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Event Abstract:
We will discuss mathematics and the theory of applying a real option methodology based on dynamic programming to evaluate high-risk innovation projects. This new approach addresses a well-known fact for innovation projects that project stages can be serially correlated. Project that in a bad/good stage may have a high likelihood to stay bad/good in the next stage. The real option model that captures this intuition using dynamic programming and serial correlations will be discussed. We will also introduce partial derivatives like the Greeks that we called "control maps". These control maps will help the firm’s management to assess the financial impact of resource reallocations to project success factors. The proposed framework lets management synchronize its management decisions with financial decisions.
About the Speakers:
Dr. Andrew Kumiega has applied his Ph.D. in Industrial Engineering to research positions in both the manufacturing and the financial industry over the last 30 years. He has held multiple director and partner-level positions in financial services firms. At most of these firms, Dr. Kumiega was responsible for IT Governance/Risk including model governance and overall IT systems reliability management. Dr. Kumiega pioneered the application of software quality engineering and risk management to reduce risk and increase system availability for financial platforms. He applied this unique approach to investment management, market making, fund administration, and compliance. His relentless approach of continuous improvement resulted in moving many systems from 99.9% availability to 99.999% availability. Dr. Kumiega is a facility member at the Illinois Institute of Technology. His current industry research interests include: Governance utilizing Blockchain, multi-factor stock selection models utilizing autoML, quality, IT risk management , and project management for the fintech industry.
Dr. Greg Sterijevski is the founder of CommodityVol.com, the web’s preeminent source of implied volatility and market statistics centered on commodity markets. He is also the co-founder of The Asset Risk Company, the creator of the world’s first commercial commodity factor model. Greg holds a PhD in Economics from the University of Illinois at Chicago. He started his career at the SAS Institute, building statistical techniques and codes for the flagship SAS System. His career took him back to Chicago and its financial markets. There, he helped create and release the first Monte Carlo Margin Model for equity options. Greg has since held positions in market making options and futures in commodity markets, long short equity trading among other endeavors. His roles have included; quant, risk manager, partner and trader. The constant has been a model and datacentric approach to risk and trading.
