About

Mr. Erhan Sahin has work experience in various positions within the Financial Industry in New York Metropolitan Area in the USA, where he developed strong proficiency with quantitative analysis, financial modeling, financial engineering, market and credit risk management, research and trading. Besides that, he has work experience in market risk management department for four years, two years in trading risk department and the other two years in quantitative modeling (research) in banking (ALM) in ING Group.

He worked in ABN AMRO as a consultant in the trading risk modeling department and obtained exposure to ABN AMRO risk management processes such as risk management systems, model building approaches, trading risk measurements and analysis. Besides, he worked in Counterparty Credit Risk Analytics department in Credit Suisse and in CCAR program as a project manager in Barclays Capital in London.
In ING, he worked in the quantitative risk research department. Main Responsibilities were developing behavioral models such as Savings Models and Mortgage Prepayment Models by using Hull-White interest rate model to hedge savings and mortgage portfolio of ING Group with a value of EUR 500 billion. He also used statistical models such as logistic regression to model behavior models as well as econometric models to hedge the portfolios. He used JAVA (Netbeans and Eclipse) as a main programing language besides Excel-VBA while building models.

In addition, he worked on Trading Risk Models such as VaR-Covar, Monte Carlo, Historical Simulation and Expected Shortfall. In ABN AMRO, he worked on producing high and lower priority model re-validation DNB (Dutch Central Bank) reports. He re-validated trading risk models and closed model validation open action points for DNB reporting. He worked on SABR, SVI++ as well as Heston models. He prepared three documents for DNB. +In Credit Suisse, He worked in Credit Analytics Department Modeling Counterparty Credit Risk Exposure and Stress Testing. He worked on projects such as “Stressed Leverage Ratio” which he stressed the exposure component of the Leverage Ratio. The second project was “Stressed sensitivities to calculate Initial Margin” and the third project was “Scenario-EPE RWA Alternate Repo VaR Brownian Bridge Simulator Refactoring”, which he simulated asset returns for four asset classes (Equity, Interest Rate, FX and Credit) by using Monte Carlo Simulation. For the calculation of the Repo VaR, he used C# programming language during model development. The same methodology is used to value CVA and DVA.  
In Barclays Capital, he worked as a project manager in the Comprehensive Capital Assessment and Review (CCAR) program in Infrastructure and technology department. He worked with four program managers, two of them are located in London and the other two are located in New York. He managed twelve stakeholders; six system support teams, four asset class teams which are IR, Credit, Structured Notes and Securitized Products, a developer team and a testing team. He tested the system in four different environments; Dev Stack, SIT Stack, UAT Stack and Production. The products were valued and the risk is calculated by the risk engine by applying the US Federal Reserve scenarios. Two reports are prepared 14-Q and 14-A as an output.  

He possesses experience and exposure to ING, ABN AMRO, Credit Suisse and Barclays Capital Risk Management systems and models. He worked on the Vasicek model and its application to pricing plain vanilla caps and swaptions. Next,  he studied the arbitrage-free models of Ho-Lee and Hull-White and calibrated them to the implied-volatility term structure. He applied the Black-Derman-Toy model to pricing Bermudan and American swaptions using interest rate trees. He also applied Multi-factor LIBOR Market Models to the pricing of mortgage-backed securities. He priced accrual swaps and other path-dependent derivatives. He has also modeled caps and swaptions under the implied volatility smile. He is familiar with the pricing barrier interest rate derivatives, Monte Carlo simulation, and hedging of interest rate derivative portfolios.
He calculated IRC by simulating scenarios for how issuer credit ratings might change by taking corporate and sovereign rating migration probabilities and correlations between different issuers and loss-given-default (LGD) rates into account. He calculated potential losses due to rating migrations and defaults in the portfolios of the trading book over a one year time horizon at a 99.9% confidence level. He used one factor Gaussian Copula function to calculate IRC. He calculated IRC for all non-securitized trading positions which are subject to specific interest rate risk included in the internal model approach for market risk regulatory capital (CAD2).
He worked on the intensity and structural models, unwind CDS Trades. He derived Par CDS Spread Prices and Asset Swaps from Bond Prices. Besides that, he worked on deriving forward CDS spreads.
He has covered risky bonds and credit default swaps, through basket swaps, structured products and CDOs. In synthetic CDO, he worked on risk-neutral CDO valuation methodology, risk-neutral default probabilities, stochastic asset returns and defaults, single factor Gaussian models, portfolio loss distributions, the compensator method for generating defaults, Cholesky transformation, generating correlated default times, cash flow analysis, tranche delta distribution, and single-tranche synthetic CDOs.

For risk management purposes, he implemented and worked on three VaR models, variance-covariance, Monte Carlo simulation, historical simulation. Besides that, he priced and valued fixed income instruments by using various programs such as C/C++, C#, Python, R-Studio, Java and others.