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2. Monte Carlo methods in finance - Wikipedia

   en.wikipedia.org/wiki/Monte_Carlo_methods_in_finance

   Pricing using Monte Carlo simulation, a practical example, Prof. Giancarlo Vercellino; Personal finance. A Better Way to Size Up Your Nest Egg, Businessweek Online: January 22, 2001; Online Monte Carlo retirement planner with source code, Jim Richmond, 2006; Free spreadsheet-based retirement calculator and Monte Carlo simulator, by Eric C., 2008

3. Retirement planning - Wikipedia

   en.wikipedia.org/wiki/Retirement_planning

   The Monte Carlo method is a common form of a mathematical model that is applied to predict long-term investment behavior for a client's retirement planning. [8] Its use helps to identify adequacy of client's investment to attain retirement readiness and to clarify strategic choices and actions.

4. Monte Carlo method - Wikipedia

   en.wikipedia.org/wiki/Monte_Carlo_method

   Monte Carlo method: Pouring out a box of coins on a table, and then computing the ratio of coins that land heads versus tails is a Monte Carlo method of determining the behavior of repeated coin tosses, but it is not a simulation. Monte Carlo simulation: Drawing a large number of pseudo-random uniform variables from the interval [0,1] at one ...

5. Don't Gamble When It Comes to Your Retirement - AOL

   www.aol.com/.../retirement-planning-tool-monte-carlo

   A "Monte Carlo analysis" can be used to determine if you are on track to As investors, however, you should be familiar with another meaning. Don't Gamble When It Comes to Your Retirement

6. Asset/liability modeling - Wikipedia

   en.wikipedia.org/wiki/Asset/liability_modeling

   Proponents of Monte Carlo simulation contend that these tools are valuable because they offer simulation using randomly ordered returns based on a set of reasonable parameters. For example, the tool can model retirement cash flows 500 or 1,000 times, reflecting a range of possible outcomes.

7. Stochastic simulation - Wikipedia

   en.wikipedia.org/wiki/Stochastic_simulation

   A stochastic simulation is a simulation of a system that has variables that can change stochastically (randomly) with individual probabilities. [1] Realizations of these random variables are generated and inserted into a model of the system. Outputs of the model are recorded, and then the process is repeated with a new set of random values.