Irina M. Luneva

E-mail: iluneva@wharton.upenn.edu

Office address: 360 Steinberg Hall-Dietrich Hall, 3620 Locust Walk, 

Philadelphia, PA, USA, 19104

What Does The Market Know?

Revise & resubmit - Journal of Accounting Research

I measure how much information the market knows about firms' fundamentals and managers' incentives to misreport on these fundamentals. The market knows 76.5% of current earnings and 36.8% of managers' incentives to misreport in a current report before the current earnings report arrives. 40.0% of this fundamental and 88.5% of this misreporting incentives information is learned about one year in advance, concurrently with the previous earnings report. A 1% increase in the market's fundamental information will increase earnings quality by 0.885% and improve price efficiency by 1.254%. A 1% increase in the market's misreporting incentives information will reduce earnings quality by 0.158% and improve price efficiency by 0.067%.

A Theoretical Framework for ESG Reporting to Investors

(with Henry L. Friedman and Mirko S. Heinle)

Revise & resubmit - Journal of Accounting Research

We provide a theoretical framework for reporting of firms' environmental, social, and governance (ESG) activities to investors. In our model, investors receive an ESG report and use it to price the firm. Because the manager is interested in the firm's price, disclosing an ESG report provides effort and greenwashing incentives. We analyze the impact of different reporting characteristics on the firm's price, cash flows, and ESG performance. In particular, we investigate the consequences of whether the report captures ESG inputs or outcomes, how the report aggregates different ESG dimensions, and the manager's tradeoffs regarding ESG efforts and reporting bias. We find that, for example, an ESG report that weights efforts by their impact on the firm's cash flows tends to have a stronger price reaction than an ESG report that focuses on the ESG impact per se. ESG reports aligned with investors' aggregate preferences provide stronger incentives and lead to higher cash flows and ESG than reports that focus on either ESG or cash flow effects individually. Additionally, in the presence of informative financial reporting, ESG reports that focus on ESG impacts lead to the same cash flow and better ESG results than reports focusing on cash flow impacts alone.

Where Do Brown Companies Borrow from?

(with S. Sarkisyan)

We study sources of debt for companies with poor ESG performance. Using a structural model of credit risk, we show that for low-ESG-rated firms, it is less expensive to borrow from banks than from public market compared to high-ESGrated firms. As a result, after a company experiences an adverse ESG event, it starts borrowing more from banks than from the bond market. At the same time, we find that banks have incentives to discipline brown companies that they lend to: banks’ stocks drop after a public announcement that a borrower experienced an adverse ESG event. The stronger the market’s reaction and the more adverse events borrowers experience, the higher loan spreads that the banks set for their brown borrowers. We conclude that both loan and bond markets offer higher costs of debt to brown firms, but the bond market’s “punishment” is higher than the loan market’s.

Financial Information and Diverging Beliefs

(with Mirko S. Heinle and Christopher S. Armstrong)

Standard Bayesians' beliefs converge when they receive the same piece of new information. However, when agents have uncertainty about the precision of a signal, their beliefs might instead diverge more despite receiving the same information. We demonstrate that this divergence leads to a unimodal effect of the absolute surprise in the signal on trading volume. We show that this prediction is consistent with the empirical evidence using trading volume around earnings announcements of US firms. We find evidence of elevated volume following moderate surprises and depressed volume following more extreme surprises, a pattern that is more pronounced when investors are more uncertain about earnings' precision. Because investors can disagree even further after receiving the same piece of news, the relationship between news and trading volume is not necessarily linear, suggesting that trading volume may not be an appropriate proxy for market liquidity.