Price dispersion, information and learning

Essays on Pricing and Learning in Bertrand Markets

The thesis studies sellers’ pricing and learning behaviour in Bertrand oligopoly markets using a bounded rational approach. It consists of four chapters. Chapter 1 develops a quantal response adaptive learning model which combines sellers’ bounded rationality with adaptive belief learning in order to explain price dispersion and dynamics in laboratory Bertrand markets with perfect information. ...

Using Machine Learning to Explain Violations of the “law of One Price” Aaron Bodoh-creed, Jörn Boehnke, and Brent Hickman

Substantial price variation for homogeneous goods in online markets is a well-known puzzle that has withstood attempts by empirical researchers to explain it. Economic theory suggests two possible sources of the dispersion: either market frictions are more important than previously thought, or there are subtle differences between product listings presented to e-commerce consumers that applied e...

Inflation And Relative Price Dispersion: Evidence For Iran

Stock Price Prediction using Machine Learning and Swarm Intelligence

Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this...

Using Machine Learning ARIMA to Predict the Price of Cryptocurrencies

The increasing volatility in pricing and growing potential for profit in digital currency have made predicting the price of cryptocurrency a very attractive research topic. Several studies have already been conducted using various machine-learning models to predict crypto currency prices. This study presented in this paper applied a classic Autoregressive Integrated Moving Average(ARIMA) model ...