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.

Peer-to-peer data trading to preserve information

Abstract: Data archiving systems rely on replication to preserve information. This paper discusses how a network of autonomous archiving sites can trade data to achieve the most reliable replication. A series of binary trades among sites produces a peer-to-peer archiving network. Two trading algorithms are examined, one based on trading collections (even if they are different sizes) and another based on trading equal sized blocks of space (which can then store collections). The concept of deeds is introduced; deeds track the blocks of space owned by one site at another. Policies for tuning these algorithms to provide the highest reliability, for example by changing the order in which sites are contacted and offered trades, are discussed. Finally, simulation results are presented that reveal which policies are best. The experiments indicate that a digital archive can achieve the best reliability by trading blocks of space (deeds), and that following certain policies will allow that site to maximize its reliability.

Trading activity and price reversals in futures markets

Abstract: We use the standard contrarian portfolio approach to examine short-horizon return predictability in 24 US futures markets. We find strong evidence of weekly return reversals, similar to the findings from equity market studies. When interacting between past returns and lagged changes in trading activity (volume and/or open interest), we find that the profits to contrarian portfolio strategies are, on average, positively associated with lagged changes in trading volume, but negatively related to lagged changes in open interest. We also show that futures return predictability is more pronounced if interacting between past returns and lagged changes in both volume and open interest. Our results suggest that futures market overreaction exists, and both past prices and trading activity contain useful information about future market movements. These findings have implications for futures market efficiency and are useful for futures market participants, particularly commodity pool operators.

The Trading Decision and Market Clearing under Transaction Price Uncertainty

Abstract: This paper models an individual's trading decision, given: (1) his/her demand function to hold shares of an asset, (2) his/her expectation on what the market clearing price will be, and (3) the design of the market which determines how orders will be translated into trades. The particular market design we consider is the batched trading (periodic call) regime. Assuming investors are distributed according to their propensities to hold shares, we model the aggregation of orders to obtain market clearing values of price and volume and to show the way in which, with trading friction, these solutions differ from Pareto efficient values. The importance of this analysis for various issues concerning market design is noted. WHEN MARKETS ARE NOT frictionless and transaction prices are uncertain, the act of trading requires analysis. This paper models an individual's trading decision in secondary financial asset markets. In so doing, we study the order flow as an endogenous part of the system. We show how, given an underlying demand curve, the trader will choose an optimal (price, quantity) order to transmit to the market, and we model the aggregation of orders to obtain market clearing values for price and volume. These models are used to show the way in which the prices and trading volume established on the market will in general differ from their Pareto efficient values. Much of the microstructure literature that studies the behavior of transaction prices in a nonfrictionless market has assumed that orders are generated by some exogenously given stochastic process. This has been true, for instance, in the

Equilibrium Fast Trading

Abstract: High-speed market connections improve investors' ability to search for attractive quotes in fragmented markets, raising gains from trade. They also enable fast traders to observe market information before slow traders, generating adverse selection, and thus negative externalities. When investing in fast trading technologies, institutions do not internalize these externalities. Accordingly, they overinvest in equilibrium. Completely banning fast trading is dominated by offering two types of markets: one accepting fast traders, the other banning them. However, utilitarian welfare is maximized by having i) a single market type on which fast and slow traders coexist and ii) Pigovian taxes on investment in the fast trading technology.

Program Trading and Individual Stock Returns: Ingredients of the Triple-Witching Brew

Abstract: The price and trading volume behaviors of individual stocks in the Standard and Poor's 500 Stock Index (S&P 500) are analyzed on stock index futures expiration days, a time when the market is known to be subject to heavy program trading. The price behavior of stocks that are subject to program trading is shown to be very similar to stocks that are not. Stocks that decline in price in the last half hour Friday tend to increase in price at the opening on Monday and vice versa. The Monday reversal as a fraction of the Friday price change is only slightly higher for the S&P 500 stocks than for non-S& P 500 stocks, indicating that the price reversals reflect, for the most part, the bid-ask spreads of the individual stocks. Trading volume in the last half hour of expiration days is shown to be substantially higher than normal. Copyright 1990 by the University of Chicago.