Browsing by Author "Chen, Qi"

A central function of commodity futures markets is to help firms in the real sector insure against commodity price fluctuations. I examine how greater availability of information about commodity fundamentals (henceforth, information transparency) affects the capacity of these markets to accommodate firms’ hedging needs. Theory suggests that while greater availability of information can reduce adverse selection and increase traders’ willingness to absorb risk, it can also accelerate the realization of risk and hinder the transfer of risk via the markets. Using both cross-sectional variation in information transparency across 26 commodity markets over 20 years and information shocks induced by the launch of the Agricultural Market Information System (AMIS) and the SEC’s revision of firms’ 10-K oil and gas reserve disclosures, I document that information transparency (i) makes it costlier to use commodity futures to hedge commodity price risk and (ii) reduces traders’ propensity to trade futures. Evidence suggests that these findings are consistent with theories positing that information disclosure impairs risk-sharing opportunities. This study contributes new evidence on how information influences the efficient allocation of commodity price risk across the real and financial sectors.

This paper analyzes a manager's optimal ex-ante reporting system using a Bayesian persuasion approach (Kamenica and Gentzkow (2011)) in a setting where investors affect cash flows through their decision to finance the firm's investment opportunities, possibly assisted by the costly acquisition of additional information (inspection). I examine how the informativeness and the bias of the optimal system are determined by investors' inspection cost, the degree of incentive alignment between the manager and the investor, and the prior belief that the project is profitable. I find that a mis-aligned manager's system is informative

only when the market prior is pessimistic and is always positively biased; this bias decreases as investors' inspection cost decreases. In contrast, a well-aligned manager's system is fully revealing when investors' inspection cost is high, and is counter-cyclical to the market belief when the inspection cost is low: It is positively (negatively) biased when the market belief is pessimistic (optimistic). Furthermore, I explore the extent to which the results generalize to a case with managerial manipulation and discuss the implications for investment efficiency. Overall, the analysis describes the complex interactions among determinants of firm disclosures and governance, and offers explanations for the mixed empirical results in this area.

This paper studies firms' optimal qualitative disclosure about hard-to-quantify risk exposure to affect investors' information acquisition under the feedback effect channel. Based on a model with unknown payoff distribution, disclosure softness, and ambiguity aversion, I find that firms with lower risk exposure disclose more precisely. Particularly, low (medium) exposure firms provide perfect (partially informative) risk disclosures, whereas high exposure firms always disclose vaguely. In addition, the softness of risk disclosure enables firms to induce different risk perceptions among informed and uninformed investors with one disclosure, which gives firms the flexibility to separately influence the beliefs of the two groups of investors. Finally, I find that lower cost of information acquisition may improve economic efficiency at the expense of risk disclosure quality.

Using aggregate-level difference-in-differences analysis across 34 countries, I find that the extent to which aggregate accruals predict change in Gross Domestic Product (GDP) is greater for countries that adopted International Financial Reporting Standards (IFRS) than for countries that did not. I do not find a similar change in the predictive ability of aggregate cash flows following IFRS adoption. IFRS adoption also enables aggregate accruals to better predict a component of GDP (corporate profits) and factors related to GDP change (change in corporate investment and unemployment rate). The results are more pronounced for adopting countries with greater differences between local accounting standards and IFRS and for adopting countries with stronger enforcement. These findings support the view that IFRS adoption improves the measurement and recognition of firms’ fundamentals, and suggest that a change in accounting standards can reduce imperfections in accounting measurements of real output from business activities. These inferences have implications for accounting standard setters, users of financial statements, and policy-makers interested in understanding and predicting macroeconomic activity.

I examine the long-term valuation consequence of over-investment in mergers and acquisitions (M&As) on acquiring firms through the "anticipation effect," in which forward-looking prices embed investors' expectations about the profitability of firms' potential future acquisitions. Using a sample of 1,451 firms with past acquisition activities, I find that their market valuations depend on both the profitability of their past acquisitions and their current free cash flow. Specifically, among firms with positive free cash flow, those with the worse history of value-destroying acquisitions experience lower market valuations. Among firms with negative free cash flow, the history of value-destroying acquisitions is not systematically associated with firm value. In addition, a significant portion of the discount is from lowered valuation of firms' cash holdings. These findings are consistent with investors forming expectations about the profitability of future possible acquisitions based on the realized performance outcomes of firms' past acquisitions and value these firms accordingly based on the likelihood of engaging in future acquisitions. They also provide empirical support for using observed market prices to proxy for investors' expectations about firms' future investment opportunities.

Prior literature finds that algorithmic trading (AT) benefits the financial market by improving liquidity and accelerating the incorporation of existing information into prices. This paper shows that AT also has negative real effects: it reduces the sensitivity of corporate investment to stock prices. Moreover, firms’ future operating performance deteriorates following periods of high AT activity. The evidence is consistent with algorithmic traders crowding out fundamental traders’ information acquisition, leading to less information in prices for managers to learn and hence worse investment efficiency. Supporting evidence is also observed among financial analysts, who also learn less from stock prices when making forecast revisions.