Assume that interest rate is 0.02, growth rate of the Geometric Brownian Motion of the stock price is 0.03, and its volatility is 0.1. The current stock price is $100. If one independent sample from a standard normal distribution is 0.6, simulate the stock prices at t = 0.05 using the Euler-Maruyama scheme under the risk-neutral probability measure.
Assume that interest rate is 0.02, growth rate of the Geometric Brownian Motion of the stock price is 0.03, and its volatility is 0.1. The current stock price is $100. If one independent sample from a standard normal distribution is 0.6, simulate the stock prices at t = 0.05 using the Euler-Maruyama scheme under the risk-neutral probability measure.
Assume that interest rate is 0.02, growth rate of the Geometric Brownian Motion of the stock price is 0.03, and its volatility is 0.1. The current stock price is $100. If one independent sample from a standard normal distribution is 0.6, simulate the stock prices at t = 0.05 using the Euler-Maruyama scheme under the risk-neutral probability measure.
Assume that interest rate is 0.02, growth rate of the Geometric Brownian Motion of the stock price is 0.03, and its volatility is 0.1. The current stock price is $100. If one independent sample from a standard normal distribution is 0.6, simulate the stock prices at t = 0.05 using the Euler-Maruyama scheme under the risk-neutral probability measure.
Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.
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