In order to carry out the simulation, the first step is to capture the recurring valuation and decision patterns in the form of an algorithm. This algorithm is then applied to each scenario in accordance with the applicable time schedule, exactly as it would happen in reality.
The simulation captures
|all relevant national and international accounting rules and regulations in order to generate complete balance sheets and P&L statements in each node|
|analyses required by regulation (e.g. stress tests and forecasting, solvency requirements)|
|typical portfolio management metrics (e.g. duration, convexity for AL matching, etc.) and individual metrics for strategic control|
|any decision-making and management rules, e.g. all kinds of deterministic or event-triggered portfolio reallocations, contributions or profit realisations depending on portfolio returns, the coverage ratio, a return requirement to cover a discount factor, or regulatory requirements such as solvency, etc.|
|all forms of conditional strategies for liquidity-preserving, risk-minimising asset accumulation or asset protection (e.g. insurance approaches, trailing stops, derivatives for hedging, etc.).|
The result is a complete and realistic representation of the decision-making environment: All effects of decisions can be calculated and presented in the metrics that are of real, practical relevance to the decision-maker, since he or she has to answer for these – and not for abstract, theoretical metrics.
Only through this approach, which refrains from simplification, can the real risks of decisions be made transparent. This creates a solid basis for defining and optimising objectives and constraints effectively, and ultimately for making informed decisions.