Modelling and forecasting liquidity supply using semiparametric factor dynamics

We model the dynamics of ask and bid curves in a limit order book market using a dynamic semiparametric factor model. The shape of the curves is captured by a factor structure which is estimated nonparametrically. Corresponding factor loadings are modelled jointly with best bid and best ask quotes using a vector error correction specification. Applying the framework to four stocks traded at the Australian Stock Exchange (ASX) in 2002, we show that the suggested model captures the spatial and temporal dependencies of the limit order book. We find spill-over effects between both sides of the market and provide evidence for short-term quote predictability. Relating the shape of the curves to variables reflecting the current state of the market, we show that the recent liquidity demand has the strongest impact. In an extensive forecasting analysis we show that the model is successful in forecasting the liquidity supply over various time horizons during a trading day. Moreover, it is shown that the model's forecasting power can be used to improve optimal order execution strategies.     

Intraweek and intraday trade anomalies: evidence from FOREX market

In this article, we search for the evidence of intraweek and intraday anomalies on the spot foreign exchange (FOREX) market. Having in mind the international scope of this market, empirical evidence against market efficiency (i.e. market anomalies) will have important consequences for the substantial number of FOREX investors all around the globe. We explore intraweek, intraday and interaction between days and hour trade anomalies on the FOREX market over the period of 10 years using hourly time-series data of Euro and US Dollar (EUR/USD) exchange rate on Swiss FOREX market from 1 January 2004 to 11 January 2014. We compare by analysis of variance test all pairs of mean returns on a daily, hourly and daily/hourly basis. t-Test is used to test whether intraday returns are significantly different from zero. We employ Tukey’s honestly significant difference test to explore which intraday pairs of hourly mean returns are significantly greater than zero. We find that intraday and interaction between day and hour anomalies are present in trading EUR/USD on the spot FOREX market over the period of 10 years. The best arbitrage opportunity is evidenced on Fridays, when selling USD and buying EUR at 00:00 and selling EUR and buying USD at 03:00 the same day.     

Local Adaptive Multiplicative Error Models for High‐Frequency Forecasts

We propose a local adaptive multiplicative error model (MEM) accommodating time‐varying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data‐driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time. Analysing 1‐minute cumulative trading volumes of five large NASDAQ stocks in 2008, we show that local windows of approximately 3 to 4 hours are reasonable to capture parameter variations while balancing modelling bias and estimation (in)efficiency. In forecasting, the proposed adaptive approach significantly outperforms a MEM where local estimation windows are fixed on an ad hoc basis. Copyright © 2014 John Wiley & Sons, Ltd.     

Technostress from a Neurobiological Perspective

Despite the positive impact of information and communication technology (ICT) on an individual, organizational, and societal level (e.g., increased access to information, as well as enhanced performance and productivity), both scientific research and anecdotal evidence indicate that human-machine interaction, both in a private and organizational context, may lead to notable stress perceptions in users. This type of stress is referred to as technostress. A review of the literature shows that most studies used questionnaires to investigate the nature, antecedents, and consequences of technostress. Despite the value of the vast amount of questionnaire-based technostress research, we draw upon a different conceptual perspective, namely neurobiology. Specifically, we report on a laboratory experiment in which we investigated the effects of system breakdown on changes in users’ levels of cortisol, which is a major stress hormone in humans. The results of our study show that cortisol levels increase significantly as a consequence of system breakdown in a human-computer interaction task. In demonstrating this effect, our study has major implications for ICT research, development, management, and health policy. We confirm the value of a category of research heretofore largely neglected in ICT-related disciplines (particularly in business and information systems engineering, BISE, as well as information systems research, ISR), and argue that future research investigating human-machine interactions should consider the neurobiological perspective as a valuable complement to traditional concepts.