Linear Pricing Research Articles

Fisheries management through optimal sustainable policies with constant effort in random environments

Event Abstract Back to Event Fisheries management through optimal sustainable policies with constant effort in random environments Nuno M. Brites1* and Carlos A. Braumann1, 2 1 Centro de Investigação em Matemática e Aplicalções, Instituto de Investigação e Formação Avançada, Universidade de Évora, Portugal 2 Departamento de Matemática, Universidade de Évora, Portugal To describe the growth of a harvested population when the environment is subjected to random fluctuations one can use Stochastic Differential Equation models. We consider logistic and Gompertz models for the average natural growth to which we subtract a harvesting yield term based on a constant or variable fishing effort. There is previous work on the optimal design of the harvesting policy with the purpose of maximizing the expected accumulated profit (discounted by a depreciation rate) over a finite time horizon. We consider a quite general profit structure which includes linear prices per unit yield and linear costs per unit effort. The harvesting efforts of the optimal policies vary with the randomly varying population size and such policies can, under certain conditions, even be of bang-bang type. These policies are not applicable to harvesting since they need to constantly evaluate population size and require very frequent randomly determined changes in harvesting effort. Our approach, based on sustainable and applicable fishing policies, leads to sustainability of the population and to a stationary distribution of the population size and do not require evaluation of population size. We determine the constant harvesting effort policy that optimizes the expected sustainable profit per unit time and check what we lose profitwise by using this policy instead of the optimal inapplicable policy with variable effort. Using Monte Carlo simulations, we show that, for common situations, our approach is almost as profitable as the first. Acknowledgements Nuno M. Brites and Carlos A. Braumann belong to the Centro de Investigação em Matemática e Aplicações, Universidade de Évora, a research centre supported by FCT (Fundação para a Ciência e a Tecnologia, Portugal). The first author holds a PhD grant from FCT (ref. SFRH/BD/85096/2012). Keywords: Fishing effort, optimal sustainable policy, logistic model, Gompertz model, stochastic differential equations Conference: IMMR | International Meeting on Marine Research 2016, Peniche, Portugal, 14 Jul - 15 Jul, 2016. Presentation Type: Oral presentation Topic: Fisheries and Management Citation: Brites NM and Braumann CA (2016). Fisheries management through optimal sustainable policies with constant effort in random environments. Front. Mar. Sci. Conference Abstract: IMMR | International Meeting on Marine Research 2016. doi: 10.3389/conf.FMARS.2016.04.00113 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 14 Apr 2016; Published Online: 13 Jul 2016. * Correspondence: Dr. Nuno M Brites, Centro de Investigação em Matemática e Aplicalções, Instituto de Investigação e Formação Avançada, Universidade de Évora, Évora, Évora, 7000-671, Portugal, brites@uevora.pt Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Nuno M Brites Carlos A Braumann Google Nuno M Brites Carlos A Braumann Google Scholar Nuno M Brites Carlos A Braumann PubMed Nuno M Brites Carlos A Braumann Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

随机区间收益金融市场的无强占优分析

文章提出了具有随机区间收益的金融市场，在该市场中，证券价格被描述为区间值随机变量，并将研究的金融市场所在的概率空间框架从有限维拓展为一般概率空间，是传统随机市场的推广。在此模型中，提出了强占优策略和线性定价测度的概念，证明了市场无强占优与存在线性定价测度等价的定理，并且研究了随机区间收益市场无强占优与经典市场无占优的关系。该结论既包含经典随机金融市场的结论，又将金融分析推广到随机区间收益金融市场中。 In this article, a new financial market model, in which all securities have random interval pay- offs, is proposed. In the market, the probability space from finite dimensional expands general probability space. Some concepts, such as robust dominant strategy and linear pricing measures, are given and discussed parallel to those in traditional market analysis. With these new concepts, it is discussed that the requirement of no robust dominant strategy is equivalent to the existence of linear pricing measures and the relations between the analysis of the no robust dominant strategy in the market with random interval payoffs and it’s in traditional market. This conclusion includes the traditional random market analysis conclusions, extending to this new financial market.

Optimal Nonlinear Pricing in Social Networks under Asymmetric Network Information

We study the optimal nonlinear pricing of products and services in social networks, where customers are strategic and their consumption exhibits local externality. The stochastic network formation process generates both network uncertainty and information asymmetry: customers know about their local network characteristics but the selling firm only has knowledge of global network. The firm may adopt nonlinear pricing to serve customers with heterogeneous and unobservable network positions. The firm’s profit maximization resembles a principal-agent problem, complicated with the externalities in agents’ payoffs.We develop a novel solution approach using calculus of variations to tackle this non-standard principal-agent problem. We show that the optimal pricing scheme involves either a quantity premium or quantity discount, which is in strict contrast with the linear pricing case. Applying our results to the random graph (a special case of the social network model we use), we find that the pricing scheme should not discriminate by network positions; consequently, the firm can offer a simple uniform price.

Three-echelon supply chain with centralised and decentralised inventory decisions under linear price dependent demand

In the current global business environment, the competition is between the supply chains, but not among echelons of the chain. Hence, it is highly essential to bring down the cost of the supply chain rather than reducing the costs of individual echelons independently. This work focuses on modelling and optimisation of a coordinated and non-coordinated three-echelon supply chain with the consideration of ordering/setup costs, transportation and carrying costs. The objective of the present work is to demonstrate the optimality of inventory replenishment decisions, shipment frequencies and the annual total relevant costs under linear price dependent demand. Numerical illustration is carried out to find out the optimal values of objective function and decision variables. Also, the parametric analysis is carried out to show the influence of model parameters.

Non-Affine GARCH Option Pricing Models, Variance Dependent Kernels, and Diffusion Limits

This paper investigates the pricing and weak convergence of an asymmetric non-affine, non-Gaussian GARCH model when the risk-neutralization is based on a variance dependent exponential linear pricing kernel with stochastic risk aversion parameters. The risk-neutral dynamics are obtained for a general setting and its weak limit is derived. We show how several GARCH diffusions, martingalized via well-known pricing kernels, are obtained as special cases and we derive necessary and sufficient conditions for the presence of financial bubbles. An extensive empirical analysis using both historical returns and options data illustrates the advantage of coupling this pricing kernel with non-Gaussian innovations.

Impact of Oil Price Shocks on the Sri Lankan Economy: A Vector Auto Regression Assessment

Oil price shocks have the potential to slow down the economic growth and create inflationary pressures in oil importing small economies. A vector auto regression (VAR) model, augmented by Toda and Yamamoto procedure, was estimated using monthly data from 2000-2013 to examine the impacts of oil price shocks on Sri Lankan economy. The results indicate that linear oil price shocks affect GDP, foreign reserves and interest rate. Positive oil price shocks affect foreign reserves and the interest rate, while negative oil price shocks affect GDP, interest rates and exports. Oil price decreases have larger and quicker impacts on GDP. Thus, there is evidence for presence of asymmetric oil price impacts in Sri Lankan economy. No evidence to show that oil price shocks cause inflation. As such, the government has the ability to employ expansionary monetary policy to avoid stagflation during high oil price periods. Overall, the results indicate that the economy has a certain degree of insulation from international oil price increases. In addition, energy policy has also contributed to insulate the economy from oil price shocks through reduction in energy intensity. Sri Lankan Journal of Agricultural Economics Vol. (16) No. 1 (2014) pp. 1-33

Testing Alternative Multi-Factor Models

A GMM-based system for two different linear factor pricing models is used to test if the pricing errors are the same. Simulations demonstrate the small sample properties. As an illustration, the test is applied to the Fama-French (1996, 2015) models.

Welfare Effects of Water Pricing in Germany

The observed two-part tariff price structure (consisting of a lump-sum price and linear marginal price) for drinking water in Germany does not reflect the cost structure reported in the literature. Recovering marginal costs from a sample of 251 German counties, we see that there are positive price-cost margins, while lump-sum prices are too low. A price structure readjustment along welfare economic principles (marginal cost pricing, lump-sum price ensures cost-recovery) would increase the mean consumer surplus by 0.037% of the local GDP or €[Formula: see text]2.129 million per county, assuming a share of 15% variable costs in total costs.

First Degree Price Discrimination Goes to School

Personalized pricing is widely discussed but seldom observed, making studies of its efficacy rare. Yet, first degree price discrimination is common in the pricing of higher education, and I use data on prices and the characteristics of students admitted to a professional graduate program at a public university to estimate a matriculation demand function. I then derive linear pricing functions that maximize revenue for a target number of students. By allowing these functions to depend on progressively richer sets of observables, I explore the effect of personalization of pricing on profit. Tailoring prices to a one‐dimensional measure of student quality would raise revenue by 2.2 per cent above the revenue with uniform pricing. Pricing based on both student quality and state residency raises revenue by 8.4 per cent, and further tailoring based on available observables raises prices 9.0 per cent above the maximum revenue under uniform pricing. Pricing that obeys current statutory tuition limits raises revenue less but still by just over half as much. I also infer the welfare weights that the pricing process implicitly attaches to student characteristics.

Half-size me? How calorie and price information influence ordering on restaurant menus with both half and full entrée portion sizes

Many restaurants are increasingly required to display calorie information on their menus. We present a study examining how consumers' food choices are affected by the presence of calorie information on restaurant menus. However, unlike prior research on this topic, we focus on the effect of calorie information on food choices made from a menu that contains both full size portions and half size portions of entrées. This different focus is important because many restaurants increasingly provide more than one portion size option per entrée. Additionally, we examine whether the impact of calorie information differs depending on whether full portions are cheaper per unit than half portions (non-linear pricing) or whether they have a similar per unit price (linear pricing). We find that when linear pricing is used, calorie information leads people to order fewer calories. This decrease occurs as people switch from unhealthy full sized portions to healthy full sized portions, not to unhealthy half sized portions. In contrast, when non-linear pricing is used, calorie information has no impact on calories selected. Considering the impact of calorie information on consumers’ choices from menus with more than one entrée portion size option is increasingly important given restaurant and legislative trends, and the present research demonstrates that calorie information and pricing scheme may interact to affect choices from such menus.

Dynamic optimal execution in a mixed-market-impact Hawkes price model

We study a linear price impact model, including other liquidity takers, whose flow of orders is driven by a Hawkes process. The optimal execution problem is solved explicitly in this context, and the closed-form optimal strategy describes in particular how one should react to the orders of other traders. This result enables us to discuss the viability of the market. It is shown that Poissonian arrivals of orders lead to quite robust price manipulation strategies in the sense of Huberman and Stanzl (Econometrica, 72:1247–1275, 2004). Instead, a particular set of conditions on the Hawkes model balances the self-excitation of the order flow with the resilience of the price, excludes price manipulation strategies, and gives some market stability.

Demand Response Management in Smart Grids With Heterogeneous Consumer Preferences

Consumer demand profiles and fluctuating renewable power generation are two main sources of uncertainty in matching demand and supply. This paper proposes a model of the electricity market that captures the uncertainties on both the operator and user sides. The system operator (SO) implements a temporal linear pricing strategy that depends on real-time demand and renewable generation in the considered period combining real-time pricing with time-of-use pricing. The announced pricing strategy sets up a noncooperative game of incomplete information among the users with heterogeneous, but correlated consumption preferences. An explicit characterization of the optimal user behavior using the Bayesian Nash equilibrium solution concept is derived. This explicit characterization allows the SO to derive pricing policies that influence demand to serve practical objectives, such as minimizing peak-to-average ratio or attaining a desired rate of return. Numerical experiments show that the pricing policies yield close to optimal welfare values while improving these practical objectives.

Setting prices in mixed logit model designs

We investigate different procedures to set prices in designs for choice-based conjoint analysis using the mixed logit model which captures latent consumer heterogeneity. Besides discrete attributes, we include a linear price term in the deterministic utility function thereby treating price as continuous variable. We consider two different price intervals and several price sets which contain either two or three prices. We compare these alternatives to set prices by simulating choices for different constellations on the basis of the mixed logit model. Furthermore, we generate ten designs simultaneously instead of just one. Using these simulated choices, we estimate the parameters of the mixed logit model in the next step. To reduce the needed sample size and computation time caused by accounting for latent consumer heterogeneity, we apply Halton draws and set a minimum potential design for prior draws. ANOVA with root mean squared error between estimated and true price coefficient values of individual consumers as dependent variable shows that using more extreme prices as interval bounds and one intermediate price positioned to the right of the interval performs best.

Offloading in Software Defined Network at Edge with Information Asymmetry: A Contract Theoretical Approach

The proliferation of highly capable mobile devices such as smartphones and tablets has significantly increased the demand for wireless access. Software defined network (SDN) at edge is viewed as one promising technology to simplify the traffic offloading process for current wireless networks. In this paper, we investigate the incentive problem in SDN-at-edge of how to motivate a third party access points (APs) such as WiFi and smallcells to offload traffic for the central base stations (BSs). The APs will only admit the traffic from the BS under the precondition that their own traffic demand is satisfied. Under the information asymmetry that the APs know more about own traffic demands, the BS needs to distribute the payment in accordance with the APs' idle capacity to maintain a compatible incentive. First, we apply a contract-theoretic approach to model and analyze the service trading between the BS and APs. Furthermore, other two incentive mechanisms: optimal discrimination contract and linear pricing contract are introduced to serve as the comparisons of the anti adverse selection contract. Finally, the simulation results show that the contract can effectively incentivize APs' participation and offload the cellular network traffic. Furthermore, the anti adverse selection contract achieves the optimal outcome under the information asymmetry scenario.

Market Proxies as Factors in Linear Asset Pricing Models: Still Living with the Roll Critique (Extended Version)

A new model misspecification measure for linear asset pricing models is proposed. The origins of this measure are in Shanken (1987) and Kandel and Stambaugh (1985, 1995), where it is argued that the true market return is inherently latent and, as a consequence, only ever partially observed. Tests of asset pricing models that rely on the market return as a risk factor and are based, by necessity, on an observable proxy to this factor are then misspecified. The proposed misspecification measure, which assigns an upper bound to the correlation between the true market return and the observable proxy return used to conduct the test, can be estimated entirely and directly from observable data. This measure is suited both for testing models that include the market return as a pricing factor in a traditional sense (i.e., determining whether the given model does or does not price a collection of risky assets) and ranking those models (i.e., gauging which model performs the best). The measure is used to price portfolios reflecting the size, value, and momentum premiums. While neither the conditional CAPM nor the ICAPM is shown to offer any improvement over the simple CAPM, all three models are shown to perform materially better under the proposed measure, with improvements in model fit of as much as 45%. Also, it is discovered that winner stocks in a momentum portfolio may have higher market betas than loser stocks.

Back to Fundamentals: Equilibrium in Abstract Economies

We propose a new abstract definition of equilibrium in the spirit of competitive equilibrium: a profile of alternatives and a public ordering (expressing prestige, price, or a social norm) such that each agent prefers his assigned alternative to all lower-ranked ones. The equilibrium operates in an abstract setting built upon a concept of convexity borrowed from convex geometry. We apply the concept to a variety of convex economies and relate it to Pareto optimality. The “magic” of linear equilibrium prices is put into perspective by establishing an analogy between linear functions in the standard convexity and “primitive orderings” in the abstract convexity. (JEL I11, I18, J44, K13)

Cost-efficient contingent claims with market frictions

In complete frictionless securities markets under uncertainty, it is well-known that in the absence of arbitrage opportunities, there exists a unique linear positive pricing rule, which induces a state-price density (e.g., Harrison and Kreps (1979)). Dybvig (1988) showed that the cheapest way to acquire a certain distribution of a consumption bundle (or security) is when this bundle is anti-comonotonic with the state-price density, i.e., arranged in reverse order of the state-price density. In this paper, we look at extending Dybvig's ideas to complete markets with imperfections represented by a nonlinear pricing rule (e.g., due to bid-ask spreads). We consider an investor in a securities market where the pricing rule is "law-invariant" with respect to a capacity (e.g., Choquet pricing as in Araujo et al. (2011), Chateauneuf et al. (1996), Chateauneuf and Cornet (2015), or Cerreia-Vioglio et al. (2015)). The investor holds a security with a random payoff X and his problem is that of buying the cheapest contingent claim Y on X, subject to some constraints on the performance of the contingent claim and on its level of risk exposure. The cheapest such claim is called "cost-efficient". If the capacity satisfies standard continuity and a property called "strong diffuseness" introduced in Ghossoub (2015), we show the existence and monotonicity of cost-efficient claims, in the sense that a cost-efficient claim is anti-comonotonic with the underlying security's payoff X. Strong diffuseness is satisfied by a large collection of capacities, including all distortions of diffuse probability measures. As an illustration, we consider the case of a Choquet pricing functional with respect to a capacity and the case of a Choquet pricing functional with respect to a distorted probability measure. Finally, we consider a simple example in which we derive an explicit analytical form for a cost-efficient claim.

Simple Forecasting Heuristics that Make Us Smart: Evidence from Different Market Experiments

We study a model in which individual agents use simple linear first order price forecasting rules, adapting them to the complex evolving market environment with a smart Genetic Algorithm optimization procedure. The novelties are: (1) a parsimonious experimental foundation of individual forecasting behaviour; (2) an explanation of individual and aggregate behavior in four different experimental settings, (3) improved one-period and 50-period ahead forecasting of lab experiments, and (4) a characterization of the mean, median and empirical distribution of forecasting heuristics. The median of the distribution of GA forecasting heuristics can be used in designing or validating simple Heuristic Switching Model.

An optimal trading problem in intraday electricity markets

We consider the problem of optimal trading for a power producer in the context of intraday electricity markets. The aim is to minimize the imbalance cost induced by the random residual demand in electricity, i.e. the consumption from the clients minus the production from renewable energy. For a simple linear price impact model and a quadratic criterion, we explicitly obtain approximate optimal strategies in the intraday market and thermal power generation, and exhibit some remarkable properties of the trading rate. Furthermore, we study the case when there are jumps on the demand forecast and on the intraday price, typically due to error in the prediction of wind power generation. Finally, we solve the problem when taking into account delay constraints in thermal power production.

TRADING WITH SMALL PRICE IMPACT

An investor trades a safe and several risky assets with linear price impact to maximize expected utility from terminal wealth. In the limit for small impact costs, we explicitly determine the optimal policy and welfare, in a general Markovian setting allowing for stochastic market, cost, and preference parameters. These results shed light on the general structure of the problem at hand, and also unveil close connections to optimal execution problems and to other market frictions such as proportional and fixed transaction costs.