We study the conglomerate discount from a novel perspective. We argue that the discount – measured in terms of Tobin's Q – far from being a sign of lower value is, instead, a sign of higher value for the conglomerate. This can be explained as conglomerates being less financially constrained...

We study how the relative availability of bond and bank financing supply affects the firm's ability to borrow and to use its leverage to buffer shocks. We define a measure that proxies for the regional borrowing inflexibility in the availability of bank and bond financing: “debt...

In an analytically tractable model of the global economy, we calculate the Pareto improvement where a country experiencing a favourable supply side shock consumes more against expected future output and spreads the risk by selling shares. With capital inflows to finance the 'New Economy'...

Based on the observed behavior of monetary aggregates and exchange rates, we classify inflation stabilization episodes into two categories: de facto exchange rate-based stabilizations (ERBS) and non-ERBS. Unlike the standard de jure ERBS studied in the literature, de facto ERBS encompass cases...

This study quantifies firm-specific operating exposure to cumulative unexpected weather variations and examines how it affects earnings predictability and analysts’ forecasts. Two competing hypotheses are tested. The reduction in earnings seasonality hypothesis posits that operating weather...

This study investigates the impact of weather conditions on the performance of institutional investors. I test two competing hypotheses. The negative mood hypothesis posits that bad weather induces a negative mood among asset managers and results in worse portfolio performance. The productivity...

This study investigates the effect of corporate hedging on stock price crash risk. We test two competing hypotheses. Under the transparency hypothesis, hedging reduces a firm's information asymmetry and lowers crash risk. Under the opacity hypothesis, hedging decreases financial reporting...

While deep learning algorithms demonstrate a great potential in scientific computing, its application to multi-scale problems remains to be a big challenge. This is manifested by the ``frequency principle" that neural networks tend to learn low frequency components first. Novel architectures...

Pulsed magnetic fields can improve ferromagnetic and paramagnetic materials by improving their stress structure, domain variation, phase structure distribution and grain size of both solid and molten metals. Therefore, according to the characteristics of a pulsed magnetic field and combined with...

Working fluid preparation using treated drilling wastewater is of great potential for drilling wastewater reuse, especially in water-deficient and ecologically fragile areas, which require low levels of organic matter and suspended solids. This study established the dissolved ozone flotation...