Information Based Trading

Information Based Trading

Models Developed to Capture the Probability of Information Based Trading

I. Introduction

Almost all of the observers of financial markets consider trade for informational reasons as a key motive for trade. This is known as information-based trade. It is unlikely that all trade is drive by pure risk-sharing motivations, which is the only alternative to information-based trading under standard assumptions. In particular, one would need only to speculate that risk sharing needs evolve rapidly to account for the large high-frequency fluctuations observed in trading volumes; and market participants agree to devote substantial resources to acquire information. Because of this theory, many models have been developed to capture the probability of information based trading.

David Easley, Nicholas M. Kiefer and Maureen O'Hara published a paper in July of 1996 detailing the process they used to develop and to test their hypothesis concerning agreements between dealers or trading locales and brokers for retail order flow. Easley, Kiefer and O'Hara viewed such agreements as being used to "cream skim" uninformed liquidity trades, which left the information-based trades to established markets. They used a model of the stochastic process of trades and estimated this model for a sample of stocks that are used in order purchase agreements that trade on the New York Stock Exchange (NYSE) and the Cincinnati Stock Exchange.

In September of 1996, the same group, along with Joseph B. Paperman, published a paper investigating whether differences in information-based trading could explain the observed differences in infrequently traded and active stocks. A new empirical technique was used to estimate the risk of information-based trading for a sample of NYSE listed stocks.

David Easley, Nicholas M. Kiefer and Maureen O'Hara published another paper together in Autumn of 1997. This paper used the model structure already formed by Easley and O'Hara to demonstrate how the parameters of the market-maker's beliefs could be estimated from trade data. It focused on whether large and small trades contained different information.

In April of 1998, David Easley, Maureen O'Hara and P.S. Srinivas published a paper that investigated "the informational role of transactions volume in options markets". They developed an asymmetric information model that demonstrated how informed traders might trade in option or equity markets. They showed conditions under which informed traders trade options. They also investigated the implications for this connection between markets.

David Easley, Soeren Hvidkjaer and Maureen O'Hara published a paper in October of 2002 analyzing the effect of information-based trading on asset returns. Using a rational expectation example, they showed how private information affects equilibrium asset returns. Their main result was that information does affect asset prices.

II. Cream-Skimming or Profit-Sharing? The Curious Role of Purchased Order Flow

David Easley, Nicholas M. Kiefer and Maureen O'Hara

This article begins with the discussion of the global capital markets and the striking feature of proliferation of trading venues. New markets such as Frankfurt, Milan, Madrid and Amsterdam are a few that are now challenging the dominance of established trading centers such as the London Stock Exchange. This trend is seen in the United States in the increasing volume of Nasdaq, in the dramatic growth of electronic trading systems such as the Portfolio System for Institutional Trading and Instinet and in the growth of regional exchanges such as the Arizona Stock Exchange and the Cincinnati Stock Exchange (CSE).

It is debatable whether this fragmentation of trading is desirable. "Increased competition could reduce the monopoly power of price-setting agents and thus result in better execution and prices for traders". On the other hand, this same competition also potentially limits any markets ability to provide stable prices by reducing the liquidity available in any one setting. Also, the crucial price discovery role of markets is assisted by liquidity. "As order flow fragments, the ability of prices to aggregate information can be reduced, and with it the efficiency of the market; this problem can be exacerbated if markets choose to compete by focusing on particular components of the order flow". By "cream-skimming' the order flow, the viability of old markets and the trading process itself could be undermined by new markets.

In their research, a test of the cream-skimming versus the competition issue that is not based on prices was developed. Their approach used "the more basic information in the trade flow to infer any difference in information content between trading locales". The formal structure of a market microstructure model was used to formulate the learning problem confronting agents watching the trade flow. The researchers decided that by estimating this model for a sample of stocks trading on the NYSE and an alternative site, CSE, they could determine whether the information content of trades varies by order locale. The Cincinnati Stock Exchange was chosen as an alternative because they found that the price behavior on the CSE was closest to that of the NYSE, "a pattern consistent with the Ð''free riding' on prices allegedly underlying the execution of purchased orders.

A. Hypothesis

If "cream-skimming" is the basis for purchased order flows, then the information content of orders should differ between markets. Alternatively, if purchased orders merely reflect a simple partitioning of the existing order flow, then this difference should not arise.

B. Methods for Testing Hypothesis

The first involves using restrictions of the general model to test for differences in information content between markets. The second approach uses their parameter estimates to calculate directly the probability of informed trading on each market.

C. Parameters for Each Stock

i. The probability of an information event

ii. The probability that the information is bad news

iii. The arrival rate of traders who know the new information exists (the informed

traders)

iv.

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