Global client's demands driving change in global business advisory firms
David M. Brock, Michael J. Powell, C. R. Hinings in Restructuring the Professional Organization, 2012
Since the late 1960s, a variety of writers in international business have outlined the evolution of the multinational enterprise. Vernon (1966) suggested that after developing home markets a firm expands through exports, then moves to production facilities in new markets. It sets up local subsidiaries producing at low cost locations. Stopford and Wells (1972) suggested that movement is from international divisions, to area divisions, to a worldwide product division with a global matrix structure. Recently Buckley and Casson (1998) have argued that a new research agenda on MNEs has emerged in the 1990s. They suggest: The new agenda emphasizes dynamic issues. It highlights the uncertainty that is generated by volatility in the international business environment. To cope with volatility, corporate strategies have to be flexible and flexibility can be achieved by several means. New dimensions of corporate strategy therefore have to be recognized.(pp. 21–22)
Rationale and technique of malaria control
David A Warrell, Herbert M Gilles in Essential Malariology, 2017
These insecticides act slowly and some of them irritate the mosquitoes, leading to their flight towards the light out of the house. The fate of the mosquitoes after that depends on whether or not they take away a small quantity of insecticide on their legs (tarsi). Crystals formed after the evaporation of the solvents used in solutions and emulsions vary in size, but the range of insecticide particles in a wettable powder formulation is determined in the course of manufacture and is standardized to a specification that can be checked by suitable suspensibility tests to ensure optimum size for biological effectiveness. Volatility is important because a volatile product disappears in time whatever the quality of the wall, but exerts some fumigant effect, which will kill insects not in actual contact.
Quality Control of Herbal Medicine
Ravindra Kumar Pandey, Shiv Shankar Shukla, Amber Vyas, Vishal Jain, Parag Jain, Shailendra Saraf in Fingerprinting Analysis and Quality Control Methods of Herbal Medicines, 2018
The following predictable changes may occur in an herbal medicinal product during storage and in shelf life determination: hydrolysis, oxidation, racemization, geometric isomerization, temperature, moisture, and light. Environmental factors such as temperature, light, air (specifically oxygen, carbon dioxide, and water vapor), and humidity can affect stability. Similarly, factors such as particle size, pH, the properties of water and other solvents employed, the nature of container, and the presence of other chemicals resulting from contamination or from the intentional mixing of different products can influence stability (Figure 7.1). Physical instability is one of the major problems related to the stability of herbal products. This is due to the presence of impurities and reactions with the container. Volatility is the problem related to the active components of natural medicine and their decreasing activity during storage for a long time. The rate of chemical reaction increases with an increase in temperature and this leads to degradation of quality. Thus, this tropical area must be taken into consideration during preparation of the formula of the herbal substance. Moisture absorbed on the surface of a solid drug will often increase the rate of decomposition if it is susceptible to hydrolysis. Many types of chemical reactions are induced by exposure to light of high energy. Autoxidation of volatile oil/fixed oil takes place and the substance becomes colored.
A closed testing procedure for comparison between successive variances
Published in Journal of Applied Statistics, 2020
Navdeep Singh, Parminder Singh
Many statistical inference procedures assume equality of variances across the populations under comparison. For example, the classical analysis of variance procedure assumes the equality of variances of populations and the procedure is not robust when there is a deviation from the assumption. Also, in many studies, it is common to know whether there is equality among the variances of several populations. For example, in stock prices data analysis, one would like to know about the volatility in the prices over different periods of time. Bartlett [1] proposed a test procedure for testing the equality of 9] proposed a test procedure for testing the homogeneity of variances which is a robust test under the deviation from normality. In many experimental studies, it is natural to assume either increasing or decreasing trend in variances, see Noguchi and Gel [11]. In such a situation, an experimenter wishes to test the null hypothesis of homogeneity of variances against the alternative hypothesis of a monotonic trend (increasing or decreasing) in variances. Fujino [3] proposed a test procedure for testing the null hypothesis of equality of
Robust and efficient estimation of GARCH models based on Hellinger distance
Published in Journal of Applied Statistics, 2022
Qiang Zhao, Liang Chen, Jingjing Wu
In this section we demonstrate the implementation of the proposed estimators through analysing the daily returns of S&P 500 index collected from 18 December 2007 to 18 December 2017 (2531 trading days in total). Note that the daily return is defined as the daily change in log-index (log of asset price) which is preferred over daily change in index as the former approximates the daily percentage change in asset price, a better indicator of performance than absolute change. Figure 6 displays the returns of S&P 500 index over this time period. Figure 6(a) exhibits volatility clustering where the returns appear to be more volatile from year 2008 to the mid of year 2009 when the global financial crisis occurred. We also observe that the returns fluctuate around zero horizontal line which indicates that the unconditional mean of the daily returns is around zero. Looking at Figure 6(b), we observe that the underlying innovation distribution is roughly symmetric about zero with a quite heavy tail than normal (red curve). These suggest that a GARCH model with non-normal (unknown) innovation is appropriate to model the data. We use the more general GARCH
Jumps beyond the realms of cricket: India's performance in One Day Internationals and stock market movements
Published in Journal of Applied Statistics, 2020
Konstantinos Gkillas, Rangan Gupta, Chi Keung Marco Lau, Muhammad Tahir Suleman
Note that financial market volatility is used as an important input in investment decisions, option pricing and financial market regulation [45]. In light of this, financial market participants care not only about the nature of volatility, but also about its level, with all traders making the distinction between good and bad volatilities [17]. Good volatility is directional, persistent and relatively easy to predict, while, bad volatility is jumpy and comparatively difficult to foresee. Therefore, good volatility is generally associated with the continuous and persistent part, while bad volatility captures the discontinuous and jump component of volatility. Given this, it has been stressed that studying jumps can improve the overall understanding of the latent process of volatility [29,30]. In light of this, we too in our study incorporate the impact of ODI match results involving India on the predictability of various types of volatility jumps (small, big, good, and bad), besides return and realized volatility, as well as good and bad versions of the latter.