QUANTITATIVE FINANCE TECHNICAL MENTORSHIP PROGRAM

LEARN HOW YOU COULD PAY ZERO UPFRONT TUITION FEES

QUANTITATIVE ANALYSTS: THE ROCKET SCIENTISTS OF WALLSTREET

In the trading world, quantitative analysts are especially in demand. The 21st century has seen an explosion in the popularity of electronic trading based on numerical algorithms.

A quantitative analyst is a professional who uses quantitative methods to help companies make business and financial decisions. Investment banks, asset managers, hedge funds, private equity firms, and insurance companies all employ quantitative analysts, or “quants,” to help them identify profitable investment opportunities and manage risk.

TOP RATED QUANTITATIVE FINANCE PROGRAM IN NORTH AMERICA

DID YOU KNOW LANTERN INSTITUTE IS THE ONLY PROGRAM IN NORTH AMERICA THAT OFFERS BOTH A QUANTITATIVE FINANCE TRAINING PROGRAM AND TECHNICAL MENTORSHIP PROGRAM

WORK WITH SENIOR INDUSTRY PROFESSIONALS​

WE CANNOT EMPHASIZE THIS ENOUGH. THE DATA INDUSTRY IS CONSTANTLY CHANGING AND ADAPTING, SO SHOULDN'T YOUR TRAINING PROGRAM BE THE SAME? HAVING INDUSTRY PROFESSIONALS NOT ONLY GIVES US A DIRECT INSIDER VIEW TO THE INDUSTRY ITSELF BUT IT ALSO ALLOWS US TO MAKE SURE OUR TRAINING STAYS CONSISTENT TO THE NEEDS AND DEMANDS OF YOUR INDUSTRY.​

ITS NOT ALWAYS WHAT YOU KNOW BUT WHO YOU KNOW​

WORKING WITH INDUSTRY PROFESSIONALS HAS OPENED NETWORKS FOR OUR STUDENTS TO OTHER PROFESSIONALS WITHIN THEIR DOMAINS. AT LANTERN WE PUSH NETWORKING OPPORTUNITIES, LEVERAGING INTERNAL OPPORTUNITIES AND MORE THROUGH OUR TEAM OF PROFESSIONALS AND COMMUNITY PARTNERS.

CURRENT PROJECTS

DR. Dmitry Vyushin

DIRECTOR OF FIXED INCOME CASH ANALYTICS
RBC

Dr. Dmitry Vyushin is a Director in Non-Trading Book Risk Modelling Team of Market Risk Department at RBC. He is currently developing a new Enterprise VaR system that covers Trading, Treasury, Insurance, and Pension portfolios. After graduating from the University of Toronto with a PhD in Physics in 2009, he joined the Operational Risk Department of Scotiabank. In 2012, he was promoted to the position of Director, Enterprise Risk Stress Testing at Scotiabank, where he led the development of statistical Non-Retail and Retail Credit Risk Stress Testing models. In the beginning of 2015 Dmitry assumed the role of Director, Market & Counterparty Credit Risk Modelling at the Bank of Montreal, where he was involved in the redevelopment of an existing Trading Book IRC model into a Monte-Carlo based model for Credit, Counterparty Credit, and CVA economic capital calculation.

DR. markiyan sloboda

vp capital markets
BMO

Dr. Markiyan Sloboda finished his PhD in Computer Science from University of Guelph. His research was related to applying artificial intelligence to model calibration. Then he joined TD Bank as manager of Advanced Analytics in the Anti-Money Laundering department. He and his team of four PhD scientists were responsible for building predictive models to identify suspicious transactions for 2.5 years. After that Dr. Sloboda joined Bank of Montreal (BMO) as a manager in Model Vetting, focusing on models related to pricing derivatives. He was responsible for validating equity, interest rate and exotic options for more than three years. Currently, Dr. Sloboda is working as a Vice President in BMO Capital Markets, responsible for developing equity vanilla pricing models and supporting the volatility trading desk in their everyday activities. During his tenure at TD and BMO, Dr. Sloboda was also teaching for 3 years at the Ted Rodgers Business School, Ryerson University.

APPLICATION OF MACHINE LEARNING TO DERIVATIVE PRICING

PROJECT DETAILS

This project will be focusing on derivative pricing using classical financial mathematics methods as well as on novel approaches of applying machine learning (ML) techniques to valuation. Students will start from understanding market data, risk factors and derivative valuation. A simple Monte Carlo (MC) simulation engine will be built by the students at this stage. Then two popular ML techniques, Gaussian Processes and Deep Learning, will be applied to derivative pricing. Finally, a thorough analysis and comparison between ML techniques and classical methods will be conducted. The MC simulation engine built in the beginning of the project will be used to generate training data. We will focus on pricing basket options and, time permitting, on some other type of derivatives. Results of different ML approaches will be benchmarked against the market, classical financial mathematics approaches, and similar published studies. Python will be used as a main programming language. After completing the project the students will have a good understanding of financial data, MC simulations, derivatives, risk sensitivities, valuation, as well as ML and its application to derivatives pricing.

POTENTIAL EMPLOYMENT OPPORTUNITIES

PROJECT DURATION & COST

COMPLETE A TECHNICAL ASSESSMENT

AS A PART OF OUR APPLICATION PROCESS FOR THE TECHNICAL MENTORSHIP PROGRAM, ALL APPLICANTS MUST COMPLETE THE TECHNICAL ASSESSMENT.

PROVEN RECIPE FOR SUCCESS

Through market research and working closely with our community partners, we’ve created a proven program that is results driven on helping our students become industry professionals. We focus on technical skills and soft skills training to help our students become hireable professionals.

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