Improved goodness-of-fit measures

New goodness-of-fit measures which are significant improvements on existing measures are described. They use the intuitive geometrical concept of the area enclosed by the curve of a fitted distribution and the profile of the empirical cumulative distribution function.A transformation of this profile simplifies the geometry and provides three new goodness-of-fit tests. The integrity of this transformation is justified by topological arguments. The new tests provide a quantitative justification for qualitative judgements on goodness-of-fit, are independent of population size and provide a workable way to objectively choose a best fit distribution from a group of candidate distributions

Adaptive risk consensus models: simulations and applications

A simulation framework that implements adaptive agent–agent interaction is developed, such that agent behaviour typical of complex adaptive systems is observed. Within this framework, agents monitor the state of the system they inhabit, and adapt their actions so as to optimise a local utility. No central control is present. The context for state is intended to be very general, but is interpreted as risk state, in which optimisation implies a minimisation of risk. Three adaptive interaction modes are proposed. In each, there is a trade-off between simplicity and effectiveness. Additionally a fourth ‘counter-adaptive’ mode is proposed to model situations of a prolonged high risk state. Corresponding ‘real’ examples from recent events are proposed

Systemic shock propagation in a complex system

We study the effects of delivering a shock to a complex system comprising components (‘agents’) that interact in a pairwise fashion, independent of other parts of the system and with no central control. There are three aspects to the contribution of this paper. First, shock propagation in a network is developed purely from fundamental principles of complex systems. Second, systemic risk is shown to arise naturally in such a complex system. If a shock is delivered either to one agent or to many agents simultaneously, that shock may be transmitted further, thereby resulting in systemic risk. Third, the monetary loss to the entire system as a result of systemic shock is quantified. Simulations are used to study two particular characteristics of the interactions. The first is the resistance or susceptibility of individual agents to a shock. The second is the time it takes for the shock to affect the entire system. The results show that if a shock is applied to all agents in a network, the systemic effect of that shock is transmitted very quickly. Applying a shock to very few agents results only in an idiosyncratic effect. If an agent can transmit the shock further, a systemic effect will result. The recovery period for agents affected by a systemic shock can be orders of magnitude greater than the time taken for the shock to take effect. The overall effect of the shock on the system is quantified by formulating a ‘contagion index’, which measures the ratio of the total capital lost due to the systemic effect to the total capital before the shock was delivered. The result (approximately 7%) is consistent with other studies, but is more widely applicable because it is not based on one empirical data set

Symbolic-Numeric Option Valuation

Techniques for option valuation, both analytic and numeric, are well-established. Many of them cannot be used if the nature of the option is such that knowledge of the future is a prerequisite for valuation. For example, the value when the option expires may depend on the price of the underlying asset during the lifetime of the option. This paper describes a method of overcoming this problem by manipulating a symbolic parameter in a numeric scheme. This parameter characterises the option price at any stage in its lifetime as a function of the price history of the underlying asset. Certain options may then be valued by symbolic manipulations involving this parameter, such that it is not necessary to know a numerical value for a parameter in advance. This enables a limited amount of 'path-dependency' to be introduced into option valuation when using established numerical techniques, which has hitherto been very difficult or impossible

Estimation of value-at-risk for conduct risk losses using pseudo-marginal Markov chain Monte Carlo

We propose a model for conduct risk losses, in which conduct risk losses are characterized by having a small number of extremely large losses (perhaps only one) with more numerous smaller losses. It is assumed that the largest loss is actually a provision from which payments to customers are made periodically as required. We use the pseudo-marginal (PM) Markov chain Monte Carlo method to decompose the largest loss into smaller partitions in order to estimate 99.9% value-at-risk. The partitioning is done in a way that makes no assumption about the size of the partitions. The advantages and problems of using this method are discussed. The PM procedures were run on several representative data sets. The results indicate that, in cases where using approaches such as calculating a Monte Carlo-derived loss distribution yields a result that is not consistent with the risk profile expressed by the data, using the PM method yields results that have the required consistency

AMK: An Interface For Object-oriented Newtonian Particle Mechanics

This article describes an object-oriented environment with an associated user interface, AMK, for modelling simple Newtonian particle mechanics. It is intended for educational use, and provides a framework for modelling which generalises methodology. Physical objects are treated as logical objects, and mathematical models are formulated by linking them. The implementation is within the Windows environment using Mathematica and Visual Basic. Modelling is done by constructing objects and linking them to produce new objects. The aim is to produce an equation of motion object. The interface forces the user into a modelling cycle of constructing and linking objects, and accessing their methods. It constructs a Mathematica input automatically from information supplied by the user, and communicates with Mathematica. The combination of a generalised environment plus interface produces correct answers when modelling many specific physical systems

Influence of Intra-cell Traffic on the Output Power of Base Station in GSM

In this paper we analyze the influence of intracell traffic in a GSM cell on the base station output power. It is proved that intracell traffic increases this power. If offered traffic is small, the increase of output power is equal to the part of intracell traffic. When the offered traffic and, as the result, call loss increase, the increase of output power becomes less. The results of calculation are verified by the computer simulation of traffic process in the GSM cell. The calculation and the simulation consider the uniform distribution of mobile users in the cell, but the conclusions are of a general nature

Standardised Reputation Measurement

Well-defined formal definitions for sentiment and opinion are extended to incorporate the necessary elements to provide a formal quantitative definition of reputation. This definition takes the form of a time-based index, in which each element is a function of a collection of opinions mined during a given time period. The resulting formal definition is validated against informal notions of reputation. Practical aspects of data procurement to support such a reputation index are discussed. The assumption that all mined opinions comprise a complete set is questioned. A case is made that unexpressed positive sentiment exists, and can be quantified.Comment: 8 pages, submitted to IDEAL 2017, October/November Guilin Chin

Differences in the Psychological Profiles of Elite and Non-elite Athletes

One of the main goals of sport psychology is to identify those psychological factors that are relevant for sport performance as well as possibilities of their development. The aim of the study was to determine whether the set of specific psychological characteristics [generalized self-efficacy, time perspective, emotional intelligence (EI), general achievement motivation, and personality dimensions] makes the distinction between athletes based on their (non)-participation in the senior national team, that is, their belonging to the subsample of elite or non-elite athletes depending on this criterion. According to the group centroids it can be said that elite athletes are characterized by a positive high score in self-efficacy, emotionality, present fatalistic time perspective, past positive time perspective, and openness to experience. They are also characterized by low past negative time perspective, emotional competence, and future time perspective. Non-elite athletes have the opposite traits. The results have been discussed in the context of their application in the process of talent selection and development in sport as well as the development of life skills in athletes