Welcome to my page. My full name is Efstathios, but I usually go by my nickname, Stathi. I am an associate professor of finance at the Alberta School of Business, which I joined after graduating from the Wharton School in 2012. My research focuses on information asymmetry, market inefficiencies, and financial time-series econometrics.
Maximum Likelihood Estimation of the Equity Premium, with J. Wachter, 2017, Journal of Financial Economics
Information Tradeoffs in Dynamic Financial Markets, 2016, Journal of Financial Economics
Power Algorithms for Inverting Laplace Transforms, with W. Whitt, 2007, INFORMS Journal on Computing
Working papers and work in progress
Rational-expectations Whiplash, with Masahiro Watanabe (Alberta)
Clear and liquid: The interaction of firm disclosure and trader competition, with Sanjay Banerjee (Alberta)
Trading in Large Markets
A Rumour-based Approach to Price Noise
Associative Expectations in Financial Markets
- Information in financial markets
- Financial time-series econometrics
- Artificial intelligence in financial markets
- Dynamic incentives
- Investments (undergraduate)
- Financial economics, continuous-time finance (PhD)
Normally restricted to third- and fourth-year Business students. Prerequisites: FIN 301 or consent of Department. Additional prerequisites may be required.
Provides advanced mathematical coverage of important topics in finance. Potential topics include continuous-time models of asset pricing and portfolio choice, pricing and hedging of derivative securities, and the applications of contingent claim pricing models to the valuation of real assets and corporate liabilities. Prerequisite: Open to doctoral students in the Faculty of Business, the Department of Economics and the Program of Mathematical Finance. For all other students, written permission of instructor required. Approval of the Business PhD Program Director is also required for non-PhD students.
Research - Associative Expectations in Financial Markets
Standard models of rational learning in financial markets prescribe that economic agents learn according to Bayes's rule. This type of learning requires that agents learn consciously by fully incorporating all available information in observed price changes. It also implies that there is no room for preferences to directly affect how humans learn. Drawing on ideas from psychology and artificial intelligence, I propose a model of non-conscious learning, based on perceived changes in utility.
Research - Clear and liquid: The interaction of firm disclosure and trader competition, with Sanjay Banerjee
In an economy where traders absorb information partially, we study the effect of disclosure accuracy and disclosure clarity on financial markets. Accuracy measures how precisely a disclosure identifies the firm's fundamentals, whereas clarity measures how well traders understand the disclosure. Increasing clarity promotes competition among informed traders more so than it increases the information asymmetry between informed traders and market makers. Increasing accuracy has the opposite effect. Trading volume increases monotonically in clarity, while liquidity has a U-shaped relationship with clarity if competition among traders is intense. Volume and liquidity both decrease in accuracy due to adverse selection among different market participants. Moreover, traders' attention to disclosure is hump-shaped in clarity, but increasing in accuracy. Trading profits mimic the patterns of attention, but only under intense competition. Overall, our results suggest that the current trend of increasing complexity in firm disclosures is detrimental to liquidity and volume.More Information
Research - Online appendix for "Information Trade-offs in Dynamic Financial Markets"
The value of information for a fully-dynamic economy in continuous time.More Information
Research - Online appendix for "Maximum Likelihood Estimation of the Equity Premium", with J. Wachter
A detailed derivation of the estimator for univariate, multivariate, and heteroskedastic settings.More Information
Research - Rational-expectations whiplash, with M. Watanabe
We present a financial market with investors who have nested private information. Small perturbations of price informativeness, coming from distortions of dividend expectations, can trigger an oscillating shock throughout the economy that destabilizes the feedback loop between prices and expectations. Moreover, decreasing the volatility of liquidity trading makes the equilibrium less stable. We investigate what the distribution of informed investors implies for equilibrium stability and for the risk premium of the asset. We find that different investor distributions have different implications, depending on whether adverse-selection or risk-sharing effects dominate in the economy.More Information
Research - Risk seekers: trade, noise, and the rationalizing effect of market impact on convex preferences
Long-held intuition dictates that information-based trade is impossible without exogenous noise. Risk seekers can resolve this conundrum. Even though such agents have negative risk aversion, they act as utility maximizers because they fully internalize their impact on prices. If their love of risk increases, information decreases in the aggregate, making prices noisier and returns more volatile. If public information becomes more precise, risk sharing decreases but welfare increases, contradicting the Hirshleifer effect. If private information becomes cheaper, liquidity always increases, rendering economies with risk seekers empirically distinct from economies with noise traders or random endowments.More Information
Efstathios Avdis, Jessica Wachter
Journal of Financial Economics. 2017 January; 125 (3):589-609
Journal of Financial Economics. 2016 January; 122
Efstathios Avdis, Ward Whitt
INFORMS Journal on Computing. 2007 January; 19 (3):341–355