Olga Obizhaeva
Central University
Assistant Professor of Finance
Stockholm School of Economics
Assistant Professor of Finance (on leave)
Swedish House of Finance
Resident Researcher
​​
CV
​​
Email:
Olga.Obizhaeva (at) hhs.se
​
Address:
Central University
Gasheka street, 7, Moscow
Russia
About Me
I am working in the areas of institutional asset management, web analytics and search engines, big data, fintech, and market microstructure.
Stock Buyback Motivations and Consequences: A Literature Review
​
with Alvin Chen
CFA Institute Research Foundation Books, February 2022, ISBN 978-1-952927-26-3
​
​
Publications
Working Papers
Does Search Engine Visibility Help ETFs Attract Flows?
​
I use a unique web analytics dataset to study online activities of exchange-traded funds (ETFs) and propose a novel methodology to characterize these activities. Even after controlling for conventional factors as well as variations in product and consumer characteristics, I find that ETF issuers compete with each other in online space and gain an advantage in attracting flows through search engine marketing and improved online visibility. Better online visibility of financial products, as proxied by their average rank on search engine result pages, helps to attract more capital flows, especially for listing on pages with high pay-per-click ad auctions.
Fundraising in the Hedge Fund Industry
(reject and resubmit at Management Science)
This paper studies fundraising process in the hedge fund industry. Using the SEC form D filings of hedge funds, I document that funds that are sold to investors by intermediary brokers underperform funds that are offered to investors directly by 2% (1.6%) per year on a risk-adjusted basis before (after) fees. Funds that are sold to investors directly on average have larger investorsment size, larger minimum investment size and charge higher performance fees comparing to funds offered to investors by brokers. These results are consistent with separating "cut-off" equilibrium in a stylized model of fundraising where hedge funds choose fees and capital raising channels and investors with heterogenous due diligence costs allocate capital across hedge funds.
​
Order Shredding, Invariance, and Stock Returns
with Pete Kyle and Anna Obizhaeva
​
We introduce a new structural model for stock returns generating process. The model assumes that stock prices change in response to buy and sell bets that arrive to the market place as predicted by market microstructure invariance. These bets are shredded by traders into sequences of transactions according to some bet-shredding algorithms. Arbitrageurs take advantage of any noticeable returns predictability, and market makers clear the market. This structural model is calibrated to match empirical time-series and cross-sectional patterns of higher moments of returns. We find that historical idiosyncratic kurtoses of inactively traded stocks are usually higher than that of actively traded stocks, whereas idiosyncratic skewness is positive and stable across stocks, but decrease over time. We calibrate implied hard-to-observe parameters of bet-shredding algorithms using the method of simulated moments and analyse its properties, finding that shredding has increased over
time.
Size of Share Repurchases and Market Microstructure
​
This paper studies cross-sectional and time series variation in the size of repurchase programs. I find that this variation is explained by the variables motivated by the theory of market microstructure invariance. The size of (authorized and realized) share repurchase program as a fraction of trading volume is approximately proportional to trading activity of stock in power of -1/3. The results suggest that when determining the size of repurchase programs, managers may target percentage impact costs of these programs or target inventory levels sufficient to allocate their future bets about their companies.
​