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Volatility is an important parameter for financial risk management and it is applied in many issues such as option pricing, portfolio optimization, VaR methodology and hedging; thus the forecasting of volatility or variance can be regarded as a problem of financial modelling. The objective of this paper is to forecast FTSE 100 Stock Prices of top 100 companies listed on London Stock Exchange by using the Exponential Weighted Moving Average (EWMA) Model. The data for this model are directly obtained from the UK FTSE 100 Index. In this research paper, we have examined the daily returns of FTSE 100 Stock Prices of top 100 companies listed on London Stock Exchange from the thirtieth day of June 2009 to the first day of December 2014 and equally forecasted the daily returns from the first day of December 2014 to the fifth day of February 2015 with the Exponential Weighted Moving Average (EWMA) Model. We found that there is a very high possibility that the stock prices will start to fall as from 5th February 2015 downwards.
Botrytis cinerea affects plant yield and quality. Many Botrytis species are morphologically similar leading to difficulty in pathogen identification. Spectroscopy can be used to identify pathogenic fungi. This study describes a novel method for fungal characterization. Here, we determined the spectral signatures of different B. cinerea isolates as well as various fungal genera. A unique spectral pattern was investigated at both genus and isolate level. The short wave infrared II (2055 - 2315 nm) provided the best discrimination between the fungal samples observed. Moreover, the spectral analysis was performed on non-transformed data and investigated significant differences among fungal genera as well as B. cinerea isolates, while the results investigated high similarity among replicates of the same isolate of B. cinerea. The results of each spectral test were obtained reproducibly without an expensive cost consumable during sample preparation and measurements. This innovative approach would allow us to identify, discriminate and classify fungi rapidly and inexpensively at the genus, species and isolate level.