In investigating the effects of algorithmic trading on stock market liquidity and commonality in liquidity in different market conditions in an electronic limit order market, we find algorithmic trading increases stock liquidity by narrowing quoted and effective bid–ask spreads. Furthermore, algorithmic trading decreases commonality in liquidity; this finding is robust across a variety of liqui...

Advanced electronic trading systems, such as the third phase of the TELCOT system, provide a negotiation mechanism for traders. The purpose of such a negotiation mechanism is to make the trading procedure more flexible. In principle, an electronic trading system establishes an environment in which traders select their partners based on posted trading terms such as product bid/offer prices, prod...

Exhaustive global array data flow analysis for communication optimization is expensive and considered to be impractical for large programs. This paper proposes a demand-driven analysis approach that reduces the analysis cost by computing only the data flow information related to optimizations. In addition, the analysis cost of our scheme can be effectively managed by trading space for time or c...

This article addresses the residential energy cost optimization problem in smart grid. To date, most of the previous research only consider a partial aspect of the cost optimization problem. As a result, they fail to analyze scenarios when the interconnected components along with their properties have to be considered simultaneously. The proposed model combines these partial models into a singl...

A model of competitive stock trading is developed in which investors are heterogeneous in their information and private investment opportunities and rationally trade for both informational and noninformational motives. I examine the link between the nature of heterogeneity among investors and the behavior of trading volume and its relation to price dynamics. It is found that volume is positivel...

I n this paper, trading symbols of the 30 largest companies listed in the Tehran Stock Exchange (TSE) were ranked based on the asymmetry information risk. Using the Ersan and Alici (2016) modified clustering algorithm (EA), we estimated the probability of informed trading (PIN) to measure the asymmetry information among traders for each trading symbol and trading day through two-year...