We offer two options: __reference stock__ and __pre-IPO treatment__. The system **automatically screens for** stocks and mutual funds with* insufficient data points* in the portfolio during calculation and **automatically memorizes** the settings for the next round of calculations to save your time. Subsequent modifications are still possible.

**Single VaR: **The value-at-risk of a single investment target without consideration of the risk diversification effects present in the portfolio.

**Incremental VaR: **Additional value-at-risk attributable to the inclusion of a new investment target.

**Component VaR: **The value-at-risk of the entire portfolio attributable to a certain investment target while accounting for risk diversification effects.

**Backtesting: **Historical VaRs and gains/losses are calculated based on a fixed portfolio.

**Daily backtesting: **Historical VaRs and gains/losses are calculated based on actual historical portfolios.

The purpose of backtesting portfolios is to validate the model.

Information on newly established mutual funds can be found in“Newly Listed Assets”under the“Notes”section of the system. A“Mutual Fund Code Name Index”is also available for quick reference.

A data point is only considered valid if there is no missing value for any of the risk factors. Invalid data points are excluded from the analysis. The number of asset types usually increases after consolidation, and because each factor has a different set of transaction dates, the likelihood of exclusion becomes higher.

The system relies on widely accepted statistical methods for risk assessment, including variance/covariance analysis, factor analysis, historical simulation, and the Monte Carlo method. Test results are in keeping with predictions found in relevant literature. Furthermore, TEJ has renowned scholars on staff to validate the system.

The system is installed on the client’s own infrastructure, so all computation is done locally within your company, keeping your portfolio data safely guarded.

Stress events are extreme financial market anomalies that have occurred in the past (such as the 9/11 attacks). Values are arrived at objectively through research of similar events. Alternatively, users may set their own criteria based on their experience.

The system provides a price-weighted stock market index as well as sector-specific indices (financial sector index, electronics sector index, etc.) as performance indices for equity assets. It also provides the real effective exchange rate (REER) published by the Taipei Foreign Exchange Market Development Foundation as an exchange rate index and the UOB Government Bond Index as an interest rate index. The Taiwan Government Bond Index will be included in the near future.

The system auto saves all of your operations. You can look up previous value-at-risk results using the “search for reports” function. Alternatively, you may export data to an Excel spreadsheet if you so choose.

The system currently provides transaction data from the stock markets of seven East Asian countries. For stocks traded in other countries, you will need to upload the daily transaction data yourself and set the corresponding exchange rate in order for the system to perform calculations.

Due to the increasing likelihood of extreme market events (also called “fat-tail distribution”), and because the historical simulation method is based on actual market performance, risk values may sometimes appear larger than if normal distribution is assumed (as is the case with other statistical methods).

The best method really depends on the asset type. Variance and covariance methods are best suited for linear assets, while historical simulation and the Monte Carlo method are recommended for portfolios with a significant proportion of non-linear assets. In addition, the configuration of parameters also influences accuracy. Backtesting can be used to determine the best model for your portfolios.

VaR is the quantification of unrealized gain/loss, so RAROC (risk-adjusted return on capital) values also pertain to unrealized gain/loss only. Realized gains and losses are no longer categorized as risks, so the system does not include them in RAROC calculation.

To update a portfolio, simply reupload it to the system. Historical values will remain in the system. Warning: Do not delete the portfolio. Doing so will also delete all historical reports from the system.

Geometric Brownian Motion (GBM) is used for equity and foreign exchange factors, whereas the Vasicek Model is used for interest rate factors owing to their tendency of mean reversion.

Performance index VaR is the benchmark VaR per unit of investment target. It is useful when comparing the risk of a given target with a benchmark instrument (e.g., securities vs. weighted stock market indices). It can be interpreted as the increase in the target’s risk exposure per additional unit of VaR.

Yield values come from three sources: benchmark government bond yields, spline-fitted zero-coupon yields, and interest rate swap (IRS) yields.

Assuming that all variables are independent and identically distributed (so that time conforms to the laws of arithmetic) and because variance is a square value, the total VaR is calculated as daily VaR multiplied by the square root of the number of days for which the assets are held.

You will find a“diversification effects”column in the reports which shows the risk reduction effect if an asset negatively correlated with the portfolio is constructed. You can also infer this information from the positive or negative sign of the incremental VaR.