Numerix
Numerix is the global leader in cross-asset analytics for OTC derivatives, structured products and variable annuities, providing software and services for structuring, pre-trade pricing, trade capture, valuation, and risk management. Numerix offers a comprehensive model library and a transparent deal-definition architecture that allows rapid modeling of any instrument, including commodity, credit, equity, fixed income, foreign exchange, and inflation derivatives, plus a unique hybrid model framework for exotics and structured products. Numerix analytics are available through Windows applications, Excel add-ins, developer kits and a wide range of partner systems, with over 700 clients and 80 partners across more than 25 countries.
All content by Numerix
Negative Rates: The Challenge and the Opportunity
Negative interest rates have recently become a critically important issue in finance, as they impact some of the most basic calculations and procedures used by the financial community. Two prominent examples are the quotation of option volatilities and volatility smile interpolation models.
Navigating the Murky Waters of Initial Margin for OTC Derivatives
This white paper looks at a breakdown of the different regulations for non-centrally cleared trades, how the new IM requirements affect the OTC derivative markets participants, IM based methodologies, the potential issues of the new sanctions and how to manage the ambiguities around IM.
The Free Boundary SABR: Natural Extension to Negative Rates
This white paper describes one such extension of the widely used SABR model. We stress that our solution is more natural and attractive than the shifted SABR. An exact formula is derived for the option prices in the case of zero correlation between the rate and its volatility. For nonzero…
Reducing the Risk of Using Financial Models
At their core, institutional financial markets exist to transfer risk. Whether via corporate lending, equity ownership or the creation and sale of structuredcredit derivatives, financial firms work to shuffle around different forms of risks—from those looking to mitigate it to those looking to take…
Real-World Equity & Volatility Behavior: Implications for Economic Scenario Generation
This paper examines the differences between risk-neutral dynamics and real-world dynamics, and the important role of risk premia. We highlight why real-world dynamics are necessary for risk analysis and scenario generation, and also explore the roles of the equity premium and volatility premium in…
Integrating Risk into Pre-Trade Analysis: Practical Ways of Bringing Credit, Liquidity, Funding and Regulatory Costs into an Integrated Profitability Framework
As regulations in the derivatives market continue to be rolled out and implemented, financial institutions face growing pressure on their current business models. To survive and thrivein this new era of derivatives trading, today’s practitioners need to adopt a more integrated and holistic approach…
Risk Neutral Modeling for Economic Scenario Generation: In Theory and Practice
This white paper explores the theory behind and practice surrounding Risk Neutral Modeling for Economic Scenario Generation (ESG). In addition to laying out the foundations of the RiskNeutral Measure and Fundamental Theorem, this study also sets forth several practical case study examples that…
Model Validation: New Approaches in Testing Mathematical and Financial Correctness of Models
In this paper, we will examine model validation as it is typically practiced today and then explore new approaches, including the benefits of testing with mathematical identities.
The OIS & FVA Relationship: The Evolution of OTC Derivative Funding Dynamics
We will begin this paper with a discussion of the basics of OIS discounting and FVA for OTC derivatives—and then explore the relationship between the two concepts. We will also look at a case study that highlights the potential impact of FVA on trade profitability.
Model Risk: The Challenges of Legacy Code and Best Practices
In this paper, we will examine the most common types and sources of model risk, and then outline best practices that practitioners can utilize in their model validation processes.