Semiparametric estimation of multinomial discrete‐choice models using a subset of choices

Nonlogit maximum‐likelihood estimators are inconsistent when using data on a subset of the choices available to agents. I show that the semiparametric, multinomial maximum‐score estimator is consistent when using data on a subset of choices. No information is required for choices outside of the subset. The required conditions about the error terms are the same conditions as for using all the choices. Estimation can proceed under additional restrictions if agents have unobserved, random consideration sets. A solution exists for instrumenting endogenous continuous variables. Monte Carlo experiments show the estimator performs well using small subsets of choices.     

The performance of the gph estimator of the fractional difference parameter: Simulation results

This paper investigates the behavior of the GPH estimator of the fractional difference parameter suggested by Geweke and Porter-Hudak (1983), through Monte Carlo simulations. The simulation results indicate that when considering a stationary AR(1) generating process the GPH estimator of the fractional difference parameter has serious bias which increases with the value of the autoregressive parameter, even for relatively large samples. The results suggest that tests and point estimates based on this procedure can be seriously misleading with hypothesis ests yielding incorrect inferences and thus must be used with great care.     

Price discovery on the S&P 500 index markets: An analysis of spot index,index futures,and SPDRs

This paper investigates the price discovery function in three S&P 500 index markets: the spot index, index futures, and S&P Depositary Receipts markets. Four hypotheses regarding market structure and security design are proposed to differentiate the price discovery function performed by the three index instruments. Using matched synchronous intraday trading data, Johansen's maximum likelihood estimator is employed to disclose the cointegration relationships among the three markets. Results indicate that the three price series are a cointegrated system with one long-run stochastic trend. Estimated coefficients of the vector error correction model suggest that price adjustment takes place in the spot index market and for SPDRs, but not in the futures market. When the common stochastic trend is decomposed, it is found that the futures market serves the dominant price discovery function. The leverage hypothesis and the uptick rule hypothesis explain its superior price discovery function.     

Two Decades of Commercial Property Returns: A Repeated-Measures Regression-Based Version of the NCREIF Index

This article documents 20 years of performance of commercial real estate in the United States using a portfolio of properties that comprise the widely followed NCREIF Property Index (NPI). We develop an extension of the repeated-measures regression (RMR) to produce an improved version of the NCREIF Index that eliminates the stale appraisal and seasonality problems. We use this RMR version of the index to examine the magnitude and duration of the of the crash in property values in the early 1990s. The RMR Index is also compared with the NAREIT Index, and property-type subindices are developed using a Bayesian estimator. Finally, it is also shown how the RMR can be used to estimate the average magnitude of random valuation error in commercial property valuation.     

Computing a Multivariate Normal Integral for Valuing Compound Real Options

We extend the Geske (1979) model to a multivariate normal integral for the valuation of a compound real option. We compared the computing speeds and errors of three numerical integration methods, namely, Drezner's improved Gauss quadrature method, Monte Carlo method and Lattice method, together with appropriate critical value finding methods. It is found that secant method for finding critical values combined with Lattice method and run by Fortran took merely one second, Monte Carlo method 120 seconds. It is also found that the real option decreases with interest rate, not necessarily positively correlated with volatility , a result different from that anticipated under financial option theory. This is mainly because the underlying of real option is a non-traded asset, which brings dividend-like yield into the formula of compound real options. Dividend-like yield rises with the multiplication of correlation coefficient and . High indicates the poor diversification advantage of the new investment project in relation to the existing market portfolio, and the value of real call option decreases with . Conversely, when is low, the proposed project provides better diversification advantage and the real call option rises with . Irrespective of the value of , when interest rate increases, the value of real call option drops, especially when is high, the value of the project is dominated by interest rate.     

Hybrid scheme for Brownian semistationary processes

We introduce a simulation scheme for Brownian semistationary processes, which is based on discretizing the stochastic integral representation of the process in the time domain. We assume that the kernel function of the process is regularly varying at zero. The novel feature of the scheme is to approximate the kernel function by a power function near zero and by a step function elsewhere. The resulting approximation of the process is a combination of Wiener integrals of the power function and a Riemann sum, which is why we call this method a hybrid scheme. Our main theoretical result describes the asymptotics of the mean square error of the hybrid scheme, and we observe that the scheme leads to a substantial improvement of accuracy compared to the ordinary forward Riemann-sum scheme, while having the same computational complexity. We exemplify the use of the hybrid scheme by two numerical experiments, where we examine the finite-sample properties of an estimator of the roughness parameter of a Brownian semistationary process and study Monte Carlo option pricing in the rough Bergomi model of Bayer et al. (Quant. Finance 16:887–904, 2016), respectively.     

The present value model with time-varying discount rates: Implications for commercial property valuation and investment decisions

A vector autoregressive model is developed for predicting cash flow and returns in the private (unsecuritized) commercial property markets. The model predicts both of these variables quite well during the sample period. The forecasting model is then used to develop a simple buy/sell rule for identifying property market value peaks and troughs. An improved present value model, taking account of the predictability of property returns, is described and found to track historical market values much more closely than does either the appraisal-based index or the traditional present value model with constant expected returns. Analysis in this paper suggests that most of the change in commercial property market values has been due to changes in expected returns, rather than to changes in expected future operating cash flows.     

German rail vehicle construction in the context of market globalisation

Conclusion In the guise of ABB Daimler-Benz Transportation and Siemens, Germany has two powerful systems suppliers in a good position to keep pace with other systems suppliers on global markets. As in the air-travel industry it is conceivable that developments are moving towards a uniform rail technology. Although the buy national principle still dominates procurement practices, and national egos still dominate the development of rail systems (ICE, TGV), growing competition from Japan could force Europe to develop a European system. This would significantly increase the chances of European industry in bidding for international contracts. For this reason the EU should not relent in its efforts to standardise European rail systems.     

The Information Content of Bank Examinations

We identify three types of information from bank examinations—auditing information from verifying the honesty and accuracy of the bank's books, regulatory discipline information about the treatment of the bank by regulators, and private information about bank condition. We estimate these information effects by comparing the cumulative abnormal market returns associated with examinations in which the CAMEL rating remained unchanged, improved, and worsened. All three information effects are found to be greater for banks entering the examination process with unsatisfactory ratings from prior examinations. The only consistently strong effect found is that examination downgrades appear to reveal unfavorable private information about bank condition. The evidence also suggests that the information may reach the market in part through loan quality data released in quarterly financial statements.     

Conduit Entities: Implications of Indirect Tax-Efficient Financing Structures for Real Investment

As well known, companies shift income from high to low tax jurisdictions. Typically, profit shifting is achieved by direct financing structures whereby companies use debt finance in the high tax entity and equity finance in the low tax entity. However, certain tax policies can lead to indirect financing structures whereby a conduit entity provides an opportunity to achieve at least two deductions for interest expenses for an investment made in the host country. The effect of direct and indirect financing structures on real investment is compared.     

Comparing Alternative Hedge Accounting Standards: Shareholders' Perspective

We study the economic consequences of alternative hedge accounting rules in terms of managerial hedging decisions and wealth effects for shareholders. The rules we consider include the fair-value and cash-flow hedge accounting methods prescribed by the recent SFAS No. 133. We illustrate that the accounting method used influences the manager's hedge decision. We show that under no-hedge accounting, the hedge choice is different from the optimal economic hedge the firm would make under symmetric and public information. However, under a certain definition of fair-value hedge accounting, the hedging decision preserves the optimal economic hedge. We then demonstrate that long-term and future shareholders prefer a certain definition of fair-value hedge accounting to no-hedge accounting, while short-term shareholders prefer either approach depending on risk preferences and the level of uncertainty. We speculate about circumstances in which a manager would choose not to adopt fair-value hedge accounting when he has the option not to do so.     

Modeling daily price limits

This paper characterizes the behavior of observed asset prices under price limits and proposes the use of two-limit truncated and Tobit regression models to analyze regression models whose dependent variable is subject to price limits. Through a proper arrangement of the sample, these two models, the estimation of which is easy to implement, are applied only to subsets of the sample under study, rather than the full sample. Using the estimation of simple linear regression model as an example, several Monte Carlo experiments are conducted to compare the performance of the maximum likelihood estimators (MLEs) based on these two models and a generalized method of moments (GMM) estimator developed by K. C. John Wei and R. Chiang. The results show that under different price limits and various distributional assumptions for the error terms, the MLEs based on the two-limit Tobit and truncated regression models and the GMM estimator perform reasonably well, while the naive OLS estimator is downward biased. Overall, the MLE based on the two-limit Tobit model outperforms the other estimators.     

On Pricing Exponential Square Root Barrier Knockout European Options

A barrier option is one of the most popular exotic options which is designedto give a protection against unexpected wild fluctuation of stock prices.Protection is given to both the writer and holder of such an option.Kunitomo and Ikeda (1992) analytically obtained a pricing formula forexponential double barrier knockout options. Since the logarithm of theirproposed barriers for the stock price process S(t), whichisassumed to be geometric Brownian motion, are nothing but straight lineboundaries, the protection provided by them is not uniform over time. Toremedy this problem, we propose square root curved boundaries±btfor the underlying Brownian motion process W(t). Since thestandarddeviation of Brownian motion is proportional to t, theseboundaries(after transformation) can be made to provide more uniform protectionthroughout the life time of the option. We will apply asymptoticexpansions of certain conditional probabilities obtained by Morimoto (1999)to approximate pricing formulae for exponential square root double barrierknockout European call options. These formulae allow us to computenumerical values in a very short time (t < 10^–6sec), whereas it takesmuch longer to perform Monte Carlo simulations to determine optionpremiums.     

Multivariate GARCH hedge ratios and hedging effectiveness in Australian futures markets

We use the All Ordinaries Index and the corresponding Share Price Index futures contract written against the All Ordinaries Index to estimate optimal hedge ratios, adopting several specifications: an ordinary least squares‐based model, a vector autoregression, a vector error‐correction model and a diagonal‐vec multivariate generalized autoregressive conditional heteroscedasticity model. Hedging effectiveness is measured using a risk‐return comparison and a utility maximization method. We find that time‐varying generalized autoregressive conditional heteroscedasticity hedge ratios perform better than constant hedge ratios in terms of minimizing risks, but when return effects are also considered, the utility‐based measure prefers the ordinary least squares method in the in‐sample hedge, whilst both approaches favour the conditional time‐varying multivariate generalized autoregressive conditional heteroscedasticity hedge ratio estimates in out‐of‐sample analyses.     

Hedging with Chinese Aluminum Futures: International Evidence with Return and Volatility Spillover Indices Under Structural Breaks

This paper examines the hedging performance of the Shanghai futures market, with the London futures market acting as the channel for volatility spillover. Taking into consideration structural change, basis effects, and return and volatility spillover effects, the authors find that the estimated hedging performance is not improved. Their findings suggest that the effectiveness of the hedging performance of aluminum futures contracts in China is not affected by the magnitude or direction of return and volatility spillovers. Therefore, even when the magnitude and direction of volatility spillover from other markets can be correctly predicted, the hedging performance of a futures contract cannot be significantly improved. This paper uses precise measures of return spillovers and volatility spillovers based directly on the framework of vector autoregressive variance decompositions. The study also includes an analysis of both crisis and noncrisis episodes, with modeling on bursts in spillovers.     

Heterogeneity in Financial Market Participation: Appraising its Implications for the C-CAPM

This paper presents empirical evidence that accounting for heterogeneity in financial market participation is important for evaluating the empirical performance of the Consumption-based Capital Asset Pricing Model (C-CAPM). Using the US Consumer Expenditure Survey as a common testing ground, I re-assess three well-known characterizations of the equity premium puzzle (i) the inconsistency of the representative agent's IMRS with Hansen and Jagannathan bounds; (ii) Mehra and Prescott's calibration of a large representative agent's risk aversion; (iii) Hansen and the Singleton's large structural estimates of the preference parameters based on aggregate data. In all three cases, the estimates of risk aversion conditional upon financial market participation are not as far from reasonable values as the corresponding unconditional ones. The differences suggest that part of the equity premium puzzle can be accounted for by the use of a representative agent assumption rather than a more appropriate "representative stockholding agent assumption.     

Specification and estimation of discrete time quadratic stochastic volatility models

I propose a new class of stochastic volatility models that nests the commonly used log normal autoregressive specification. As with the eigenfunction specification of Meddahi (Meddahi, Nour, 2001. An eigenfunction approach for volatility modeling. Unpublished.), the log-quadratic model can generate high kurtosis, a key feature of asset returns, even with Gaussian innovations. I discuss maximum likelihood estimation based on numerical integration of the log-quadratic specification that allows for leverage effects. A small Monte Carlo simulation experiment demonstrates the feasibility of maximum likelihood estimation and the importance of allowing for leverage effects. I fit the log-quadratic specification to the daily S&P 500 index return series and find that it provides a better fit than the commonly used log autoregressive specification with Gaussian and Student-t mean equation innovations.     

Corporate Real Estate and Stock Market Performance

An interesting question in corporate real estate literature is whether real estate can improve the stock market performance of property-intensive non-real estate firms. Using a data set comprising 75 non-real estate corporations that own at least 20 percent properties, this paper empirically assesses and compares the pair-wise return, total risk, systematic risk and Jensen abnormal return performance of composite (with real estate) and hypothetical business (without real estate) firms. We employed Morgan Stanley Capital International world equity index instead of a local market index to provide some insights into the performance of the local market relative to the global market during the 1997–2001 volatile periods experienced by many Asian countries. Our results suggest the inclusion of real estate in a corporate portfolio appears to be associated with lower return, higher total risk, higher systematic risk and poorer abnormal return performance. It is therefore likely that non-real estate firms own properties for other reasons in addition to seeking improvement in their stock market performance. Further research is needed to explore the main factors contributing to corporate real estate ownership by non-real estate firms.     

Commercial Mortgage Default: A Comparison of Logit with Radial Basis Function Networks

This article explores the use of artificial neural networks in the modeling of foreclosure of commercial mortgages. The study employs a large set of individual loan histories previously used in the literature of proportional hazard models on loan default. Radial basis function networks are trained (estimated) using the same input variables as those used in the logistic. The objective is to demonstrate the use of networks in forecasting mortgage default and to compare their performance with that of the logistic benchmark in terms of prediction accuracy. Neural networks are shown to be superior to the logistic in terms of discriminating between good and bad loans. The study performs sensitivity analysis on the average loan and offers suggestions on further improving prediction of defaulting loans.     

Multilevel Monte Carlo for exponential Lévy models

We apply the multilevel Monte Carlo method for option pricing problems using exponential Lévy models with a uniform timestep discretisation. For lookback and barrier options, we derive estimates of the convergence rate of the error introduced by the discrete monitoring of the running supremum of a broad class of Lévy processes. We then use these to obtain upper bounds on the multilevel Monte Carlo variance convergence rate for the variance gamma, NIG and \(\alpha\)-stable processes. We also provide an analysis of a trapezoidal approximation for Asian options. Our method is illustrated by numerical experiments.