The application to people of prediction algorithms, especially ones based on statistical classifier methods, can be perilous — and not only when limitations, bias and systemic effects are ill-understood by those using them as has often been the case. This is topical as such methods, sometimes...

This Comment is written in response to DOJ-FTC Request for Information on Merger Enforcement. We explain that the use of pricing algorithms based on artificial intelligence methodologies (hereinafter: "pricing algorithms"), by one or both parties, should be taken into account in the merger...

This paper evaluated the performance of the numerical integration methods applied to the transient multiphysics reactor core models. The models were integrated by the Backward Difference Formula (BDF) with automatic order and step size selection. The in-step non-linear system was solved by the...

Motivated by applications in cloud computing spot markets and selling banner ads on popular websites, we study the online resource allocation problem with "costly buyback". To model this problem, we consider the classic edge-weighted fractional online matching problem with a tweak, where the...

In the Computer Field, data arranging is one of the important task. This paper describes about a new data arranging algorithm, “Sort3 Algorithm” which is compared with bubble sort, selection sort, and insertion sort algorithms. Here input is divided into two parts. One part is called as...

Motivated by online decision-making in time-varying combinatorial environments, we study the problem of transforming offline algorithms to their online counterparts. We focus on offline combinatorial problems that are amenable to a constant factor approximation using a greedy algorithm that is...

In the service industry, a service provider may sell a collection of service activities as a package, also known as a service bundle. Empirical studies indicate that the customer's ex-post perception of a service bundle depends on not only the utility of each activity but also the sequence of...

This paper examines the impact of algorithmic trading (AT) on investors’ incentives to initiate block ownership in U.S. public companies. We find that a one standard deviation change in AT activity reduces the block ownership initiation likelihood by 3.5%. Using the SEC’s randomised tick...

This paper adopts Wavelet transform and Support Vector Regression (SVR) algorithm to predict all stock returns and form a time-varying Machine Learning (ML) factor added in CH4 of Liu, Stambaugh, et al. (2019) in the Chinese stock market from 2000 to 2020. The result shows that the decile sorted...

This paper provides a general representation of endogenous and threshold-based regime switching models and develops an efficient numerical solution method. The regime-switching is triggered endogenously when some variables cross threshold conditions that can themselves be regime-dependent. We...