Scientific Computing For tomorrows market

Our Competency

Our Competency

We have compiled a collection of numerical and computational methodologies that are part of our offerings. Most of these specializations are based on current research papers which describe numerical and statistical algorithms alongside their theoretical developments.

Programming

We program in C#, MatLab2009, MFC6, C++, Java and S-Plus. Special emphasis is given to programs used in financial software, with extensive understanding of the theory.

Genetic Algorithms

Simulation

- Monte Carlo Simulations

- Quasi-Monte Carlo Simulations

- Tree Simulations

- Historical Simulations

Numerical Methods in Partial Differential Equations

Neural Networks

- Feed Forward Networks

- Recurrent Networks

- Self Organized Maps

- Stochastic Machines

- Classification

- Neurodynamic Programming

Credit DerivativesTop

Time Series Analysis

Default-time Modeling

Copula

Geometric Brownian Motion

Levy Process

Martingale Theory

Hazard Rate Modeling

Partial Differential Equations

Interest Rate ModelingTop

FAVAR Model

SABR Model

Stochastic Calculus

Affine Methods

Martingale Theory

Curve Fitting

Levy Process

Monte Carlo Methods

Geometric Brownian Motion

Quantitative ModelingTop

Main software used for quantitative analysis is Mathematica & MatLab which is the most powerful and versatile tool in the market for this type of work. We are specialized in a number of areas pertaining to finance. Partial differential equation

Stochastic differential equations

Numerical methods in partial differential equations

Pricing models

- Binomial

- Black-Derman-Toy

- Black-Karasinski

- Black-Scholes

- Cox-Ingersoll-Ross

- Cox-Ross-Rubinstein

- Duffie-Singleton

- Garman-Kohlhagen

- Heath-Jarrow-Morton

- Hull-White

- Trinomial model

Volatility ModelTop

ARCH/GARCH & it's variations

Implied Volatility

Volatility Surface Modeling

Statistical AnalysisTop

Main software used is S-Plus and MatLab, which is the most widely used statistical package for research and analysis. We provide an assortment of statistical tools used in Finance.

Bootstrap

- Block and moving window bootstrap

- Bootstrap methods for stationary time series models

Subsampling

- Nonparametric curve estimation

- Kernel Regression

- Kernel Smoothing

Time Series Models

- Time Series Regression Modeling

- Univariate GARCH Modeling

- Long Memory Time Series Modeling

- Rolling Analysis of Time Series

- Systems of Regression Equations

- Vector Autoregressive Models for Multivariate Time Series

- Multivariate GARCH Modeling

- State Space Models

- Factor models for Asset Returns

- Term Structure of Interest Rates

- Robust Change Detection

Portfolio ManagementTop

Dynamic Programming

Genetic Algorithm

Bayesian Networks

Kernel Methods (SVM)

Co-integration

Trend Analysis

Numerical Optimization

Monte Carlo Methods

Risk ManagementTop

Time Series Analysis

Extreme Value Theory

Copula

Heavy Tailed Distribution

Macro-Economic AnalysisTop

FAVAR

Linear Regression

Principal Component Analysis

Clustering

Gibbs Sampling

Dynamic Programming

Trading ToolsTop

Continuous Time Optimization

Monte Carlo

Time Series Analysis

Trend Analysis

Heavy Tailed Distribution

Stochastic Calculus

Combination of these activities result in a client specified financial product. We provide a varied range of analytical activities that support the development and evaluation of tools in quantitative finance.