Market Architecture and Nonlinear Dynamics of Australian Stock and Futures Indices

Abstract

This paper studies the All Ordinaries Index in Australia, and its futures contract known as the Share Price Index. We use a new form of smooth transition model to account for a variety of nonlinearities caused by transaction costs and other market/data imperfections, and given the recent interest in the effects of market automation on price discovery, we focus on how the nonlinear properties of the basis and returns have changed, now that floor trading in the futures contract has been replaced by electronic trading.

Why Do Emerging Stock Markets Experience More Persistent Price Deviations From a Random Walk Over Time? A Country-Level Analysis

“…This occurs because investors have additional private information or different prior beliefs, or they use different models to evaluate the impact of news. Third, nonlinearity can arise due to the presence of market frictions such as transaction costs that may deter arbitrage trading [see Dwyer et al (1996); Martens et al (1998); Anderson and Vahid (2001)]. Finally, McMillan (2003) argues that the most promising explanation is the interaction between arbitrageurs and noise traders where investor cognitive biases and limits to arbitrage can give rise to nonlinearity.…”

A Partially Linear Approach to Modelling the Dynamics of Spot and Futures Prices

“…We now provide a statistical single-equation test to examine the hypothesis whether model (11) is as accurate a description of the data as model (1). Formally, we are interested in testing the hypotheses…”

A Partially Linear Approach to Modeling the Dynamics of Spot and Futures Prices

“…VAR models were introduced (e.g., Stoll & Whaley, 1990) and soon thereafter replaced by error correction (ECM) models (e.g., Wahab & Lashgari, 1993). An obvious candidate is a smooth transition error correction (STECM) model as applied by Taylor, van Dyck, Franses, and Lucas (2000), Anderson and Vahid (2001), Tse (2001), Fung and Yu (2007), and Chen, Sub Choi, and Hong (2013). This is unlikely to be the case, however.…”

“…If, on the other hand, traders are heterogeneous with respect to the transaction costs they face, a less restrictive model is warranted. An obvious candidate is a smooth transition error correction (STECM) model as applied by Taylor, van Dyck, Franses, and Lucas (2000), Anderson and Vahid (2001), Tse (2001), Fung and Yu (2007), and Chen, Sub Choi, and Hong (2013).…”