Local Polynomial Kernel Forecasts and Management of Price Risks using Futures Markets

This study contributes to understanding price risk management through hedging strategies in a forecasting context. A relatively new forecasting method, nonparametric local polynomial kernel (LPK), is used and applied to the hog sector. The selective multiproduct hedge based on the LPK price and hedge ratio forecasts is, in general, found to be better than continuous hedge and alternative forecasting procedures in terms of reduction of variance of unhedged return. The findings indicate that combining hedging with forecasts, especially when using the LPK technique, can potentially improve price risk management.Marketing,

NONPARAMETRIC KERNEL ESTIMATION OF MULTIPLE HEDGE RATIOS

It is possible for the traditional hedge ratio estimation to produce erroneous guidance to risk managers because of the restrictive assumptions. This study adopts nonparametric locally polynomial kernel estimation to exclude the assumptions. Results from the hog complex find that hedge ratios estimated by local polynomial kernel regression outperform naïve and GARCH models. Because of the potential assumption violations associated with the estimation and implementation of hedge ratios by GARCH models, LPK is a reasonable alternative for estimating hedge ratios to manage price risks.Marketing, Research Methods/ Statistical Methods, Risk and Uncertainty,

Identifying behaviour in a multiproduct oligopoly: Incumbents reaction to tariffs dismantling

The Spanish automobile market of the nineties experienced a perfectly foreseeable tariff dismantling and a strong demand downturn, with the observed result of an apparently sharpened producer competition in products and perhaps in prices. This paper is aimed at testing whether or not there really was a change in pricing behaviour, using a structural model of competition. To answer that question, we specify, estimate and test semiparametric pricing equations with panel data for 164 models belonging to the 31 firms which competed in the market. The specification includes several equilibriums as alternative estimating models, considering prominently tacit coalitions by which a group of firms sets prices, taking into account the cross effects on their demands. The statistical test selects as the best model given the data an unbroken coalition of domestic and European producers. Comparative results using tight demand side specifications show that an inadequate specification of the demand side may induce wrong inferences.behaviour; tariffs; oligopoly; coalition;

Identifying Demand with Multidimensional Unobservables: A Random Functions Approach

We explore the identification of nonseparable models without relying on the property that the model can be inverted in the econometric unobservables. In particular, we allow for infinite dimensional unobservables. In the context of a demand system, this allows each product to have multiple unobservables. We identify the distribution of demand both unconditional and conditional on market observables, which allows us to identify several quantities of economic interest such as the (conditional and unconditional) distributions of elasticities and the distribution of price effects following a merger. Our approach is based on a significant generalization of the linear in random coefficients model that only restricts the random functions to be analytic in the endogenous variables, which is satisfied by several standard demand models used in practice. We assume an (unknown) countable support for the the distribution of the infinite dimensional unobservables.

Near-Optimal Bisection Search for Nonparametric Dynamic Pricing with Inventory Constraint

We consider a single-product revenue management problem with an inventory constraint and unknown, noisy, demand function. The objective of the fi rm is to dynamically adjust the prices to maximize total expected revenue. We restrict our scope to the nonparametric approach where we only assume some common regularity conditions on the demand function instead of a speci fic functional form. We propose a family of pricing heuristics that successfully balance the tradeo ff between exploration and exploitation. The idea is to generalize the classic bisection search method to a problem that is a ffected both by stochastic noise and an inventory constraint. Our algorithm extends the bisection method to produce a sequence of pricing intervals that converge to the optimal static price with high probability. Using regret (the revenue loss compared to the deterministic pricing problem for a clairvoyant) as the performance metric, we show that one of our heuristics exactly matches the theoretical asymptotic lower bound that has been previously shown to hold for any feasible pricing heuristic. Although the results are presented in the context of revenue management problems, our analysis of the bisection technique for stochastic optimization with learning can be potentially applied to other application areas.http://deepblue.lib.umich.edu/bitstream/2027.42/108717/1/1252_Sinha.pd

SCALE ECONOMIES AND EFFICIENCIES FOR CHINESE RURAL CREDIT COOPERATIVES

This paper evaluates scale economies and efficiencies for Rural Credit Cooperatives (RCCs) in China using both parametric and nonparametric techniques. Diseconomies of scale and allocative inefficiency are found. The results reveal the need for RCCs to decrease their size and the need for government to liberalize the financial market.Agribusiness,

Collusion, competition and piracy

In this paper we analyze firms' ability to tacitly collude on pricesin an infinitely repeated duopoly game of vertical productdifferentiation. We show that firms collude if and only if their discountfactor is high enough, i.e. if they value future profits sufficiently. We alsoshow that a lower cost of copying facilitates collusion but that a higherquality of the copy hinders collusion. Thus, the overall effect of thesenew characteristics of copies made by consumers is ambiguous.Collusion, competition, piracy, consumers, cost of copying,

Static Pricing Problems under Mixed Multinomial Logit Demand

Price differentiation is a common strategy for many transport operators. In this paper, we study a static multiproduct price optimization problem with demand given by a continuous mixed multinomial logit model. To solve this new problem, we design an efficient iterative optimization algorithm that asymptotically converges to the optimal solution. To this end, a linear optimization (LO) problem is formulated, based on the trust-region approach, to find a "good" feasible solution and approximate the problem from below. Another LO problem is designed using piecewise linear relaxations to approximate the optimization problem from above. Then, we develop a new branching method to tighten the optimality gap. Numerical experiments show the effectiveness of our method on a published, non-trivial, parking choice model