Tehran Institute for Advanced Studies (TEIAS)

/ Big Data Economics I

Summer School

Big Data Economics I

September 5-8, 2016


Khatam University
Address: Mollasadra, North Shiraz, Hakim Azam, No 30. See location on Google map



Scientific Chair

Ali Habibnia


Organization Chair

Mohammad Morovati
Ali Habibnia
Maryam Hejazinia



World’s data is doubling every couple of years. A new challenge for the economy and industry is, therefore, how to manage and benefit from this colossal data. Big Data has become ubiquitous in modern society and has also opened up new possibilities for economic research. It challenges state-of-the-art data acquisition, computation and analysis methods. This summer school event aims to address some of these issues through a series of talks from leading academic experts. The focus will be the broad theme of theoretical, computational and statistical underpinnings of Big Data analysis, emphasizing high-dimensional econometric models and novel machine learning techniques to manipulate and analyze the Big Data and their Implications in banking and finance or on research focusing on interesting economic questions that arise from considering the rapid changes in data availability, computational technology and software. With the rise of big data and the very real opportunities that machine learning now brings, there is no better time to find out how novel techniques can be used for economic research.


  • Faculty members and graduate (Masters and Ph.D.) students
  • Banking and financial industry experts and policy makers
  • Researchers (from Econ, Finance, Math, Stat, CS and ML backgrounds)



Ali Habibnia

Videos: YouTube, Takhtesefid



First Session: A Visit of the Economics of the Future I, Slides, Videos: YouTube, Takhtesefid
Second Session: A Visit of the Economics of the Future II, Slides, Videos: YouTube, Takhtesefid

J. Doyne Farmer is Director of the Complexity Economics program at the Institute for New Economic Thinking at the Oxford Martin School, Professor in the Mathematical Institute at the University of Oxford, and an External Professor at the Santa Fe Institute.His current research is in economics, including agent-based modeling, financial instability and technological progress.He was a founder of Prediction Company, a quantitative automated trading firm that was sold to the United Bank of Switzerland in 2006.

This was a remarkable event, with excellent students and extraordinary hospitality. I met many interesting people, and it was fascinating to get a glimpse of Iran. Not to mention the nice carpet I bought:).



First Session: Time Series Predictability and Stock Returns, Slides, Videos: YouTube, Takhtesefid
Second Session: Cross-Sectional Predictability and Stock Returns, Slides, Videos: YouTube, Takhtesefid

Svetlana Bryzgalova is an Assistant Professor of Finance at the Stanford Graduate School of Business. She joined the GSB in September 2015 after receiving her PhD and MRes degrees in Economics from London School of Economics. Prior to attending LSE, Professor Bryzgalova graduated summa cum laude with a MSc in Financial Economics and BA in Economics (Mathematics) from the Higher School of Economics (Russia).

This was a fantastic experience for me – getting to know so many wonderful students and sharing our views on research. I am very grateful for the opportunity to teach at the Summer School, and I am certain that this event will continue to grow, becoming a well-established platform to inspire new projects and foster international cooperation.


First Session: Big Data, Model Selection, Aggregation-Indexing, Slides, Videos: YouTube, Takhtesefid
Second Session: Moment and Selection Approaches: A Comparative Simulation Study, Slides, Videos: YouTube, Takhtesefid

Esfandiar (Essie) Maasoumi is the Arts and Sciences Distinguished Professor of Economics at Emory University, Atlanta, GA. He is the author and coauthor of more than 100 articles, reviews, and books, including special issues of the Journal of Econometrics and Econometric Reviews . He has written theoretical and empirical papers in both economics and econometrics and consults on law and economics issues. Maasoumi received BSc (1972), MSc (1973), and PhD (1977) degrees from the London School of Economics, United Kingdom.

As a speaker at this summer school, I found the experience to be enriching and far beyond my already high expectations. I was impressed by the evident thoughtfulness of the organizers and sponsors, and their commitment to having a first rate experience for the audience and the speakers. I was pleasantly surprised that the organizers were able to attract such caliber of speakers, stay focused on the extremely high impact theme of “Big data”, and to manage to bring all their speakers to the country, in time. The organizers knowledge of the field and frontier research is always key, and was evident throughout the process, including preliminary effort to attract participants to this event. All the speakers were unanimous in their reactions concerning the graciousness and hospitality of the organizers and sponsors, at all levels. For me, this effort competed with the best I have seen from some seasoned organizers from China who are engaged in a massive international effort to bring the best of frontier research and training to their country and institutions. I have been a participant and contributor to those Chinese efforts, and really liked what I have seen of this effort by Pasargad and Khatam. For this reason and evident success of this first effort, I expect to support similar future efforts and conferences. I congratulate all the organizers and sponsors of this extremely successful and meaningful scholarly gathering. I took very positive memories and impressions from this event and it is already having an impact on social and other media.


First Session: Casual Inference in High-Dimensional Approximately Sparse Structural Linear Models, Slides, Videos: YouTube, Takhtesefid
Second Session: Double machine learning for causal and treatment effects, Slides, Videos: YouTube, Takhtesefid

Victor Chernozhukov works in econometrics and mathematical statistics, with much of recent work focusing on the quantification of uncertainty in very high dimensional models. He is a fellow of The Econometric Society and a recipient of The Alfred P. Sloan Research Fellowship and The Arnold Zellner Award. He was elected to the American Academy of Arts and Sciences in April 2016.


High Frequency Market Making in the Foreign Market, Slides, Videos, Part1: YouTube, Takhtesefid
Videos, Part2: YouTube, Takhtesefid

Shahram Nikbakhtian, joined the Bank of America Merrill Lynch quant research team in 2015.He has been working extensively on various aspect of algorithmic trading, derivative modelling, pricing , hedging , risk management, market making. One of particular themes of his recent work is High frequency Market making of foreign currency market.


Text Mining and Computational Text Analytics, Slides, Videos, Part1: YouTube, Takhtesefid
Videos, Part2: YouTube, Takhtesefid

Kenneth Benoit is currently Professor of Quantitative Social Research Methods, and Head of the Department of Methodology at the London School of Economics and Political Science. He received his Ph.D. (1998) from Harvard University, Department of Government. His current research focuses on automated, quantitative methods for processing large amounts of textual data, mainly political texts and social media.


First Session: Big Data Strategy, Slides, Videos: YouTube, Takhtesefid
Second Session: Data platforms-platform revolution and data platform, Slides, Videos: YouTube, Takhtesefid

Aija Leiponen received her Ph.D. in Economics from the Helsinki School of Economics. Prior to joining Cornell University, she carried out research at Haas School of Business, University of California at Berkeley, the International Institute of Applied Systems Analysis (IIASA) in Austria, and the Research Institute of the Finnish Economy (ETLA) in Finland. Between 2009-2011 she was on the faculty of Imperial College Business School (London UK) and continues to hold a part-time affiliation there.


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