Topic
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 published on a yearly basis
Papers
More filters
Patent•
23 Jan 2004
TL;DR: In this article, the authors present a system for trading and hedging product and brand sales based on parimutuel principles, which facilitates trading through the Internet, through web and calculation servers, and databases storing required trader, product and contract information relevant for executing trades.
Abstract: The present invention provides a system of trading and hedging product and brand sales (100). Financial institutions, investors, and corporations face sales risk when a product is to be brought to market (200). The invention involves identifying products and brands appropriate for trading, such as box office receipts on a particular movie (300). The invention provides for a process for pricing financial contracts based on parimutuel principles. The system also provides for secondary market trading of the financial contracts. The system facilitates trading through the Internet, through web and calculation servers, and databases storing required trader, product and contract information relevant for executing trades (700).
37 citations
TL;DR: In this paper, the authors use a unique and unusually rich high-frequency intraday dataset from the world's largest financial market, namely, the electronic inter-dealer spot foreign exchange market, to examine their relationship with bid-ask spreads and return volatility.
37 citations
Posted Content•
TL;DR: In this article, the authors investigate the options market around a revision in the financial analysts' consensus recommendation and find that options investors trade in the correct direction of the upcoming revision approximately three days prior to the announcement.
Abstract: This article investigates the options market around a revision in the financial analysts’ consensus recommendation. The results demonstrate that options investors trade in the correct direction of the upcoming revision approximately three days prior to the announcement. We find this behavior in options-implied prices, implied volatilities, and options trading volume. Tests confirm that the options market leads the stock market before the financial analysts’ revision. Moreover, using all firms with outstanding options, an out-of-sample analysis produces a profitable zero-cost trading strategy net of transaction costs based on the relative valuations between the synthetic and the underlying equity security.
37 citations
Patent•
13 Oct 2000TL;DR: In this paper, the authors present a system for use on an electronic network for negotiating contracts between at least one buyer and one seller, in which proposals may be made or called for by buyers and/or sellers, and in which each party is represented by a software agent.
Abstract: A system for use on an electronic network for negotiating contracts between at least one buyer and at least one seller, in which proposals may be made or called for by buyers and/or sellers, and in which each party is represented by a software agent.
37 citations
Posted Content•
TL;DR: In this article, a simulation environment is presented that provides stylized implementations of algorithmic trading behavior and allows for modeling latency, and an assessment of the impact of Algorithmic Trading models can be conducted by comparing different simulation runs including and excluding a trader constituting an algorithm trading model in its trading behavior.
Abstract: Innovative automated execution strategies like Algorithmic Trading gain significant market share on electronic market venues worldwide, although their impact on market outcome has not been investigated in depth yet. In order to assess the impact of such concepts, e.g. effects on the price formation or the volatility of prices, a simulation environment is presented that provides stylized implementations of algorithmic trading behavior and allows for modeling latency. As simulations allow for reproducing exactly the same basic situation, an assessment of the impact of algorithmic trading models can be conducted by comparing different simulation runs including and excluding a trader constituting an algorithmic trading model in its trading behavior. By this means the impact of Algorithmic Trading on different characteristics of market outcome can be assessed. The results indicate that large volumes to execute by the algorithmic trader have an increasing impact on market prices. On the other hand, lower latency appears to lower market volatility.
37 citations