Research articles for the 2021-04-17

Climate Uncertainty and Corporate Investment: Evidence from State-Led Climate Change Adaptation Plans
Heo, Yuna
We document that climate uncertainty negatively affects corporate investment. The effect is more pronounced for firms with higher capital intensity, higher operating inflexibility, and less redeployable capital. Our results are robust to using an instrumental variable approach and to using alternative climate uncertainty measure. Further, we find that climate adaptation plans mitigate the negative effects of climate uncertainty on corporate investment. We establish this result using the staggered introduction of State-led Climate Change Adaptation Plans. Our findings suggest that climate uncertainty can depress corporate investment, but climate adaptation plans shield firms from climate uncertainty contributing to investment resilience.

Corporate Bankruptcy and Banking Competition: The Effect of Financial Leverage
Cathcart, Lara,Dufour, Alfonso,Rossi, Ludovico,Varotto, Simone
We investigate the impact of banking competition on corporate credit risk. Although banking competition does not, on average, affect corporate bankruptcy rates, we find that it causes corporate bankruptcies to increase significantly for high-leverage firms. This effect lasts up to eight years after the increase in banking competition and comes mainly from firms that have high short-term debt. These results suggest that banking competition may lead to tougher credit conditions particularly for firms that are more heavily dependent on the credit market.

Cyberattacks on Small Banks and the Impact on Local Banking Markets
Gogolin, Fabian,Lim, Ivan,Vallascas, Francesco
Small banks are targets of a large number of cyberattacks. Using a sized-matched difference-in-differences design, we document that successful cyberattacks decrease branch deposit growth rates at small US banks. This decrease is due to bank-specific reputational damages that erode the trust of bank customers. The loss of trust results in a reallocation of deposits within local banking market to large banks. The reallocation is the consequence of a “flight-to-reputation” by depositors since it favours primarily large banks with a high reputation. We next document that cyberattacks affect the relationships between banks and customers in mortgage markets wherein hacked banks attract riskier applicants and are forced to lower their credit standards. Ultimately, our results imply that cybersecurity investments are crucial for banks to attract and retain customers and indicate that financial constraints in small banks can lead to local banking markets increasingly dominated by large banks. We highlight how this change in market structure can affect access to credit of small local businesses and impede the development of local economies.

Equity Crowdfunding and the Characteristics of Voluntary Disclosure
Aland, John
This paper provides descriptive evidence about the firm and managerial characteristics that drive voluntary disclosure when the investor base is inexperienced and information asymmetry is high â€" equity crowdfunding offerings issued under Regulation Crowdfunding. I find evidence that disclosure of financial information is driven primarily by the revenue levels of the firm, disclosure more qualitative in nature is driven by non-financial attributes such as social media presence and experience in unregistered security offerings, and disclosures of projected financial information are driven by manager specific characteristics. Additionally, I show that firms tailor disclosures based on whether the firm is seeking investment from “accredited” or “non-accredited” investors. The success of these offerings appears driven primarily by a firm’s qualitative disclosure. These findings contribute to our existing knowledge about voluntary disclosure, and better our understanding of the emerging equity crowdfunding market.

Nonlinearity, Nonstationarity, and Spurious Forecasts
Marmer, Vadim
Implications of nonlinearity, nonstationarity and misspecification are considered from a forecasting perspective. Our model allows for small departures from the martingale difference sequence hypothesis by including a nonlinear component, formulated as a general, integrable transformation of the I(1) predictor. We assume that the true generating mechanism is unknown to the econometrician and he is therefore forced to use some approximating functions. It is shown that in this framework the linear regression techniques lead to spurious forecasts. Improvements of the forecast accuracy are possible with properly chosen nonlinear transformations of the predictor. The paper derives the limiting distribution of the forecastsíMSE. In the case of square integrable approximants, it depends on the L2-distance between the nonlinear component and approximating function. Optimal forecasts are available for a given class of approximants.

Optimal Hedging Strategies for Options in Electricity Futures Markets
Hess, Markus
In this paper, we derive optimal hedging strategies for options in electricity futures markets. Optimality is measured in terms of minimal variance and the associated minimal variance hedging portfolios are obtained by a stochastic maximum principle. Our explicit results are particularly useful for electricity retailers, who have sold an option to a client, and now want to hedge the payoff of this option by investing into an electricity futures and into the issued option itself. Another innovative aspect of the paper lies in the derivation of the time dynamics of the stochastic option price process by Malliavin calculus methods and the Clark-Ocone formula. We also apply our theoretical results to several practical examples. Our investigations are based upon the popular arithmetic multi-factor electricity spot price model proposed by Benth, Kallsen & Meyer-Brandis (Appl. Math. Finance 14(2):153-169, 2007).

The Demand for Public Information by Local and Nonlocal Investors: Evidence from Investor-Level Data
Dyer, Travis
I examine the demand for public information by local and nonlocal investors. Using novel data on institutional investors’ requests for financial information from the SEC, I document that investors acquire approximately 20% more financial information for their local investments. This pattern holds after controlling for investors’ 13(f) portfolio holdings. I further demonstrate that this pattern is concentrated in stocks eliciting behavioral biases as well as among investors with strong company relationships. Consistent with public information acquisition being more beneficial to local investors, I find that local investors exhibit both enhanced timeliness in acquiring public information and superior portfolio trading decisions when acquiring public information (on the order of 0.5% per quarter). In sum, these results provide evidence that investors demand more, and benefit more from, public information on local investments.

US Cross-Listing and Domestic High-Frequency Trading: Evidence from Canadian Stocks
Dodd, Olga,Frijns, Bart,Indriawan, Ivan,Pascual, Roberto
We find that US cross-listing of Canadian stocks enhances domestic high-frequency trading (HFT) activity in the form of both opportunistic trading and market-making. First, US cross-listing boosts HFT low-latency cross-border arbitrage. This highly correlated HFT activity across markets enhances price efficiency by correcting mispricing. Second, US cross-listing leads to an increase in news trading activity by high-frequency traders around US public macro-news releases. Finally, cross-listing increases a stock’s reliance on high-frequency market makers to provide liquidity. Yet, we find no evidence of higher fragility in liquidity supply after cross-listing.

Wheat Price Volatility Over 140 Years: An Analysis of Daily Price Ranges
Haase, Marco,Zimmermann, Heinz,Huss, Matthias
This paper analyzes daily wheat price volatility over an observation period of more than 140 years, using daily high and low prices of futures contracts traded at the Chicago Board of Trade (CBOT), starting in 1877. We find that volatility differences between the identified regimes is much more important than volatility differences within the regimes, even when conditioning on state variables such as business cycles or inflation. Our findings suggest that the neglect of regimes can lead to a severe misinterpretation of the results when volatilities are correlated with exogenous variables. Further, historical volatility estimates derived from average price data, as is typically done in literature, are upward biased. The bias ranges between 0% and 22% across regimes. The magnitude potentially explains contradictory findings on volatility patterns in earlier studies.