Amidst the ongoing debate surrounding algorithmic price discrimination,the regulation of price discrimination in the platform economy has once again emerged as a prominent topic of discussion in various spheres.The ce...Amidst the ongoing debate surrounding algorithmic price discrimination,the regulation of price discrimination in the platform economy has once again emerged as a prominent topic of discussion in various spheres.The central focus and challenge of this matter lies in understanding the welfare implications of price discrimination,specifically how it impacts firms,consumers,and society as a whole.By comparing discriminatory pricing with uniform pricing(without price discrimination),we can find the changing laws of firms’profit,consumer surplus,and social welfare.Based on the complete information static game,we derive the analytical expressions for the profit increment,the consumer surplus increment,and the social welfare increment through a mathematical model.The study focuses on the third-degree price discrimination in two consumer groups of m(any positive integer)firms.Additionally,we prove the characteristics of these increments,whether they are positive,negative,or zero.The research results show that algorithmic price discrimination is beneficial to firms but detrimental to consumers.Its impact on the whole society is conditional and depends on the sum of the marginal costs of the m firms.The study examines this issue through the lens of four core values:consumer rights,social welfare,fair value,and competition protection.Based on the experiences of developed countries,regulatory countermeasures are proposed to address this issue,focusing on protecting personal information and civil rights.展开更多
We consider sequential auctions wherein seller and bidder agents need to price goods on sale at the‘right’market price.We propose algorithms based on a binomial model for both the seller and buyer.Then,we consider t...We consider sequential auctions wherein seller and bidder agents need to price goods on sale at the‘right’market price.We propose algorithms based on a binomial model for both the seller and buyer.Then,we consider the problem of calibrating pricing models to market data.To this end,we studied a stochastic volatility model used for option pricing,derived,and analyzed Monte Carlo estimators for computing the gradient of a certain payoff function using Finite Differencing and Algorithmic Differentiation.We then assessed the accuracy and efficiency of both methods as well as their impacts into the optimization algorithm.Numerical results are presented and discussed.This work can benefit those engaged in electronic trading or investors in financial products with the need for fast and more precise predictions of future market data.展开更多
文摘Amidst the ongoing debate surrounding algorithmic price discrimination,the regulation of price discrimination in the platform economy has once again emerged as a prominent topic of discussion in various spheres.The central focus and challenge of this matter lies in understanding the welfare implications of price discrimination,specifically how it impacts firms,consumers,and society as a whole.By comparing discriminatory pricing with uniform pricing(without price discrimination),we can find the changing laws of firms’profit,consumer surplus,and social welfare.Based on the complete information static game,we derive the analytical expressions for the profit increment,the consumer surplus increment,and the social welfare increment through a mathematical model.The study focuses on the third-degree price discrimination in two consumer groups of m(any positive integer)firms.Additionally,we prove the characteristics of these increments,whether they are positive,negative,or zero.The research results show that algorithmic price discrimination is beneficial to firms but detrimental to consumers.Its impact on the whole society is conditional and depends on the sum of the marginal costs of the m firms.The study examines this issue through the lens of four core values:consumer rights,social welfare,fair value,and competition protection.Based on the experiences of developed countries,regulatory countermeasures are proposed to address this issue,focusing on protecting personal information and civil rights.
文摘We consider sequential auctions wherein seller and bidder agents need to price goods on sale at the‘right’market price.We propose algorithms based on a binomial model for both the seller and buyer.Then,we consider the problem of calibrating pricing models to market data.To this end,we studied a stochastic volatility model used for option pricing,derived,and analyzed Monte Carlo estimators for computing the gradient of a certain payoff function using Finite Differencing and Algorithmic Differentiation.We then assessed the accuracy and efficiency of both methods as well as their impacts into the optimization algorithm.Numerical results are presented and discussed.This work can benefit those engaged in electronic trading or investors in financial products with the need for fast and more precise predictions of future market data.
