Certificates are structured financial instruments that aim to provide investors with investment solutions tailored to their needs. Certificates can be modeled using a bond component and a derivative component, typically an options strategy. The pricing of certificates is typically performed using the Monte Carlo numerical methodology. Such method allows for projections of the underlying using series of random numbers. The results obtained display an error (standard deviation) that depends on the number of simulations used and on the specific characteristics of the structured product. This work has the objective of minimizing the experimental error, and, consequently, of accelerating the speed of convergence using statistical techniques known in the literature as variance reduction methods. The most popular stochastic dynamics have been analyzed, like the classical Black and Scholes model, the Local Volatility model and the Heston model. Three certificates are analyzed in the paper and they are characterized by different payoffs. The variance reduction techniques, implemented in different programming languages (Python, Matlab and R), are: Latin Hypercube, Stratified Sampling, Antithetic Variables, Importance Sampling, Moment Matching and Control Variates

The Monte Carlo method, thanks to its flexibility in designing even extremely complex payoffs, is assuming an increasingly important role in quantitative analysis. Its main limitation is the high computational cost linked to its modest speed of convergence to the fair value of the product. One of the best-known statistical techniques is to replace the random number generator with “low discrepancy” deterministic numerical sequences, producing a Quasi-Monte Carlo. Through its implementation for the analysis of three investment certificates featuring different characteristics and different stochastic processes used for the underlying simulation, the study demonstrates the possibility of achieving interesting results in terms of performance even for pricing these structured products ever more popular in the financial industry.