  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.
