Disagreement in a Multi-Asset Market

This paper provides a simple framework to study the effect of disagreement in a multi-asset market equilibrium by considering two agents who disagree about expected returns, variances, and correlation of returns of two risky assets. When agents' subjective beliefs are characterized by mean preserving spreads of a benchmark homogeneous belief, we show that the effect of the disagreement does not cancel out in general and the effect in a multi-asset market can be very different from a single asset market. In particular, the market risk premium can increase and the risk-free rate can decrease significantly even when the market is overoptimistic and overconfident. © International Review of Finance Ltd. 2012

Boundedly rational equilibrium and risk premium

When people agree to disagree, the impact of the disagreement among agents on the market is the main concern of this paper. With the standard mean variance framework, this paper considers a market of two risky assets and two agents who have different preference and disagreement about the mean and variance/covariance of the asset returns. By constructing a consensus belief, the paper develops an concept of boundedly rational equilibrium (BRE) to characterize the market equilibrium and examines explicitly the impact of heterogeneity on the market equilibrium and risk premium when the disagreements among the two agents are mean preserved spreads of a benchmark homogeneous belief. It shows that, in market equilibrium, the biased mean preserved spreads in beliefs among the two agents have significant impact on the risk premium of the risky assets and market portfolio, and adding a riskless asset in the market magnifies the impact of the heterogeneity on the market. The results show that both optimism/pessemism and confidence/doubt can increase the market risk premium and reduce the riskfree rate. © 2011 The Authors. Accounting and Finance © 2011 AFAANZ

Index portfolio and welfare analysis under heterogeneous beliefs

© 2016 Elsevier B.V. With a growing popularity of index funds, we adopt a differences-in-opinion, general equilibrium framework to examine theoretically whether investors are better off with an index portfolio than active investing. In contrary to the conventional view, we find that, even for an active investor with the most accurate belief, switching to an index portfolio can significantly improve his expected ex-post welfare when the active investors have incorrect beliefs or face incomplete information. Moreover, the welfare improvement becomes more substantial when the active investors are more risk averse

Optimal time series momentum

We develop a continuous-time asset price model to capture the time series momentum documented recently. The underlying stochastic delay differential system facilitates the analysis of effects of different time horizons used by momentum trading. By studying an optimal asset allocation problem, we find that the performance of time series momentum strategy can be significantly improved by combining with market fundamentals and timing opportunity with respect to market trend and volatility. Furthermore, the results also hold for different time horizons, the out-of-sample tests and with short-sale constraints. The outperformance of the optimal strategy is immune to market states, investor sentiment and market volatility

A behavioural model of investor sentiment in limit order markets

© 2016 Informa UK Limited, trading as Taylor & Francis Group. By incorporating behavioural sentiment in a model of a limit order market, we show that behavioural sentiment not only helps to replicate most of the stylized facts in limit order markets simultaneously, but it also plays a unique role in explaining those stylized facts that cannot be explained by noise trading, such as fat tails in the return distribution, long memory in the trading volume, an increasing and non-linear relationship between trade imbalance and mid-price returns, as well as the diagonal effect, or event clustering, in order submission types. The results show that behavioural sentiment is an important driving force behind many of the well-documented stylized facts in limit order markets

Dimension reduction based on canonical correlation

Dimension reduction is helpful and often necessary in exploring nonlinear or nonparametric regression structures with a large number of predictors. We consider using the canonical variables from the design space whose correlations with a spline basis in the response space are significant. The method can be viewed as a variant of sliced inverse regression (SIR) with simple slicing replaced by B-spline basis functions. The asymptotic distribution theory we develop extends to weakly dependent stationary sequences and enables us to consider asymptotic tests that are useful in determining the number of significant dimensions for modeling. We compare several tests for dimensionality and make specific recommendations for dimension selection based on our theoretical and empirical studies. These tests apply to any form of SIR. The methodology and some of the practical issues are illustrated through a tuition study of American colleges.published_or_final_versio