Note: Meanwhile, when one looks at historical data on market price movements, the distribution of the size of movements looks very much like the so-called bell curve, the normal distribution: there are more days when price changes are small than when they are big. Consequently, the evaluation and communication of variability or risk in finance often assumes that outcomes follow the normal distribution. Under that assumption, the calculation of probabilities for a certain outcome becomes a straightforward exercise. One only needs to ascertain how many standard deviations away is the outcome from the mean. Once that number is obtained, probability can easily be calculated using the cumulative distribution function of standard normal distribution.

Question: If an investor was exposed to SP500 stock index and her exposure

was valued at $100 million, what is the daily VaR at the confidence level of 99%

(one-sided) of that position when the daily volatility is 1% (round to the nearest

thousand dollars)?