Search results

Outlines the reasons for using stochastic simulation rather than other methods for this development of a capital budgeting model to quantify the risk and uncertainty connected with establishing a new bank branch. Uses net present value (NPV) and the internal rate of return (IRR) as the profit criteria, explains the variables included in the model, expresses them as mathematical equations and determines probability distributions for those which are random. Compares the results of 5,000 iterations of the simulation for NPV/IRR values and with the evaluation criteria used by the sample bank. Shows that the model gives a better indication of the risk involved in the project.

Explains the strengths and weaknesses of neural networks and uses them to analyse racial patterns in 1994 mortgage (conventional and FHA) data for the city of Atlanta (USA). Admits the difficulty of interpreting the results of neural network models but suggests that race does have an impact on lending patterns. Compares the results from a regression analysis and finds that as the percentage black increases in a neighbourhood FHA loans increase, conventional loans decreased and conventional loans denied increase; but these trends reverse when the black percentage rises further. Considers the practical reasons for the findings and concludes that race remains an important factor in the spatial distribution of lending.

Eastern European countries are undergoing a transition from centralized economic planning to more open economic systems. A team of Bulgarian and U.S. researchers have collaborated to study this problem, using a real Bulgarian winery as the focus of their research. System dynamics modeling was selected as a tool to provide better understanding of management issues. A framework for future objective research, and as a pedagogical tool. This system dynamics model generates output on a number of measures. This paper presents initial output from the model, reporting profit ability, risk, and market share measures. These multiple measures create the need for multiple criteria analysis. Three multiple criteria techniques are demonstrated, and their value in the system dynamics simulation modeling process is discussed.

Outlines previous research relevant to the risks involved in residential mortgages and suggests some reasons for the gap between theory and market practice. Develops a model which adds household income, ability to pay problems and mortgage underwriting constraints to the standard pricing models, using a combination of Monte Carlo simulation and the backward finite difference method to apply it to data on house prices, income and interest rates for 62 US metropolitan areas. Discusses the results which suggest that prepayment risk dominates default risk in all except very low growth housing markets. Adds that increasing loan‐to‐value levels decrease loan values in low growth markets, slightly increase them in high growth/low volatility markets (due to decline in prepayment risk), but have little impact on high growth/high volatility markets (because they are offset by changes in default and prepayment costs). Considers the practical implications of the findings, e.g. for portfolio managers.

Traces the history of the Community Reinvestment Act (CRA), which requires US lenders to meet the credit needs of their local customers, and presents a study of its effect on profitability. Looks at financial institutions which received revized CRA ratings between 1990 and 1995, analysing their characteristics before and after revision, and finds upgraded banks hold more loans and are likely to be either rapidly growing and/or reaching deeper into the pool of applicants. Goes on to show that interest on CRA‐related loans is lower than on others, i.e. profitability is reduced and risk increased. Concludes that although CRA activities may open new markets and build new skills for lenders, their costs are likely to exceed their benefits for most institutions.

Outlines Warren and Shelton’s system for modelling a firm’s operations as a set of simultaneous equations, its limitations and the addition of Monte Carlo simulation into it by Coats and Chesser. Develops these ideas further and applies the new simulation model to a Greek clothing firm to test its effectiveness. Considers other possible applications, e.g. forecasting, calculating the cost of capital and valuation.

Introduces the concept of jury trial simulation and outlines a number of different techniques used. Briefly looks at the future development through new computer software and concludes that the evidence available suggests that jury trial simulation works.

Gives an in depth view of the strategies pursued by the world’s leading chief executive officers in an attempt to provide guidance to new chief executives of today. Considers the marketing strategies employed, together with the organizational structures used and looks at the universal concepts that can be applied to any product. Uses anecdotal evidence to formulate a number of theories which can be used to compare your company with the best in the world. Presents initial survival strategies and then looks at ways companies can broaden their boundaries through manipulation and choice. Covers a huge variety of case studies and examples together with a substantial question and answer section.

Summarizes the main hypotheses used in previous research on dividend policy and reports a study of patterns in dividend payouts/growth using neural networks as a data mining technique. Discusses the properties of neural networks, recognizes that they are unsuitable for hypothesis testing and uses sensitivity analysis on 1992‐1997 data from 201 US firms. Presents the results, which do not outperform a previous model based on factor analysis, finds no significant nonlinear relationship in the data; but shows that dividend variability is sensitive to input variables, especially dividend growth.

Outlines an effective procedure for recruitment. Briefly considers job analysis, methods of recruitment, methods of assessment, reference checks and job previews. Encourages employers to see this area as long term investment in their human resource portfolio.