) Almost Ideal Demand System (AIDS) and Banks et al.’s (Rev Econ Stat 79(4):527–539, 1997) Quadratic AIDS. Using Irish Household Budget Survey data, we show that tax reform results exhibit a low degree of sensitivity to changes in the underlying demand system. An adjustment for a mass of observed zero-expenditures in the data for certain goods produces most sensitivity in the tax reform results. Even in these cases, many of the tax reform recommendations remain constant. Including demerit good arguments in the tax reform model can substantially alter the tax reform recommendations relating to demerit goods. Notably though, when we include these arguments in the tax reform model, the results are particularly insensitive to changes in the underlying demand system.     

A four-factor stochastic volatility model of commodity prices

The number of factors driving the uncertain dynamics of commodity prices has been a central consideration in financial literature. While the majority of empirical studies relies on the assumption that up to three factors are sufficient to explain all relevant uncertainty inherent in commodity spot, futures, and option prices, evidence from Trolle and Schwartz (Rev Financ Stud 22(11):4423–4461, 2009b) and Hughen (J Futures Mark 30(2):101–133, 2010) indicates a need for additional risk factors. In this article, we propose a four-factor maximal affine stochastic volatility model that allows for three independent sources of risk in the futures term structure and an additional, potentially unspanned stochastic volatility process. The model principally integrates the insights from Hughen (2010) and Tang (Quant Finance 12(5):781–790, 2012) and nests many well-known models in the literature. It can account for several stylized facts associated with commodity dynamics such as mean reversion to a stochastic level, stochastic volatility in the convenience yield, a time-varying correlation structure, and time-varying risk-premia. In-sample and out-of-sample tests indicate a superior model fit to futures and options data as well as lower hedging errors compared to three-factor benchmark models. The results also indicate that three factors are not sufficient to model the joint dynamics of futures and option prices accurately.     

On the Price of Risk Under a Regime Switching CGMY Process

In this paper, we study option pricing under a regime-switching exponential Lévy model. Assuming that the coefficients are time-dependent and modulated by a finite state Markov chain, we generalise the work in Momeya and Morales (Method Comput Appl Probab, 2014, doi: 10.1007/s11009-014-9399-2), and Siu and Yang (Acta Mathe Appl Sin 2:369–388, 2009), that is, we use a pricing method based on the Esscher transform conditional on the information available on the Markov chain. We also carry out numerical analysis, to show the impact of the risk induced by the underlying Markov chain on the price of the option.     

Risk measures with the CxLS property

In the present contribution, we characterise law determined convex risk measures that have convex level sets at the level of distributions. By relaxing the assumptions in Weber (Math. Finance 16:419–441, 2006), we show that these risk measures can be identified with a class of generalised shortfall risk measures. As a direct consequence, we are able to extend the results in Ziegel (Math. Finance, 2014, http://onlinelibrary.wiley.com/doi/10.1111/mafi.12080/abstract) and Bellini and Bignozzi (Quant. Finance 15:725–733, 2014) on convex elicitable risk measures and confirm that expectiles are the only elicitable coherent risk measures. Further, we provide a simple characterisation of robustness for convex risk measures in terms of a weak notion of mixture continuity.     

Erratum to: Utility maximization in incomplete markets with random endowment

K. Larsen, M. Soner and G. ?itkovi? kindly pointed out to us an error in our paper (Cvitani? et al. in Finance Stoch. 5:259–272, 2001) which appeared in 2001 in this journal. They also provide an explicit counterexample in Larsen et al. (https://arxiv.org/abs/1702.02087, 2017).In Theorem 3.1 of Cvitani? et al. (Finance Stoch. 5:259–272, 2001), it was incorrectly claimed (among several other correct assertions) that the value function \(u(x)\) is continuously differentiable. The erroneous argument for this assertion is contained in Remark 4.2 of Cvitani? et al. (Finance Stoch. 5:259–272, 2001), where it was claimed that the dual value function \(v(y)\) is strictly concave. As the functions \(u\) and \(v\) are mutually conjugate, the continuous differentiability of \(u\) is equivalent to the strict convexity of \(v\). By the same token, in Remark 4.3 of Cvitani? et al. (Finance Stoch. 5:259–272, 2001), the assertion on the uniqueness of the element \(\hat{y}\) in the supergradient of \(u(x)\) is also incorrect.Similarly, the assertion in Theorem 3.1(ii) that \(\hat{y}\) and \(x\) are related via \(\hat{y}=u'(x)\) is incorrect. It should be replaced by the relation \(x=-v'(\hat{y})\) or, equivalently, by requiring that \(\hat{y}\) is in the supergradient of \(u(x)\).To the best of our knowledge, all the other statements in Cvitani? et al. (Finance Stoch. 5:259–272, 2001) are correct.As we believe that the counterexample in Larsen et al. (https://arxiv.org/abs/1702.02087, 2017) is beautiful and instructive in its own right, we take the opportunity to present it in some detail.     

The impact of executive inside debt on sell-side financial analyst forecast characteristics

Debt-like compensation, referred to as inside debt, is prevalent in US firms and affects firm operating, investing and financial reporting activities. The amount of inside debt can be used to extract information that benefits analyst forecasting activities. This study finds that forecast accuracy increases, while forecast dispersion and revision volatility decrease with the magnitude of inside debt. Further analysis shows that inside debt is associated with increased propensity of firms to provide voluntary disclosures and the documented benefits on analyst characteristics accrue only to firms that offer close to optimal level of inside debt (Jensen and Meckling in J Financ Econ 3:305–360, 1976; Edmans and Liu in Rev Finance 15:75–102, 2011). Our research is the first to link debt-like compensation to financial analyst behavior and contributes to the understanding of the implications of inside debt to outside market participants.     

The pricing of common exchange rate factors in the U.S. equity market

We extend Lustig et al. (Rev Financ Stud 24:3731–3777, 2011) and Brusa et al. (The International CAPM Redux, 2014) by examining if the common exchange rate factors, the dollar and carry factors, are priced in the US equity market. Our results suggest that while the carry factor has incremental pricing information relative to the US market factor, the dollar factor (or the trade-weighted exchange rate index) is redundant. Our results have important theoretical as well as practical implications. Theoretically, we suggest that financial economists take an endogenous perspective of exchange rates. Practically, we suggest that practitioners incorporate in the carry factor to measure the exposure of exchange rate risk.     

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.     

Tukey’s transformational ladder for portfolio management

Over the past half-century, the empirical finance community has produced vast literature on the advantages of the equally weighted Standard and Poor (S&P 500) portfolio as well as the often overlooked disadvantages of the market capitalization weighted S&P 500’s portfolio (see Bloomfield et al. in J Financ Econ 5:201–218, 1977; DeMiguel et al. in Rev Financ Stud 22(5):1915–1953, 2009; Jacobs et al. in J Financ Mark 19:62–85, 2014; Treynor in Financ Anal J 61(5):65–69, 2005). However, portfolio allocation based on Tukey’s transformational ladder has, rather surprisingly, remained absent from the literature. In this work, we consider the S&P 500 portfolio over the 1958–2015 time horizon weighted by Tukey’s transformational ladder (Tukey in Exploratory data analysis, Addison-Wesley, Boston, 1977): \(1/x^2,\,\, 1/x,\,\, 1/\sqrt{x},\,\, \text {log}(x),\,\, \sqrt{x},\,\, x,\,\, \text {and} \,\, x^2\), where x is defined as the market capitalization weighted S&P 500 portfolio. Accounting for dividends and transaction fees, we find that the 1/\(x^2\) weighting strategy produces cumulative returns that significantly dominate all other portfolio returns, achieving a compound annual growth rate of 18% over the 1958–2015 horizon. Our story is furthered by a startling phenomenon: both the cumulative and annual returns of the \(1/x^2\) weighting strategy are superior to those of the 1 / x weighting strategy, which are in turn superior to those of the \(1/\sqrt{x}\) weighted portfolio, and so forth, ending with the \(x^2\) transformation, whose cumulative returns are the lowest of the seven transformations of Tukey’s transformational ladder. The order of cumulative returns precisely follows that of Tukey’s transformational ladder. To the best of our knowledge, we are the first to discover this phenomenon.