SciComp Inc. Newsletter ~ Summer 2010
Here is the latest news from SciComp on SciFinance®, the complete solution that automates coding and delivers source code (C/C++/CUDA) for derivatives pricing and risk models. For more information on SciFinance, contact SciComp sales.
Table of Contents
Download Reval / SciFinance Case Study
Sign-up and download this case study which details Reval's search for a cost-effective way of accelerating the development and valuation time for highly structured financial instruments.
SciFinance New Capabilities
SciFinance's general Monte Carlo GPU code generation capabilities have been significantly extended in the latest release. This includes support for CUDA 3.0 and Fermi class GPU hardware (Tesla 20-Series).
New Products
SciComp's latest standalone pricing solutions include:
- Bond Calculator: A standalone calculation engine that provides a robust suite of bond calculations for both primary and secondary bond issues.
- Standard Convertible Bond Pricing Model: PDE valuation of a full range of convertible bonds.
- CDS Pricer: A Credit Default Swap pricing solution.
New SciFinance Examples
Expanded SciXpress, SciMC and SciCommodity Examples Catalogs.
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Download Case Study
Reval was looking for a cost-effective and easy to deploy solution for pricing complex derivative instruments using PDEs or Monte Carlo in their flagship SaaS product Reval®. Instruments include Dual Currency bonds, Power Reverse Dual Currency bonds, Inverse Floaters and CMS Steepeners, all with embedded caps and floors and call/put options, as well as Range Accruals and Principal Protected Notes. Reval turned to SciFinance and GPU-enabled models, together with NVIDIA hardware to speed up pricing complex instruments in the cloud.
Click here to download the case study
SciFinance New Capabilities
SciFinance's general Monte Carlo GPU code generation capabilities have been significantly extended in the latest release. This includes support for CUDA 3.0 and Fermi class GPU hardware (Tesla 20-Series). In addition, a variety of refinements have led to a further 30-50% performance increase in already very fast multi-factor Monte Carlo models.
A new market model for commodity futures with storage costs has been added to the commodities example suite. Storage costs are characterized by the contango limits of the futures curve. A no-arbitrage argument is applied to determine the relation between different futures. The model is applied to price commodity derivatives of several kinds.
The Stein stochastic recovery model for CDO pricing has been implemented. It is about 1000 times faster than the Krekel grid method. Running the serial stochastic recovery code with 10,000 scenarios on a Windows XP machine with 2.4GHz CPU, the total serial execution time is about 606 sec, for an average of 5.05 millisec per tranche-scenario.
Re-synthesizing for the GPU and running on a single Fermi card, execution time is reduced from 606 sec to 3.67 sec (30.6 microsec per tranche-scenario) for an acceleration factor of about 165X over serial code. Thus, realistic portfolio risk computations for several thousand tranches and 50,000 scenarios could execute in O(~1hr).
New Products
Each of these SciComp products can be enhanced/modified to meet any particular modeling needs you may have and are available as C/C++ source code, Windows/Linux executable, or a ready-to-use Excel spreadsheet and add-in.Bond Calculator
The Bond Calculator is a standalone calculation engine that provides a robust suite of bond calculations for both primary and secondary bond issues.
Bonds calculations include:
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The Bond Calculator supports:
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Average computing time per function call is approximately 3 msec on a 32 bit Windows XP machine with Intel Core2 CPU @ 2.40GHz and 1 GB of RAM.
The Bond Calculator is available with various interfaces including:
- DLL and sample test harness
- Excel spreadsheet and add-in
- Python wrappers through SWIG
- C/C++ source code
- Microsoft Visual Studio project
Need more information on the SciComp Bond Calculator? Contact SciComp sales.
Standard Convertible Bond Pricing Model
The Standard Convertible Bond Pricing Model (SCB) is an off-the-shelf solution that employs a partial differential equation (PDE) methodology for valuing a full range of convertible bonds. SCB accurately captures dividends and provides much smoother and faster convergence than tree-based approaches. SCB provides comprehensive support for CBs with the standard range of features including:
- Fixed, proportional, or mixed fixed/proportional dividend models.
- Hazard rates calibrated from CDS spreads (or exogenous user input).
- Fixed, floating or mixed fixed/floating coupon models. Explicit coupon date schedules or built internally.
- Soft calls with time variable call price/protection price schedules, including coupon and premium make whole provisions.
- Contingent conversion (COCOs), conversion ratio resets.
- Discrete put schedules
- Funding spread, borrow rate, choice of day count basis and holiday calendar support, switches for inclusion of accrued interest upon call, conversion, put, or default
Need more information on the Standard Convertible Bond Pricing Model? Contact SciComp sales.
CDS Pricer
The CDS Pricer employs an intensity-based framework to price a standard credit default swap contract with upfront payment and subsequent running coupons. A CDS Calibrator is included to extract the underlying piecewise constant hazard curve from standard CDS market quotes.
The CDS Pricer provides comprehensive support for valuing credit default swaps with the standard range of features including:
- Running coupon rate, upfront point and recovery rate
- Both constant hazard rate or term structure hazard rates
- Calibration of hazard rates to CDS market quotes (spreads or upfront points with running coupons)
- Coupon date and maturity date adjustments, roll conventions, choice of day count basis and holiday calendar support
Need more information on the CDS Pricer? Contact SciComp sales.
New SciFinance Examples
The SciFinance Examples Catalogs provide hundreds of pricing and risk model specifications for all asset classes. The SciXpress Catalog has been updated with new concise specifications for PDEs. The SciMC and SciCommodity catalogs have been updated with new examples and revisions of existing ones.
Here is a sampling of the new and revised SciFinance examples:
| Cross Currency | |
mcFXCrossBarrier1 |
A continuously monitored, foreign exchange cross barrier (outside barrier) option. |
| xpdeFXCrossBarrier1 | A continuously monitored foreign exchange cross barrier (outside barrier) option. |
mcSVFXCrossBarrier1 |
A continuously monitored FX cross barrier option. FX rate processes follow a combined local / stochastic volatility model. A 7-factor model; 2 factors for each of the FX processes and 1 factor for each of 3 stochastic interest rates. |
| mcG2G2CMSSpreadRangeAccrual1 | A cross-currency CMS spread range accrual swap, each rate under a G2 short rate model. |
| Asian options | |
| mcAsian1 | Prices a discretely sampled, average rate or average strike Asian option. |
| mcAsian2 | Identical to mcAsian1, except that average stock price is specified using the AveOf[] operator. |
| xpedAveRate3 | A European discretely sampled average-rate option using a simple Black-Scholes model. It is identical to that of xpdeAveRate2 except that it allows averaging with a general power p. |
| xpdeAveStrike3 | A European, discretely sampled, average- strike option generalized to allow averaging with a general power p. It is identical to xpdeAveRate3 except that the spot price has replaced the fixed strike K in the payoff and the grid equations. |
| Commodities | |
mcStorageCost1 |
A market model for commodity futures with storage costs applied to an Asian option on the futures. |
mcStorageCostPath1 |
Identical to mcStorageCost1 except for the generated paths are for Futures prices are stored. |
| Multi-Asset | |
| mcTimeDepRho2 | A two-asset European basket option with time-dependent correlation matrix. Off-diagonal correlation coefficient is given by an interpolation. |
| Fokker-Planck | |
xpdeLVSVFokkerPlanck1 |
Computes the probability distribution function for the forward price S under a combined local/stochastic volatility model. |
| Fixed Income (Short Rate Models, Two factor Gaussian models of these already exist) | |
| mcG1CallSnowballNote1 | Prices a callable snowball note under a one-factor Gaussian short rate model (G1). A callable snowball note under a one- factor Gaussian (G1), short-rate model. The snowball note pays coupons that depend on the previous rate and the current Libor rates with a spread. |
| mcG1RatchetCap1 | Prices a ratchet cap under a one-factor Gaussian short-rate model (G1). |
| mcG1CallFRN1 | Prices a callable Floating Rate Note under a one-factor Gaussian short rate model (G1). |
| xpdeG1Cap2 | Prices a cap under the G1 short rate model. Similar to xpdeG1Cap1, but with a more accurate structured grid. |
| xpdeG1CancelAmortSwap1 | Prices a Bermudan payer/receiver amortizing swap cancellable by the holder, under a one factor additive Gaussian short rate model (G1). |
| Fixed Income (LIBOR) | |
| mcLMCallRangeBond1 | Prices a callable Range Bond in a two factor Libor market model. |
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