Mohammad Khodadadi was born in Birjand, Iran. He obtained a high school diploma in mathematics from National Organization for Development of Exceptional Talents (NODET) in Iran and then joined Industrial Engineering program at Sharif University of Technology in Tehran, Iran in 2001. After graduation, he began to work in industry for 4 years and gained hands on experiences on privatization of state-owned enterprises.
Equipped with industrial experience, Mohammad returned to academia in 2009 and pursued a master’s degree in Financial Engineering at the School of Economic Sciences of Tehran (later merged with Kharazmi University). The main focus of his research and study was to implement algorithmic trading to find an appropriate policy for stock trading. He utilized simulation-based dynamic programming (also known as reinforcement learning) to define a set of instructions for placing a trade on the stocks based on timing and price.
Upon finishing his master’s degree, Mohammad moved to the Netherlands and started an MPhil degree in Finance at Erasmus University Rotterdam. He investigated the sensitivity to the nominal-real covariance of inflation risk premiums and betas of two sectors of the economy in terms of durable versus nondurables goods. He received his MPhil degree in 2017 and then joined Vienna Graduate School of Finance as a Ph.D. student in September 2017.