Risk Engine – aixigo’s Financial Risk Management Software

aixigo's Risk Engine provides you with the financial software for portfolio risk management. The software is a solid and professional tool for in-depth portfolio risk management and risk analysis - robust and based on scientific findings. Risks are clearly described using intuitive, understandable risk factors, such as the price of gold, the economic performance of a region or industry, the exchange rate of a currency and many more.

The contribution of risk factors to the risk and return of investment recommendations or existing portfolios is examined using any historical scenario and the expected return is forecast using a Monte Carlo simulation. How well a portfolio or a recommendation is diversified and which risk factors or securities contribute how strongly to the risk of the portfolio can thus be incorporated into investment decisions as objective and comprehensible information - thanks to the fast and scalable algorithms of our Risk Engine software, it is even suitable for masses of portfolios.

Capabilities of the Risk Engine Modules

The ability to determine portfolio risks in a scientifically sound manner and to make them visible and explainable is one of the key capabilities of aixigo's financial risk management software, the Risk Engine. The analysis not only covers the past, but also provides a forecast for the future development of returns. The following sections provide you with information on the risk management functionalities contained in the Risk Engine modules.

Risk Examination

The Risk Examination module of our financial risk management software takes care of the precise examination of various risk-related characteristics and variables.

Classification of risk type
The volatility of the return on an investment, consists of two types of risk: the systematic and the idiosyncratic risk. The systematic risk can easily be explained and represented by risk factors, while the idiosyncratic risk makes up the unexplainable, usually very small part. For the assessment of risks, the portfolio risk management software classifies the risks into these two risk types.

Structural decomposition
For portfolios with structured financial instruments, the Risk Engine also outputs which risk factors have an effect on the portfolio by breaking down the instruments into their elements and underlyings, which in turn can be attributed to risk factors.

Key Figures
The Value at Risk is the key figure determined by the system from volatility and expected return. For a portfolio the contribution to risk analysis breaks down each position or risk factor's contribution to the volatility and Value at Risk of the portfolio. This makes it possible to assess which securities are risk drivers in the portfolio and which specific risk factors influence the portfolio.

Tracking Error
The return of a portfolio can be compared with that of any benchmark. The tracking error analysis determines how well the benchmark return reflects the portfolio return. By minimising the tracking error, the risk management software finds the benchmark that best describes the fluctuation of the portfolio return and can serve as an impulse to optimise the portfolio.

Risk Scout

The risk of a portfolio and individual positions is determined by the volatility of the returns. Volatility therefore expresses both the chance of price gains and also the risk of price losses. Based on the historical yield time series, the financial risk management software, the Risk Engine forecasts future volatility and calculates the Value at Risk. The system uses Monte Carlo simulations with a freely definable simulation horizon for possible future developments of the Value at Risk and their probabilities of occurrence.

In addition to the analysis of historical yield time series, expert opinions on the level of volatility to be applied can also be included. A weighting, e.g. 30% from historical analysis, 70% from expert opinion, can also be mapped.

Under the assumption that there is a correlation between the volatility of the return and the expected return, the expected return can also be determined using efficiency lines of volatility and return. This is done by using the previously forecast volatility and specifying the associated returns. 

Risk Scenarios – How Does the Risk Analysis of a Portfolio Work?

The Risk Engine, a portfolio risk management software from aixigo, can be used to store any scenarios that could occur in the future to examine an existing portfolio for possible changes in volatility and expected returns.

The software's stress test allows you to enter individual forecasts for the volatility and return of risk factors. For example, to test the potential behaviour of the portfolio under extreme conditions.

In addition, a view of the historical return development of a portfolio under various scenarios that have occurred, such as the dot-com bubble or the financial crisis, is possible for any period in the past - even if the financial instruments of the portfolio under review have not yet been issued. This is only possible through the special consideration of risk in the form of risk factors by the Risk Engine as risk factors have a particularly long price history.

Risk Setup & Administration

Risk factors are parameters whose development can be reflected by the price time series of corresponding indices, e.g. on shares, certificates, bonds, regions, sectors, currencies, etc. The risk and return of any securities that possess these risk factors can therefore be related to one another.

With the portfolio risk management software from aixigo, all risk factors are stored with their quote time series against which financial instruments are to be examined. These pairs, e.g. type: stock with an index for equities, type: bond with an index for bonds, country: Germany with the DAX, currency: € with a currency index for the Euro, etc., form the basis for the analyses of our Risk Engine.

A rule-based language is then used to establish links between risk factors and general financial instrument characteristics. They map the justifiable causal relationships between risk factors and securities characteristics and protect against misinterpretation of a purely statistical correlation as a cause-effect relationship. Finally, the risk factors are automatically assigned to those securities that possess the corresponding properties.

The quality of the risk factor model can be evaluated and optimised with the aid of mathematical key figures and optimisation methods. This ensures that sufficient and correct risk factors are incorporated into the model.

As part of a holistic financial planning approach, illiquid assets such as real estate or art can also be included ad hoc in the calculations. In preparation for this use, the connection with the relevant risk factors is described as a logical expression in the system.

Learn more about our other software solutions and our base modules