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Ashish Kumar


Quantitative Analyst


ASHISH KUMAR|+36 703545096

Type of Residence: EU Blue Card Holder

•    Experienced academician and front office Credit Quant at Citi. Skilled in quantitative modeling, XVA, R, Python, C++, SQL, MS tools and Machine learning algorithms. Strong analytical and business development professional with a PhD in Mathematics

• Ph.D. Candidate in Applied Mathematics and Machine Learning aspirant with more than 5 years of experience developing mathematical models in Quantitative Finance

•    Developed a new approach to assessing wrong-way risk and the effect on CVA in counterparty credit risk. The results show that the assumption of constant correlation underestimates CVA

•    Author of 4 scientific research articles and currently developing a model for deep calibration of rough stochastic correlation


Citi, Hungary                                                                                                                                                                  October 2020 – Present

AVP, Credit Quant

·    Develop analytics libraries used for pricing and risk management

·    Create, implement, and support quantitative models for the trading business leveraging a wide variety of mathematical and computer science methods and tools including hardware acceleration, advanced calculus, C++ including STL, C, .NET, Java, object-oriented software design, Python, kdb, Structured Query Language (SQL), mathematical finance/ programming and statistics and probability

·    Develop pricing models using numerical techniques for valuation including Monte Carlo Methods and partial differential equation solvers

·    Collaborate closely with Traders, Structures, and technology professionals

Morgan Stanley, Hungary                                                                                                                   November 2019 – September 2020

Risk Associate

·    Performed timely quantitative analysis and tests for review of the models, identified limitations and found solutions for proper model control

·    Contributed to the improvement of the IMM Risk Assessment Framework

·    Conducted  review of the quantitative models for the regulatory exercises for various regulators

·    Coordinated with Risk Analytics team to test the implementation of counterparty credit risk models

·    Worked on different asset classes within IMM framework: credit, credit derivatives, equity, Interest rate, mortgage-backed securities, and FX

·    Developed automatized Python tools for the IMM team which reduced the time for generating reports

·    Performed a high-level review of Counterparty Credit Risk (CCR), Internal Model Method (IMM) models and produced written model reviews reports submitted to different regulators

·    Actively collaborated with model development stakeholders and CVA front office businesses, validated model changes with model developers on various aspects of Credit Capital exposure, risk management, valuation, internal risk management, and capital teams, proactively advise on risk and capital-related projects and issues, facilitate better risk and capital decisions


Szechenyi Istvan University, Gyor, Hungary                                                                                           September 2018 – August 2019

Research Fellow

·    EFOP project on modeling the general and geographical health risk factors for health insurance premiums and classifying disease-prone areas in Hungary using different machine learning techniques

·    EFOP project on the intensification of the activity of the Hungarian industrial innovation mathematical service network

E¨otv¨os Lorand University, Budapest, Hungary                                                                                                       September 2015 -Present

Ph.D. Researcher

·    Carried out advanced and quantitative research, modeled the dependence between assets, credit derivatives and interest rate products by using stochastic correlation approach

·    Recently demonstrated that the correlation is rough for high-frequency trading data. This is a standalone result till date which shows that the correlation is highly unstable for high-frequency data

·    Developed a model to assess wrong way risk with stochastic correlation approach and established that models using constant correlation under-estimate wrong-way risk.

·    Results published and submitted to 4 scholarly papers and reported in 3 international conferences and 2 seminar lectures


Ph.D. Candidate in Applied Mathematics                                                                                                     Expected 2020 E¨otv¨os Lorand University, Budapest, Hungary

Supervisor:  Prof.  L´aszl´o M´arkus

Received: Stipendium Hungaricum Scholarship

MSc. Mathematics with Computer Science                                                                                                                            2014
Jamia Millia Islamia, New Delhi, India

BSc[H]. Mathematics                                                                                                                                                                       2011
Jamia Millia Islamia, New Delhi, India


•    Expertise in theoretical and market practiced mathematical models for different asset classes.

•    More than 5 years of experience in mathematical modeling of financial products

•    Capable of conducting advanced quantitative research with a team as well as independently

•    Proficient in statistical language R, hands-on experience in Python, SQL, C, C++, Java, Latex, and MS Office tools. Ready to learn any programming language

•    Able to communicate and write effectively in English at all levels; speaker in several conferences, seminars and author of 4 scientific research articles

•    Ability to perform in a high-pressure environment, multi-task and prioritize and exceptional organizational and time management skills; ability to learn quickly and adapt quickly to changes


E¨otv¨os Lorand University, Budapest, Hungary                                                                                          September 2018- January 2020

University Lecturer

·    Lecturer of Probability Theory and Statistics course for bachelor and master students


•    Nominated as Young Statistician from Hungary                                                                                                                                                                                             2019

•    EFOP research project on health insurance premium                                September 2018 – August 2019

•    Stipendium Hungaricum Scholarship, Government of Hungary 2015 -2018

•    Excellence Merit Scholarship for academic achievements in BSc and MSc 2011 -2012

  • Updated 2 Monaten ago

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