SEED VARIABLES AND RANDOM NUMBER GENERATION

At the most basic level, the random element in a financial simulation model is a random variable, which is a quantification that can change. How a random variable is first established and how it changes each time is critical. The first and most obvious characteristic of a random variable is that it is random, meaning that the random variables created should not evolve and repeat in a pattern. The two key elements to preventing repetition are the initial starting point or seed state and the algorithm used to create the random variables.

Prior to explaining the details of a seed variable and random number generation algorithms, we should pause a moment to reflect that the mere mention of using a seed variable suggests that the numbers are not truly random. The proper terminology for random numbers that have deterministic attributes is pseudorandom numbers. More advanced methods of creating random numbers use observable real-world phenomena that can be detected and converted numerically. For example, low-level thermal or voltage change can be measured and converted to a numeric value. I once read that the decay of radioactive material would be one of the best random number generators. I could just picture a junior analyst at an investment bank with his computer hooked up to a protective, radiation-proof box containing uranium, explaining to his boss that he needs it to run his simulations. For practical computational purposes in finance, ...

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