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Our Derivatives Research group can help clients make existing strategies more efficient or new strategies possible. This information is available via e-mail, alerts or our Institutional Portal. We are fully committed to servicing each client's specific requests, and have a dedicated team to tailor our solutions to your individual needs.
Beans quantitative research team develops models for the pricing and hedging of cross-asset derivatives and Hybrids. Model development consists of defining the mathematical framework within which structures requested by the business can be evaluated. This is then implemented in software and made available to the business. The complete library of models developed by the team is used for all pricing, trading, hedging and risk management applications throughout the derivative community.

The quantitative research team also undertakes long-term research projects. These projects are typically either more advanced model frameworks for existing structures or models for more sophisticated structures. We also provide quantitative support to the global derivatives community.
Quantitative research team participates in the structuring, pricing and risk management of all types of Derivative and Hybrids for an array of global finance community. We work closely with sales, trading and technology to help develop innovative structures and enable risk management
   
White Papers
 
Volatility Smile Capture in FX Markets


Options with different strikes and maturities are usually priced with different implied volatilties, this is commonly referred to as the smile effect. In this we would review various commonly used approaches for capturing smile effect in ethe FX matkets. The techniques reviews include Stochastic volatility models such as Heston Model, Local volatility models and pratical approached used by traders and brokers such as Vanna-Volaga approach.

 

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Practical Derivative Pricing - Vanna-Volga Approach


Vanna-Volga approach is method used by traders to determine the cost of risk managing the volatility risk of exotic options with vanilla options. This cost is added to the theoretical value in the Black-Scholes model and is called the overhedge. Sensitivity parameters vanna and volga play a very important role in this methodology and the cost of such vanna and volga exposure can be used to obtain the prices of the option closer to the market than their theoretical Black-Scholes value.

 

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Derivatives Pricing & Structuring Platform - Technology Perspective


Beans & Intellect has developed a technology frameowork providing complete set of tools for rapid structuring, pricing and processing complex financial products. The platform would help automating the management of complex structured product and addressing the day-to-day needs of both sales and trading by supporting in structuring, simulating and selling structured derivatives.

 

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Pricing Hybrid Derivative Products: A Copula Approach


Copulas are important as it enables us to construct joint distribution functions from marginal functions in a way that enables us to captures the complete dependency structure between the underlying variables. In simple terms, marginal distributions, which describes the way in which a random variable moves independently - “on its own” and the copula function tells us how they join - “come together” to determine the multivariate distribution. In this we analyse the application of copulas in pricing and valuation of Hybrid Derivative products.

 

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Treasury System Implementation - Technology Issues


The selection and implementation of a treasury management system ("TMS") can be a difficult and complicated undertaking involving, in many cases, significant costs. As a result, expectations are justifiably high and as such a system must deliver significant benefits to maximise the return on the investment and become an acceptable working solution. This deals with key steps/process involved in evaluating and implementing treasury management systems in financial institutions.
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USD
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INR
0.0215123
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1
1.958235
0.02262745
0.1667015
2.325715
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EUR
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0.9009
136.083
1.572365
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1.61649
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77.139
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12.8592
1.7942
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3
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86.555
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13.0374
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0.618605
0.55734
84.198
0.9728
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6
0.662095
0.596402
90.101
1.04115
7.67023
1.07015
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