'Learning Styles' and 'Approaches to Studying' in Sports-Related Programmes: Relationships to Academic Achievement and Implications for Successful Learning, Teaching and Assessment: Project Report Summary

There are relatively few recent investigations that have addressed the issues of preferred learning styles and approaches to studying in sports-related disciplines such as: Sports Studies; Sports and Exercise Science; Coaching Science; Sport and Leisure Management and Outdoor Recreation Management. The purpose of this study was therefore to examine student learning across a range of sport-related programmes at a UK University College. It applied tools from two related, but different, educational research paradigms: approaches to learning and learning styles analysis. Thus, these differing means of researching student learning were tested against the same student group. Results were compared to students’ perceptions of their own developing autonomy of learning and achieved grades; insights were generated into the particular learning approaches and styles of sports students; and tentative recommendations are made on the implications of the findings for higher education teachers seeking to promote improvements in the learning of sports subjects

Stochastic simulation framework for the Limit Order Book using liquidity motivated agents

In this paper we develop a new form of agent-based model for limit order books based on heterogeneous trading agents, whose motivations are liquidity driven. These agents are abstractions of real market participants, expressed in a stochastic model framework. We develop an efficient way to perform statistical calibration of the model parameters on Level 2 limit order book data from Chi-X, based on a combination of indirect inference and multi-objective optimisation. We then demonstrate how such an agent-based modelling framework can be of use in testing exchange regulations, as well as informing brokerage decisions and other trading based scenarios

Survival Models for the Duration of Bid-Ask Spread Deviations

Many commonly used liquidity measures are based on snapshots of the state of the limit order book (LOB) and can thus only provide information about instantaneous liquidity, and not regarding the local liquidity regime. However, trading in the LOB is characterised by many intra-day liquidity shocks, where the LOB generally recovers after a short period of time. In this paper, we capture this dynamic aspect of liquidity using a survival regression framework, where the variable of interest is the duration of the deviations of the spread from a pre-specified level. We explore a large number of model structures using a branch-and-bound subset selection algorithm and illustrate the explanatory performance of our model

Langevin and Hamiltonian based Sequential MCMC for Efficient Bayesian Filtering in High-dimensional Spaces

Nonlinear non-Gaussian state-space models arise in numerous applications in statistics and signal processing. In this context, one of the most successful and popular approximation techniques is the Sequential Monte Carlo (SMC) algorithm, also known as particle filtering. Nevertheless, this method tends to be inefficient when applied to high dimensional problems. In this paper, we focus on another class of sequential inference methods, namely the Sequential Markov Chain Monte Carlo (SMCMC) techniques, which represent a promising alternative to SMC methods. After providing a unifying framework for the class of SMCMC approaches, we propose novel efficient strategies based on the principle of Langevin diffusion and Hamiltonian dynamics in order to cope with the increasing number of high-dimensional applications. Simulation results show that the proposed algorithms achieve significantly better performance compared to existing algorithms

Liquidity commonality does not imply liquidity resilience commonality: A functional characterisation for ultra-high frequency cross-sectional LOB data

We present a large-scale study of commonality in liquidity and resilience across assets in an ultra high-frequency (millisecond-timestamped) Limit Order Book (LOB) dataset from a pan-European electronic equity trading facility. We first show that extant work in quantifying liquidity commonality through the degree of explanatory power of the dominant modes of variation of liquidity (extracted through Principal Component Analysis) fails to account for heavy tailed features in the data, thus producing potentially misleading results. We employ Independent Component Analysis, which both decorrelates the liquidity measures in the asset cross-section, but also reduces higher-order statistical dependencies. To measure commonality in liquidity resilience, we utilise a novel characterisation as the time required for return to a threshold liquidity level. This reflects a dimension of liquidity that is not captured by the majority of liquidity measures and has important ramifications for understanding supply and demand pressures for market makers in electronic exchanges, as well as regulators and HFTs. When the metric is mapped out across a range of thresholds, it produces the daily Liquidity Resilience Profile (LRP) for a given asset. This daily summary of liquidity resilience behaviour from the vast LOB dataset is then amenable to a functional data representation. This enables the comparison of liquidity resilience in the asset cross-section via functional linear sub-space decompositions and functional regression. The functional regression results presented here suggest that market factors for liquidity resilience (as extracted through functional principal components analysis) can explain between 10 and 40% of the variation in liquidity resilience at low liquidity thresholds, but are less explanatory at more extreme levels, where individual asset factors take effect

Loss Distribution Approach for Operational Risk Capital Modelling under Basel II: Combining Different Data Sources for Risk Estimation

The management of operational risk in the banking industry has undergone significant changes over the last decade due to substantial changes in operational risk environment. Globalization, deregulation, the use of complex financial products and changes in information technology have resulted in exposure to new risks very different from market and credit risks. In response, Basel Committee for banking Supervision has developed a regulatory framework, referred to as Basel II, that introduced operational risk category and corresponding capital requirements. Over the past five years, major banks in most parts of the world have received accreditation under the Basel II Advanced Measurement Approach (AMA) by adopting the loss distribution approach (LDA) despite there being a number of unresolved methodological challenges in its implementation. Different approaches and methods are still under hot debate. In this paper, we review methods proposed in the literature for combining different data sources (internal data, external data and scenario analysis) which is one of the regulatory requirement for AMA

Participation Motivation in Martial Artists in the West Midlands Region of England

The objectives were to identify the participation motivations and the perceived importance of certain participation factors in martial artists in the West Midlands, England, UK. A 28-item adapted version of the Participation Motivation Questionnaire with additional demographic questions was distributed to 30 martial arts clubs in the West Midlands region. Eight questions that assessed the perceived importance for participation of progression through grades, learning self defence skills, technical ability of instructors, cost of participating, development of confidence, underpinning philosophy and instructional style were included. Seventy-five questionnaires were returned from a total of 11 clubs from across representing practitioners in Tai Chi, Karate, Kung fu, Aikido, Jeet Kune Do, British Free Fighting, Taekwon-Do and Jujitsu. Results indicated that the rank order in terms of participation motives was: 1- Affiliation; 2-Friendship; 3-Fitness; 4-Reward/status; 5-Competition; 6-Situational and 7-Skill development. Participants who trained for more than 4 hours per week placed greater importance on the underpinning philosophy of the martial art. Findings suggest that whilst there is a gender discrepancy in participation level, once engaged, females were equally committed to weekly training. The ‘style’ of the instructor is of paramount importance for enhancing student motivation to participate. High volume practitioners would appear to be fully immersed in the holistic appreciation of the martial art through increased value placed on its underpinning philosophy