Research
Working Papers
Sell-side Analysts' Career Concerns During Banking Stresses. 
(with Nolte, I. and Nolte, S.)
Journal of Banking and Finance (forthcoming), http://ssrn.com/abstract=2405828
This paper presents evidence that media coverage of sell-side analysts' employers affects analysts' forecasting behavior in real time. A unique high-frequency dataset on individual firms' media coverage allows us to construct employer/sector specific news sentiment measures that serve as a direct proxy for analysts' career concerns in real time. We find that positive media coverage leads to individual analysts' forecasts that deviate stronger from the consensus forecasts (and vice versa) regardless of the type of firm or sector they follow. We show that this effect is generally time dependent and strengthened during the recent financial turmoil.
We explore the information content of counterparty identities and how their disclosure can be exploited by other investors in a post-trade transparent market. Using data from the Helsinki Stock Exchange, we form dynamic mean-variance strategies with daily rebalancing which condition on the net flow of individual brokers. We find that investors can benefit greatly, up to 36% in annualized risk adjusted returns, from knowing who has been trading. We demonstrate a link between the information content of broker order flow and the sophistication of their clients. Brokers who have clients that trade with a momentum style or who are predominantly institutions or foreign investors have much more informative flow than do others. In the Finnish setting, this means that brokers with large market share have uninformative flows.
In this paper we provide a simple framework for the estimation of the variance-covariance matrix in the presence of MMS noise and non-synchronous trading. To accomplish that we start from the formula of the realized variance and the Hayashi-Yoshida realized covariance estimator and derive two separate pooled OLS regressions whose byproducts are the intergrated variance and covariance, respectively. An comprehensive simulation study shows that the least square approach gives rise to very precise estimators for all elements of the covariation matrix and outperforms other widely applied estimation techniques. A similar picture emerges when we use historical high frequency data.
Work in Progress