Algorithmic trading

About: Algorithmic trading is a research topic. Over the lifetime, 6718 publications have been published within this topic receiving 162209 citations. The topic is also known as: algotrading & Algorithmic trading.

Trading Volume with Private Valuation: Evidence from The Ex-Dividend Day

Abstract: We test a theory of the interaction between investors' heterogeneity, risk, transaction costs, and trading volume. We take advantage of the specific nature of trading motives around the distribution of cash dividends, namely the costly trading of tax shields. Consistent with the theory, we show that when trades occur because of differential valuation of cash flows, an increase in risk or transaction costs reduces volume. We also show that the nonsystematic risk plays a significant role in determining the volume of trade. Finally, we demonstrate that trading volume is positively related to the degree of heterogeneity and the incentives of the various groups to engage in trading. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.

The Intertemporal Relation Between the U.S. and Japanese Stock Markets

Abstract: This paper finds a high correlation between the open to close returns for U.S. stocks in the previous trading day and the Japanese equity market performance in the current period. In contrast, the Japanese market has only a small impact on the U.S. return in the current period. High correlations among open to close returns are a violation of the efflcient market hypothesis; however, in trading simulations, the excess profits in Japan vanish when transactions costs and transfer taxes are included. THE TWO LARGEST STOCK markets in the world in terms of capitalization, volume, and shares listed are the Tokyo Stock Exchange (TSE) and the New York Stock Exchange (NYSE). Because Tokyo is 14 hours ahead of New York, there is an eight and one-half hour difference between the close of the TSE and open of the NYSE. Since there is no overlap between the two markets, traders or technical analysts may look to the TSE as a predictor of market movement on the NYSE and/or examine changes on the NYSE as indicators of TSE performance. As shown in Figure 1, the TSE opens at 7:00 p.m. Eastern Standard Time (EST) and closes at 1:00 a.m. EST.1 The NYSE opens at 11:30 p.m. Japanese time (9:30 a.m. EST) and closes at 5:00 a.m. Japanese time (4:00 p.m. EST). Thus, there is no common time interval in which both markets are open. High correlations between the respective open to close returns are a violation of the efficient market hypothesis because public information about the performance in one market could be used to profitably trade in another market. If the markets are efficient, information about the open to close performance in one market (for example, the U.S. return in period t - 1) will be fully reflected in the open price of the other market (Japan in period t, for example). Since new information flows randomly into the market, subsequent price changes should be random and the open to close returns in Japan will be uncorrelated with the U.S. returns. Thus, the U.S. performance should affect the open price in Japan, and the correlation between the open to close returns of the two markets will be zero. Early research on the synchronization among stock prices across countries (Grubel (1968), Levy and Sarnat (1970), Agmon (1972), Ripley (1973), Lessard

Algorithmic Trading and Information

Abstract: We examine algorithmic trades (AT) and their role in the price discovery process in the 30 DAX stocks on the Deutsche Boerse. AT liquidity demand represents 52% of volume and AT supplies liquidity on 50% of volume. AT act strategically by monitoring the market for liquidity and deviations of price from fundamental value. AT consume liquidity when it is cheap and supply liquidity when it is expensive. AT contribute more to the efficient price by placing more efficient quotes and AT demanding liquidity to move the prices towards the efficient price.