Assessment of business potential at retail sites: empirical findings from a US supermarket chain

We address the problem of estimating retail business potential at alternative sites, with concern for assessing performance relative to potential in existing markets and for identifying the best sites for expansion into new markets. At question is the utility of information typically used in formal retail patronage models, in comparison with additional information considered important by retail executives. Relevant data are gathered from secondary sources and intensive in-store surveys are conducted to produce a portfolio of information about neighbourhood demographics, store ambience, variety and quality of products and services, relative prices of selected products, etc. for stores in a retail grocery chain and competitive stores in the chain's markets. We experiment with alternative statistical models for store performance to determine the consequence of restricting the types of data available when constructing the models. Our findings suggest that while information about store location and surrounding areas, store characteristics and competitive position are all required to obtain the best assessment for business potential at a site, a few key variables on each dimension offer the bulk of explanatory power. Further, the spatial-locational variables affect all measures of store performance in intuitive directions, whereas the effects of other variables differ according to performance measure and reflect the store's market position.     

On Level Curves of Value Functions in Optimization Models of Expected Utility

We study the level sets of value functions in expected utility stochastic optimization models. We consider optimal portfolio management models in complete markets with lognormally distributed prices as well as asset prices modeled as diffusion processes with nonlinear dynamics. Besides the complete market cases, we analyze models in markets with frictions like correlated nontraded assets and diffusion stochastic volatilities. We derive, for all the above models, equations that their level curves solve and we relate their evolution to power transformations of derivative prices. We also study models with proportional transaction costs in a finite horizon setting and we derive their level curve equation; the latter turns out to be a Variational Inequality with mixed gradient and obstacle constraints.     

Optimal hedging with futures options

This paper explores the use of commodity options as risk management tools in incomplete markets with particular attention to alternative hedging strategies in the presence of basis and quantity risks. Hedgers typically face basis and quantity risks, which result in incomplete markets. In such markets, portfolios of commodity options prove a viable means of managing risks.Hedging opportunities are characterized using partial equilibrium frameworks, comparative statics, and an illustration from a simulation. A nonlinear optimization technique determines optimal portfolios of commodity options. All models examined are static two-date models. Therefore, they ignore the dynamic aspects of the hedger's problem, and distinguish neither American from European options, nor futures from forward markets.     

Principal components analysis for correlated curves and seasonal commodities: The case of the petroleum market

This article presents a family of term structure models that can be applied to value contingent claims in multicommodity and seasonal markets. We apply the framework to the futures contracts on crude and heating oils trading on NYMEX. We show how to deal with the problem of having to value products depending on the “whole” market, such as spread options on contracts on a single commodity maturing at different times (time‐spreads) or spread options on the added value of the products derived from the raw commodity (crack spreads). Also, we show how to build term structure models for a commodity that experiences seasonality, such as heating oil. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:1019–1035, 2002     

The economics of the super‐multiplier: A comprehensive treatment with labor markets

This paper links the super‐multiplier to Keynesian macroeconomics, showing it to be the most Keynesian of growth perspectives. Next, the paper shows that the super‐multiplier is a micro‐economically coherent theory of investment and capital accumulation. Firms’ decisions regarding capital accumulation coordinate demand and supply growth in goods markets. The paper then explores the implications of incorporating the super‐multiplier in the neo‐Kaleckian and Cambridge growth models. Lastly, it shows how labor markets and unemployment can be added into super‐multiplier models to provide a comprehensive growth model that addresses Solow's (1956, Journal of Economics, 70, 65–94) labor market knife‐edge problem. Incorporating labor markets does not change the fundamental super‐multiplier result that growth is determined by the growth of autonomous demand.     

Super‐replication in fully incomplete markets

In this work, we introduce the notion of fully incomplete markets. We prove that for these markets, the super‐replication price coincides with the model‐free super‐replication price. Namely, the knowledge of the model does not reduce the super‐replication price. We provide two families of fully incomplete models: stochastic volatility models and rough volatility models. Moreover, we give several computational examples. Our approach is purely probabilistic.     

SUPERHEDGING IN ILLIQUID MARKETS

We study superhedging of securities that give random payments possibly at multiple dates. Such securities are common in practice where, due to illiquidity, wealth cannot be transferred quite freely in time. We generalize some classical characterizations of superhedging to markets where trading costs may depend nonlinearly on traded amounts and portfolios may be subject to constraints. In addition to classical frictionless markets and markets with transaction costs or bid‐ask spreads, our model covers markets with nonlinear illiquidity effects for large instantaneous trades. The characterizations are given in terms of stochastic term structures which generalize term structures of interest rates beyond fixed income markets as well as martingale densities beyond stochastic markets with a cash account. The characterizations are valid under a topological condition and a minimal consistency condition, both of which are implied by the no arbitrage condition in the case of classical perfectly liquid market models. We give alternative sufficient conditions that apply to market models with general convex cost functions and portfolio constraints.     

Marketing perspectives on digital business models: A framework and overview of the special issue

Strong digital developments are changing markets, and firms may adopt a digital business model to deal with these developments. This special issue focuses on such digital business models. In this editorial, we discuss the relevance of digital business models, propose a conceptual framework, and discuss how digital business models affect firms, firm performance, and markets. We introduce the papers in this issue and show how they each fit within the conceptual framework. We discuss four important areas for future research.     

Clustering in emerging equity markets

We consider pairwise tail behavior of return series for identifying the most important emerging markets clusters. Pairs of markets belonging to the same group present similar type and strength of interdependence during stressful times, represented by a common copula and a statistically equivalent measure of tail dependence. By collapsing data from d markets in to a group we overcome the difficult problem of finding their (higher dimensional) d-variate distribution. Results may help portfolio managers to deal with risk due to co-movements within clusters. We provide examples on how this can be done. Our study contributes to the discussion about the international association among stock markets during turbulent periods, and does not confirm the intuition that the observed association between extremes should be credited to linkages to leading markets. The study also confirms the importance of stock selection, particularly among the non-dominant stocks, instead of holding market-value weighed portfolios of stocks from countries within the same region.     

The impact of market similarity on international marketing strategies: The automobile industry in Western Europe

The formulation of an optimal marketing mix is quite complex when that mix must be effective across multiple international markets. At the crux of the problem is whether markets are similar to each other or interdependent and how this influences marketing mix decisions. Examining the marketing mixes of more than 30 automobile companies competing in the five major markets in Western Europe, it was found that easily changed marketing mix elements, such as prices and advertising, reflect market similarity, interdependence, and product‐market conditions, although not always in the expected ways. The least flexible element, the number of models offered, does not appear to reflect any of these types of conditions. © 2000 John Wiley & Sons, Inc.     

Convex duality for Epstein–Zin stochastic differential utility

This paper introduces a dual problem to study a continuous‐time consumption and investment problem with incomplete markets and Epstein–Zin stochastic differential utilities. Duality between the primal and dual problems is established. Consequently, the optimal strategy of this consumption and investment problem is identified without assuming several technical conditions on market models, utility specifications, and agent's admissible strategies. Meanwhile, the minimizer of the dual problem is identified as the utility gradient of the primal value and is economically interpreted as the “least favorable” completion of the market.     

Valuation of futures and commodity options with information costs

In this article, futures and commodity options are analyzed in the context of Merton's (1987) model of capital market equilibrium with incomplete information. First, following Dusak (1973) and Black (1976), the conditions under which Merton's model can be applied to the valuation of forward and futures contracts are proposed. Then an application to futures markets is given. We provide a partial differential equation and the formulas for European commodity options, futures contracts, and American options in the same context. The models are simulated and compared to standard models with no information costs. We find that model prices are not significantly different from standard model prices. However, our models correct for some pricing biases in standard models. In particular, they reduce the overvaluation bias for European and American commodity options. It seems that the costs of gathering and processing information regarding the option and its underlying asset play a role in explaining the biases observed in standard models. This work can be applied to other futures markets. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 645–664, 1999     

PORTFOLIO OPTIMIZATION AND STOCHASTIC VOLATILITY ASYMPTOTICS

We study the Merton portfolio optimization problem in the presence of stochastic volatility using asymptotic approximations when the volatility process is characterized by its timescales of fluctuation. This approach is tractable because it treats the incomplete markets problem as a perturbation around the complete market constant volatility problem for the value function, which is well understood. When volatility is fast mean‐reverting, this is a singular perturbation problem for a nonlinear Hamilton–Jacobi–Bellman partial differential equation, while when volatility is slowly varying, it is a regular perturbation. These analyses can be combined for multifactor multiscale stochastic volatility models. The asymptotics shares remarkable similarities with the linear option pricing problem, which follows from some new properties of the Merton risk tolerance function. We give examples in the family of mixture of power utilities and also use our asymptotic analysis to suggest a “practical” strategy that does not require tracking the fast‐moving volatility. In this paper, we present formal derivations of asymptotic approximations, and we provide a convergence proof in the case of power utility and single‐factor stochastic volatility. We assess our approximation in a particular case where there is an explicit solution.     

The volatility effect in emerging markets

We examine the empirical relation between risk and return in emerging equity markets and find that this relation is flat, or even negative. This is inconsistent with theoretical models such as the CAPM, which predict a positive relation, but consistent with the results of studies for developed equity markets. The volatility effect appears to be growing stronger over time, which we argue might be related to the increased delegated portfolio management in emerging markets. Finally, we find that the volatility effect in emerging markets is only weakly related to that in developed equity markets, which argues against a common-factor explanation.     

MAXIMIZING THE GROWTH RATE UNDER RISK CONSTRAINTS

We investigate the ergodic problem of growth-rate maximization under a class of risk constraints in the context of incomplete, Itô-process models of financial markets with random ergodic coefficients. Including value-at-risk , tail-value-at-risk , and limited expected loss , these constraints can be both wealth-dependent (relative) and wealth-independent (absolute). The optimal policy is shown to exist in an appropriate admissibility class, and can be obtained explicitly by uniform, state-dependent scaling down of the unconstrained (Merton) optimal portfolio. This implies that the risk-constrained wealth-growth optimizer locally behaves like a constant relative risk aversion (CRRA) investor, with the relative risk-aversion coefficient depending on the current values of the market coefficients.     

On the Existence of Linear Equilibria in Models of Market Making

We derive necessary and sufficient conditions for a linear equilibrium in three types of competitive market making models: Kyle type models (when market makers only observe aggregate net order flow), Glosten–Milgrom and Easley–O'Hara type models (when market makers observe and trade one order at a time), and call markets models (individual order models when market makers observe a number of orders before pricing and executing any of them). We study two cases: when privately informed (strategic) traders are symmetrically informed and when they have differential information. We derive necessary and sufficient conditions on the distributions of the random variables for a linear equilibrium. We also explore those features of the equilibrium that depend on linearity as opposed to the particular distributional assumptions and we provide a large number of examples of linear equilibria for each of the models.     

Early warning indicators of asset price boom/bust cycles in emerging markets

We apply recently developed early warning indicator systems to a cross-section of emerging markets. We find that, with little or no modification, models designed to predict asset price booms/busts in advanced countries may be useful for emerging markets. The concept of monitoring a set of asset prices, real activity and financial indicators is generally found to be efficacious. We also find that, in addition to this set of variables, early warning indicator systems for emerging countries may be augmented with capital flow indicators.     

Toward A Convergence Theory For Continuous Stochastic Securities Market Models1

This article reviews some recently developed approximation schemes for financial markets with continuous trading. Two methods for approximating continuous-time stochastic securities market models whose exogenously given prices have continuous sample paths are described and compared One method approximates both the paths and the information structure; the other is an approximation in distribution with a Markovian structure. In both cases, the approximating models have a finite state space, discrete time, and possess the same “structural” properties (e.g., “no arbitrage” and “completeness”) as the continuous model. the latter characteristic is an important criterion for judging the merits of the approximations. Taking advantage of the “structure-preserving” characteristic, one can formulate a convergence theory for frictionless markets with continuous trading. the theory provides convergence results for objects such as contingent claim prices, replicating portfolio strategies (hedging policies), optimal consumption policies, and cumulative financial gains (i.e., stochastic integrals), which are constructed along the approximation. the convergence theory enables one to combine the intuitive appeal of discrete models and the analytic tractability of continuous models to provide new insight into the theory of modern financial markets. We survey the current state of such a convergence theory and illustrate the results with some examples of well-known continuous securities market models.     

A systems perspective on markets – Toward a research agenda

This paper addresses the implications of an emerging, increasingly important way of thinking about markets: systems thinking. A market is one of the most founational abstractions in marketing and business research; yet, it often receives too little attention. As a result, the taken-for-granted assumptions about markets spur from over-simplified conceptualizations of neoclassical economics that depict markets as static and mechanistic. Systems thinking represents a major change in perspective that involves transcending this mechanistic worldview and thinking instead in terms of wholes, relationships, processes, and patterns. We argue that building a theory of markets based on systems thinking, would enable scholars to develop more realistic models that correspond with fast-changing business environment and therefore, increase both the rigor and relevance of future research. To further this aim, we identify the main implications of systems thinking and formulate them into a research agenda to further the systemic understanding of markets.     

Market Development Determinants for Corporate Bonds in National Currencies: Emerging Markets Review

Our paper offers analysis of tendencies and determinants of development of local currency corporate bond markets in the period from 2006 to 2015. We consider a wide range of macroeconomic and institutional factors for 15 bond markets. The sample consists of 600 country-quarter observations. Multifactor linear regression models and the generalized method of moments are applied for the balanced panel data. Our analyses reveals that inflation and its stability, exchange rate, and market capitalization have a significant influence on the share of local currency bonds. Financial and macroeconomic instability stimulates the growth of local currency bond markets.