Function Of Price Research Articles

Centralized exchanges vs. decentralized exchanges in cryptocurrency markets: A systematic literature review

Research on cryptocurrency exchanges, consisting of both centralized exchanges (CEXs) and decentralized exchanges (DEXs), has seen a significant increase in contributions in recent years, driven by growing interest in the conceptual design of cryptocurrency markets. Through a comprehensive review of literature published between January 2019 and September 2023, I identify and analyze different dimensions of the ongoing CEX vs. DEX debate. While DEXs emphasize decentralization, user control, and resistance to censorship, CEXs offer higher liquidity, advanced trading features, and a more established track record. Regulatory challenges, such as Know Your Customer (KYC) and Anti-Money Laundering (AML) compliance, also feature prominently in the literature and influence the choice of exchange for both traders and policymakers. In addition, I observe a growing interest in the design of pricing functions for CEXs and DEXs, particularly in the area of automated market makers (AMMs). Finally, based on my findings, I outline future research opportunities in this context and derive research gaps as well as recommended actions for practitioners.

Quality Uncertainty and Repeat Purchases in Fish Auctions: Are Price Affected?

Abstract Auctions are widely used for agricultural and seafood products worldwide. However, buyer uncertainty regarding product quality may affect auction participation and efficiency negatively. This study examines repeat purchases (RPs) as a strategy to reduce buyer uncertainty regarding product quality and whether prices are affected. We also examine whether prices are affected by buyers’ option to prioritise among bids for several lots in the same auction period. Using hedonic price functions on data from the Norwegian pelagic auction, we find that RPs are associated with lower prices and that lots with first priority obtain higher prices than comparable random transactions.

Balance function generated by limiting conditions

This article conducts an analysis of the inherent constraints governing the formation of the price function that describes the interaction between two markets. The research not only identifies these constraints but also obtains an explicit form of the specified function.The key factors considered in constructing the price function are defined in the article. Through analyzing these constraints and their impact on market interaction, a formula for the price function is provided. This approach not only reveals the essence of natural constraints in forming the price function but also provides a contextual foundation for negotiations shaping a fair exchange price for the interaction process between two markets. This offers a theoretical basis for modeling and solving similar problems arising during practical economic activities.Two economies, Economy 1 and Economy 2, producing goods X and Y with linear Production Possibility Curve (PPC) graphs, are under consideration. The cost of producing one unit of good X relative to Y is denoted as R1 for Economy 1 and R2 for Economy 2. Exchange between economies occurs in a market, where the possible exchange is Δx units of X for Δy = Rmarket · Δx units of Y, and vice versa.If R1 is less than R2, Economy 1 specializes in the production of X, and Economy 2 specializes in Y, fostering mutually beneficial trade. For mutually beneficial exchange on the market with a price Rmarket, it is necessary and sufficient that R1 ≤ Rmarket ≤ R2.The article also explores the concept of a fair exchange price, specifying conditions for symmetry, reciprocity, and scale invariance. Notably, it indicates that the unique solution satisfying these conditions is f(R1,R2) = √ R1 · R2.In the context of balanced exchange, where economies gain equal profit per unit of the acquired good, the balanced exchange price Rmarket[balance] is determined as Rmarket = √ R1 · R2. This serves as a fair price, meeting the aforementioned conditions of symmetry, reciprocity, and scale invariance.In the provided example with R1 = 2 and R2 = 8, the article examines the mutually beneficial interval for Rmarket and computes the balanced and fair exchange price.

Density analysis for coupled forward–backward SDEs with non-Lipschitz drifts and applications

We explore the existence of a continuous marginal law with respect to the Lebesgue measure for each component (X,Y,Z) of the solution to coupled quadratic forward–backward stochastic differential equations (QFBSDEs) for which the drift coefficient of the forward component is either bounded and measurable or Hölder continuous. Our approach relies on a combination of the existence of a weak decoupling field (see Delarue and Guatteri, 2006), the integration with respect to space time local time (see Eisenbaum, 2006), the analysis of the backward Kolmogorov equation associated to the forward component along with an Itô-Tanaka trick (see Flandoli et al., 2009). The framework of this paper is beyond all existing papers on density analysis for Markovian BSDEs and constitutes a major refinement of the existing results. We also derive a comonotonicity theorem for the control variable in this frame and thus extending the works (Chen et al., 2005; Dos Rei and Dos Rei 2013).As applications of our results, we first analyse the regularity of densities of solution to coupled FBSDEs. In the second example, we consider a regime switching term structure interest rate models (see for e.g., Ma et al. (2017)) for which the corresponding FBSDE has discontinuous drift. Our results enables us to: firstly study classical and Malliavin differentiability of the solutions for such models, secondly the existence of density of such solutions. Lastly we consider a pricing and hedging problem of contingent claims on non-tradable underlying, when the dynamic of the latter is given by a regime switching SDE (i.e., the drift coefficient is allowed to be discontinuous). We obtain a representation of the derivative hedge as the weak derivative of the indifference price function, thus extending the result in Ankirchner et al. (2010).

Aggregative games with discontinuous payoffs at the origin

Recently a framework was developed for aggregative variational inequalities by means of the Selten–Szidarovszky technique. By referring to this framework, a powerful Nash equilibrium uniqueness theorem for sum-aggregative games is derived. Payoff functions are strictly quasi-concave in own strategies but may be discontinuous at the origin. Its power is illustrated by reproducing and generalising in a few lines an equilibrium uniqueness result in Corchón and Torregrosa (2020) for Cournot oligopolies with the Bulow–Pfleiderer price function. Another illustration addresses an asymmetric contest with endogenous valuations in Hirai and Szidarovszky (2013).

Risk‐Constrained Optimal Scheduling in Water Distribution Systems Toward Real‐Time Pricing Electricity Market

AbstractIn recent years, as a result of emerging renewable energy markets, several developed regions have already launched Real‐Time Pricing (RTP) strategies for electricity markets. Establishing optimal pump operation for water companies in RTP electricity markets presents a challenging problem. In a RTP market, both positive and negative electricity prices are possible. These negative prices create economically attractive opportunities for Water Distribution System (WDS) to dispatch their energy consumption. On the other hand, excessively high prices may put WDS at risk of supply disruptions and reduced service levels. However, the continuous development of wind power and photovoltaics results in more volatile and unpredictable fluctuations in the price of renewable energy. The risk arising from uncertainty in electricity prices can lead to a significant increase in actual costs. To address this issue, this paper develops an a posteriori random forest (AP‐RF) approach to forecast the probability density function of electricity prices for the next day and provide a risk‐constrained pump scheduling method toward RTP electricity market. The experimental results demonstrate that the developed method effectively addresses the issue of increased costs caused by inaccurate electricity price forecasting.

Some Aspects of Animal Husbandry in Africa

It is emphasized that animal husbandry, which has existed since ancient times in many regions of Africa and is one of the most important areas of human activity, is an integral part of the socio-cultural code of the African population. To date, pastoralism plays an important role not only in the economic, but also in the social sphere of the inhabitants of vast regions of the continent; the size of herds is the main criterion for assessing the property and social status of its owner. Being the subject of trade and direct exchange, cattle bring a significant and stable income to their sellers, while at the same time performing the function of a bride price at the conclusion of marriages. The challenges of our time require a certain degree of flexibility and adaptability from the population of livestock regions, which is associated with inevitable changes in the centuries-old way of life and the system of socio-cultural ties. Attention is drawn to the fact that the tradition of husbandry is influenced by numerous factors of modern development: climate change and epizootics of recent decades have a negative imprint on livestock activities. High losses of livestock, a reduction in their per capita population over time, combined with demographic growth, have had a negative impact on the well-being of pastoralists, significantly increasing their poverty level. The governments of many African countries, in which husbandry plays a leading role, have an interest not only in maintaining existing positions, but also in improving them. In situations of epizootic danger, national livestock health surveillance systems in African countries are approached by international partners, including FAO, WHO, as well as one of the world’s leading organization whose functions include the formation of links in the field of veterinary medicine, ensuring the interaction of national and regional veterinary authorities – the International Epizootic Office (OIE). Continuous field research in livestock regions in a number of African countries provides significant assistance in the fight against livestock diseases. The use of modern information technologies in epizootiological diagnostics is increasingly becoming the basis of anti-epizootic and preventive measures.

Dynamic Cooperative Oligopolies

An n-person cooperative oligopoly is considered without product differentiation. It is assumed that the firms know the unit price function but have no access to the cost functions of the competitors. From market data, they have information about the industry output. The firms want to find the output levels that guarantee maximum industry profit. First, the existence of a unique maximizer is proven, which the firms cannot determine directly because of the lack of the knowledge of the cost functions. Instead, a dynamic model is constructed, which is asymptotically stable under realistic conditions, and the state trajectories converge to the optimum output levels of the firms. Three models are constructed: first, no time delay is assumed; second, information delay is considered for the firms on the industry output; and third, in addition, information delay is also assumed about the firms’ own output levels. The stability of the resulting no-delay, one-delay, and two-delay dynamics is examined.

Forward starting options pricing under a regime-switching jump-diffusion model with Wishart stochastic volatility and stochastic interest rate

Vanilla options become effective immediately after they are entered, while some exotic options will only come to effective some time after they are bought or sold. Forward starting options are one kind of such exotic options started actually at some pre-specified future date. This paper presents an extension of regime-switching jump diffusion model, in which the parameters are driven by a continuous time and stationary Markov chain on a finite state space, by introducing the Wishart process into the instantaneous variance-covariance matrix of the risky asset price and stochastic interest rate. We derive the discounted conditional joint characteristic function and the forward characteristic function of the log-asset price and its the instantaneous variance-covariance process, and thereby the price of forward starting options are well evaluated by the probabilistic approach combined with the Fourier-cosine (COS) method. We also provide efficient Monte Carlo simulation of this proposed model, and simulated solutions to forward starting options pricing within a two-state regime switching framework. Numerical results show that the COS method is accurate and efficient for pricing forward starting options. Finally, we analyse impacts of some main parameters (especially, parameters in the Wishart stochastic volatility) in this proposed model on option prices and Δ values. Also, we consider the forward implied volatility. Furthermore, the forward starting options under the regime-switching jump diffusion model with Wishart stochastic volatility and stochastic interest rate which we derived are more generalized than those recently appeared in the derivatives pricing literature, and thus have wider application.

Finite control set model-free predictive current control of permanent magnet synchronous motor

This thesis proposes finite control set model-free predictive current control (FCSMFPCC) algorithm of permanent magnet synchronous motor (PMSM). To address issue of degraded performance during motor operation due to parameter mismatch, a model-free predictive current control arithmetic is devised, which utilizes ultra-local model (ULM) of PMSM. This proposition takes sum of known and sealed disturbances of the system as an unknown quantity, and uses sliding mode observer (SMO) to take stock of sealed quantity. To address the issue of operation delay in predictive control, a two-step method is used to make up for the system. When using price function to choose the first-rank voltage vector, vector selection optimization link is added, which effectively simplifies the algorithm while optimizing the inverter switching action. The simulation outcomes highlight the advantages of the described control algorithm in terms of better dynamic response performance and stronger robustness.

AI pricing algorithms under platform competition

AbstractPlatforms play an essential role in the modern economy. At the same time, due to advances in artificial intelligence (AI), algorithms are becoming more widely used for pricing and other business functions. Previous literature examined algorithmic pricing, but not in the context of network effects and platforms. Moreover, platform competition literature has not considered how algorithms may affect competition. We study the performance of AI pricing algorithms (Q-learning and Particle Swarm Optimization) and naïve algorithms (price-matching) under platform competition. We find that algorithms set an optimal price structure that internalizes network effects. However, no algorithm is always the best because profitability depends on the type of competing algorithms and market characteristics, such as differentiation and network effects. Additionally, algorithms learn autonomously when an equilibrium is unstable and avoid it. When algorithm adoption is an endogenous strategic decision, several algorithms can be adopted in equilibrium; we characterize the conditions for the various outcomes and show that the equilibrium and platform profits are sensitive to algorithm design changes. Overall, our research suggests that AI algorithms can be effective in the presence of network effects, and platforms are likely to adopt a variety of algorithms. Lastly, we reflect on the business value of AI and identify opportunities for future research at the intersection of AI algorithms and platforms.

Reporting bias and feedback effect

AbstractStock prices often provide firm managers with new information that can be used in real decisions. Studies generally focus on the ex ante disclosure policy and show that the presence of market feedback crowds out firms' disclosure. We instead examine a manager's ex post biasing incentives and find that market feedback amplifies overreporting bias, but not necessarily underreporting bias, due to three interacting effects. First, the manager biases the report more with feedback since decreased information quality crowds in the speculator's private information acquisition and improves investment efficiency, regardless of the reporting scenario (the information rationing effect). Second, the manager biases more in the overreporting scenario and less in the underreporting scenario, because reporting more favorable information crowds in private information acquisition, as the speculator expects a higher subsequent investment and therefore higher trading profits (the investment scale effect). Third, market feedback influences reporting bias not only through the speculator's information acquisition but also directly through the market maker's pricing function. Specifically, the market maker decreases the price discount, as he expects that the manager may learn correct information from the price and may invest more efficiently. Expecting a lower price penalty in the presence of feedback, the manager biases more in the overreporting scenario and less in the underreporting scenario (the investment correction effect). Overall, our results suggest that granting firms reporting discretion could improve investment efficiency and firm value when managers can learn through price.

Optimization of Financial Indicators in Shale-Gas Wells Combining Numerical Decline Curve Analysis and Economic Data Analysis

We present a methodology to determine optimal financial parameters in shale-gas production, combining numerical simulation of decline curves and stochastic modeling of the gas price. The mathematical model of gas production considers free gas in the pore and the gas adsorbed in kerogen. The dependence of gas production on petrophysical parameters and stimulated permeability is quantified by solving the model equations in a 3D geometry representing a typical fractured shale well. We use Monte Carlo simulation to characterize the statistical properties of various common financial indicators of the investment in shale-gas. The analysis combines many realizations of the physical model, which explores the variability of porosity, induced permeability, and fracture geometry, with thousands of realizations of gas price trajectories. The evolution of gas prices is modeled using the bootstrapping statistical resampling technique to obtain a probability density function of the initial price, the drift, and the volatility of a geometric Brownian motion for the time evolution of gas price. We analyze the Net Present Value (NPV), Internal Rate of Return (IRR), and Discounted Payback Period (DPP) indicators. By computing the probability density function of each indicator, we characterize the statistical percentile of each value of the indicator. Alternatively, we can infer the value of the indicator for a given statistical percentile. By mapping these parametric combinations for different indicators, we can determine the parameters that maximize or minimize each of them. We show that, to achieve a profitable investment in shale-gas with high certainty, it is necessary to place the wells in extremely good locations in terms of geological parameters (porosity) and to have exceptional fracturing technology (geometry) and fracture permeability. These high demands in terms of petrophysical properties and hydrofracture engineering may explain the industry observation of “sweet spots”, that is, specific areas within shale-gas plays that tend to yield more profitable wells and where many operators concentrate their production. We shed light on the rational origin of this phenomenon: while shale formations are abundant, areas prone to having a multi-parameter combination that renders the well profitable are less common.

The hedonic price model for the wine market: A systematic and comparative review of the literature

AbstractThis paper carries out a thorough review of the literature on the estimation of hedonic price functions in the wine market, compiling and carefully documenting all research work on the subject. The review analyses the main methodological decisions taken by the different authors, as well as the typology of the available databases: identification of the relevant market, specification of the price function, sources and types of prices, econometric methodology, and type of publication. The variance decomposition analysis of the Adjusted‐R‐squared values from the estimated hedonic price functions suggests that attribute selection, the definition of the product market, the characteristics of information sources, and the implemented econometric procedures are the most relevant factors in explaining the models’ explanatory power.

Derivation of discrete analog of Breeden–Litzenberger relation for risk-neutral density

This short paper derives a formula for the risk-neutral density function at discrete points over the strike range using Abel’s summation formula in terms of the arbitrage-free call price function in a European option contingent. The estimate of risk-neutral density is crucial from a risk management perspective and other crucial assessments.

Research on pricing and replenishment decision of vegetable and fruit commodities-Based on nonlinear programming model and ARIMA time series forecasting

Due to the timeliness of vegetable and fruit sales, supermarkets generally supplement each product on a daily basis based on the past sales and demand of each product according to the specific situation. In order to make replenishment and pricing decisions for vegetables and fruits in commercial supermarkets, this paper considers cost, sales volume, supply and demand relationship and loss factors under profit maximization based on cost plus pricing method. Sales volume, cost plus pricing functions are defined, and seasonal ARMIA model is used for forecasting. The sales profit function and constraint conditions are established, and the nonlinear programming model is constructed to solve the problem to obtain the profit maximization scheme.

Opportunities and Challenges of New Energy Vehicles in Carbon Neutrality and Financial Investment Banking

One of the biggest problems the world is currently experiencing is global climate change, requiring all industries to work together to mitigate its adverse effects on the environment and society. In this context, carbon neutrality has become a topic of widespread concern and discussion. This article focuses on the role that financial investment banks play in initiatives for carbon neutrality and their function in the area of alternative fuel vehicles. This study will go into the history and difficulties of creating new energy vehicles, highlighting the critical function of market-based carbon pricing in achieving emissions reduction targets. The research results show that the new energy vehicle field has good development prospects, but there are also development challenges. Financial investment banks play a crucial role in advancing the carbon neutrality strategy and provide important support for enterprises to achieve sustainable development by providing services such as financial support, risk management and market analysis. Finally, the research significance of this article lies in an in-depth discussion of the role of financial investment banks in carbon neutrality strategies, which provides useful reference and guidance for achieving sustainable development goals.

A Quantum Oscillator Model of Stock Markets

Classical oscillators have long been used to model financial time series, but suffer from the drawback that the underlying system does not behave like a mechanical spring: there are no regular oscillations, and price is not a well-defined mechanical quantity but always has a degree of uncertainty. In recent years a number of authors have attempted to address these problems by basing their models on quantum harmonic oscillators, which always have a non-zero volatility, however the role of other features that are characteristic of quantum systems, such as discrete energy levels, has not been clear. This paper develops a quantum model in which the energy level corresponds to an integer number of transactions. The model is derived by quantizing entropic forces which represent the intentions of buyers and sellers to transact as a function of price. It is shown that the model captures the non-Gaussian nature of financial statistics, and correctly predicts empirical phenomena including the square-root law of price impact, along with its associated variance.

The existence, uniqueness and stability of steady state for a class of first-order difference equations with application to the housing market dynamic

We study the existence, uniqueness and stability of the steady state for the dynamic described by a class of first-order difference equations. We then apply the result to analyse a housing market where the supply is linear and demand is a bounded and monotone decreasing function of price, derived from households’ optimization behaivour. Under two linear price adjustment mechanisms, we prove the existence and uniqueness of an equilibrium, which is independent of the mechanisms. That is, the house price converges to a same steady state where it clears the market under both mechanisms. The result is general in the sense that we do not need to specify a particular form of demand function. Besides, the same approach can be utilized to analyse the dynamics of other markets.

Game-theoretic policy computing and simulation for blockchained buffering system via diffusion approximation

AbstractWe study 2-stage game-theoretic problem oriented 3-stage service policy computing, convolutional neural network (CNN) based algorithm design, and simulation for a blockchained buffering system with federated learning. More precisely, based on the game-theoretic problem consisting of both “win-lose” and “win-win” 2-stage competitions, we derive a 3-stage dynamical service policy via a saddle point to a zero-sum game problem and a Nash equilibrium point to a non-zero-sum game problem. This policy is concerning users-selection, dynamic pricing, and online rate resource allocation via stable digital currency for the system. The main focus is on the design and analysis of the joint 3-stage service policy for given queue/environment state dependent pricing and utility functions. The asymptotic optimality and fairness of this dynamic service policy is justified by diffusion modeling with approximation theory. A general CNN based policy computing algorithm flow chart along the line of the so-called big model framework is presented. Simulation case studies are conducted for the system with three users, where only two of the three users can be selected into the service by a zero-sum dual cost game competition policy at a time point. Then, the selected two users get into service and share the system rate service resource through a non-zero-sum dual cost game competition policy. Applications of our policy in the future blockchain based Internet (e.g., metaverse and web3.0) and supply chain finance are also briefly illustrated.