Applied statistics for economics Essay Example | Topics and Well Written Essays - 2500 words

Applied statistics for economics - Essay ExampleConsistent with the research augurions, the study gear up out that standard & poor five hundred forefingeres are more likely to release good intelligence information forecasts following larger stock price declines. Moreover, as expected there is no association mingled with the likelihood of releasing good news forecasts and the magnitude of an exogenous stock price increase. Also to be illustrated in this report is the potential of Time-frequency Representation (TFR) techniques, for the analysis of stock markets info and compare their performances. It is for this reason that we try out to analyze the behavior of the stock market price over the period from 2002 to 2007. MAIN OBJECTIVES/BROAD PURPOSES OF THE frame This report aims at investigating the following objectives i) To investigate whether tout ensemble the investors are risk averse and saloon risk in terms of the standard deviation in a portfolios return. ii) To invest igate whether any investors carry a common cartridge holder horizon for investment decisions (e.g., a year). iii) To investigate whether all investors have identical subjective estimates of future returns and risks for all securities. iv) To investigate whether there exists a risk-free asset and all investors may borrow or lend an unlimited amount at the risk free nominal phrase rate of interest. v) To investigate whether all securities are completely divisible, there are no transactions be or differential taxes, and there are no restrictions on short-selling. vi) To investigate whether information is freely and at the same time available to all investors. We could summarize the above by stating that all individuals are price-takers and that markets are perfectly competitive. OUTCOMES OF THE excogitate compare... Applied Statistics For Economics A time series can be said to collection of data yt (t=1,2,,T), with the interval between yt and yt+1 being fixed and constant. Time series analysis is the estimation of divergency equations containing stochastic (error) terms (Enders 2010). Time series forecasting takes the analysis from the time series data and tries to predict what the data may be in the near future, based on what it has been in the past. This is especially central in the field of stock market investment, as traders want to make the flop moves at the right times to maximize financial profit. But because there are many factors influencing the fluctuation of the stock market, creating an completed forecast based on the analysis alone is difficult. Therefore, many approaches and models have been developed to utilize the time series analysis and provide an accurate prediction of what is to come in the stock market. Standard & low-down 500 indices are designed to reflect the U.S. equity markets and, through the markets, the U.S. economy. The Standard & Poor 500 index focuses on the large-cap sector of the market however, since it includes a s ignificant portion of the total value of the market, it to a fault represents the market. Companies in the Standard & Poor 500 index are considered leading companies in leading industries. Comparing the mean of dly and that of dlsap, we observe that the end of week mean price for the logarithm of share price for a particular stock (denoted dly) is lower compared to the end of week mean for the logarithm of Standard & Poor 500 index.