# Research articles for the 2019-09-12

A new concept of technology with systemic-purposeful perpsective: theory, examples and empirical application
Mario Coccia
arXiv

Although definitions of technology exist to explain the patterns of technological innovations, there is no general definition that explain the role of technology for humans and other animal species in environment. The goal of this study is to suggest a new concept of technology with a systemic-purposeful perspective for technology analysis. Technology here is a complex system of artifact, made and_or used by living systems, that is composed of more than one entity or sub-system and a relationship that holds between each entity and at least one other entity in the system, selected considering practical, technical and_or economic characteristics to satisfy needs, achieve goals and_or solve problems of users for purposes of adaptation and_or survival in environment. Technology T changes current modes of cognition and action to enable makers and_or users to take advantage of important opportunities or to cope with consequential environmental threats. Technology, as a complex system, is formed by different elements given by incremental and radical innovations. Technological change generates the progress from a system T1 to T2, T3, etc. driven by changes of technological trajectories and technological paradigms. Several examples illustrate here these concepts and a simple model with a preliminary empirical analysis shows how to operationalize the suggested definition of technology. Overall, then, the role of adaptation (i.e. reproductive advantage) can be explained as a main driver of technology use for adopters to take advantage of important opportunities or to cope with environmental threats. This study begins the process of clarifying and generalizing, as far as possible, the concept of technology with a new perspective that it can lay a foundation for the development of more sophisticated concepts and theories to explain technological and economic change in environment.

Accounting Standards and Earnings Quality â€" Evidence from Registered ADRS
Alhaj-Yaseen, Yaseen,Wu, Kean,Fletcher, Leslie
SSRN
This paper examines the changes in earnings quality of registered ADRs as a result of switching accounting standards. We aim to shed light on the potential impact of IFRS adoption on US firms. A suboptimal approach to achieve this goal is through examination of US firmsâ€™ surrogates such as ADRs. Unlike previous studies, we made a distinction between registered and unregistered ADRs, and affirmed that registered ADRs are the closest surrogates with which to conduct our analysis because they are exclusively required to adhere to the SECâ€™s stringent disclosure requirements. When cross-listing their equity on the US exchanges, foreign issuers can file their financial reports with the SEC using IFRS, US GAAP, or their domestic GAAP with reconciliation to US GAAP. An improvement in earnings quality is documented when ADRs adopt US GAAP or IFRS versus domestic GAAP. However, when the comparison is made between US GAAP and IFRS, no difference in earnings quality is documented. These results indicate that switching to high-quality accounting standards is likely to improve earnings quality. This improvement is maximized when the difference between reporting standards is high and minimized if otherwise. Our conclusion is that the adoption of IFRS in the US is unlikely to change earnings quality of local issuers. Moreover, we drew a distinction between reconciliation with and adoption of high-quality accountings standards and find that while the former can enhance earnings quality, the latter can further improve it.

Another Path to the Joint-Stock Company
Le Bris, David,Pouget, Sebastien
SSRN
Common wisdom views the 17th century English and Dutch East India companies as key institutional innovations based on the commenda commercial contracts. We mobilize historical, legal and economic literatures to characterize an alternative path to the joint-stock company in Southern Europe. A medieval institution, the pariage, gave birth to large-scale business organizations similar to joint-stock companies as early as the 14th century in Genoa and in Toulouse. Pariage originated in the Roman rule of equal inheritance that led to the division of assets into theoretical shares. When the asset includes a business activity, pariage as an institution becomes closer to a modern joint-stock company. We show that, at the eve of the industrial revolution, these companies display a higher level of institutional modernity than East India-type companies. These observations have implications for the debate regarding the links between institutions and economic development.

Board Independence and Information Asymmetry in Family Firms vs. Non-Family Firms
Wu, Kean,Sorensen, Susan,Sun, Li
SSRN
This study investigates the role of independent board members in insider-controlled firms by examining the effectiveness of independent boards in reducing information asymmetry in family versus non-family firms. We show a negative relation between the proportion of independent directors and information asymmetry, proxied by trading volume, the bid-ask spread, and price volatility. We also find negative relation is more pronounced for a family firm versus a non-family firm. These results are robust after controlling for the endogenous choice of board members in various models. Our findings ease the concern that founding families may over-ride independent boards and exhibit opportunistic behavior.

Comparison Analysis of ICO, DAOICO, IEO and STO. Case Study.
Myalo, Alina,Glukhov, Nikita
SSRN
Despite of the fact that the history of Initial Coin Offering (ICO) is short, new modification of it has already suggested. According to the ICORating, in the second half of 2018, the profitability of investments in blockchain startups decreased by 22%, and 58% of ICO projects announced in Q4 2018 were not able to raise more than 100,000 USD. Moreover, in Q4 2018 40% of projects with previously announced ICOs have already deleted their social network accounts and websites. The founder of Ethereum Vitalik Buterin (2015), who started the first ICO, proposed a new way of decentralized fundraising called DAICO in 2018. This new model will include elements of Decentralized Autonomous Organizations (DAO), and its purpose will be to minimize the difficulties and risks associated with the ICO. At the same time, in 2018 another model of financing appeared called Initial Exchange Offering (IEO) in order to minimize risks, problems of liquidity and the postponement of the listing of the tokens at the end of tokensale step. More than 70 IEOs listed on ICObench with average rating of 3.6 and 42 IEOs have been ended and raised $266 million in total. Nevertheless, there three types of tokens 95% of ICO projects are utility-based token. This makes ICO comparable to crowfunding. In order to be more attractive for investors the focus on a new wave of ICO projects is on the security type of tokens. The security token is any cryptocurrency that pays dividends, profits, shares or interest or invests in any other asset that also generates profits. The U.S. Securities and Exchange Commission (SEC) use the Howey Test and concludes the securities token are securities in contract to classical utility token of ICO projects. In order to back by real assets and follow the SEC's guidance on compliance, issuance, and trading new model is called Security Token Offering (STO) and differs from ICO. All three new models are a new focus for small and medium-sized enterprises (SME) and investors. The absence of any type of academic works emphasizes the relevance and scientific novelty of the forthcoming research. The contribution to the existing literature is the systematization of information and comparison analyses of ICO, DAOICO, IEO and STO by method of case study. Covered Interest Rate Parity Deviations In External Emerging Market Sovereign Debt Hartley, Jonathan SSRN Non-U.S. dollar denominated external emerging market debt issuance in euros, yen, and sterling has grown substantially in recent years. This paper is the first study to explore how non-dollar external emerging market bonds violate covered interest rate parity relative to their dollar-denominated external emerging market debt counterpart bonds for a given country. Such mispricing in the post-Great Recession era creates arbitrage opportunities for investors and suggests that emerging market country policymakers could create fiscal savings by instead more cheaply issuing external sovereign debt in dollars (versus non-dollar developed world currencies like euro, yen, and sterling) and swapping the proceeds to non-dollar currencies with currency forward and spot transactions. Such hypothetical fiscal savings from switching to dollar funding collectively are estimated to be more than$1 billion annually.

Deep Prediction of Investor Interest: a Supervised Clustering Approach
Baptiste Barreau,Laurent Carlier,Damien Challet
arXiv

We propose a novel deep learning architecture suitable for the prediction of investor interest for a given asset in a given timeframe. This architecture performs both investor clustering and modelling at the same time. We first verify its superior performance on a simulated scenario inspired by real data and then apply it to a large proprietary database from BNP Paribas Corporate and Institutional Banking.

Loan to Value Caps and Government-Backed Mortgage Insurance: Loan-Level Evidence From Dutch Residential Mortgages
de Haan, Leo,Mastrogiacomo, Mauro
SSRN
Using loan level data on mortgage loans originated by Dutch banks during 1996 to 2015, we analyse the determinants of the incidence of non-performance. We find that both the originating loan-to-value ratio (OLTV) and the debt-service-to-income ratio (DSTI) are significantly positively associated with the probability of non-performance. The results suggest that mortgages with government-loan-guarantees perform better. Moreover, several mortgage loan and borrower characteristics, such as the (interest-only) loan type and the underwater status of the borrower, increase credit risk. Our model predictions suggest a novel policy implication: in order to avoid acceleration of non-performance probabilities, the OLTV-limit should be set to about 70%-80% for uninsured mortgages, and to about 90% for those with mortgage insurance.

Managing to Target (II): Dynamic Adjustments for Retirement Strategies
Estrada, Javier
SSRN
All individuals need to determine a withdrawal policy for their retirement. This decision needs to balance the goal of funding a desired lifestyle (and perhaps leaving a bequest) with the goal of not running out of money too early, which is best done by making a financial plan. When the returns of his portfolio differ from those expected in the plan, what should a retiree do? Should he statically stick to the withdrawals specified in his plan? Should he introduce dynamic adjustments in order to push the portfolio closer to the path outlined in the plan instead? This article evaluates two types of dynamic policies, broadly referred to as â€˜managing to targetâ€™ (M2T) strategies, that adjust either the periodic withdrawals or the portfolioâ€™s asset allocation. The results reported show that dynamic M2T strategies outperform a static strategy of sticking to the plan, and that adjusting withdrawals is superior to adjusting the portfolioâ€™s asset allocation.

Modelling election dynamics and the impact of disinformation
Dorje C Brody
arXiv

Complex dynamical systems driven by the unravelling of information can be modelled effectively by treating the underlying flow of information as the model input. Complicated dynamical behaviour of the system is then derived as an output. Such an information-based approach is in sharp contrast to the conventional mathematical modelling of information-driven systems whereby one attempts to come up with essentially {\it ad hoc} models for the outputs. Here, dynamics of electoral competition is modelled by the specification of the flow of information relevant to election. The seemingly random evolution of the election poll statistics are then derived as model outputs, which in turn are used to study election prediction, impact of disinformation, and the optimal strategy for information management in an election campaign.

Mortality rate forecasting: can recurrent neural networks beat the Lee-Carter model?
Gábor Petneházi,József Gáll
arXiv

This article applies a long short-term memory recurrent neural network to mortality rate forecasting. The model can be trained jointly on the mortality rate history of different countries, ages, and sexes. The RNN-based method seems to outperform the popular Lee-Carter model.

Opioid Crisis Effects On Municipal Finance
Cornaggia, Kimberly Rodgers,Hund, John,Nguyen, Giang,Ye, Zihan
SSRN
This paper provides county-level evidence on the impact of opioid abuse on U.S. municipalities' tax revenues, law enforcement costs, credit risk, and access to finance. Complementing prior research on various costs of the crisis mostly at state- and national levels, we offer a first close look at the effects of the crisis at a much more granular level of government to quantify more accurately capital market impacts relevant to municipalities that need financing for schools, utilities, roads, and other infrastructure projects. Our analysis is based on a comprehensive database compiled from various sources, some of which have not been heretofore explored in the literature. Employing a battery of empirical approaches (panel fixed effect regressions, instrumental variable regressions, and difference-in-differences analysis), we find evidence of a significant causal increase in municipal borrowing costs and a reduction in credit ratings. However, the economic magnitude of these effects is surprisingly small given evidence of substantially reduced tax revenue and increased law enforcement costs. Our results indicate either that the economic impact of the opioid crisis on local government finance is not yet a significant credit risk factor, or that credit rating agencies and municipal bond investors overlook a significant credit risk factor.

Political Connections and Share Repurchases
Nnadi, Modestus,Sorwar, Ghulam,Roddy, Eileen
SSRN
We find that political connections are positively associated with the probability of a company repurchasing shares, and the value of shares repurchased. The effect of political connections on share repurchase decisions persists whether a firm is connected either through a Republican or Democratic politician. Further analysis shows that politically connected boards generated higher stock returns around share repurchase announcement period and in the long-term than their non-connected counterparts. Our results are robust to controls for firm characteristics, firm fixed effects, using a two-stage regression, and matching estimation.

Political Uncertainty and A-H Share Premium
cheng, Xu,Wang, Junbo,Kong, Dongmin
SSRN
Using the turnover of city-level local leaders in mainland China, we construct a measure of political uncertainty and use this measure to explain the change of A-H share premium. Our empirical evidence shows that political uncertainty significantly reduces A-H share premium. The reduction effect is lower for the turnovers with lower political uncertainty, stronger for firms with more political exposure and in cities with lower marketization level and economic conditions. Our results are robust to alternative specifications.

Pricing Reliability Options under different electricity prices' regimes
Luisa Andreis,Maria Flora,Fulvio Fontini,Tiziano Vargiolu
arXiv

Reliability Options are capacity remuneration mechanisms aimed at enhancing security of supply in electricity systems. They can be framed as call options on electricity sold by power producers to System Operators. This paper provides a comprehensive mathematical treatment of Reliability Options. Their value is first derived by means of closed-form pricing formulae, which are obtained under several assumptions about the dynamics of electricity prices and strike prices. Then, the value of the Reliability Option is simulated under a real-market calibration, using data of the Italian power market. We finally perform sensitivity analyses to highlight the impact of the level and volatility of both power and strike price, of the mean reversion speeds and of the correlation coefficient on the Reliability Options' value.

Redefining Accredited Investor: Thatâ€™s One Small Step for the SEC, One Giant Leap for Our Economy
Thomas, Jeff
SSRN
New ventures move our economy. Most of these ventures need additional capital to grow. They raise this capital through exempt offerings, and exempt offerings are essentially limited by the pool of accredited investors (AIs). Currently, individuals must meet either net worth or income thresholds to be considered AIs. Because of this, AIs make up only 13% of U.S. households, and only a small fraction of these households actually invest in exempt offerings. There is consensus that it is time to consider criteria besides net worth and income. Expanding the AI population by welcoming people who pass a relevant exam is a responsible way to increase the number of AIs. Even if no other securities laws or rules change, the AI exam would help ensure investor protection while generating more investment alternatives for individuals, additional capital for new ventures, and increased liquidity for the market.

The Emergence of Innovation Complexity at Different Geographical and Technological Scales
Emanuele Pugliese,Lorenzo Napolitano,Matteo Chinazzi,Guido Chiarotti
arXiv

We define a novel quantitative strategy inspired by the ecological notion of nestedness to single out the scale at which innovation complexity emerges from the aggregation of specialized building blocks. Our analysis not only suggests that the innovation space can be interpreted as a natural system in which advantageous capabilities are selected by evolutionary pressure, but also that the emerging structure of capabilities is not independent of the scale of observation at which they are observed. Expanding on this insight allows us to understand whether the capabilities characterizing the innovation space at a given scale are compatible with a complex evolutionary dynamics or, rather, a set of essentially independent activities allowing to reduce the system at that scale to a set of disjoint non interacting sub-systems. This yields a measure of the innovation complexity of the system, i.e. of the degree of interdependence between the sets of capabilities underlying the system's building blocks.

The Role of the Business Press in Creating and Disseminating Information Around Earnings Announcements
Coyne, Joshua G.,Kim, Kevin,Kim, Sangwan
SSRN
This paper investigates the role of the business press in creating and disseminating information around earnings announcements by examining different motivations of trading volume. We find that press coverage is positively associated with trading activity motivated by differential interpretation and by differential belief revision, consistent with the press playing both an information creation and information dissemination role around earnings announcements. When we divide press coverage into full articles with additional editorial content and news flashes merely repeating verbatim of firm-disclosed press releases, we find that trading volume motivated by both differential interpretation and differential belief revision increases as coverage by full articles increases, and trading volume motivated by differential belief revision increases as coverage by news flashes increases. We also report that the differential interpretation effect of full articles is more pronounced when information usersâ€™ sophistication is high. Overall, we provide new evidence to the literature by showing that each type of press coverage plays an informational role in different motivations of trading activity.

Utility Based Model Selection and Model Averaging
Navratil, Robert,Vecer, Jan
SSRN
This paper presents a novel approach to model selection and model averaging based on economic theory. We study model prediction in the form of a distributional opinion about a random variable X. We show how to test this prediction against alternative views. Different model opinions can be traded on a hypothetical market that trades their differences. Using a utility maximization technique, we describe such a market for any general random variable X and any utility function U. We specify the optimal behavior of agents and the total market that aggregates all available opinions and show that a correct distributional opinion realizes profit in expectation against any other opinion, giving a novel technique for model selection. Analytical solutions are available for random variables from the exponential family. We determine the distribution corresponding to the aggregated view of all available opinions, giving a novel technique for model averaging.

Weak comonotonicity
Ruodu Wang,Ricardas Zitikis
arXiv

The classical notion of comonotonicity has played a pivotal role when solving diverse problems in economics, finance, and insurance. In various practical problems, however, this notion of extreme positive dependence structure is overly restrictive and sometimes unrealistic. In the present paper, we put forward a notion of weak comonotonicity, which contains the classical notion of comonotonicity as a special case, and gives rise to necessary and sufficient conditions for a number of optimization problems, such as those arising in portfolio diversification, risk aggregation, and premium calculation. In particular, we show that a combination of weak comonotonicity and weak antimonotonicity with respect to some choices of measures is sufficient for the maximization of Value-at-Risk aggregation, and weak comonotonicity is necessary and sufficient for the Expected Shortfall aggregation. Finally, with the help of weak comonotonicity acting as an intermediate notion of dependence between the extreme cases of no dependence and strong comonotonicity, we give a natural solution to a risk-sharing problem.

Why is There a Secular Decline in Idiosyncratic Risk in the 2000s?
Bartram, SÃ¶hnke M.,Brown, Gregory W.,Stulz, RenÃ© M.
SSRN
Except for relatively short but intense episodes of high market risk, average idiosyncratic risk (IR) falls steadily after 2000 until almost the end of our sample period in 2017. The decrease has been such that from 2012 to 2017 average IR was lower than any time since 1965. The secular decline can be explained by the fact that U.S. publicly listed firms have become larger, older, and their stock more liquid. The same changes that bring about historically low IR lead to increasingly high market-model R-squareds.

XBRL Mandate and Timeliness of Financial Reporting: Do XBRL Filings Take Longer
Du, Hui,Wu, Kean
SSRN
We examine the impact of the Securities and Exchange Commission (SEC)â€™s XBRL (eXtensible Business Reporting Language) mandate on the timeliness of financial reporting, measured by the reporting lag between fiscal period end and the filing date. Using annual and quarterly filing data from 2007 to 2014, we compare the reporting lags of XBRL reports to the lags of non-XBRL reports in three separate filing categories as defined by the SEC. Our results show that by using XBRL the reporting lag is shortened by one to two days when companies file annual reports while the reporting lag is shortened by one day in quarterly filings. However, the results are manifest for both large accelerated filers and accelerated filers. In our multivariate analysis, we do not observe the improved reporting lag when using XBRL among non-accelerated filers. The results are robust to various model specifications and additional differential effect analyses. While we provide the evidence that the XBRL mandate improves the timeliness of financial reporting for large filers, we question the public policy-making of the XBRL mandate that has the intention of benefiting small companies.