Modeling Risk Evolving over Time
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Risks are not static, and least so in the world of nance. In the real-world, the risk factors discussed in Chapter 1 are dynamic, evolving quantities mimicking the forces of change in nance. For instance, after a one-period return modeled by a lognormal distribution, what happens in the next period? After a bank sees a surge in the number of defaults in its loan portfolio in a quarter, what would it expect of the risk in the subsequent quarters? This dynamic evolution of risk is an essential feature to capture for risk management.