Firms frequently enter into dividend hibernation, periods during which dividends remain unchanged for consecutive quarters. Employing a dividend event framework, we show that hibernating firms experience higher unexpected future earnings growth compared to matched non-hibernating firms for up to five years by reducing underinvestment. We construct an index of adverse selection measures and find that hibernating firms are more opaque, indicating that the information gap between insiders and outsiders widens when there is no change in dividends. Extended hibernation episodes increase the opaqueness, while dividend changes after prolonged periods of no signaling reduce the information gap more effectively. 

In this first part of the INFINITECH book series, which is a series of three books, the principles of the modern economy that make the modern financial sector and FinTech the most disruptive areas in today’s global economy are discussed. INFINITECH envision many opportunities emerging for activating new channels of innovation on the local and global scale while at the same time catapulting opportunities for more disruptive user-centric services. At the same time, INFINITECH is the result of a shared vision from a representative global group of experts, providing a common vision and identifying impacts in the financial and insurance sectors. 

In this second part of the INFINITECH book series, which is a series of three books, the basic concepts for Fintech referring to the diversity in the use of technology to underpin the delivery of financial services are reviewed. The demand and the supply side in the financial sector are demonstrated, and further discussed is why Fintech is the focus of industry nowadays and the meaning for waves of digitization. Financial technology (FinTech) and insurance technology (InsuranceTech) are rapidly transforming the financial and insurance services industry. An overview of Reference Architecture (RA) for BigData, IoT and AI applications in the financial and insurance sectors (INFINITECH-RA) is also provided. Moreover, the book reviews the concept of innovation and its application in INFINITECH, and innovative technologies provided by the project for financial sector practical examples. 

This third and final part of the INFINITECH book series begins by providing a definition for Fintech, namely: the use of technology to underpin the delivery of financial services. The book further discusses why Fintech is the focus of industry nowadays as the waves of digitization and the way financial technology (FinTech) and insurance technology (InsuranceTech) are rapidly transforming the financial and insurance services industry. The book also introduces technology assets that follow the Reference Architecture (RA) for BigData, IoT and AI applications. Moreover, the series of assets includes the domain area where applications from the INFINITECH innovation project and the concept of innovation for the financial sector are described. Further described is the INFINITECH Marketplace and its components including details of available assets, as well as a description of solutions developed in INFINITECH. 

 INFINITECH is a joint effort of global leaders in ICT and finance towards lowering the barriers for BigData/IoT/AI driven innovation, boosting regulatory compliance and stimulating additional investments. INFINITECH will provide novel BigData/IoT technologies for seamless management and querying of all types of data interoperable data analytics, blockchain-based data sharing, real-time analytics, as well as libraries of advanced AI algorithms. It also produces regulatory tools incorporating various data governance capabilities and facilitating compliance to regulations (e.g., PSD2, 4AMLD, MIFiD II). INFINITECH encompasses nine novel and configurable testbeds & sandboxes, each one offering Open APIs and other resources for validating autonomous and personalized solutions, including a unique collection of data assets for finance/insurance. 

FAME is a joint effort of world class experts in data management, data technologies, the data economy and digital finance to develop, deploy and launch to the global market a unique, open, publicly accessible, trustworthy, energy efficient, and secure federated data marketplace for EmFi, which will offer novel decentralized programmable pricing and trading of data assets. The FAME data marketplace will alleviate the proclaimed limitations of centralized cloud marketplaces towards demonstrating the full potential of the data economy. In this direction, the project will enhance a state of the art data marketplace infrastructure (namely the H2020 i3-MARKET marketplace) with novel functionalities in three complementary directions. 

 We provide evidence that dividend smoothing negatively affects firm value. To overcome endogeneity concerns embedded in dividend studies, we employ several identification strategies. Further, we hypothesize and verify empirically that the negative impact of smoothing is more pronounced during positive shocks to transitory earnings. Consistent with the prediction of agency theory, we find that high-smoothing firms experience a value loss since they do not distribute additional funds when hit by positive shocks. The results are robust to alternative measures of dividend smoothing and firm value.

We study dividend smoothing in tandem with debt and investment policies. Avid dividend smoothers resort to net debt issuance to absorb cash flow variations since altering dividends is not a fully available option. Financially constrained firms are unable to rely entirely on debt to mitigate smoothing frictions, curbing investments to fund transitory cash flow shocks. The impact of smoothing persists for total cash flow and its transitory component, making it unlikely to be driven by the heterogeneous growth options of the firm. We use an instrumental variable approach, exploiting differences in the loadings of dividend smoothing on the S&P500 dividend strip returns, to address endogeneity concerns. Further, we show that the results are mainly caused by the rigidity of dividends rather than total payout and magnify for instances of fixed dividends.

This study explores whether changes in aggregate uncertainty affect the efficiency of corporate decision making. We argue that higher macroeconomic uncertainty hampers managers’ ability to accurately predict firm-specific information and induce them to implement similar liquidity, investment, payout, and debt policies.

Section 302 of the US Internal Revenue Code requires that distributions must be "substantially disproportionate" to be treated as share repurchases, whereas dividends are by definition proportionate distributions. By applying a unique instrumental variable, we investigate whether stock buybacks increase ownership concentration.

Zombie firms are defined as mature firms with low growth prospects such that their current profit fails to cover their interest on debt over an extended period. Weak banks, low interest rates, and deficient insolvency regimes are listed as probable causes behind the rise of the zombie firms. Apparently, equity markets are inefficient in purging these firms from their rank. I assert that if such a systemic inefficiency exists, it is non-trivial since up to 10% of U.S. publicly-listed industrial firms in Compustat are diagnosed as zombies. Given that evidence suggests that debt holders are the losers, who are the winners of this venture?

Distress risk anomaly is a well-established and persistent asset pricing phenomenon. Firms with higher default risk earn lower returns, leading to a dysfunctional risk-return trade-off. I show that zombie firms, defined as mature firms with low growth prospects such that their current profit fails to cover their interest on debt over an extended periods, are to blame. Equity markets are inefficient in purging these firms from the exchange, leading to a sizable abnormal negative return. Excluding zombies from the sample reduces the default risk anomaly.