Strategic Trading in Informationally Complex Environments
We study trading behavior and the properties of prices in informationally complex markets.
Our model is based on the single-period version of the linear-normal framework of Kyle (1985).
We allow for essentially arbitrary correlations among the random variables involved in the model:
the value of the traded asset, the signals of strategic traders and competitive market makers, and
the demand from liquidity traders. We show that there always exists a unique linear equilibrium,
characterize it analytically, and illustrate its properties with a number of applications. We
then use this characterization to study the informational efficiency of prices as the number of
strategic traders becomes large. If liquidity demand is positively correlated (or uncorrelated)
with the asset value, then prices in large markets aggregate all available information. If liquidity
demand is negatively correlated with the asset value, then prices in large markets aggregate all
information except that contained in liquidity demand.
The general issues of determining the liquidation value are discussed, such as the choice of market liquidity risk model and the choice of a price benchmark for estimating transaction costs. The layout for the portfolio management process is proposed which is grounded on a previously developed approach to determining the liquidation value of a portfolio. It allows not only defining and linking the rational liquidation strategies for different time horizons but also considering some microstructural effects, such as volatility momentum, corresponding to the intervals between trading sessions.
Research of nonlinear dynamics of finance series has been widely discussed in literature since the 1980s with chaos theory as the theoretical background. Chaos methods have been applied to the S&P 500 stock index, stock returns from the UK and American markets, and portfolio returns. This work reviews modern methods as indicators of nonlinear stochastic behavior and also shows some empirical results for MICEX stock market high-frequency microstructure variables such as stock price and return, price change, spread and relative spread. It also implements recently developed recurrence quantification analysis approaches to visualize patterns and dependency in microstructure data.
The paper analyses applicability of the market multipliers for the diagnostics of overheating of the stock market and the formation of a financial bubble. Advantages and shortcomings of employed multipliers are discussed Historical averages of multipliers are provided. Examples are given of diagnosing the overvaluation by using the multipliers. The author concludes concludes that the optimal multiplier for estimating the overvaluation of the stock market is the P/E coefficient, however other coefficients can also be used if their limitations are taken into account.
Relaxation time is one of the most significant aspects of market liquidity. We study estimates of relaxation time of the limit order market after a shock triggered by sudden movement of price, large trade or news. We also provide formal definition of a shock on order-driven market.
This paper reviews the contribution of Eugene Fama, Lars Hansen and Robert Shiller to financial asset pricing research. We show how the Nobel prize winners have changed the approach to asset pricing research, as well as the views of academic economists and investors about price predictability and the risk-return relationship.