Tests of non‐linearity using LIFFE futures transactions price data

Abstract

This paper presents and implements a number of tests for non-linear dependence and a test for chaos using transactions prices on three LIFFE futures contracts: the Short Sterling interest rate contract, the Long Gilt government bond contract, and the FTSE 100 stock index futures contract. While previous studies of high frequency futures market data use only those transactions which involve a price change, we use all of the transaction prices on these contracts whether they involve a price change or not. Our results indicate irrefutable evidence of non-linearity in two of the three contracts, although we ¢nd no evidence of a chaotic process in any of the series. We are also able to provide some indications of the e¡ect of the duration of the trading day on the degree of non-linearity of the underlying contract. The trading day for the Long Gilt contract was extended in August 1994, and prior to this date there is no evidence of any structure in the return series. However, after the extension of the trading day we do ¢nd evidence of a non-linear return structure. " IntroductionA number of recent studies have examined the possibility that economic data are non-linear. These studies question whether linear models are an adequate characterization of the data generating process, and attempt to determine whether non-linear time series models might be worthy of further investigation as forecasting tools. The discovery of a non-linear process which is chaotic, however, has even more important implications for the modelling and prediction of the series under

Linear Predictability vs. Bull and Bear Market Models in Strategic Asset Allocation Decisions: Evidence from UK Data

“…The law of motion for wealth in (8) implicitly assumes that consumption at time  and any transaction costs to be paid at time  are obtained by liquidating costlessly the risky and the riskless assets in the proportions {  }  =1 . This assumption is sensible for liquid assets, especially when they pay coupons or dividends that can be readily used to 6 In the case of a VAR(),…”

Chaos and the Dancing Stars

“…The motivation for examining whether a link exists between the ability to detect and predict chaos comes from the work of Heath (2002), who finds that some people are more sensitive to chaos than others. Since chaos is widely believed to be found in variables that are of crucial interest in business-such as financial series (ap Gwilym, Brooks, Clare & Thomas, 1999)-it is plausible to hypothesise that individuals who are more sensitive than others to chaos might be more successful than others in the functions of initiation and leadership that are characteristic of entrepreneurship.…”