MODELLING THE ADAPTATION OF BUSINESS CONTINUITY PLANNING BY BUSINESSES USING NEURAL NETWORKS

Business continuity planning is an important element of business continuity management and is regarded as a fundamental step towards reducing the negative impacts of business disruptions caused by internal and external hazardous events. Many businesses are not prepared for such events, and very few studies have tried to examine and model the factors that contribute to business continuity management planning by various companies. In this paper we propose and develop a feed‐forward neural network for modelling businesses continuity planning by businesses based on a dataset of 283 businesses operating in the Greater Toronto Area in Ontario, Canada. The fully connected neural network applied was trained on 65 % of the dataset records using different subsets of input variables. In order to preserve the generalization ability of the trained network, 15 % of the dataset records were used as a validation set for early stopping during the network's training process. Prediction capability of the trained networks was evaluated on 20 % and never‐seen records of the dataset. The classification ability of the networks was then analysed using receiver operating characteristic and detection error trade‐off curves, where the results obtained were promising. The equal error rate for the best models was 12 %, which reflects a very good accuracy of these models in predicting the existence of business continuity planning for a generic company. Copyright © 2011 John Wiley & Sons, Ltd.     

A Cramér-type large deviation theorem for sums of functions of higher order non-overlapping spacings

Let U ₁, U ₂, . . . , U _n–1 be an ordered sample from a Uniform [0,1] distribution. The non-overlapping uniform spacings of order s are defined as \({G_{i}^{(s)} =U_{is} -U_{(i-1)s}, i=1,2,\ldots,N^\prime, G_{N^\prime+1}^{(s)} =1-U_{N^\prime s}}\) with notation U ₀ = 0, U _n = 1, where \({N^\prime=\left\lfloor n/s\right\rfloor}\) is the integer part of n/s. Let \({ N=\left\lceil n/s\right\rceil}\) be the smallest integer greater than or equal to n/s, f _m (u), m = 1, 2, . . . , N, be a sequence of real-valued Borel-measurable functions. In this article a Cramér type large deviation theorem for the statistic \({f_{1,n} (nG_{1}^{(s)})+\cdots+f_{N,n} (nG_{N}^{(s)} )}\) is proved.     

The impact of news,oil prices,and global market developments on Russian financial markets1

This paper analyses the impact of news, oil prices, and international financial market developments on daily returns on Russian bond and stock markets. First, regarding returns, energy news affects returns, while news from the war in Chechnya is not significant. Market volatility does not appear to be sensitive to either type of news. Second, a significant effect of the growth in oil prices on Russian stock returns is detected. Third, the international influence on Russian financial markets depends upon the degree of financial liberalization. The higher the degree of financial liberalization, the stronger is the impact of US stock returns on Russian financial markets. In addition, banking reform and interest rate liberalization efforts seem to dictate the globalization of Russian stock markets, while it is the progress in liberalizing securities markets and non‐bank financial institutions that matters more for the globalization of Russian bond markets.     

Information flows within and across sectors in Chinese stock markets

We examine the patterns of information flows within and across sectors of the two Chinese stock exchanges in Shanghai and Shenzhen during 1994–2001. Using the generalized forecast error variance decomposition, we find a high degree of interdependence, indicating that the sectors are highly integrated and sector prices reflect information from other sectors. Industry is the most influential sector in both exchanges, while Finance in Shenzhen is the least integrated with other sectors. Implications of the findings for investors and policymakers are also discussed.     

Estimation of the scale matrix of a multivariate t-model under entropy loss

This paper deals with the estimation of the scale matrix of a multivariatet-model with unknown location vector and scale matrix to improve upon the usual estimators based on the sample sum of product matrix. The well-known results of the estimation of the scale matrix of the multivariate normal model under the assumption of entropy loss function have been generalized to that of a multivariatet-model. The paper is based on the first author’s unpublished Ph.D. dissertation ‘Estimation of the Scale Matrix of a Multivariate T-model’, University of Western Ontario, Canada. Present address: School of Mathematics and Statistics, The University of Sydney, NSW 2006, Australia.     

Do Taxes Matter for Foreign Direct Investment?

The tax sensitivity of foreign direct investment (FDI) has importantpolicy implications. If FDI is not responsive to taxation, thenit may be an appropriate target for taxation by the host country.This question is examined for Mexico by estimating the responseof FDI from retained earnings and transfers from abroad to thetax regimes in Mexico and the home country, the credit statusof multinationals, country risk factors, and regulatory andtrade regimes in Mexico. FDI in Mexico is found to be sensitiveto the tax regimes in Mexico and the United States, the creditstatus of multinationals, country credit ratings, and the regulatoryenvironment. Thus Mexico's current policies to dismantle regulationsand employ a tax system competitive with the United States areexpected to have salutory effects on FDI in Mexico.     

Pioneering Versus Incremental Innovation: Review and Research Propositions

Marketing's role in supporting a company's efforts to develop pioneering and incremental products can be quite different. Abdul Ali examines published articles and offers a set of propositions to show how several factors influence the product development decision. He cites examples from the business world to illustrate these propositions. This article suggests that a firm should take into account several factors relating to its capabilities, along with various project and market characteristics, in order to decide what products it should develop.     

Real (adaptation) options and the valuation of equity: some empirical evidence

Data from 1,374 firms across four broad industrial groupings are used to assess the contribution that real (adaptation) options make to overall equity values. The analysis indicates that real (adaptation) options make a significant contribution to the equity value of firms with a market to book ratio (of equity) of around unity or less. As the market to book ratio grows beyond this level, however, the contribution made by real (adaptation) options decays quickly away and equity values are mainly comprised of the present value of the dividends that firms are expected to pay. This means that for around one in every five of the firms in our sample real (adaptation) options make a significant contribution to overall equity value. Thus, while linear equity valuation models would seem to be appropriate for the substantial majority of firms on which our sample is based, there is a sizeable minority of firms where real (adaptation) options have a significant impact on equity values. For this latter group of firms there will be a non-linear relationship between equity value and its determining variables. This has important implications for the regression procedures that are applied in this area of accounting research.