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The Options Based Portfolio Insurance (OBPI) should avoid losses and capture gains, by the cost of a “premium”, but in practice the premium cost can be too high to capture gains in the different market conditions. Based on this premise, the objective of this study is to analyze an optimized alternative to Options Based Portfolio Insurance, assuming that the probability of an Extreme Negative Event varies with time, and therefore the insurance floor should not be maintained at any cost. To achieve the objective, data were crossed between the rollover date and a fixed insurance cost on equity, using historical data from 678,546 trades carried out in the US market, which resulted in 3,700 portfolios. Data analysis was performed using descriptive and econometric statistics with simple linear regressions. The results demonstrated that the insured floor varied with the volatility implied in option prices, indicating the possibility of obtaining better return-risk ratio and lower drawdown when compared to the unprotected portfolio, showing a positive correlation between insurance cost and return-risk ratio for low costs and a negative correlation for higher costs. Furthermore, it can be indirectly inferred that the explanation for the results comes from the perception of risk by the market not representing the real risk. As with the stabilization and possible recovery of prices that occur after a significant drop, market confidence is not restored to the same proportion. That’s why volatility remains at high levels, consequently, raising the insurance cost, even with lower probabilities of Extreme Negative Events.     

The Options Based Portfolio Insurance (OBPI) should avoid losses and capture gains, by the cost of a “premium”, but in practice the premium cost can be too high to capture gains in the different market conditions. Based on this premise, the objective of this study is to analyze an optimized alternative to Options Based Portfolio Insurance, assuming that the probability of an Extreme Negative Event varies with time, and therefore the insurance floor should not be maintained at any cost. To achieve the objective, data were crossed between the rollover date and a fixed insurance cost on equity, using historical data from 678,546 trades carried out in the US market, which resulted in 3,700 portfolios. Data analysis was performed using descriptive and econometric statistics with simple linear regressions. The results demonstrated that the insured floor varied with the volatility implied in option prices, indicating the possibility of obtaining better return-risk ratio and lower drawdown when compared to the unprotected portfolio, showing a positive correlation between insurance cost and return-risk ratio for low costs and a negative correlation for higher costs. Furthermore, it can be indirectly inferred that the explanation for the results comes from the perception of risk by the market not representing the real risk. As with the stabilization and possible recovery of prices that occur after a significant drop, market confidence is not restored to the same proportion. That’s why volatility remains at high levels, consequently, raising the insurance cost, even with lower probabilities of Extreme Negative Events.