Imperfectly credible disinflation under endogenous time-dependent pricing

The real effects of an imperfectly credible disinflation depend critically on the extent of price rigidity. Therefore, the study of how policymakers’ credibility affects the outcome of an announced disinflation should not be dissociated from the analysis of the determinants of the frequency of price adjustments. In this paper we examine how the policymaker’s credibility affects the outcome of an announced disinflation in a model with endogenous time-dependent pricing rules. Both the initial degree of price ridigity, calculated optimally, and, more notably, the changes in contract length during disinflation play an important role in the explanation of the effects of imperfect credibility. We initially evalute the costs of disinflation in a setup where credibility is exogenous, and then allow agents to update beliefs about the “type” of monetary authority that they face. We show that, in both cases, the interaction between the endogeneity of time-dependent rules and imperfect credibility increases the output costs of disinflation.

Information asymmetry and competition in credit markets: the pricing of overdraft loans in Brazil

This paper evaluates how information asymmetry affects the strength of competition in credit markets. A theory is presented in which adverse selection softens competition by decreasing the incentives creditors have for competing in the interest rate dimension. In equilibirum, although creditors compete, the outcome is similar to collusion. Three empirical implications arise. First, interest rate should respond asymmetrically to changes in the cost of funds: increases in cost of funds should, on average, have a larger effect on interest rates than decreases. Second, aggressiveness in pricing should be associated with a worseing in the bank level default rates. Third, bank level default rates should be endogenous. We then verify the validity of these three empirical implications using Brazilian data on consumer overdraft loans. The results in this paper rationalize seemingly abnormallly high interest rates in unsecured loans.

Existence of nash equilibrium in competitive nonlinear pricing games with adverse selection

We show that for a large class of competitive nonlinear pricing games with adverse selection, the property of better-reply security is naturally satisfied - thus, resolving via a result due to Reny (1999) the issue of existence of Nash equilibrium for a large class of competitive nonlinear pricing games.

Determinants of differential pricing of equity classes in the Brazilian equity market

We examine the differential pricing of equity classes between voting and non-voting shares in Brazilian listed companies with particular emphasis on privatized companies, and we discuss the role of majority control, liquidity, and governance issues that may influence these differentials over time. We include a brief discussion on the Brazilian corporate law system, its impact on controlling and minority shareholders, and the characteristics of the Brazilian privatization process, before proceeding to the econometric analysis. We find empirical evidence to support that liquidity is a major component for determining this differential pricing over time. Other variables, such as the ratio of non-voting equity to total equity, type of majority control, and changes in regulation signal the high level of agency costs between majority controllers and minority shareholders in explaining the differential pricing of equity classes.

Nonlinear pricing beyond the demand profile approach

Wilson [16] introduced a general methodology to deal with monopolistic pricing in situations where customers have private information on their tastes (‘types’). It is based on the demand profile of customers: For each nonlinear tariff by the monopolist the demand at a given level of product (or quality) is the measure of customers’ types whose marginal utility is at least the marginal tariff (‘price’). When the customers’ marginal utility has a natural ordering (i.e., the Spence and Mirrlees Condition), such demand profile is very easy to perform. In this paper we will present a particular model with one-dimensional type where the Spence and Mirrlees condition (SMC) fails and the demand profile approach results in a suboptimal solution for the monopolist. Moreover, we will suggest a generalization of the demand profile procedure that improves the monopolist’s profit when the SMC does not hold.

Time-dependent or state-dependent pricing? Evidence from a large devaluation episode

State-dependent and time-dependent price setting models yield distinct implications for how frequency and magnitude of price changes react to shocks. This note studies pricing behavior in Brazil following the large devaluation of the Brazilian Real in 1999 to distinguish between models. The results are consistent with state-dependent pricing

Time-dependent or state-dependent pricing? Evidence from firms’ response to inflation shocks

This paper proposes a test for distinguishing between time-dependent and state-dependent pricing based on whether the timing of pricing changes is affected by realized or expeted inflation. Using Brazilian data and exploring a large discrepancy between realized and expected inflation in 2002-3, we obtain a strong relation between expected inflation and duration of price spells, but little effect of inflation shocks on the frequency of price adjustment. The results thus support models with timedependent pricing, where the timing for following changes is optimally chosen whenever firms adjust prices

Pricing the cost of an election: the impact of the 2014 elections on stock markets

Qual o efeito de eleições em ativos reais? É possível mensurar diretamente a diferença de preços mesmo que só possamos enxergar um dos resultados potenciais? Essa dissertação estima esses efeitos utilizando metodologia baseada em opções sobre ações. O modelo aqui desenvolvido adaptção tradicional Black-Scholes para incorporar dois novos parâmetros: um salto no preço do ativo perfeitamente antecipado e uma série de probabilidades diárias refletindo as crenças sobre quem venceria a corrida eleitoral. Aplicamos esse método para o caso brasileiro das Eleições Presidenciais de 2014 e a Petrobras - uma importante companhia do setor petrolífero do país -utilizando dados de bolsa do segundo turno das eleições. Os resultados encontrados mostram uma diferença de 65-77% para o valor da companhia, dependendo de quem vencesse nas urnas. Isso é equivalente a aproximadamente 2.5% do PIB de 2014 do país.

Testing option pricing with the Edgeworth expansion

There is a well-developed framework, the Black-Scholes theory, for the pricing of contracts based on the future prices of certain assets, called options. This theory assumes that the probability distribution of the returns of the underlying asset is a Gaussian distribution. However, it is observed in the market that this hypothesis is flawed, leading to the introduction of a fudge factor, the so-called volatility smile. Therefore, it would be interesting to explore extensions of the Black-Scholes theory to non-Gaussian distributions. In this paper, we provide an explicit formula for the price of an option when the distributions of the returns of the underlying asset is parametrized by an Edgeworth expansion, which allows for the introduction of higher independent moments of the probability distribution, namely skewness and kurtosis. We test our formula with options in the Brazilian and American markets, showing that the volatility smile can be reduced. We also check whether our approach leads to more efficient hedging strategies of these instruments. (C) 2004 Elsevier B.V. All rights reserved.

Optimal Contract Pricing of Distributed Generation in Distribution Networks

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Location and contract pricing of distributed generation using a genetic algorithm

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Optimal contract pricing of distributed generation under a competitive framework

A bilevel programming approach for the optimal contract pricing of distributed generation (DG) in distribution networks is presented. The outer optimization problem corresponds to the owner of the DG who must decide the contract price that would maximize his profits. The inner optimization problem corresponds to the distribution company (DisCo), which procures the minimization of the payments incurred in attending the expected demand while satisfying network constraints. The meet the expected demand the DisCo can purchase energy either form the transmission network through the substations or form the DG units within its network. The inner optimization problem is substituted by its Karush- Kuhn-Tucker optimality conditions, turning the bilevel programming problem into an equivalent single-level nonlinear programming problem which is solved using commercially available software. © 2010 IEEE.

Reactive power support pricing of distributed generators with primary energy source uncertainty

In this paper, a novel methodology to price the reactive power support ancillary service of Distributed Generators (DGs) with primary energy source uncertainty is shown. The proposed methodology provides the service pricing based on the Loss of Opportunity Costs (LOC) calculation. An algorithm is proposed to reduce the uncertainty present in these generators using Multiobjective Power Flows (MOPFs) implemented in multiple probabilistic scenarios through Monte Carlo Simulations (MCS), and modeling the time series associated with the generation of active power from DGs through Markov Chains (MC). © 2011 IEEE.

Pricing of reactive power support provided by distributed generators in transmission systems

Distributed Generation, microgrid technologies, two-way communication systems, and demand response programs are issues that are being studied in recent years within the concept of smart grids. At some level of enough penetration, the Distributed Generators (DGs) can provide benefits for sub-transmission and transmission systems through the so-called ancillary services. This work is focused on the ancillary service of reactive power support provided by DGs, specifically Wind Turbine Generators (WTGs), with high level of impact on transmission systems. The main objective of this work is to propose an optimization methodology to price this service by determining the costs in which a DG incurs when it loses sales opportunity of active power, i.e, by determining the Loss of Opportunity Costs (LOC). LOC occur when more reactive power is required than available, and the active power generation has to be reduced in order to increase the reactive power capacity. In the optimization process, three objectives are considered: active power generation costs of DGs, voltage stability margin of the system, and losses in the lines of the network. Uncertainties of WTGs are reduced solving multi-objective optimal power flows in multiple probabilistic scenarios constructed by Monte Carlo simulations, and modeling the time series associated with the active power generation of each WTG via Fuzzy Logic and Markov Chains. The proposed methodology was tested using the IEEE 14 bus test system with two WTGs installed. © 2011 IEEE.