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The first generation of financial planning (1970s through 1990s) used static modeling with a constant return expectation. The chief limitation was that it didn’t accurately reflect the real sequence of returns observed, which created very unrealistic results and underrepresented the risk of failure. In this century, financial plans were primarily conducted using single-factor Monte Carlo simulations (the second generation of financial planning), which addressed the sequence of return risk. While a vast improvement over the first generation of financial plans, typical Monte Carlo simulations still have material weaknesses in how they represent potential future circumstances. The most notable weaknesses include the assumption of a constant risk level (determining expected return), a constant volatility (standard deviation) for potential portfolio returns, a single path for potential inflation and a constant terminal point for evaluating the simulation.

The third generation of financial planning mathematical infrastructure has emerged, which incorporates additional variables to more realistically reflect potential future outcomes.

The first generation – Static models

As computing power evolved, the ability to incorporate more intricate cash-flow assumptions improved. General assumptions for portfolio returns, taxes and inflation expectations evolved. Even life expectancy changed and thus the time horizon for the financial plan increased. These improved assumptions enhanced the reliability of the outcome. However, they were often biased based on the then current economic climate (e.g. late 1970s/early 1980s with inflation and interest rates above 10%), which didn’t necessarily accurately reflect an uncertain future.

The chief limitation of the first generation of financial plans was inherent in the portfolio return assumptions. An individual could be lucky enough to retire at the beginning of a strong market or unlucky enough to retire at the beginning of a weak market economy. The difference could be as stark as success or failure. Assuming, for example, a 6% return every year ignored the massive variance that occurred during most retirement horizons.