Testing for Evidence of Nonlinear Structure in Daily and Weekly United Kingdom Stock and Property Market Indicies

In this paper we have tested for evidence of nonlinear structure in United Kingdom asset returns including those of real estate and investment trusts, stock market indices and returns for listed real estate companies. While some of our test procedures are designed to test for nonlinear deterministic (chaotic) structure against a random alternative, others have power against nonlinear stochastic structure. If nonlinear deterministic and random walk models are not appropriate to explain asset returns behaviour, then stochastic nonlinearity seems like a logical alternative. The results from our study lead us to that conclusion.

Liquidity Costs, Idiosyncratic Volatility and Expected Stock Returns

This paper considers liquidity as an explanation for the positive association between expected idiosyncratic volatility (IV) and expected stock returns. Liquidity costs may affect the stock returns, through bid-ask bounce and other microstructure-induced noise, which will affect the estimation of IV. We use a novel method (developed by Weaver, 1991) to eliminate microstructure influences from stock closing price-based returns and then estimate IV. We show that there is a premium for IV in value-weighted portfolios, but this premium is less strong after correcting returns for microstructure bias. We further show that this premium is driven by liquidity in the prior month after correcting returns for microstructure noise. The pricing results from equally-weighted portfolios indicate that IV does not predict returns either before or after controlling for liquidity costs. These findings are robust after controlling for common risk factors as well as analysing double-sorted portfolios based on IV and liquidity

Predicting Corporate Bankruptcy Risk in Australia: A Latent Class Analysis

Abstract In this paper a latent class model (LCM) i

Bitcoin futures - what use are they?

Early analysis of Bitcoin concluded that it did not meet the economic conditions to be classified as a currency. Since this conclusion, interest in Bitcoin has increased substantially. We investigate whether the introduction of futures trading in Bitcoin is able to resolve the issues that stopped Bitcoin from being considered a currency. Our analysis shows that spot volatility has increased following the appearance of futures contracts, that futures contracts are not an effective hedging instrument, and that price discovery is driven by uninformed investors in the spot market. We therefore argue that the conclusion that Bitcoin is a speculative asset rather than a currency is not altered by the introduction of futures trading

The destabilising effects of cryptocurrency cybercriminality

This paper investigates the financial market effects of recent cybercriminality in cryptocurrency markets. Hacking events are found to increase both the price volatility of the targeted cryptocurrency and broad cross-cryptocurrency correlations. Further, cybercrime events significantly reduce price discovery sourced within the hacked currency relative to other cryptocurrencies. Finally, abnormal returns in the hours prior to the cybercrime event, revert to zero when news is publicly announced

Stylized facts of intraday precious metals

This paper examines the stylized facts, correlation and interaction between volatility and returns at the 5-minute frequency for gold, silver, platinum and palladium from May 2000 to April 2015. We study the full sample period, as well as three subsamples to determine how high-frequency data of precious metals have developed over time. We find that over the full sample, the number of trades has increased substantially over time for each precious metal, while the bid-ask spread has narrowed over time, indicating an increase in liquidity and price efficiency. We also find strong evidence of periodicity in returns, volatility, volume and bid- ask spread. Returns and volume both experience strong intraday periodicity linked to the opening and closing of major markets around the world while the bid-ask spread is at its low- est when European markets are open. We also show a bilateral Granger causality between returns and volatility of each precious metal, which holds for the vast majority subsamples

Factors Affecting the Probability of Bankruptcy

The majority of classification models developed have used a pool of financial ratios combined with statistical variable selection techniques to maximise the accuracy of the classifier being employed. Rather than follow an "ad hoc" variable selection process, this paper seeks to provide an economic basis for the selection of variables for inclusion in bankruptcy models, which are based on accounting information. Variables which occur in bankruptcy probability expressions derived from the solution of an stochastic optimising model for a firm are 'proxied' by variables constructed from financial statement data. The random nature of the life time of a single firm provides the rationale for the use of duration or hazard-based statistical methods in the validation of the derived bankruptcy probability expressions. The Cox (1972) proportional hazards model is used to estimate the coefficients and standard errors that are required for the validation of the derived bankruptcy probability expressions. Results of the validation exercise confirm that the variables included in the empirical hazard formulation behave in a way that is consistent with the model of the firm.

Asymmetry in the Business Cycle: Evidence from the Australian Labour Markets

Cyclical asymmetry has been recognised as a nonlinear phenomenonin recent studies examining unemployment rate time series. In this paper we use a number of established and new tests for identifying nonlinearities of the bilinear (BL), exponential autoregressive (EXPAR), smooth transition autoregressive (STAR), and self-exciting threshold autoregressive (SETAR) types as they occur in time series of the seasonally differenced logarithm of monthly Australian aggregate and regional unemployment rates. After identifying nonlinearity of a particular form within a given time series, the appropriate model is fitted and representations from the model analysed for their cyclical behaviour.asymmetry; unemployment; dynamic; nonlinear dependence

Testing for Nonlinearities in Economic and Financial Time Series

Cyclical asymmetry has been recognised as a nonlinear phenomenon in numerous recent studies examining various economic and financial time series. If the nonlinear phenomena can be modelled by a nonlinear stochastic structure like the bilinear (BL), exponential autoregressive (EAR), smooth transition autoregressive (STAR), or self-exciting threshold autoregressive (SETAR) types, then we need tests to enable us to identify these various nonlinear models. In this paper we suggest modifications to the Tsay (1991) general test for identifying nonlinearities of the BL, EAR, and SETAR types as they occur in time series. Our testing procedure is simulated to determine its empirical properties.