However , normally the returns and risk measures are provided on an annualized basis. The calculations above are actually on a daily basis. To convert to an annual basis multiply the daily return by JO days any: uni : [gilt 5250 For risk the standard measure is in standard deviation form. On an annualized basis this is referred to as volatility. The standard deviation is the siuare root of variance; To obtain the annualized volatility then multiply the daily volatility by the square root of 250 Cam: = OQQEJZSO For each of the four series use Lxcel formulas to calculate the percentage change in daily prices P in [Pi i , Then using the Average 3.) and SthevO Cor similar) function compute the daily mean 21) change in price and its standard deviation, and the annualized return and volatility . Go to the comsoy prices historical tab; this dataset provides daily corn and soybean prices ($s'bu) from December 1968 through early January 2019. As in the preamble , it is standard in nancial economics to measuring asset risk in terms of the variance of the percentage change in prices. This is usually done using LN(P(t)fl'(tl)] for a continuous time measure and sometimes ((P(t)-r(t-1)).-'P(t-1) for the arithmetic return. The rst assumes continuous time, the second simple time. On a daily basis they are usually quite close. We will use continuous time. 1) [4 pts) For both corn and soybeans Calculate the daily rate of change using the natural logarithmic rule. Take the mean and stande deviation of these numbers. Since the data are daily then multiply the mean by 250 (days) and the standard deviation by sqrt (250). This converts rates of return and volatility om daily measures to annual measures , which is the tradition. Report your results and explain in words (a single sentence for each) what they mean. 2) [3 pts) Looking at skewness for level prices , and then % changes , what would you expect to see if prices are lognormally distributed " 3) [4 pts) The answer in (l) is the long run historical volatility measure, but sometimes traders and analysts prefer more recent measures of variance . Calculate rolling (overlapping) 250 day volatilities . Graph and describe with means and standard deviation , what you observe . To get these measures go to row 265 which is day 251. Calculate the annualized volatility for the previous 250 days. Repeat for all remaining days in the dataset. 4) [2 pts) Are volatilities as measured consistent with a geometric Brownian motion