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A company provides the following information:
1) The probability distribution of ‘Cash inflow’ (i.e. cash sales and collections etc):
(Rs. in ‘000): 30 – 34 34 – 38 38 – 42 42 – 46
Probability: 0.1 0.3 0.4 0.2
Probability distribution of ‘Direct Costs and other Variable Costs’:
DCs & VCs
(Rs, in ‘000): 14 – 18 18 – 22 22 – 26 26 – 30
Probability: 0.2 0.3 0.3 0.2
Fixed Operating Costs amount to Rs. 14,000 per month.
Opening Cash Balance may be taken as Rs. 50,000.
Cash inflow: 0, 6, 6, 8, 0, 2
DCs & VCs: 4, 5, 1, 0, 3, 8
Using the above information and the random numbers given, simulate the cash inflow and cash outflow for the next six months and find out the simulated closing cash balance(s).
Monte Carlo Method:
The ‘Monte Carlo’ simulation technique involves conducting repetitive experiments on the model of the system under study, with some known probability distribution to draw random samples (observations) using random numbers. If a system cannot be described by a standard probability distribution such as normal, Poisson, exponential, etc, an empirical probability distribution can be constructed. The Monte Carlo simulation technique consists of the following steps:
(1) Setting up a probability distribution for variables to be analyzed.
(2) Building a cumulative probability distribution for each random variable.
(3) Generating random numbers and then assigning an appropriate set of random numbers to represent value or range (interval) of values for each random variable.
(4) Conducting the simulation experiment using random sampling.
(5) Repeating Step – 4 until the required number of simulation runs has been generated.
(6) Designing and implementing a course of action and maintaining control.
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