Volpredict is a forecasting tool of market volatility.

  • On agricultural commodities markets, It will help organizations like agricultural cooperatives or large farmers.
  • On financial markets, investors, funds’ managers, trackers’ managers as well as hedge funds will find it important to use it.
  • It is a thoroughly innovative product, which demonstrates the potential of a quantitative behavioral finance compared to established statistical approaches in appraising dynamic systems or time series. The model outperforms in virtually every respect the best Garch-models and can lead to as desirable results as the most up-t-date (and over-sophisticated) models.
  • Volpredict analyses market time series as simple dynamic systems. It transforms an underlying model (by Maurice Allais, Nobel Prize winner 1988) into an out of sample forecasting tool, yielding a forecasted long term tendency of volatility. It then builds on this first stage a short term appraisal of volatility peaks – well beyond what the Gaussian vision of « modern » financial theory claims. The result is a forecast of the average volatility for the next month which fits observed data better than the best existing statistical Garch models, both in terms of volatility measures and in terms of changes of direction in market volatility (increase or decrease in the next month).

In finance, this type of information is of obvious strategic use, be it for short term investment or for internal determination of most likely prices in the near future. In agriculture, it is one of the important determinants in timing sales of crops or timing buys of needed commodities in the agri-business industry.

NERP7.1 (NewEraRiskProfiler™7.1)

To all organizations which care - for one reason or another - about the risk behavior of their individual clients (notably in the financial sector) or of their individual employees, this software will yield a precise and appropriate answer in less than 10 minutes, based on a scientific protocol-algorithm designed by Riskinnov Ltd.. It doesn’t pre-suppose any mathematical underlying model and is able to capture 85% of all possible human attitudes. Examples of use can be found in:

  • Wealth management (private banks, insurance companies, individual wealth managers, e.g.)
  • Gambling houses,
  • Hiring maintenance employees in organizations running dangerous sensitive systems, etc.

In the first set of companies, the tool is both a brand signal from the company and a consumer-investor protection tool (the famous “suitability” issue in investment and advisory), yet informing correctly the banker and smoothing up the client-investment house relationship. In addition, its design makes it also an internal coordination tool.

In the other situations evoked it is both a protective tool to preserve the smooth functioning and the image of the company (examples of the nuclear industry), while giving to the rules of the game practical meaning for the candidates to jobs.

In all cases, this marketing tool is transparency enhancing, corporate culture enhancing, and a great facilitation tool in a large number of corporations.

For more, see https://rissk.com. For a more technical appraisal, see: “International Encyclopedia for Risk Analysis and Assessment”, vol. 4, article “Risk Attitude”, by B. Munier and C. Tapiero, 1512-1524 (Wiley)


  • All sectors in the economy ask for decision-aid when it comes to far fletched decisions under risk involving multiple aspects. Evaluating under Risk Multi-objective Options (ERMO) to reach smart decisions is then no simple matter.
  • ERMO will enable decision makers to conduct a bespoke check their of their intuitions and rank accordingly available solutions from best to worst. More specifically, it allows bespoke decision-aiding because it will help decision makers rank available solutions taking into account their own strategic thinking as well as their own risk-attitude.
  • In addition, in B-to-B risky project management, it allows reconstructing the decision system of the major buyers and hence serves as a marketing tool.
  • Example: An international heavy equipment firm wants to launch a new bulldozer. We helped reconstruct an effective model of the decision system of their typical buyers. The firm was consequently enabled to consider many quality-selling price combinations which would not hamper the loyalty of its clients and yet could be an argument for the client to reach the decision to buy the new equipment. Based on these strategic marketing possibilities, the firm was able to rank all possible variants of quality-delay- profitability- from the point of view of its own decision makers. The new equipment sold quite well.
  • For more, see our paper Oxford IMA Management Mathematics Journal: https://academic.oup.com/imaman/article-abstract/doi/10.1093/imaman/dpw018/2670290/On-bespoke-decision-aid-under-risk-the-engineering