UNIVDRV - Universal Derivatives Add-in
1. INTRODUCTION |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1.1. What is new in the UNIVDRV - Universal Derivatives Add-in package? | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
UNIVDRV - Universal Derivatives Add-in comprises three integrated algorithm libraries :
UNIVDRV was developed by MBRM as a result of MBRM’s Research and Development on some common problems encountered with the pricing and hedging of European and American style options, e.g. options with :
Standard methodology for option pricing, when the above situations are encountered, can result in pricing functions with poor stability and/or pricing/hedging biases. This is due to two main reasons:
Apart from handling all the above option characteristics, UNIVDRV is capable of :
UNIVDRV is implemented as function calls in a Dynamic Link Library (DLL), thus assisting in the ease of use and integration into the user's analytical environment. It can therefore be called from Excel, Access, Visual Basic, C, C++, Fortran etc. This object-orientated building-block approach provides unequalled speed, cost-effectiveness and flexibility. The software can be linked with most real-time feeds to provide a dynamic analytical environment. The source code for UNIVDRV is written in C++ and is available at extra cost. 1.2. The three models contained in UNIVDRVAlthough UNIVDRV is an integrated package, the algorithms (theoretical models) may be grouped into three categories:
1.2.1. Universal Finite Difference Add-in(UNIVFDIF)UNIVFDIF calculates the option price and the full set of sensitivities of European, American style and Bermudan variable strike exotic options (including discrete windowed and double barriers) on bonds, commodities, currencies, energy, futures and shares (with discrete dividend payments). Exotic options with discrete monitoring of the underlying are valued accurately with the ability to specify the window (i.e. the time of the first and last sampling point/price check) and the number of sampling points/price checks inside the window. Another interesting feature of the model is the way it handles windowed boundaries, term structures and discrete dividends thousands of times more efficiently than Monte Carlo, especially in calculating the sensitivities. The implemented finite difference model has exceptional stability and flexibility. It is very effective in pricing/hedging discrete exotic options regardless of the frequency of monitoring of the underlying, from a single price-check to almost continuous monitoring. The level of accuracy required is a parameter of the pricing function. Usually the three or four most significant digits of the option price are obtained almost instantaneously. Delta, Gamma, Fugit and Theta are calculated with the same accuracy as the option price. These are the options that UNIVFDIF can handle:
As previously mentioned, for every option the user may also define:
1.2.2. Analytical extension to UNIVEXOTThis implements the latest research papers, combined with MBRM’s internal R&D, on the analytical pricing of exotic options (i.e. with formulas or special algorithms). These are the options that the Analytical extension to UNIVEXOT can handle:
1.2.3. Universal Garch Add-in (UNIVGARCH)Monte Carlo pricing of a range of Exotic options of European style handling the term structures of volatilities and interest rates, discrete dividends, windows. UNIVGARCH can assume that the underlying follows either the usual Geometric Brownian Motion or a GARCH process. The non-uniform time stepping of the Monte Carlo simulator (the same principle as the finite difference) allows the most flexible and efficient handling of term structures, windows and discrete dividends; while variance reduction techniques further increase the speed/accuracy ratio. GARCH Option Pricing allows risk-neutral option pricing. With its fat-tailed and asymmetric return distribution it is successful in correcting well known biases of the Black-Scholes formula when the option is out-the-money or short-to-maturity. It is particularly effective in measuring the impact of abnormal returns, sudden changes of volatility, and in anticipating changes of option price on a daily basis, especially in frequently changing markets or when assets do not follow a perfect log-normal distribution. UNIVGARCH implements many other useful functions for the pricing and hedging of options. E.g. a simulator that shows Monte Carlo simulations of prices or volatilities from the same inputs (and with the same flexibility) as the pricing function. Also implemented is an "estimator" function to imply the GARCH volatility parameters from historical prices using an optimised proprietary algorithm, and a function to calculate the expected forward volatility over a short (or long) time horizon. These are the options that UNIVGARCH can handle:
1.3. Confidence in the resultAll the above pricing/hedging models are accessible through the same function by simply changing the model number, enabling immediate comparisons between random walk, GARCH, analytical and finite difference pricing of the same option. This enables the user to choose the model with the speed/accuracy ratio that best suits his needs and also boosts confidence in the result. |
2. PERFORMANCE OF THE SOFTWARE |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
This section shows the performance of the software in dealing with the most common situations. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
2.1. Effect of "discrete monitoring"It is interesting to examine the effect of "discrete monitoring": the frequency with which a price is recorded for the purpose of calculating the payoff of the option (e.g., for a knock-in/out checks are made on whether or not the underlying is beyond a boundary). 2.1.1. A double barrierConsider the following double barrier put: underlying price 100, strike 105, volatility 25%, risk-free rate 5%, expiry one year, and two knock-out boundaries at 70 and 120.
2.1.2. A lookback
2.2. Dividends
2.3. Sensitivities of a discrete double-barrier-in
2.4. Low frequency down-and-in with dividends
2.5. American and Bermudan style options
2.6. Speed of calculation and robustness
|
Cost Saving Bundle
UNIVDRV - Universal Derivatives Add-in is an inclusive package of : | |
UNIVEXOT+ - Universal Analytical Exotics Add-in | |
UNIVFDIF - Universal Finite Difference Add-in | |
UNIVGARCH - Universal Garch Add-in |
Why not consider MBRM Comprehensive Combined Package : An inclusive package of our main software packages (This would be a massive saving on the individual selling price of these packages)
CLICK HERE to see our latest Price List.
Click the thumbnails below for screenshots of our sample spreadsheets: |
|
UDA_XARRAY Example | Calibration Of Local Volatility Surface |
Simulation Using UDA_SIMULATOR2( ) | Estimation Of Garch Parameters |
Fitted Vol Term Structure | |