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# Math for Quantitative Finance

Take a guided tour through the powerful mathematics and statistics used to model the chaos of the financial markets.

Your friend believes that stock prices are normally distributed. He says that the price of Stock A at the end of the year is approximately normally distributed with mean 200 and standard deviation 40, and the price of Stock B at the end of the year is approximately normally distributed with mean 180 and standard deviation 30.

According to his hypothesis, what is the approximate probability that stock B finishes the year with a higher price than stock A?

**confidence interval**. When estimating some population parameter via sampling, a confidence interval is an interval that should contain the true parameter some percentage of the time. For example, a 90% confidence interval should contain the true parameter 90% of the time.

A stock’s (daily) log-returns are normally distributed, and a quantitative analyst finds that the 95% confidence interval for the sum of the returns over a 10 day period is \([-1,1].\)

If the stock is currently $100, then the 95% confidence interval for where it will be after these 10 trading days is \([a,b].\) What is \(a+b?\)

Note that the log-return between day \(i\) with price \(S_i\) and day \(j\) with price \(S_j\) is \(\log\left(\frac{S_j}{S_i}\right).\)

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