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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.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors investigated the link between observed insider information and insider trading and also showed that insiders do indeed have superior information and use that information in trading in their firms' securities.
Abstract: It is generally supposed that corporate insiders have access to information superior to that of outsiders. Empirical work on insider trading by Jaffe (1974) and Finnerty (1976a, 1976b) has found that insiders do earn higher returns on their shareholdings than outsiders, on average. Further, insiders in different managerial positions appear to earn differential abnormal returns (Baesel and Stein 1979).1 Investors subscribe to services which summarize insider trading activity2 and act on the information released in the SEC's Official Summary of Insider Trading (Jaffe 1974). This evidence suggests that insiders do indeed have superior information and use that information in trading in their firms' securities. This paper investigates more directly the link between observed insider information and insider trading and also the link between insider trading and information-dissemination activities. The tests reported here examine the security trading of corporate insiders around the time they make public announcements about their

227 citations

Patent
04 Sep 2002
TL;DR: In this article, a data processing system receives a continuous stream of real-time transactional data regarding market transactions of fixed income securities and uses linear interpolation techniques to complete an operative data set.
Abstract: A data processing system receives a continuous stream of real time transactional data regarding market transactions of fixed income securities. The incoming data is qualified and then used to determine the term structure of interest rates based on price information. The system provides linear interpolation techniques to complete an operative data set. This set is updated with current trade data, with term structure shifting using pivot points from newly qualified data. An index value for a pre-select portfolio of securities is then calculated and expressed in terms of price relative to par, yield to maturity and duration. In a specific implementation using U.S. Treasuries as the monitored security, the index value supports an automated trading function for futures and/or options contracts based on the change in value of the index. The index provides a more accurate barometer of market changes and a more useful tool in measuring portfolio management for plan sponsors.

225 citations

Journal ArticleDOI
TL;DR: In this paper, the authors reexamine the anomalous evidence concerning the efficiency of the listed options exchanges and focus on the structure of trading costs in that market, and note several costs which generally have been ignored, the largest of which is the bid-ask spread.

223 citations

Journal ArticleDOI
TL;DR: In this article, the authors assess empirically whether speculation affects oil price dynamics and find strong evidence that oil price shifts are negatively related to stock price and exchange rate changes and that a complex web of time-varying first and second order conditional moment interactions affects both the CAPM and feedback trading components of the model.

222 citations

Journal ArticleDOI
TL;DR: It is found that market impact is strongly concave, approximately increasing as the square root of order size, and as a given order is executed, the impact grows in time according to a power law.
Abstract: We empirically study the market impact of trading orders. We are specifically interested in large trading orders that are executed incrementally, which we call hidden orders. These are statistically reconstructed based on information about market member codes using data from the Spanish Stock Market and the London Stock Exchange. We find that market impact is strongly concave, approximately increasing as the square root of order size. Furthermore, as a given order is executed, the impact grows in time according to a power law; after the order is finished, it reverts to a level of about 0.5–0.7 of its value at its peak. We observe that hidden orders are executed at a rate that more or less matches trading in the overall market, except for small deviations at the beginning and end of the order.

221 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202397
2022190
2021144
2020167
2019126
2018160