Our post-modern copula based statistical models assist our clients to accurately measure and monitor market risk & stressed losses.


Market risk refers to the risk of losses in a firm’s trading book due to changes in equity prices, interest rates, credit spreads, foreign-exchange rates, commodity prices, and other indicators whose values are set in a public market. To manage market risk, firms deploy a number of highly sophisticated mathematical and statistical techniques. Most popular among these is value-at-risk (VAR) analytics, which over the past 15 years has become established as the industry and regulatory standard in measuring market risk.


With time, firms need more efficient, versatile and highly functional analytics tools to address new, complex issues related to market risk. Market risk analytics involve a comprehensive set of integrated, scalable and productive solutions for wide-range risk management across various verticals of asset classes.


Risk analytics basically help organizations realize the existence of risks lying under business activities – by facilitating enterprises to identify, determine and manage their company risk. In lieu of this, the pressing need for risk analytics is going to increase across industries in the coming few years. New developments, like real-time risk analytics, which is an advanced form of traditional risk analytics process that estimates risk on a real-time basis, are influencing the entire market, while accentuating its mitigating abilities.


Our globally experienced team has been providing risk analytics and advisory services for past 25 years. We are a group of senior professionals, each with decades of direct market experience that includes trading, managing risk, working with regulators and serving on boards. We also specialize in derivatives, asset-backed securities, mortgage products (Agency and private label MBS, CMOs, and whole loans), structured finance and other complex financial products and strategies. We assist our client in advanced VaR based modeling, EVA modeling, tail loss estimation, development of Copula models, and neural simulation models for the estimation and risk management of equity, interest rates, commodity, foreign currency and derivatives portfolios.