Evaluating multivariate volatility forecasts : how effective are statistical and economic loss functions?

Multivariate volatility forecasts are an important input in many financial applications, in particular portfolio optimisation problems. Given the number of models available and the range of loss functions to discriminate between them, it is obvious that selecting the optimal forecasting model is challenging. The aim of this thesis is to thoroughly investigate how effective many commonly used statistical (MSE and QLIKE) and economic (portfolio variance and portfolio utility) loss functions are at discriminating between competing multivariate volatility forecasts. An analytical investigation of the loss functions is performed to determine whether they identify the correct forecast as the best forecast. This is followed by an extensive simulation study examines the ability of the loss functions to consistently rank forecasts, and their statistical power within tests of predictive ability. For the tests of predictive ability, the model confidence set (MCS) approach of Hansen, Lunde and Nason (2003, 2011) is employed. As well, an empirical study investigates whether simulation findings hold in a realistic setting. In light of these earlier studies, a major empirical study seeks to identify the set of superior multivariate volatility forecasting models from 43 models that use either daily squared returns or realised volatility to generate forecasts. This study also assesses how the choice of volatility proxy affects the ability of the statistical loss functions to discriminate between forecasts. Analysis of the loss functions shows that QLIKE, MSE and portfolio variance can discriminate between multivariate volatility forecasts, while portfolio utility cannot. An examination of the effective loss functions shows that they all can identify the correct forecast at a point in time, however, their ability to discriminate between competing forecasts does vary. That is, QLIKE is identified as the most effective loss function, followed by portfolio variance which is then followed by MSE. The major empirical analysis reports that the optimal set of multivariate volatility forecasting models includes forecasts generated from daily squared returns and realised volatility. Furthermore, it finds that the volatility proxy affects the statistical loss functions��� ability to discriminate between forecasts in tests of predictive ability. These findings deepen our understanding of how to choose between competing multivariate volatility forecasts.

‘Just stupid drama queens’ : how police constrain, regulate, and punish the public visibilities of sexual/gender diversity as out of place

Using interview data on LGBT young peoples’ policing experiences, I argue policing practices work to constrain public visibilities of sexual and gender diversity in public spaces. Police actions recounted by LGBT young people suggest the workings of a certain kind of visuality (Mason, 2002) and evidenced more subtle actions that sought to constrain, regulate, and punish public visibilities of sexual and gender diversity. Aligning with the work of sexualities academics and theorists, this paper suggests that, like violence is itself a bodily spectacle from which onlookers come to know things, policing works to subtly constrain public visibilities of “queerness”. Policing interactions with LGBT young people serves the purpose of visibly yet unverifiably (Mason, 2002) regulating displays of sexual and gender diversity in public spaces. The paper concludes noting how police actions are nonetheless visible and therefore make knowable to the public the importance of keeping same sex intimacy invisible in public spaces.

Investigative thinking and creativity : an empirical study of police detectives in Norway

This paper makes distinctions among four investigative thinking styles of detectives: method style, challenge style, skill style, and risk style. Based on previous research, this study empirically tested, to what extent there are cumulative relationships among these thinking styles. Furthermore, this research studied relationships between investigative thinking styles and creativity in police investigations. Significant relationships were found between the extent of the challenge and risk styles and the extent of creativity.

Knowledge management in law enforcement : knowledge views for patrolling police officers

This paper describes and classifies different types of knowledge that are a part of police patrol officer's practice. Even though an investigation usually forces a police officer to apply several different knowledge types, this paper discusses different forms of professional knowledge separately to enable categorisation.

Knowledge management in policing : the case of police complaints and police crime

This article is concerned with knowledge management in policing police crime. Police crime is defined as crime committed by police officers on duty. There seems to be a tendency to consider police crime as a result of bad practice rather than the acts of criminals. However, examples illustrate that criminal acts are intentionally carried out by police officers on duty. The article looks at the kinds of knowledge which agencies require to investigate police complaints and police crime successfully.

Continuum of police crime : an empirical study of court cases

The great majority of police officers are committed to honourable and competent public service and consistently demonstrate integrity and accountability in carrying out the often difficult, complex and sometimes dangerous, activities involved in policing by consent. However, in every police agency there exists an element of dishonesty, lack of professionalism and criminal behaviour. This article is based on archival research of criminal behaviour in the Norwegian police force. A total of 60 police employees were prosecuted in court because of misconduct and crime from 2005 to 2010. Court cases were coded as two potential predictors of court sentence in terms of imprisonment days, ie, type of deviance and level of deviance. Categories of police crime and levels were organised according to a conceptual framework developed for assessing and managing police deviance. Empirical findings support the hypothesis that as the seriousness of police crime increases in breadth and depth so also does the severity of the court sentence as measured by time in prison.

Resilience of a corrupt police network : the first and second jokes in Queensland

Resilient organised crime groups survive and prosper despite law enforcement activity, criminal competition and market forces. Corrupt police networks, like any other crime network, must contain resiliency characteristics if they are to continue operation and avoid being closed down through detection and arrest of their members. This paper examines the resilience of a large corrupt police network, namely The Joke which operated in the Australian state of Queensland for a number of decades. The paper uses social network analysis tools to determine the resilient characteristics of the network. This paper also assumes that these characteristics will be different to those of mainstream organised crime groups because the police network operates within an established policing agency rather than as an independent entity hiding within the broader community.

The motivation and structure of corrupt police networks : theorising the dark side of the ‘thin blue line’

In recent times considerable research attention has been directed to understanding dark networks, especially criminal and terrorist networks. Dark networks are those in which member motivations are self rather than public interested, achievements come at the cost of other individuals, groups or societies and, in addition, their activities are both ‘covert and illegal’ (Raab & Milward, 2003: 415). This ‘darkness’ has implications for the way in which these networks are structured, the strategies adopted and their recruitment methods. Such entities exhibit distinctive operating characteristics including most notably the tension between creating an efficient network structure while retaining the ability to hide from public view while avoiding catastrophic collapse should one member cooperate with authorities (Bouchard 2007). While theoretical emphasis has been on criminal and terrorist networks, recent work has demonstrated that corrupt police networks exhibit some distinctive characteristics. In particular, these entities operate within the shadows of a host organisation - the Police Force and distort the functioning of the ‘Thin Blue Line’ as the interface between the law abiding citizenry and the criminal society. Drawing on data derived from the Queensland Fitzgerald Commission of Enquiry into Police Misconduct and related documents, this paper examines the motivations, structural properties and operational practices of corrupt police networks and compares and contrasts these with other dark networks with ‘bright’ public service networks. The paper confirms the structural differences between dark corrupt police networks and bright networks and suggests. However, structural embeddedness alone is found to be an insufficient theoretical explanation for member involvement in networks and that a set of elements combine to impact decision-making. Although offering important insights into network participation, the paper’s findings are especially pertinent in identifying additional points of intervention for police corruption networks.

Police misconduct and crime : bad apples or systems failure?

There is a debate in the research literature whether to view police misconduct and crime as acts of individuals perceived as 'rotten apples' or as an indication of systems failure in the police force. Based on an archival analysis of court cases where police employees were prosecuted, this paper attempts to explore the extent of rotten apples versus systems failure in the police. Exploratory research of 57 prosecuted police officers in Norway indicate that there were more rotten apple cases than system failure cases. The individual failures seem to be the norm rather than the exception of ethical breaches, therefore enhancing the rotten apple theory. However as exploratory research, police crime may still be explained at the organizational level as well.

Organization and management of police

To understand the nature of police organisations and their management in an Australian context it is necessary to appreciate the recent history of policing at least in the last 30 years. In doing so an overall perspective is gained on the various reform efforts and organisational changes that have taken place in Australian policing. With this police reform perspective clearly in mind it then becomes possible to appreciate that the organization and management of the institution of policing in Australia is nested within the larger framework of ‘governance’. Hence, this notion of governance will be used as the key focal point around which to understand how police organizations manage their mission in the Australian context. Finally, the chapter discusses the inevitable ‘tension spaces’ that arise in policing and the need for police organizations to better manage such complexities.

Event-related brain potentials dissociate the developmental time-course of automatic numerical magnitude analysis and cognitive control functions during the first three years of primary school

In this study we set out to dissociate the developmental time course of automatic symbolic number processing and cognitive control functions in grade 1-3 British primary school children. Event-related potential (ERP) and behavioral data were collected in a physical size discrimination numerical Stroop task. Task-irrelevant numerical information was processed automatically already in grade 1. Weakening interference and strengthening facilitation indicated the parallel development of general cognitive control and automatic number processing. Relationships among ERP and behavioral effects suggest that control functions play a larger role in younger children and that automaticity of number processing increases from grade 1 to 3.

Structural damage detection using frequency response functions and neural networks

This paper illustrates the damage identification and condition assessment of a three story bookshelf structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). A major obstacle of using measured frequency response function data is a large size input variables to ANNs. This problem is overcome by applying a data reduction technique called principal component analysis (PCA). In the proposed procedure, ANNs with their powerful pattern recognition and classification ability were used to extract damage information such as damage locations and severities from measured FRFs. Therefore, simple neural network models are developed, trained by Back Propagation (BP), to associate the FRFs with the damage or undamaged locations and severity of the damage of the structure. Finally, the effectiveness of the proposed method is illustrated and validated by using the real data provided by the Los Alamos National Laboratory, USA. The illustrated results show that the PCA based artificial Neural Network method is suitable and effective for damage identification and condition assessment of building structures. In addition, it is clearly demonstrated that the accuracy of proposed damage detection method can also be improved by increasing number of baseline datasets and number of principal components of the baseline dataset.

Structural damage identification with noise polluted Frequency Response Functions (FRFs)

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, very few attempts have been made to explore the structure damage with noise polluted data which is unavoidable effect in real world. The measurement data are contaminated by noise because of test environment as well as electronic devices and this noise tend to give error results with structural damage identification methods. Therefore it is important to investigate a method which can perform better with noise polluted data. This paper introduces a new damage index using principal component analysis (PCA) for damage detection of building structures being able to accept noise polluted frequency response functions (FRFs) as input. The FRF data are obtained from the function datagen of MATLAB program which is available on the web site of the IASC-ASCE (International Association for Structural Control– American Society of Civil Engineers) Structural Health Monitoring (SHM) Task Group. The proposed method involves a five-stage process: calculation of FRFs, calculation of damage index values using proposed algorithm, development of the artificial neural networks and introducing damage indices as input parameters and damage detection of the structure. This paper briefly describes the methodology and the results obtained in detecting damage in all six cases of the benchmark study with different noise levels. The proposed method is applied to a benchmark problem sponsored by the IASC-ASCE Task Group on Structural Health Monitoring, which was developed in order to facilitate the comparison of various damage identification methods. The illustrated results show that the PCA-based algorithm is effective for structural health monitoring with noise polluted FRFs which is of common occurrence when dealing with industrial structures.

The effectiveness of traffic policing in reducing traffic crashes

Many governments throughout the world rely heavily on traffic law enforcement programs to modify driver behaviour and enhance road safety. There are two related functions of traffic law enforcement, apprehension and deterrence, and these are achieved through three processes: the establishment of traffic laws, the policing of those laws, and the application of penalties and sanctions to offenders. Traffic policing programs can vary by visibility (overt or covert) and deployment methods (scheduled and non-scheduled), while sanctions can serve to constrain, deter or reform offending behaviour. This chapter will review the effectiveness of traffic law enforcement strategies from the perspective of a range of high-risk, illegal driving behaviours including drink/drug driving, speeding, seat belt use and red light running. Additionally, this chapter discusses how traffic police are increasingly using technology to enforce traffic laws and thus reduce crashes. The chapter concludes that effective traffic policing involves a range of both overt and covert operations and includes a mix of automatic and more traditional manual enforcement methods. It is important to increase both the perceived and actual risk of detection by ensuring that traffic law enforcement operations are sufficiently intensive, unpredictable in nature and conducted as widely as possible across the road network. A key means of maintaining the unpredictability of operations is through the random deployment of enforcement and/or the random checking of drivers. The impact of traffic enforcement is also heightened when it is supported by public education campaigns. In the future, technological improvements will allow the use of more innovative enforcement strategies. Finally, further research is needed to continue the development of traffic policing approaches and address emerging road safety issues.