1. What is the primary purpose of using Simulation in statistics?
A. To replace actual experiments with theoretical models
B. To simplify regression and correlation analysis
C. To study the behavior of complex systems under uncertain conditions
D. To avoid collecting any real-life data
Simulation is mainly used to replicate real-world processes or systems in a controlled environment to understand their behavior under uncertainty and risk.
2. Monte Carlo Simulation is widely used in banking for:
A. Risk analysis and forecasting uncertain outcomes
B. Preparing organizational charts
C. Recording accounting entries
D. Preparing static budgets
Monte Carlo Simulation is used to model risk and uncertainty in financial forecasting, portfolio management, and project evaluation.
3. In a simulation exercise, generating random numbers is important because:
A. It ensures deterministic outcomes
B. It eliminates the need for probability distributions
C. It always produces the same result
D. It allows us to model variability and uncertainty
Random numbers help in imitating uncertain real-life situations and in building probability distributions for simulation experiments.
4. A bank wants to assess the risk of loan default using simulation. Which step should be performed FIRST?
A. Run random trials to generate outcomes
B. Define the variables and assign probability distributions
C. Interpret and analyze the simulation results
D. Compare simulation with actual outcomes
The first step in simulation is to define variables clearly and assign probability distributions to represent uncertainty in outcomes.
5. In a simulation of cash flows, the bank runs 1,000 trials and finds that in 20% of cases, NPV is negative. What can be inferred?
A. There is a 20% probability that the project will result in a loss
B. The project is risk-free
C. The project guarantees profit in 80% of cases
D. Simulation cannot be used for decision-making
Simulation provides probabilities of outcomes. Here, 20% negative NPV indicates a 20% risk of loss, helping managers take informed decisions.
6. The first step in Simulation methodology is usually:
A. Generating random outcomes
B. Running multiple trials
C. Defining the problem and identifying key variables
D. Analyzing the simulation results
Simulation begins with problem formulation and identification of variables to ensure correct modeling of real-life situations.
7. In Simulation methodology, assigning probability distributions to variables is done to:
A. Ensure deterministic results
B. Capture the uncertainty and variability of real-world processes
C. Eliminate the role of random numbers
D. Make outcomes independent of assumptions
Probability distributions are used to reflect uncertain outcomes (like loan defaults, cash flows, forex rates) in simulation models.
8. Which of the following is the correct sequence in Simulation methodology?
A. Generate random numbers → Define problem → Assign distributions → Analyze results
B. Assign distributions → Define problem → Analyze results → Run trials
C. Analyze results → Generate random numbers → Define problem → Run trials
D. Define problem → Assign probability distributions → Generate random numbers → Run trials → Analyze results
The correct sequence is: (1) Define problem → (2) Assign distributions → (3) Generate random numbers → (4) Run trials → (5) Analyze results.
9. A bank simulates loan repayment behavior by running 10,000 trials. This step corresponds to which stage of simulation methodology?
A. Conducting simulation trials
B. Assigning distributions
C. Defining the problem
D. Validating model assumptions
Running multiple random trials to replicate possible outcomes is the execution phase of the simulation methodology.
10. Why is validation an important step in Simulation methodology?
A. It reduces the number of trials required
B. It ensures only positive results are generated
C. It removes the need for random number generation
D. It checks whether the simulation model reflects real-world conditions accurately
Model validation ensures the simulated outcomes are realistic and consistent with actual system behavior.
11. Which of the following is a major advantage of Simulation in decision-making?
A. It allows experimentation without disturbing the real system
B. It guarantees correct results in all cases
C. It eliminates the need for probability distributions
D. It reduces all risks to zero
Simulation allows managers to test different strategies in a controlled environment without affecting actual business operations.
12. One of the key limitations of Simulation is:
A. It is always less expensive than real-world experiments
B. It requires no expertise to design models
C. It may be costly and time-consuming to develop realistic models
D. It provides exact solutions like mathematical optimization
Developing accurate simulation models often requires significant time, expertise, and computing resources, making it expensive.
13. Simulation results are often expressed in terms of:
A. Deterministic solutions
B. Probability distributions and ranges of outcomes
C. Fixed single-point estimates
D. Guaranteed maximum profits
Simulation provides probabilistic results, giving a range of possible outcomes with associated likelihoods instead of exact solutions.
14. A bank is simulating ATM cash demand to avoid cash-out situations. Which is the advantage of simulation in this context?
A. It removes the need for demand forecasting
B. It eliminates fluctuations in customer withdrawals
C. It guarantees exact prediction of withdrawals
D. It helps test different stocking policies under variable demand conditions
Simulation allows banks to test alternative policies for ATM cash stocking and evaluate their performance under uncertain demand.
15. Which of the following is NOT a limitation of Simulation?
A. Requires significant data and expertise
B. Provides guaranteed optimal solution
C. May be costly in terms of computation
D. Interpretation of results requires judgment
Simulation does not provide guaranteed optimal solutions—it only provides probabilistic outcomes. This is often misunderstood as a limitation.
16. In banking, Simulation is MOST commonly used for:
A. Preparing accounting statements
B. Branch decoration planning
C. Risk management and stress testing of portfolios
D. Printing of cheques
Banks apply simulation mainly for credit risk modeling, portfolio stress testing, market risk assessment, and capital adequacy planning.
17. A bank uses Monte Carlo simulation to forecast Value at Risk (VaR). This means:
A. The bank is estimating potential losses under different market scenarios
B. The bank is calculating the exact profit it will earn
C. The bank is ensuring zero probability of default
D. The bank is preparing only statutory financial reports
Simulation of Value at Risk (VaR) allows banks to measure potential losses in portfolios due to adverse market movements with given probability.
18. In queue management at bank branches, Simulation helps in:
A. Guaranteeing zero waiting time
B. Eliminating customer demand fluctuations
C. Avoiding all system breakdowns
D. Testing service capacity under different arrival and service rate conditions
Banks simulate customer arrivals and service rates to optimize staff allocation and reduce waiting times without disrupting real operations.
19. A project evaluation by a bank shows that in 25% of simulated cases, IRR is below the cost of capital. What should the bank infer?
A. The project is completely risk-free
B. There is a 25% probability that the project may not cover its cost of funds
C. The project guarantees positive returns
D. Simulation is not applicable to project finance
Simulation provides probability-based insights. Here, 25% trials show IRR below cost of capital → indicates a significant project risk.
20. In credit risk modeling, Simulation is mainly used to:
A. Estimate probability of default and potential loss distribution
B. Prepare customer KYC documents
C. Design promotional schemes
D. Fix bank branch working hours
Simulation helps banks assess credit risk by generating default scenarios and loss distributions, aiding capital adequacy and provisioning.
