Stage - 3a - Equity Analytics Dashboard for Market - Paris, France - Murex

Murex
Murex
Entreprise vérifiée
Paris, France

il y a 3 semaines

Sophie Dupont

Posté par:

Sophie Dupont

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Description

Job ID:
Location: PARIS (FRA)Murex is a global fintech leader in trading, risk management and processing solutions for capital markets.


Operating from our 19 offices, 2500 Murexians from over 60 different nationalities ensure the development, implementation and support of our platform which is used by banks, asset managers, corporations and utilities, across the world.


Join Murex and work on the challenges of an industry at the forefront of innovation and thrive in a people-centric environment.

You'll be part of one global team where you can learn fast and stay true to yourself.


The team:


You will become a part of the Front Office (FO) Trading Product Development Domain (PDD) which is at heart of MX.3 software evolution, where you will integrate the Financial Engineering team.

Our multi-cultural team designs, validates and delivers Murex Advanced Analytics (MACS) which is a combination of rich catalogue of derivative products covering all asset classes, a large set of models for evaluation and risk management of derivatives.

We work closely with the quant development and integration teams to enhance our products and models.

We provide our quantitative expertise and collaborate with FO Trading PDD teams like Equity Derivatives, Non-Linear Rates, Foreign Exchange Derivatives, Commodity Derivatives, etc.

to build trading solutions. Similarly, we assist Client Services and regional offices across the globe to provide cutting edge solutions to our clients.


The mission:


Local Volatility is the market standard model for pricing and risk managing exotic equity derivatives; it was specifically designed to reproduce observable market spot vanilla option smiles but fails (compared to Heston-like models) in generating realistic dynamic features, such as forward smiles or spot/volatility deformations.

It remains however the standard for several payoffs, such as the equity autocallable, the most liquid exotic structure on the equity market.


In the context of model validation, we would like to leverage our time series of financial market data to assess and exhibit the properties of the model before plugging it to a payoff and conducting validation tests.

The goal being to produce a validation document of the production system's autocall product with our local volatility pricer.

Concretely, you will interact through python with REST APIs to:

  • Build a market data dashboard to assess the quality of the equity financial information (spots, volatilities, curves, etc)
  • Build a second dashboard using the very same market data to display local volatility model properties (calibration fit, implied dynamics, calibration selection repricing, etc). we'll insist on genericity to build a framework that will show how different models perform in the same tests.
  • Use a pricing ecosystem to validate local volatility PDE pricing of monounderlying autocallables and to produce a complete validation document summarizing the tests results, as well as a list of gaps and limitations.


This internship will mix market data, model, and payoff analytics, which is at the heart of our daily activities as financial engineers.

It also requires programming skills and presentation fluency, as you'll be sharing your code and results with the entire team.

You'll interact with different experts to gather information and inputs.

It is an opportunity to learn by interacting with people in the team and outside, practicing the model, the most popular equity derivative structured product, and the brand-new internal model validation ecosystem.


Who you are?

  • You are in the last year of a master's degree looking for a 6months internship
  • You are passionate about technology and financial mathematics
  • Strong academic background in a quantitative field (Computer Science, Engineering, Physics, Mathematics)
  • Understanding of stochastic processes and financial mathematics
  • You practice python
  • You can efficiently communicate in multicultural environment: English is a must
  • You have strong analytical and problemsolving skills

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