Modelling & Controlling Monetary and Economic Identities with Constrained State Space Models

The paper presents a method for modelling and controlling time series with identity structures. The approach is presented in the context of monetary targeting where the monetary identity (e.g. reserve money equals net foreign assets plus domestic credit) is modelled using a constrained state space model and next‐period changes in domestic credit (policy variable) are estimated to reach the target level of reserve money. The constrained modelling ensures that aggregation and identity relations among items are dynamically satisfied during estimation, leading to more accurate forecasting and targeting. Applications to Germany, UK and USA show that the constrained state space model provides significant improvements in targeting and forecasting performance over the AR(1) benchmark and the unconstrained model. Reduction in the mean square error of targeting over AR(1) is in the range of 76–95% for the three countries while the gain in targeting efficiency over unconstrained modelling is between 21% and 55%. Beyond monetary targeting, the method has wide application to the dynamic modelling and control of economic and financial time series with identity and aggregation constraints (e.g. balance of payment, national income, purchasing power parity, company balance sheet).     

Arbitrage-free valuation of interest rate securities under forward curves with stochastic speed and acceleration

Arbitrage-free models for valuing interest rate securities posit that stochastic changes in spot or forward interest rates (forward rate “speed”) follow a diffusion process. This paper extends the Heath, Jarrow and Morton [Bond pricing and the term structure of interest rates: a new methodology for contingent claims valuations, Econometrica 60 (1992) 77-105], HJM framework by allowing diffusive shocks to both the “speed” and “acceleration” of forward rates. The arbitrage-free restriction on forward rates is identified and involves volatilities of the speed and acceleration dynamics and their correlation. Although the extended forward rates remain in the diffusive framework and evolve continuously, they may exhibit large changes over short intervals (as with jumps) due to stochastic acceleration. Comparisons of bond prices show that the proposed model generates more complex and intricate shapes for the restricted forward curve with the same number of stochastic factors and volatility.     

Drift Estimation of Generalized Security Price Processes from High Frequency Derivative Prices

This paper presents a framework for using high frequency derivative prices to estimate the drift of generalized security price processes. This work may be seen more generally as a quasi-likelihood approach to estimating continuous-time parameters of derivative pricing models using discrete option data. We develop a generalized derivative-based estimator for the drift where the underlying security price process follows any arbitrary state-time separable diffusion process (including arithmetic and geometric Brownian motion as special cases). The framework provides a method to measure premia in derivative prices, test for risk-neutral pricing and leads to a new empirical approach to pricing derivative contingent claims. A sufficient condition for the asymptotic consistency of the generalized estimator is also obtained. A study based on generating the S&P500 index and calls shows that the estimator can correctly estimate the drift parameter. This revised version was published online in November 2006 with corrections to the Cover Date.     

CEO compensation: A resource advantage and stakeholder‐bargaining perspective

This paper studies how CEO pay and its composition is shaped by strategic factors related to the firm's capacity to generate rents and value, the uncertainty of its resource advantage, and the competitive interaction between firm stakeholders and top management. This is done using an analytical framework in which the CEO and other firm stakeholders interact over the firm's resource surplus as utility‐maximizing claimants based on their relative bargaining power while providing shareholders their market‐based required return. Results from the model yield a number of cogent strategic insights and predictions on the causal interplay between CEO pay, firm growth and risk characteristics, stakeholder management, corporate strategy (e.g., offshoring production), and behavioral biases such as CEO optimism and overconfidence. Copyright © 2012 John Wiley & Sons, Ltd.     

Equity‐based incentives and collaboration in the modern multibusiness firm

Research summary : This paper examines the role of equity‐based incentives in fostering cross‐business‐unit collaboration in multibusiness firms. We develop a formal agency model in which headquarters offers equity and profit incentives to business‐unit managers with the objective of maximizing total expected firm returns. The resulting compensation contract provides a rich mechanism for aggregating value from collaborative interactions across business units, aligning managers' efforts with the firm's growth prospects and organization structure and managing the dual risks in profits and firm market value. The inclusion of equity incentives elicits higher levels of own‐unit and collaborative efforts over the profits‐only contract. Our results suggest that equity‐based incentives are most beneficial when profitability is uncertain relative to long‐term growth prospects, in firms pursuing related diversification strategies, and in periods of rising equity markets. Managerial summary : Equity‐based compensation such as restricted stock grants and options are increasingly common, not only for CEOs and other top executives, but also for business unit managers and other non‐C‐suite employees. The paper studies the role of such “global” incentives in enabling multibusiness firms to benefit from cross‐unit collaboration. Results from our model show that managerial contracts that include appropriate levels of equity incentives, in addition to profit‐based incentives, generate higher own‐unit and collaborative efforts. We also find that equity incentives are likely to be most beneficial for large firms in high‐growth sectors, for firms pursuing a related diversification strategy, and in periods of rising stock markets. The model can also provide useful guidance on designing return‐maximizing compensation contracts for business unit managers in different firm, organizational, and industry contexts. Copyright © 2015 John Wiley & Sons, Ltd.     

Risk and Return in the U.S. Housing Market: A Cross-Sectional Asset-Pricing Approach

This article carries out an asset-pricing analysis of the U.S. metropolitan housing market. We use ZIP code–level housing data to study the cross-sectional role of volatility, price level, stock market risk and idiosyncratic volatility in explaining housing returns. While the related literature tends to focus on the dynamic role of volatility and housing returns within submarkets over time, our risk–return analysis is cross-sectional and covers the national U.S. metropolitan housing market. The study provides a number of important findings on the asset-pricing features of the U.S. housing market. Specifically, we find (i) a positive relation between housing returns and volatility, with returns rising by 2.48% annually for a 10% rise in volatility, (ii) a positive but diminishing price effect on returns and (iii) that stock market risk is priced directionally in the housing market. Our results on the return-volatility-price relation are robust to (i) metropolitan statistical area clustering effects and (ii) differences in socioeconomic characteristics among submarkets related to income, employment rate, managerial employment, owner-occupied housing, gross rent and population density.