The sentiment pricing dynamics with short-term and long-term learning

Combining the behavioral characteristics of rational uninformed investors with learning information behavior of sentiment investors, this paper establishes a mathematical model about the impact of learning information behavior on the investor's transaction and asset equilibrium price under asymmetric information. Research shows that when rational uninformed investors learn information in the short term, on the one hand, they choose to bet against sentiment investors, thus reducing the influence of sentiment; on the other hand, they occasionally mistake sentiment for information to chase sentiment investors, then amplifying sentiment shocks. Furthermore, sentiment investors can also gain valuable information indirectly by observing the price in the long term. When sentiment investors learn information in the long term, the price fluctuations caused by sentiment and information, informativeness of the price system and market efficiency are no longer dependent on the quality of information.     

Self-organization and the persistence of noise in financial markets

A dynamic model of financial markets with learning is demonstrated to produce a self-organized system that displays critical behavior. The price contains private information that traders learn to extract and employ to forecast future value. Since the price reflects the beliefs of the traders, the learning process is self-referencing. As the market learns to correctly extract information from the price, the market deemphasizes private information. Despite the convergence of the model towards the parameters producing efficiency, pricing deviations remain constant due to the increased sensitivity of the price to small errors in information extraction produced by the model's own convergence.     

Experimental evidence on trading behavior,market efficiency and price formation in double auctions with unknown trading duration

The reasons for the highly efficient market outcomes observed under the double auction remain unclear. This paper presents a series of experimental financial markets designed to investigate the importance of unknown trading period duration on trading behavior and the convergence tendencies of such markets. Using panel data techniques the results support the conclusions that individuals generally display more aggressive trading strategies, trading earlier in a period, and that markets exhibit reduced levels of informational efficiency when unknown duration is present. Markets with imperfect information structures are also studied and, in a unique result, are associated with significantly slower rates of trade, as traders become more cautious over their trading strategies. Investigation of the price formation process provides evidence that the pricing error varies over time and the estimation of a fixed effects model provides unique support that learning effects and unknown trading period duration influence the price formation process. Future refinement of theoretical models of the price formation process or institutions of exchange should recognize the effect of unknown trading period duration on market behavior, along with potential learning effects. Copyright © 2005 John Wiley & Sons, Ltd.     

Wholesale price discrimination: Innovation incentives and upstream competition

In intermediate good markets where there are alternative supply sources, wholesale price discrimination may enhance innovation incentives downstream. We consider a vertical chain where a dominant firm and a competitive fringe supply imperfect substitutes to duopoly retailers which carry both varieties. We show that a ban on price discrimination by the dominant supplier makes uniform pricing credible and reduces retailers’ incentives to decrease the cost of acquiring the competitively supplied variety, leading to higher upstream profits and lower downstream welfare. Our analysis complements existing results by identifying a novel channel through which wholesale price discrimination can improve dynamic market efficiency.     

The influence of seller learning and time constraints on sequential bargaining in an artificial perishable goods market

This paper investigates the formation of prices in a perishable goods market where agents bargain repeatedly through pair-wise interactions. After extensive field observations, we chose to focus on two aspects that seem important to actors of this market: the passage of time and update in judgement when gathering information. The main feature of the market is that a seller bargaining with a buyer has incomplete information about buyer's willingness to pay and is not sure how her trading partner will evaluate an offer or compare it with other options. On the other hand, buyers have limited time to look for goods and cannot meet all possible sellers before making a decision. Hence agents cannot calculate the best price to offer but receive information through limited interactions, and use this information to choose their actions.An agent-based model was built to represent a framework that mimics the observed market institution and where agent's possible behaviors and learning was made as consistent as possible with gathered data. Simulations were run, first for sensitivity analysis concerning main parameters, then to test the dependance of agents’ learning to (a) the time buyers can spend on the market and (b) the frequency of update in learning by sellers. To validate the model, features produced by the simulated market are compared to the stylized facts gathered for negotiation about four goods. We reproduce the main features of the data on the dynamics of offers, transaction prices and agents’ behavior during the bargaining phases.     

Price Discrimination in Input Markets: Downstream Entry and Efficiency

The extant theory on price discrimination in input markets takes the structure of the downstream industry as exogenously given. This paper endogenizes the structure of the downstream industry and examines the effects of permitting third‐degree price discrimination on market structure and welfare. We identify situations where permitting price discrimination leads to either higher or lower wholesale prices for all downstream firms. These findings are driven by upstream profits being discontinuous due to costly entry. Moreover, permitting price discrimination fosters entry which often improves welfare. Nevertheless, entry can also reduce welfare because it may lead to a severe inefficiency in production.     

Chain-Store Pricing Across Local Markets

Chain‐stores now dominate most areas of retailing. While retailers may operate nationally or even internationally, the markets they compete in are largely local. How should they best operate pricing policy in respect of the different markets served—price uniformly across the local markets or on a local basis according to market conditions? We model this by allowing local market differences, with retail markets differing by their size and the number of players present. We show that practising price discrimination is not always best for a chain‐store. Competitive conditions exist under which uniform pricing can raise profits.     

List price and sales prices of residential properties during booms and busts

This paper investigates the relationship between the list and sale price of residential properties over the housing cycle. In down or normal markets the list price generally exceeds the sales price; however, when the housing market is strong, homes sell for more than their list price. This observation is not consistent with the assumptions made in the standard model of home sellers’ search behavior. We consider alternative models. In one, sellers set list prices based on their expectations of future changes in sales prices and the arrival rate of buyers; however, demand shocks occur. This model partially explains our data from the Belfast, U.K. housing market, but it fails to predict the list to sales price ratio during a sustained housing boom. We next describe a model where sellers’ endogenously select their search mechanism depending on the strength of the housing market. We find support for the conjecture that sellers switch to an auction-like model during housing booms. There also is evidence that during a downturn in the market, sellers’ list prices are sticky.     

Common-value auction versus posted-price selling: an agent-based model approach

Previous theoretical work has compared a private-value auction and posted-price market, and an affiliated-value auction and a posted-price market to determine the selling method preferred by sellers. Much less, however, is known about the seller’s preferred selling method when the buyers have a common value of the item. Our objective is to determine if a first-price auction or a posted-price market provides a seller with the larger expected revenue when buyers have a common value of the item being sold. An agent-based posted-price market and an agent-based first-price common-value auction with a reserve price are developed to compare these selling methods. Holding the buyers’ uncertainty about the value of the item constant, the seller prefers the posted-price market when the seller has no uncertainty about the item’s value. When the seller has an equal level of uncertainty as the buyers, the seller’s expected revenue for each market is similar. As the seller’s uncertainty increases beyond the level of the buyers’ uncertainty, the auction with a reserve price eventually becomes the preferred choice.     

Transaction Costs and the Structure of the Market: A Case Study

A bstract Drawing upon the development of fish markets in a Chinese fishery community, this paper investigates the impact of transaction costs on the institutional structure of exchange. Fish markets in this region are connected and organized into a hierarchical network. This structure of fish markets dramatically reduces the cost for geographically distanced fishermen and consumers to execute trades. However, the provision of the market itself requires entrepreneurial el forts. In this study, the market is conceptualized as a continuum of middlemen, whose entrepreneurial efforts of buying and selling make the market work. When the middleman makes profits, the market is at work. Otherwise, the market fails to emerge. Comparing the different ways of organizing fish transportation at two distinct villages, this paper shows that the choice of the market or the firm to organize fish transportation is determined by the cost of putting the market to work.     

Divergence in Reservation Prices and Its Impact on Housing Market Liquidity: A Theoretical Analysis

In this paper, we build a two-period English auction model to study the relative movements between buyers’ and sellers’ reservation prices in the housing market. We show that changes in sellers’ reservation prices are jointly determined by changes in buyers’ reservation prices, probability of buyers offering a high or low price, and the arrival rate of buyers. When the divergence between the buyers’ and sellers’ reservation prices widens, the probability of sale increases in the upward market and decreases in the downward market, contributing to the increases or decreases in market liquidity.     

Stochastic models of resonating markets

This paper describes a way to model a seasonally and irregularly peaking price dynamics, as that originated in commodity and energy markets, using a system of coupled nonlinear stochastic differential equations. The specific case of an electric power market is used to show which microeconomic features this approach is able to model. Critical point analysis is used in a simple way to show how the interaction between dynamic criticality and stochasticity can be used to develop further models, useful to explore more deeply other types of peaking price dynamics.     

On the convergence of genetic learning in a double auction market

We study the learning behavior of a population of buyers and a population of sellers whose members are repeatedly randomly matched to engage in a sealed bid double auction. The agents are assumed to be boundedly rational and choose their strategies by imitating successful behavior and adding innovations triggered by random errors or communication with other agents. This process is modelled by a two-population genetic algorithm. A general characterization of the equilibria in mixed population distributions is given and it is shown analytically that only one price equilibria are attractive for the GA dynamics. Simulation results confirm these findings and imply that in cases with random initialization with high probability the gain of trade is equally split between buyers and sellers.     

Structural Analysis of Electricity Demand and Supply Interactions*

We specify a structural asymmetric vector error‐correction model to identify and estimate the demand and supply functions in hourly day‐ahead wholesale electricity markets. In doing so, we provide, inter alia, new insights into a well‐established but unresolved issue concerning the extent of the demand elasticity to price in these markets. We show that whilst demand appears to be inelastic in the short‐run, the quantity traded on the market is significantly influenced by the price level and responds to previous disequilibria in the supply curve through an asymmetric error‐correction mechanism, reacting to a positive disequilibrium but not to a negative one.     

Can boundedly rational sellers learn to play Nash?

How does Nash pricing compare to pricing with adaptive sellers using reinforcement learning (RL)? We consider a market game similar to Varian’s model (Am Econ Rev 70:651–659, 1980) with two types of consumers differing by the size of their fixed sample search rule and derive the Nash search equilibrium (NSE) strategy (the density, the mean and the variance of the posted price distribution). Our findings are twofold. First, we find that the RL price distribution does not converge in a statistical sense to the NSE one except when competition is à la Bertrand. Second, we show that the qualitative properties of the NSE with respect to a change in buyers‘ search behavior are still valid for the RL distribution. The average price and the variance of both price distributions exhibit similar variations to a change in buyers’ search.     

Time-sensitive supply chain disruption recovery and resource sharing incentive strategy

Market demand is becoming increasingly time-sensitive in competitive environments. Hence, supply disruptions will have a more serious impact on the profits of supply chains. This study applies a Stackelberg competition between a single supplier and a single manufacturer in a time-sensitive supply chain in a cloud manufacturing environment. We aim to address the supplier’s production capacity recovery issues and the manufacturer’s incentive decision issues after supply disruption. We find that the supplier is in a weak position when the information is symmetrical. The manufacturer can encourage the supplier to shorten the recovery time by raising the unit wholesale price. When the supplier’s unit production cost remains unchanged but the unit wholesale price increases, the profit of the supplier first increases and then decreases. In addition, under the centralized decision-making setting, the optimal recovery time of the supplier is shorter and the optimal unit market price of the product is lower than that under decentralized decision-making. We further find that resource sharing can shorten the optimal recovery time, but it does not necessarily play an incentivizing role.     

Information precision and asymptotic efficiency of industrial markets

I present a strategic model of a bilateral oligopoly with asymmetric information to examine (i) the validity of the conjecture of price-taking behavior in such markets as the number of agents becomes large and (ii) the effect of the rate that individual information precision decreases with increased number of agents on convergence to price-taking and efficiency. I show that with downstream competition, increasing the number of sellers may make all participants price-takers in the limit, but increasing the number of buyers may not. When the total precision of information in the market is high, price-taking and full social efficiency is achieved in the limit with large numbers of buyers and sellers. However, if the total precision of information in the market is poor, price-taking conjecture may fail and large inefficiencies, including full inefficiency, can occur in the limiting outcome. The rate of decrease of individual information precision with increased number of agents determines the rate of convergence to efficiency, and the convergence is slower than that predicted by single-unit auction models in the literature. I also demonstrate that when the number of sellers or both the number of buyers and the sellers go to infinity, price-taking and information aggregation tend to go together. When the number of buyers goes to infinity, however, information can get aggregated when the agents do not become price-takers in the limit. Albeit, in the latter case, the aggregated information is masked by the noise in the sellers’ signals and the cost variability.     

Does oil price variability affect the long memory and weak form efficiency of stock markets in top oil producers and oil Consumers? Evidence from an asymmetric MF-DFA approach

This study examines the asymmetric multifractality and the market efficiency of the stock markets in the countries that are the top crude oil producers (USA, KSA, Canada and Russia) and consumers (Brazil, China, India, and Japan) using an asymmetric multifractal detrended fluctuation analysis (A-MF-DFA) method. The results show evidence of an asymmetric multifractal nature for all markets. Moreover, the multifractality is stronger in the upward movement of the market returns, except in China. The degree of efficiency of the stock markets is shown to be time-varying and experienced a decrease during the 2008 global financial crisis (GFC), but an upside trend occurred during the recent oil price crash followed a significant decline during COVID-19. The stock markets have an anti-persistent feature during GFC and COVID-19, whereas they exhibit a long-term persistent feature during oil price crash. More interestingly, the efficiency of the stock markets of crude oil producers is lower in general than that of oil consumers. Furthermore, the efficiency of the stock market is lower in the downward movement of the market returns than in the upward movement. Asymmetry and oil price uncertainty index are the key driver of the stock markets and can serve as predictor of the stock market dynamics of top oil producers and top oil consumers particularly during COVID-19 and oil price crash.     

Learning competitive pricing strategies by multi-agent reinforcement learning

In electronic marketplaces automated and dynamic pricing is becoming increasingly popular. Agents that perform this task can improve themselves by learning from past observations, possibly using reinforcement learning techniques. Co-learning of several adaptive agents against each other may lead to unforeseen results and increasingly dynamic behavior of the market. In this article we shed some light on price developments arising from a simple price adaptation strategy. Furthermore, we examine several adaptive pricing strategies and their learning behavior in a co-learning scenario with different levels of competition. Q-learning manages to learn best-reply strategies well, but is expensive to train.     

Dynamic Competition with Experience Goods

This paper considers dynamic competition in the case in which consumers are only able to learn about their preferences for a certain product after experiencing it. After trying a product a consumer has more information about that product than about untried products. When competing in such a market firms with more sales in the past have an informational advantage because more consumers know their products. If products provide a better-than-expected fit with greater likelihood, taking advantage of that informational advantage may lead to an informational disadvantage in the future. This paper considers this competition with an infinite horizon model in a duopoly market with overlapping generations of consumers. Two effects are identified: On one hand marginal forward-looking consumers realize that by purchasing a product in the current period will be charged a higher expected price in the future. This effect results in reduced price sensitivity and higher equilibrium prices. On the other hand, forward-looking firms realize that they gain in the future from having a greater market share in the current period and compete more aggressively in prices. For similar discount factors for consumers and firms, the former effect is more important, and prices are higher the greater the informational advantages. The paper also characterizes oscillating market share dynamics, and comparative statics of the equilibrium with respect to consumer and firm patience, and the importance of the experience in the ex post valuation of the product.