Sahil Raman Anand
Manager, Market Risk
London
Summary
Accomplished Quantitative Analyst and Financial Engineer with over 11 years of experience in the quantitative development and validation of VaR models, CCR/CVA, IPV, and derivative pricing models. Expertise in Python for prototyping, numerical methods, and data analysis, with a strong emphasis on enhancing and automating model implementation processes. Solid foundation in Stochastic Calculus, Probability Theory, and Linear Algebra. Proven success in collaborating with cross-functional stakeholders across Trading, Quant, Risk, and Finance to deliver comprehensive documentation and data-driven insights that support effective model governance.
Overview
10
10
years of professional experience
1
1
Language
Work History
Manager, Quantitative Advisory
Ernst & Young
08.2022 - Current
- Executed model development and validation projects for UK and US banks
- Key Project & Achievements:
- Developed a stochastic basis model to backfill Risk-Free-Rates in SVaR model for a UK based bank
- Reviewed the IMM-aligned Monte Carlo simulation engine of the PRISM model, assessing IR, EQ & FX dynamics, pathwise correlations, and volatility calibrations
- Validated IMM backtesting framework, reviewing Multiplication Factor calibration and exception logic against realized exposures to ensure robust monitoring
- Built ladder/grid-based methodology to compute VaR PnL (RTPL) for yield-curve shifts for a UK based bank
- Developed REM (Risk-Not in VaR) methodology for relative shifts in interest rates due to regime change.
- Validated HJM market models that incorporate intra-curve correlation, parametric skew, and stochastic variance for IR range Accruals, CMS spreads etc. for a Tier-1 American bank
- Supported regulatory deliverables under FRTB IMA for a Tier-1 European Bank, focussing on RFET, PLAT and backtesting
- Conducted VaR model backtesting for a major UK bank, identifying key limitations and proposing enhancements to improve model accuracy and reliability.
- Ongoing internal initiative: automating model documentation from Python code repository using a Gen-AI assisted pipeline. This is first step towards making agent-based model validation.
Manager
Nomura
09.2020 - 03.2022
- Validated Valuation Control/xVA/pricing models for all Global positions held by Bank
- Key Project & Achievements:
- Validated valuation reserve model on hedging risks (FX smile) and parameter uncertainty (short correlation) for a complex PRDC structured portfolio.
- Validated Fair Value Adjustment model on IR delta and Xccy risks for Valuations Control.
- Reviewed EBA Prudent Valuation RTS and assessed AVA methodology for regulatory alignment
- Validated SABR IPV model for portfolio of European swaption.
- Validated EPE and PFE for interest derivative swap portfolio in CVA model (using Hull-White one factor simulations).
- Setup governance framework and standardized validation process for this new validation group.
Consultant
Mckinsey & Company
08.2018 - 08.2020
- Developed excellent client handling skills by understanding their needs, building rapport, and providing them with quality output.
- Key Project & Achievements:
- Validated yield curve term structuring using PCA methodology for a major Swiss bank which helped them produce reliable scenario forecasts.
- Validated risk factor models for FX, Equity and Credit asset classes which were used in Monte-Carlo VaR for a French Investment bank.
- Developed validation plan for VaR models which is used as a reference across different methodologies.
- Developed pricing for nth to default Credit Default Swap using Gaussian and T-copulas.
Senior Analyst
Credit Suisse
11.2015 - 08.2018
- Provided data driven forecasts on PnL, portfolio management and risk changes for equity derivative trading desk in changing market conditions
- Key Project & Achievements:
- Analyzed and reviewed risks (Greeks), focusing on understanding behavior of derivative products (AutoCallables, VarSwaps, EQ-FX Hybrid, Barrier options etc.) under various market conditions
- Built monte-carlo stochastic volatility models for Vanilla, Barrier, American & Digital options in python
- Analyzed daily risk movements and investigate big moves in VaR and stress testing results
- Forecasted knock outs of autocallables and barrier options so that traders can take pre-emptive actions to mitigate risks in gap up/down opening of the market
- Analyzed back-testing exceptions in VaR model to help reduce RWA
- Around 3Y of work experience in retail bank analytics and as an Operations Engineer
Education
CQF -
Certificate in Quantitative Finance
01.2021
CFA (L1 & L2) - undefined
Level 1 and Level 2 cleared
01.2016
PGDM (MBA) - undefined
Management Development Institute (MDI, Gurgaon)
01.2014
FRM Charter - undefined
GARP - Financial Risk Management (Levels I and II)
01.2014
B.E. - Mechanical
Delhi College of Engineering (DTU)
01.2011
Skills
Proficient in Python, C, R, SQL, SAS and VBA
Timeline
Manager, Quantitative Advisory
Ernst & Young
08.2022 - Current
Manager
Nomura
09.2020 - 03.2022
Consultant
Mckinsey & Company
08.2018 - 08.2020
Senior Analyst
Credit Suisse
11.2015 - 08.2018
CFA (L1 & L2) - undefined
Level 1 and Level 2 cleared
PGDM (MBA) - undefined
Management Development Institute (MDI, Gurgaon)
FRM Charter - undefined
GARP - Financial Risk Management (Levels I and II)
B.E. - Mechanical
Delhi College of Engineering (DTU)
CQF -
Certificate in Quantitative Finance