In today’s world, most of the data is generated through computer applications. These applications can be used to predict and analyze the future. To achieve this phenomenon, we train the machines to read data and accordingly predict the future which is called as Machine Learning. Machine...

Algorithms, especially those based on artificial intelligence, play an increasingly important role in our economy. They are used by market participants to make pricing, output, quality, and inventory decisions; to predict market entry, expansion, and exit; and to predict regulatory moves. In a...

In financial markets, the success of an investor depends on the quality of information and the speed of his decision. Therefore, an accurate prediction allows investors to make informed decisions about investments and reduce risks. Until today, various researches have been carried out in order...

We provide a general framework to consider the effects of algorithmic demand and supply prediction in matching platforms, such as Task Rabbit for labor markets or Amazon for goods markets, where a significant proportion of matches are repeat transactions. We show that algorithmic repeat match...

This paper presents an algorithm for simulating multiple equilibria in otherwise-linearmodels with perfect foresight and occasionally-binding constraints. We extend theguess-verify approach of Guerrieri and Iacoviello (2015) to detect and simulate multipleperfect foresight equilibria, and also...

We review the modelling and pricing of American options both in classical mathematical finance and in reinforcement learning (RL). Some of the main difficulties when pricing an American put option with reinforcement learning is to make sure that the continuation value one step before maturity is...

We consider the problem of being a cross-chain wealth management platform with deposits, redemptions and investment assets across multiple networks. We discuss the need for blockchain bridges to facilitates fund flows across platforms. We point out several issues with existing bridges. We...

Predictive AI is increasingly used to guide decisions on agents. I show that even a bias-neutral predictive AI can potentially amplify exogenous (human) bias in settings where the predictive AI represents a cost-adjusted precision gain to unbiased predictions, and the final judgments are made by...