Physical Chemistry Essay Example | Topics and Well Written Essays - 1000 words

Physical Chemistry - Essay Example This motivated John Dalton to study what makes different reactions unique. John Dalton, in his childhood years was educated by his father, and a man who managed a private school, called John Fletcher. He gained a wide understanding of science from the unofficial tutoring by  John Gough. At age 27 he was appointed to teach mathematics and  natural philosophy  at the  New College  where he taught for 7 years (Emery, 1988). Dalton formulated the theory after carrying out experiments into the behaviour of various gases. These experiments were based on 2 laws. The first was the law of  conservation of mass (by Antoine Lavoisier) that posits that the overall mass in a chemical process does not change (Dial, et al., 2009). The next law was the  law of definite proportions (by Joseph Proust) that posits that when a compound is stripped into its basic elements the masses of the basic elements will have similar quantities, irrespective of the amount of the original material. As a follow-up to the experiment conducted by Proust on oxides of tin, John Dalton conducted the same experiment on the oxides of tin. He also experimented with water and how it absorbed carbon dioxide and nitrogen. Dalton also started the study of various atomic weights depending on the combinations of the mass proportions, while taking the hydrogen atom as the base standard.   From the laws Dalton established the  law of multiple proportions that posits that when 2 chemical elements combine to produce more than one likely compound then the proportion of the second element’s mass that joined with a specific mass of the first element will be represented as proportions of whole numbers (Niaz, 2001). The results of this laid the foundation for Dalton’s Atomic Laws. These are made up of five theorems. The first theorem posits that an element, in its unmixed state, is made up of particles referred to as atoms. The second posits that all the atoms in

Fianacial moduling Essay Example | Topics and Well Written Essays - 3250 words

Fianacial moduling - Essay Example Both the indices generally followed the Other January effect. Introduction New York Stock Exchange (the US Stock) was officiated on March 18, 1817. London stock exchange (the UK Stock) was founded in 1801. The two stocks combined have the highest Market cap (17.0 trillion) and largest volume (3.1 trillion) in the world [1]. Any movement in these markets pushes stock indices all over the world. Drawing parallels from the common and integrated political and economic interests the host countries of these stock indices, it can be hypnotized that these market are correlated. This paper tries to identify, if any, correlation present between the two indices. As mentioned before the NYSE and the LSE sit on huge pile of money and are influential. Hence it is important to figure out their predictability. This paper assesses the predictability of these stock indices. The paper has been segregated into three segments: First section characterizes time series properties of the stocks namely its ra te of return and its volatility. Second section identifies the January effect. Section three provides an estimation of predictability using long-horizon regressions. For the purpose, monthly data of the stock indices starting from January, 1973 till December, 2004 is analyzed. 1. Time Series Analysis The rate of return is defined as the money earned on an investment (in stocks). Volatility is the measure of fluctuation in the asset (stock) prices. Mean and variance of rate of return and volatility is used to characterize a stock [2]. Curve of distribution of data is measured by Skewness and Kurtosis of the graph. A normal distribution curve is bell shaped symmetric around the mean. A positively skewed distribution is skewed to right. Skewness is measured as 3rd movement of mean. A Kurtosis is a measure of flatness of the top of the graph. Larger value of degree of kurtosis would mean sharper peak [11]. The rate of return of the indices was analyzed against time. The volatility of th e market was also measured. The rate of return was measured as the difference of natural log of the monthly index value. Volatility was measured as the standard deviation of rate of return of the market in a year. Each Index was characterized by its mean of rate of return and its variance of rate of return and volatility. [3] Rate of return Volatility Mean (ln values) Variance Skewness Kurtosis Mean (ln values) Variance Skewness Kurtosis UK 0.010753 0.0034 -0.18 7.31 0.053 0.000682 0.94 1.65 US 0.008991 0.0022 -0.95 6.35 0.043 0.000313 0.72 0.90 The result showed that rate of return on was higher in UK index than in US index by around 20%. Also, the UK market was around 23% more volatile than the US market. Variance of rate of return and volatility showed that UK market was more spread than US stocks. High degree of kurtosis for rate of return of the UK and the US stocks suggested sharp peak of the distribution graph. From degree of kurtosis it could be inferred that volatility was not restricted to certain range of stock return values but was spread over a long value range of returns. It is to be noted that in 31 years starting from Jan 1973, US market grew from 98.66 to 3087.82 (31X) in Dec 2004, while the UK markets grew from 319.53 to 19639.99 (61X) in the same period. Distribution of rate of return data was left tailed for both US and UK stocks while distribution of volatility data was right tailed for both the stocks.