Information-Based Asset Pricing and Market Information Flows
Summary
This paper surveys an asset-pricing approach in which an asset is defined by its cash flows and market participants receive incomplete information about those future payments. Independent market factors determine the cash flows, while information processes combine signals about those factors with market noise. Prices follow from risk-neutral expectations of discounted cash flows conditional on the information available to the market. When noise is modelled with Brownian bridges, the framework yields explicit asset-price formulas and semi-analytic option prices and sensitivities.
The paper also describes using option prices to infer parameters governing information flow, and derives stochastic volatility and correlation dynamics from assumptions about cash flows rather than imposing them directly. It then considers asymmetric information, a model of informed traders that can support statistical-arbitrage analysis, and price formation among heterogeneous agents. The excerpt is an overview and does not report empirical tests or trading performance. Its conclusions depend on the information-process assumptions, and the stated analytical results may not transfer directly to settings with different noise or information structures.
Key ideas
- Asset prices are conditional risk-neutral expectations of discounted cash flows given market information.
- Information processes combine signals about cash-flow factors with market noise.
- Brownian bridge noise can produce explicit prices and semi-analytic option values and sensitivities.
- Option data can be used to infer parameters governing information flow.
- The framework derives volatility and correlation dynamics from cash-flow assumptions and considers informed trading.
Tags
Full text
# Modelling Information Flows in Financial Markets # Modelling Information Flows in Financial Markets This paper presents an overview of information-based asset pricing. In this approach, an asset is defined by its cash-flow structure. The market is assumed to have access to "partial" information about future cash flows. Each cash flow is determined by a collection of independent market factors called X-factors. The market filtration is generated by a set of information processes, each of which carries information about one of the X-factors, and eventually reveals the X-factor. Each information process has two terms, one of which contains a "signal" about the associated X-factor, and the other of which represents "market noise". The price of an asset is given by the expectation of the discounted cash flows in the risk-neutral measure, conditional on the information provided by the market. When the market noise is modelled by a Brownian bridge one is able to construct explicit formulae for asset prices, as well as semi-analytic expressions for the prices and greeks of options and derivatives. In particular, option price data can be used to determine the information flow-rate parameters implicit in the definitions of the information processes. One consequence of the modelling framework is a specific scheme of stochastic volatility and correlation processes. Instead of imposing a volatility and correlation model upon the dynamics of a set of assets, one is able to deduce the dynamics of the volatilities and correlations of the asset price movements from more primitive assumptions involving the associated cash flows. The paper concludes with an examination of situations involving asymmetric information. We present a simple model for informed traders and show how this can be used as a basis for so-called statistical arbitrage. Finally, we consider the problem of price formation in a heterogeneous market with multiple agents.
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