Effective Sub-Simulation-Free Upper Bounds for the Monte Carlo Pricing of Callable Derivatives and Various Improvements to Existing Methodologies by Mark S. Joshi and Robert Tang

We present a new non-nested approach to computing additive upper bounds for callable derivatives using Monte Carlo simulation. It relies on the regression of Greeks computed using adjoint methods. We also show that it is is possible to early terminate paths once points of optimal exercise have been reached. A natural control variate for the multiplicative upper bound is introduced which renders it competitive to the additive one. In addition, a new bi-iterative family of upper bounds is introduced which take a stopping time, an upper bound, and a martingale as inputs.

Optimal Limit Methods for Computing Sensitivities of Discontinuous Integrals Including Triggerable Derivative Securities by Jiun Hong Chan and Mark S. Joshi

We introduce a new approach to computing sensitivities of discontinuous integrals. The methodology is generic in that it only requires knowledge of the simulation scheme and the location of the integrand's singularities. The methodology is proven to be optimal in terms of minimizing the variance of the measure changes caused by the elimination of the discontinuities for finite bump sizes. An efficient adjoint implementation of the small bump-size limit is discussed, and the method is shown to be effective for a number of natural examples involving triggerable interest rate derivative securities.

Fourier Transforms, Option Pricing and Controls by Mark S. Joshi and Chao Yang

We incorporate a simple and effective control-variate into Fourier inversion formulas for vanilla option prices. The control-variate used in this paper is the Black-Scholes formula whose volatility parameter is determined in a generic non-arbitrary fashion. We analyze contour dependence both in terms of value and speed of convergence. We use Gaussian quadrature rules to invert Fourier integrals, and numerical results suggest that performing the contour integration along the real axis leads to the best pricing performance.

Accelerating Pathwise Greeks in the LIBOR Market Model by Mark S. Joshi Alexander Wiguna

In the framework of the displaced-diffusion LIBOR market model, we derive the pathwise adjoint method for the iterative predictor-corrector and Glasserman-Zhao drift approximations in the spot measure. This allows us to compute fast deltas and vegas under these schemes. We compare the discretisation bias obtained when computing Greeks with these methods to those obtained under the log-Euler and predictor-corrector approximations by performing tests with interest rate caplets and cancellable receiver swaps. The two predictor-corrector type methods were the most accurate by far. In particular, we found the iterative predictor-corrector method to be more accurate and slightly faster than the predictor-corrector method, the Glasserman-Zhao method to be relatively fast but highly inconsistent, and the log-Euler method to be reasonably accurate but only at low volatilities. Standard errors were not significantly different across all four discretisations.

Fast Gamma Computations for CDO Tranches by Mark S. Joshi and Chao Yang

We demonstrate how to compute first- and second-order sensitivities of portfolio credit derivatives such as synthetic collateralized debt obligation (CDO) tranches using algorithmic Hessian methods developed in Joshi and Yang (2010) in a single-factor Gaussian copula model. Our method is correct up to floating point error and extremely fast. Numerical result shows that, for an equity tranche of a synthetic CDO with 125 names, we are able to compute the whole Gamma matrix with computational times measured in seconds.

First and Second Order Greeks in the Heston Model by Jiun Hong Chan and Mark Joshi

In this paper, we present an efficient approach to compute the first and the second order price sensitivities in the Heston model using the algorithmic differentiation approach. Issues related to the applicability of the pathwise method are discussed in this paper as most existing numerical schemes are not Lipschitz in model inputs. Depending on the model inputs and the discretization step size, our numerical tests show that the sample means of price sensitivities obtained using the Lognormal scheme and the Quadratic-Exponential scheme can be highly skewed and have fat-tailed distribution while price sensitivities obtained using the Integrated Double Gamma scheme and the Double Gamma scheme remain stable.

Efficient Pricing and Greeks in the Cross-Currency LIBOR Market Model by Chris Beveridge, Mark Joshi, and Will Wright, to appear in *Journal of Risk*

We discuss the issues involved in an efficient computation of the price and sensitivities of Bermudan exotic interest rate derivatives in the cross-currency displaced diffusion LIBOR market model. Improvements recently developed for an efficient implementation of the displaced diffusion LIBOR market model are extended to the cross-currency setting, including the adjoint-improved pathwise method for computing sensitivities and techniques used to handle Bermudan optionality. To demonstrate the application of this work, we provide extensive numerical results on two commonly traded cross-currency exotic interest rate derivatives: cross-currency swaps (CCS) and power reverse dual currency (PRDC) swaps.

Algorithmic Hessians and the Fast Computation of Cross-Gamma Risk by Mark Joshi and Chao Yang, to appear in *Transactions of the IIE*

We introduce a new methodology for computing Hessians from algorithms for function evaluation, using backwards methods. We show that the complexity of the Hessian calculation is a linear function of the number of state variables times the complexity of the original algorithm. We apply our results to computing the Gamma matrix of multi-dimensional financial derivatives including Asian Baskets and cancellable swaps. In particular, our algorithm for computing Gammas of Bermudan cancellable swaps is order O(n^2) per step in the number of rates. We present numerical results demonstrating that the computing all n(n+1)/2 Gammas in the LMM takes roughly n/3 times as long as computing the price.

Fast Greeks for Markov-Functional Models Using Adjoint Pde Methods by Nick Denson and Mark Joshi

This paper demonstrates how the adjoint PDE method can be used to compute Greeks in Markov-functional models. This is an accurate and efficient way to compute Greeks, where most of the model sensitivities can be computed in approximately the same time as a single sensitivity using finite difference. We demonstrate the speed and accuracy of the method using a Markov-functional interest rate model, also demonstrating how the model Greeks can be converted into market Greeks.

Fast and Accurate Long Stepping Simulation of the Heston Stochastic Volatility Model by Jiun Hong Chan and Mark Joshi. Here is the C++ code including a Visual Studio 9.0 project for this scheme . to appear in *Journal of Computational Finance*

In this paper, we present three new discretization schemes for the Heston stochastic volatility model - two schemes for simulating the variance process and one scheme for simulating the integrated variance process conditional on the initial and the end-point of the variance process. Instead of using a short time-stepping approach to simulate the variance process and its integral, these new schemes evolve the Heston process accurately over long steps without the need to sample the intervening values. Hence, prices of financial derivatives can be evaluated rapidly using our new approaches.

Monte Carlo Bounds for Game Options Including Convertible Bonds by Chris Beveridge and Mark Joshi, *Management Science*

We introduce two new methods to calculate bounds for zero-sum game options using Monte Carlo simulation. These extend and generalise the duality results of Haugh--Kogan/Rogers and Jamshidian to the case where both parties of a contract have Bermudan optionality. It is shown that the Andersen--Broadie method can still be used as a generic way to obtain bounds in the extended framework, and we apply the new results to the pricing of convertible bonds by simulation.

Monte Carlo Market Greeks in the Displaced Diffusion LIBOR Market Model by Mark Joshi and Oh Kang Kwon, to appear in *Journal of Risk*

The problem of developing sensitivities of exotic interest rates
derivatives to the observed implied volatilities of caps and swaptions
is considered. It is shown how to compute these from sensitivities to
model volatilities in the displaced diffusion LIBOR market model. The
example of a cancellable inverse floater is considered.

Truncation and Acceleration of the Tian Tree for the Pricing of American Put Options by Ting Chen and Mark S. Joshi, to appear in *Quantitative Finance*

We present a new method for truncating binomial trees based on using a
tolerance to control truncation errors and apply it to the Tian tree
together with acceleration techniques of smoothing and Richardson
extrapolation. For both the current (based on standard deviations) and
the new (based on tolerance) truncation methods, we test different
truncation criteria, levels and replacement values to obtain the best
combination for each required level of accuracy. We also provide
numerical results demonstrating that the new method can be 50% faster
than previously presented methods when pricing American put options in
the Black-Scholes model.

Fast Monte-Carlo Greeks for Financial Products With Discontinuous Pay-Offs by Jiun Hong Chan and Mark S. Joshi, to appear in *Mathematical Finance*

We introduce a new class of numerical schemes for discretizing
processes driven by Brownian motions. These allow the rapid computation
of sensitivities of discontinuous integrals using pathwise methods even
when the underlying densities post-discretization are singular. The two
new methods presented in this paper allow Greeks for financial products
with trigger features to be computed in the LIBOR market model with
similar speed to that obtained by using the adjoint method for
continuous pay-offs. The methods are generic with the main constraint
being that the discontinuities at each step must be determined by a
one-dimensional function: the proxy constraint. They are also generic
with the sole interaction between the integrand and the scheme being
the specification of this constraint.

Fast and Accurate Pricing and Hedging of Long-Dated CMS Spread Options by Mark S. Joshi and Chao Yang, *International Journal of Theoretical and Applied Finance*

We present a fast method to price and hedge CMS spread options in the
displaced-diffusion co-initial swap market model. Numerical tests
demonstrate that we are able to obtain sufficiently accurate prices and
Greeks with computational times measured in milliseconds. Further, we
find that CMS spread options are weakly dependent on the at-the-money
Black implied volatility skews.

Fast Sensitivity Computations for Monte Carlo Valuation of Pension Funds by Mark S. Joshi and David Pitt, *ASTIN Bulletin*

Sensitivity analysis, or so-called 'stress-testing', has long been part
of the actuarial contribution to pricing, reserving and management of
capital levels in both life and non-life assurance. Recent developments
in the area of derivatives pricing have seen the application of adjoint
methods to the calculation of option price sensitivities including the
well-known 'Greeks' or partial derivatives of option prices with
respect to model parameters. These methods have been the foundation for
efficient and simple calculations of a vast number of sensitivities to
model parameters in financial mathematics. This methodology has yet to
be applied to actuarial problems in insurance or in pensions. In this
paper we consider a model for a defined benefit pension scheme and use
adjoint methods to illustrate the sensitivity of fund valuation results
to key inputs such as mortality rates, interest rates and levels of
salary rate inflation. The method of adjoints is illustrated in the
paper and numerical results are presented. Efficient calculation of the
sensitivity of key valuation results to model inputs is useful
information for practising actuaries as it provides guidance as to the
relative ultimate importance of various judgments made in the formation
of a liability valuation basis.

Graphical Asian Options by Mark S. Joshi, *Wilmott Journal*

We study the problem of pricing an Asian option using CUDA on a
graphics processing unit. We demonstrate that it is possible to get
accuracy of 2E-4 in less than a fiftieth of a second.

Interpolation
Schemes in the Displaced-Diffusion LIBOR Market Model and the Efficient
Pricing and Greeks for Callable Range Accruals by Christopher Beveridge and Mark S. Joshi

We introduce a new arbitrage-free interpolation scheme for the
displaced-diffusion LIBOR market model. Using this new extension, and
the Piterbarg interpolation scheme, we study the simulation of range
accrual coupons when valuing callable range accruals in the
displaced-diffusion LIBOR market model. We introduce a number of new
improvements that lead to significant efficiency improvements, and
explain how to apply the adjoint-improved pathwise method to calculate
deltas and vegas under the new improvements, which was not previously
possible for callable range accruals. One new improvement is based on
using a Brownian-bridge-type approach to simulating the range accrual
coupons. We consider a variety of examples, including when the
reference rate is a LIBOR rate, when it is a spread between swap rates,
and when the multiplier for the range accrual coupon is stochastic.

Fast and Accurate Greeks for the Libor Market Model by Nick Denson and Mark Joshi

This paper derives the pathwise adjoint method for the predictor-corrector drift approximation in the displaced-diffusion LIBOR market model. We present a comparison of the Greeks between log-Euler and predictor-corrector, showing both methods have the same computational order but the latter to be much more accurate.

Pricing and Deltas of Discretely-Monitored Barrier Options Using Stratified Sampling on the Hitting-Times to the Barrier by Mark Joshi and Robert Tang, to appear in International Journal of Theoretical and Applied Finance

We develop new Monte Carlo techniques based on stratifying the stock's hitting-times to the barrier for the pricing and Delta calculations of discretely-monitored barrier options using the Black-Scholes model. We include a new algorithm for sampling an Inverse Gaussian random variable such that the sampling is restricted to a subset of the sample space. We compare our new methods to existing Monte Carlo methods and find that they can substantially improve convergence speeds.

Efficient Greek estimation in generic market models by Mark Joshi and Chao Yang

We first develop an efficient algorithm to compute Deltas of interest rate derivatives for a number of standard market models. The computational complexity of the algorithms is shown to be proportional to the number of rates times the number of factors per step. We then show how to extend the method to efficiently compute Vegas in those market models.

Minimal Partial Proxy Simulation Schemes for Generic and Robust Monte-Carlo Greeks by Jiun-Hong Chan and Mark Joshi

In this paper, we present a generic framework known as the minimal partial proxy simulation scheme. This framework allows stable computation of the Monte-Carlo Greeks for financial products with trigger features via finite difference approximation. The minimal partial proxy simulation scheme can be considered as a special case of the partial proxy simulation scheme (Fries and Joshi, 2008b) as a measure change (weighted Monte Carlo) is performed to prevent path-wise discontinuities. However, our approach differs in term of how the measure change is performed. Specifically, we select the measure change optimally such that it minimises the variance of the Monte-Carlo weight. Our method can be applied to popular classes of trigger products including digital caplets, autocaps and target redemption notes. While the Monte-Carlo Greeks obtained using the partial proxy simulation scheme can blow up in certain cases, these Monte-Carlo Greeks remain stable under the minimal partial proxy simulation scheme. Standard errors for Vega are also significantly lower under the minimal partial proxy simulation scheme.

Flaming logs by Mark Joshi and Nick Denson, to appear in *Wilmott Journal*

This paper extends the pathwise adjoint method for Greeks to the displaced-diffusion LIBOR market model and also presents a simple way to improve the speed of the method. The speed improvements of approximately 20% are achieved without using any additional approximations to those of Giles and Glasserman.

Fast Delta Computations in the Swap-Rate Market Model by Mark Joshi and Chao Yang

We develop an efficient algorithm to implement the adjoint method that computes sensitivities of an interest rate derivative (IRD) with respect to different underlying rates in the co-terminal swap-rate market model. The order of computation per step of the new method is shown to be proportional to the number of rates times the number of factors, which is the same as the order in the LIBOR market model.

Vega Control by Nick Denson and Mark Joshi

The calculation of prices and sensitivities of exotic interest rate derivatives in the LIBOR market model is often very time consuming. One approach that has been previously suggested is to use a Markov-functional model as a control variate for prices and deltas but not vegas. We present a new approach that is effective for prices, deltas and vegas. It achieves a standard error reduction by a factor of 10 for the price of a five-factor, twenty-year Bermudan swaption, and of 5 for its vega.

Practical Policy Iteration: Generic Methods for Obtaining Rapid and Tight Bounds for Bermudan Exotic Derivatives Using Monte Carlo Simulation by Christopher Beveridge and Mark S. Joshi

We introduce a set of improvements which allow the calculation of very tight lower bounds for Bermudan derivatives using Monte Carlo simulation. These lower bounds can be computed quickly, and with minimal hand-crafting. Our focus is on accelerating policy iteration to the point where it can be used in similar computation times to the basic least-squares approach, but in doing so introduce a number of improvements which can be applied to both the least-squares approach and the calculation of upper bounds using the Andersen-Broadie method. The enhancements to the least-squares method improve both accuracy and efficiency. Results are provided for the displaced-diffusion LIBOR market model, demonstrating that our practical policy iteration algorithm can be used to obtain tight lower bounds for cancellable CMS steepener, snowball and vanilla swaps in similar times to the basic least-squares method.

Trinomial or Binomial: Accelerating American Put Option Price on Trees by Jiun Hong Chan, Mark S. Joshi, Robert Tang and Chao Yang, *Journal of Futures Markets*, Vol 29, Number 9, September 2009, 826--839

We
investigate the pricing performance of eight trinomial trees and one
binomial tree, which was found to be most effective in an earlier
paper, under twenty different implementation methodologies for pricing
American put options. We conclude that the binomial tree, the Tian
third order moment matching tree with truncation, Richardson
extrapolation and smoothing performs better than the trinomial trees.

Juggling Snowballs by Christopher Beveridge and Mark S. Joshi, *Risk Magazine*, December 2008

The pricing of snowball notes in the full-factor LIBOR market model is considered. The primary aspect of the problem considered is the early exercise feature, and it is shown how to characterize a class of sub-optimal points of exercise. By combining this characterization with least-squares regression on a suitable set of basis functions and using an extra trigger enhancement, it is shown that very tight lower bounds can be obtained in cases where previous methods required the use of sub-Monte Carlo simulations.

Conditional Analytic Monte Carlo Pricing Scheme for Auto-Callable Products by Christian Fries and Mark S. Joshi

In this paper we present a generic method for the Monte-Carlo pricing of (generalized) auto-callable products (aka. trigger products), i.e., products for which the payout function features a discontinuity with a (possibly) stochastic location (the trigger) and value (the payout). The Monte-Carlo pricing of the products with discontinuous payout is known to come with a high Monte-Carlo error. The numerical calculation of sensitivities (i.e., partial derivatives) of such prices by finite differences gives very noisy results, since the Monte-Carlo approximation (being a finite sum of discontinuous functions) is not smooth. Additionally, the Monte-Carlo error of the finite-difference approximation explodes as the shift size tends to zero. Our method combines a product specific modification of the underlying numerical scheme, which is to some extent similar to an importance sampling and/or partial proxy simulation scheme and a reformulation of the payoff function into an equivalent smooth payout. From the financial product we merely require that hitting of the stochastic trigger will result in an conditionally analytic value. Many complex derivatives can be written in this form. A class of products where this property is usually encountered are the so called auto-callables, where a trigger hit results in cancellation of all future payments except for one redemption payment, which can be valued analytically, conditionally on the trigger hit. From the model we require that its numerical implementation allows for a calculation of the transition probability of survival (i.e., non-trigger hit). Many models allows this, e.g., Euler schemes of Itô processes, where the trigger is a model primitive. The method presented is effective across a large range of cases where other methods fail, e.g. small finite difference shift sizes or short time to trigger reset (approaching maturity); this means that a practitioner can use this method and be confident that it will work consistently.

Smooth simultaneous calibration of the LMM to caplets and co-terminal swaptions by Ferdinando Ametrano and Mark S. Joshi.

We introduce a new calibration methodology that allows perfect fitting of the displaced diffusion LIBOR market model to caplets and co-terminal swaptions, whilst avoiding global optimizations. The approach works by regarding a forward rate as a difference of swap-rates and then bootstrapping through rates one by one.Comparing discretisations of the Libor market model in the spot measure by Chris Beveridge, Nick Denson and Mark S. Joshi

Various drift approximations for the displaced-diffusion LIBOR market model in the spot measure are compared. The advantages, disadvantages and implementation choices for each of predictor-corrector and the Glasserman--Zhao method are discussed. Numerical tests are carried out and we conclude that the predictor-corrector method is superior.The
Convergence of Binomial Trees for Pricing the American Put by
Mark S. Joshi, *Journal of Risk*, Vol 11, Number 4, Summer 2009, 87--108

Abstract: We study 20 different implementation methodologies for each of 11 different choices of parameters of binomial trees and investigate the speed of convergence for pricing American put options numerically. We conclude that the most effective methods involve using truncation, Richardson extrapolation and sometimes smoothing. We do not recommend use of a European option as a control. The most effective trees are the Tian third order moment matching tree and a new tree designed to minimize oscillations.

Achieving Higher Order Convergence for The
Prices of European Options In Binomial Trees by Mark S. Joshi, *Mathematical Finance, January 2010*

Abstract: A new family of binomial trees as approximations to the Black--Scholes model is introduced. For this class of trees, the existence of complete asymptotic expansions for the prices of vanilla European options is demonstrated and the first three terms are explicitly computed. As special cases, a tree with third order convergence is constructed and the conjecture of Leisen and Reimer that their tree has second order convergence is proven.

Partial
Proxy Simulation Schemes for Generic and Robust Monte-Carlo Greeks
by Christian Fries and Mark S. Joshi, *Journal of
Computational Finance, *March 2008

Abstract: We consider a generic framework which allows to calculate robust Monte-Carlo sensitivities seamlessly through simple finite difference approximation. The method proposed is a generalization and improvement of the proxy simulation scheme method (Fries and Kampen, 2005). As a benchmark we apply the method to the pricing of digital caplets and target redemption notes using LIBOR and CMS indices under a LIBOR Market Model. We calculate stable deltas, gammas and vegas by applying direct finite difference to the proxy simulation scheme pricing. The framework is generic in the sense that it is model and almost product independent. The only product dependent part is the specification of the proxy constraint. This allows for an elegant implementation, where new products may be included at small additional costs

Achieving smooth asymptotics for the prices of
European options in binomial trees by Mark S. Joshi, *Quantitative Finance, * March 2009

Abstract: A new binomial approximation to the Black–Scholes model is introduced. It is shown that for digital options and vanilla European call and put options that a complete asymptotic expansion of the error in powers of 1/n exists. This is the first binomial tree for which such an asymptotic expansion has been shown to exist.

Intensity Gamma: a
new approach to pricing portfolio credit derivatives, by Mark
S. Joshi and Alan M. Stacey, *Risk Magazine July 2006*

Abstract: We develop a completely new model for correlation of credit defaults based on a financially intuitive concept of business time similar to that in the Variance Gamma model for stock price evolution. Solving a simple equation calibrates each name to its credit spread curve and we show that the overall model can be calibrated to the market base correlation curve of a tranched CDO index. Once this calibration is performed, obtaining consistent arbitrage-free prices for non-standard tranches, products based on different underlying names and even more exotic products such as $\mathrm{CDO}^2$ is straightforward and rapid.

Using
Monte Carlo
simulation and importance sampling to rapidly obtain jump-diffusion
prices of continuous barrier options by Mark S. Joshi and Terence
Leung. *Journal of Computational Finance*, July 2007

Abstract.
The problem of pricing a
continuous barrier option in a jump-diffusion model is studied. It is
shown that via an effective combination of importance sampling and
analytic formulas that substantial speed ups can be achieved. These
techniques are shown to be particularly effective for computing deltas.

Rapid computation of drifts in a reduced
factor LIBOR Market Model
by Mark S. Joshi,
*Wilmott May 2003*

Abstract: An algorithm of order number of factors times number of rates for the computing the drifts of all the rates in the LIBOR market model. This is better than the naive algorithm which is of order number of rates squared.

Monte Carlo bounds for callable products with non-analytic break costs by Mark S. Joshi

Abstract. The pricing of callable derivative products with complicated pay-offs is studied. A new method for finding upper bounds by Monte Carlo simulation is introduced, this relies on modelling the callable product directly. The method has a wide range of applicability and is shown to be effective for Asian tail products. Presentation

Achieving
decorrelation and speed simultaneously in the LIBOR market model
by Mark S. Joshi, *Journal of Risk*, 2006

Abstract. An algorithm for computing the drift in the LIBOR market model with additional idiosynchratic terms is introduced. This algorithm achieves a computational complexity of order equal to the number of common factors times the number of rates. It is demonstrated that this allows better matching of correlation matrices in reduced-factor models.

A simple derivation of and
improvements to Jamshidian's and Rogers' upper bound methods for
Bermudan options by Mark S. Joshi, *Applied
Mathematical Finance *July 2007

Abstract. Rogers’ method for upper bounds for Bermudan options is rephrased in terms of buyers and sellers prices. It is shown how to deduce Jamshidian’s upper bound result in a simple fashion from Roger’s method, including the case of possibly zero final pay-off. Both methods are improved by ruling out exercise at suboptimal points. It is also shown that it is possible to use sub- Monte Carlo simulations to estimate the value of the hedging portfolio at intermediate points in the Jamshidian method without jeopardizing its status as upper bound.

Effective
implementation of generic market models by Mark S. Joshi and
Lorenzo Liesch, *ASTIN Bulletin* Dec 2007

Abstract. A number of standard market models are studied. For each one, algorithms of computational complexity equal to the number of rates times the number of factors to carry out the computations for each step are introduced. Two new classes of market models are developed and it is shown for them that similar results hold.

New and robust drift
approximations for the LIBOR market model by Mark S. Joshi
and Alan Stacey, *Quantitative Finance* 2008

Abstract: We present four new methods for approximating the drift in the LIBOR market model. These are compared to a variety of existing methods including PPR, Glasserman-Zhao and predictor-corrector. We see that two of them which use correlation adjustments to better approximate the drift are more effective than existing methods.

Option Pricing and
the Dirichlet problem by Mark S. Joshi, *Wilmott
Magazine, *2006

It is well-known that the Dirichlet problem for the Laplacian on a reasonably smooth compact domain in Rn can be solved using Brownian motion. Indeed the result was found by Kakutani in 1944, [3, 4]. In this note, I want to discuss how this result can be reinterpreted financially. Our objective is to increase our intuition about the problem rather than to attempt to prove new results.

See also www.quarchome.org

Here's my advice sheet for those wanting to work as a quantitative analyst in finance. It was originally aimed at pure maths PhDs, but lots of other people seem to like it.

I have now released xlw 2.1 formerly called xlwPlus. xlw is a package for creating xlls in C++ with minimal effort. An xll is a way of adding new functions to EXCEL xlwPlus has various added features, the most important is that the interfacing code is generated automatically by an extra routine instead of being coded manually. If you have any questions, please ask them on xlw-users mailing list on sourceforge. Eric Ehlers has now updated xlw to contain the new Excel Interface. Narinder Claire has provided further enhancements which have increased user-friendliness. The latest version is 4.0.

The code for C++ design patterns and derivatives pricing is available here.

Back to home page.

Coming soon: More mathematical finance.