For many decades, quantitative analysis of the financial markets' ever-expanding array of products has been the domain of a select few. These are highly skilled, quantitatively trained professionals now known often as financial engineers or simply "quants." Bolstered by the growing complexity of emerging products, quants have risen to power as gatekeepers to perhaps the most important black boxes in the financial economy, capital market pricing models.
Pricing models fall into a class of market modeling called "no-arbitrage" models. A no-arbitrage market price is based upon the notion that if we are determining the price of financial instrument A, but A is really comprised of the additive risks inherent in instruments B and C, then the price of A must be equal to the combined prices of B+C. If not, then free money exists in the market, which participants will find and exploit until the arbitrage is no longer available.
Market models in the broadest sense, however, have tremendous applicability across many industries and sectors currently not benefiting from their application. These models are usually deemed either too complex or too difficult to implement in other settings. For instance, quants are rarely if ever engaged to explore the many problems faced by non-trading institutions or individuals. What if a company's perception of risk is not driven purely by the price volatility of the instruments it holds or has issued? When the holding period for a position is long or expected to be held to maturity, the more relevant statistic may be an accrual based concept such as cash flow at risk, earnings volatility, or net income at risk. Better understanding the market risk inherent in metrics such as these often does not require the sophistication of complicated pricing models. However, this understanding is enhanced almost immeasurably by employing conceptually powerful, consistent, market models with a clear visual representation.
New comprehensive solutions are needed that incorporate the insight financial models contribute, without the complexity overhead associated with black box pricing models.