13.9 Output from Monte Carlo
The amount of data to be output in a Monte Carlo Processing Run depends on the type of processing and the requirements of the users. A Stochastic Process using Monte Carlo provides the following results:
- Market value at the dimension member level
- Value-at-Risk at the dimension member level
- Value-at-Risk at the portfolio level
The smallest set of output will result from the Market Value Processing Run. Market Value is the average across all scenarios of the sum of all Cash Flows discounted by the (scenario-specific) rate.
The output will be a single value - the market value per dimension member - stored in the FSI_O_STOCH_MKT_VAL table. The table has a simple structure:
Table 13-2 Market value per Dimension Member
| LEAF_NODE | MARKET VALUE | CURRENT BALANCE | NUMBER OF RATE PATHS |
|---|---|---|---|
|
Fixed Mortgages |
55000.00 |
54000.00 |
2000 |
|
Deposits |
10000.00 |
10100.00 |
2000 |
Value-at-Risk (VaR) is the maximum loss in value over a specific horizon (risk period) and confidence level. The horizon is specified by the user. Unlike many other products, Oracle ALM outputs VaR for any confidence level, that is, it outputs the full probability distribution of loss for each Product COA member. The output is written to the FSI_O_STOCH_VAR table:
Table 13-3 Full Probability Distribution of loss for each Product COA Member
| Probability | Fixed Mortgages VaR | Deposits VaR |
|---|---|---|
|
10% |
-200 |
-100 |
|
20% |
-150 |
-20 |
|
30% |
-100 |
-10 |
|
40% |
-20 |
10 |
|
50% |
60 |
50 |
|
60% |
70 |
75 |
|
70% |
110 |
90 |
|
80% |
150 |
100 |
|
90% |
160 |
120 |
|
100% |
175 |
160 |
The system will also output VaR at the portfolio level (into the FSI_O_STOCH_ TOT_VAR table). In this example, we assume that our portfolio has only deposits and fixed mortgages.
Table 13-4 Output VaR at the Portfolio level
| Probability | Portfolio |
|---|---|
|
10% |
-130 |
|
20% |
-100 |
|
30% |
-90 |
|
40% |
-30 |
|
50% |
-5 |
|
60% |
10 |
|
70% |
15 |
|
80% |
20 |
|
90% |
20 |
|
100% |
40 |
As you can see from the following graph, the total VaR does not necessarily equal the sum of the VaR for each portfolio because of the correlation between mortgages and deposits.
Description of graph for Output From Monte Carlo follows We selected the Monte Carlo method to implement VaR over other methods such as J.P. Morgan's RiskMetrics approach because of the following advantages:
- Better accuracy in analyzing nonlinear assets such as options.
- More flexibility to model the distribution of economic factors versus normal assumption in RiskMetrics.
- No need to decompose securities into “risk factors”; a complicated process for fixed income.
Oracle ALM also provides auditing options. Monthly rates correspond to yields of a risk-free zero-coupon bond with a maturity of one month. These rates are used for all other calculations in the stochastic Rate Generator. They are output into the FSI_INTEREST_RATES_AUDIT table, where the values are displayed for each scenario and every time step, that is, up to 2,000 scenarios times 360-time steps. Because of the amount of data being written, this process can be very time-consuming.
Cash Flows are also available for auditing purposes if the Detail Cash Flow option is selected in the Stochastic ALM Process. For more details on this process, see Detail Cash Flow Audit Options.
The Stochastic Discount factors are also output as an auditing feature. This is extremely valuable for testing purposes. The user can check this output any time the “Detail Cash Flow” output option is on. The table used is called FSI_O_PROCESS_CASH_FLOWS, Financial Element 490.