This report, written in Portuguese, presents procedures to characterize and simulate -- using Monte Carlo methods -- price trajectories and cash flows, allowing the estimation of operational costs in futures markets. First, a brief literature review analyses models and ideas about the evolution of prices in markets. This review organizes known facts about the characterization of price trajectories and pointers to methods used to provide a statistical representation for futures prices models. Second, Monte Carlo simulation methods are reviewed. Algorithms describe the overall simulation process of price trajectories and functions of these trajectories. Remarks are presented on the estimation of moments, confidence intervals and probability distributions. Third, definitions and algorithms formalize cash flow evolution (day by day) and costs in futures markets operations, based on price trajectories, exchange rules concerning margins, financial cash flows and taxes. Fourth, operational cost components in futures markets are estimated and quantified in (a) a case study concerning the BM&F corn market and (b) with a theoretical model. The estimation considered observed and simulated price trajectories, derived from ARIMA-GARCH models, estimated from the observed price trajectories. Operational costs are shown to be large and uncertain when operation begins, being strongly dependent on the price trajectory, degree of dependence on borrowed money to manage the cash flow and exposure to taxes. Because these costs apply to both the long and the short positions of the same operation, they affect twice the transaction costs in a single operation. A cost risk concept is introduced and argued as being an additional obstacle to futures markets operations, not found in the literature. In an operation for a single investor (not a firm) and with minimal assumptions, the mean percent cost for a long or a short position, was estimated to range from 2.5 to 4.5 % of the contract initial price, for an operation lasting 120 days, when annualized volatility is 25%. Mean operational costs (as well as uncertainty) tend to increase with larger volatilities and longer operations. Models with more realistic assumptions lead to larger mean cost estimates. Agents who need to borrow money to manage their cash flow will have larger costs than agents who are able to finance operations with their own capital. High interest rates, wide spreads between borrowing and investment rates, and high taxes applied to operations in futures markets are argued as major causes for high and uncertain operational costs. In addition, because there are differences in the cost of money and exposure to taxes for different classes of agents, the ones with smaller costs have more incentive to use futures markets. Agents with large costs can be excluded from these markets. These effects are argued to have economic implications.