Research articles for the 2020-08-06
SSRN
The recent booming of AI in FinTech evidences the significant developments and potential of AI for making smart FinTech, economy, finance and society. AI-empowered smart FinTech has emerged as a sexy and increasingly critical area in AI, data science, economics, finance, and other relevant research disciplines and business domains. This trend was built on the long history of AI in finance, and the new-generation AI, data science and machine learning are fundamentally and seamlessly transforming the vision, missions, objectives, paradigms, theories, approaches, tools and social aspects of economics and finance and driving smart FinTech. AI is empowering more personalized and advanced and better, safer and newer mainstream and alternative economic-financial mechanisms, products, models, services, systems, and applications. This review summarizes the lasting research on AI in finance and focuses on creating a comprehensive, multidimensional and economic-financial problem-driven research landscape of the roles, research directions and opportunities of AI in new-generation FinTech and finance.
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We investigate the trading of corporate bonds on alternative trading system (ATS) platforms. We draw a key distinction between request-for-quote (RFQ) and electronic communication network (ECN) trading protocols, which balance investorsâ preference for immediacy and anonymity. Trades on ATS platforms are smaller and more likely to involve investment-grade bonds. Trades on ATS platforms are more probable for older, less actively traded bonds from smaller issues and for bonds traded by more dealers where inventory is high. Moreover, dealer participation on ATS platforms is associated with lower customer transaction costs of between 24 and 32 basis points.
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We empirically document that banks with greater exposure to high home price-to-income or price-to-rent ratio regions before the financial crisis of 2007--2009 have higher mortgage delinquency and charge-off rates and significantly higher probabilities of failure during the crisis even after controlling for standard bank characteristics and local economic conditions. While high house prices relative to fundamentals present a greater likelihood of house price correction, we find no evidence that banks managed this risk by building stronger capital buffers. The bank level mortgage risk measures we develop could be used to improve risk management.
SSRN
This paper discusses the essence of the entrepreneurial risk, ethical and legal standards, which must be adhered to by the head of a commercial organisation. In the Russian legislation, there is debate concerning the boundaries of the responsibilities of the corporate manager. Existing literature doesnât contain many studies about the norms on the responsibility of persons authorised to act on behalf of a legal entity because it is new for Russian civil legislation, which shows the novelty of this study. We identify problematic aspects that arise both in the doctrine and judicial practice regarding the determination of the criteria of good faith and reasonable behaviour of the head of the corporation. Our study examines the legal nature of entrepreneurial risk and how it affects the formation of managerial decisions. As a result, we propose a basic model of the criteria for the good behaviour of a corporate manager within a reasonable entrepreneurial risk.
SSRN
We show that options written on stocks with low prices are over-priced. This effect is robust to a variety of tests, controlling for common stock- and option- risk characteristics, and to reasonable transaction costs. Natural experiments corroborate this finding; options tend to become relatively more expensive following stock splits; and options on mini-indices are overpriced relative to options written on otherwise identical regular-priced indices. Our evidence suggests that (less sophisticated) retail investors consider options with low underlying prices as good deals due to low prices of such options. Demand pressure from these investors leads to option overpricing.
SSRN
We use a matched sample of corporate bonds that are guaranteed by the full faith and credit of the U.S. government and non-guaranteed corporate bonds of the same issuers to examine default and non-default related components in bond spreads. We find that less than one-fifth of the yield spread between short-term, investment grade corporate bonds and Treasury securities is compensation for illiquidity. Our estimates of the liquidity component in corporate bond spreads differ significantly from the bond-CDS basis. We also find evidence that the corporate bond bid-ask spread is largely related to credit risk.
arXiv
The global minimum-variance portfolio is a typical choice for investors because of its simplicity and broad applicability. Although it requires only one input, namely the covariance matrix of asset returns, estimating the optimal solution remains a challenge. In the presence of high-dimensionality in the data, the sample covariance estimator becomes ill-conditioned and leads to suboptimal portfolios out-of-sample. To address this issue, we review recently proposed efficient estimation methods for the covariance matrix and extend the literature by suggesting a multi-fold cross-validation technique for selecting the necessary tuning parameters within each method. Conducting an extensive empirical analysis with three datasets based on the Russell 3000, we show that the data-driven choice of specific tuning parameters with the proposed cross-validation improves the out-of-sample performance of the global minimum-variance portfolio. In addition, we identify estimators that are strongly influenced by the choice of the tuning parameter and detect a clear relationship between the selection criterion within the cross-validation and the evaluated performance measure.
SSRN
This paper investigates and contrasts the determinants of four different groups of projects -social, environmental, economic, and cultural- crowdfunding success. Our results demonstrate that while social and cultural projects probability of crowdfunding success is significantly and negatively sensitive to the requested amount of funds, economic projects probability of crowdfunding success is significantly and positively sensitive to the requested amount of funds. Although, environmental projects probability of crowdfunding success does not display a significant sensitivity to the requested amount of funds. Those findings highlight that projects probability of crowdfunding success is an increasing function of financial benefits. Furthermore, competition between crowd-funders impacts social projects probability of crowdfunding success but does not impact that of economic, environmental, and cultural projects.
arXiv
This project aims at creating an investment device to help investors determine which real estate units have a higher return to investment in Madrid. To do so, we gather data from Idealista.com, a real estate web-page with millions of real estate units across Spain, Italy and Portugal. In this preliminary version, we present the road map on how we gather the data; descriptive statistics of the 8,121 real estate units gathered (rental and sale); build a return index based on the difference in prices of rental and sale units(per neighbourhood and size) and introduce machine learning algorithms for rental real estate price prediction.
SSRN
German abstract: Risiko wird häufig mit Volatilitäten zu erwarteter Rendite unter adjustiertem Risiko in Verbindung ge-bracht oder als stochastisches Verlustrisiko zum Kapitaleinsatz. Adjustierung durch Diversifikation von Assets reduziert unsystematische Risiken. In diesem Artikel beobachte ich entgegen der Moder-nen Portfolio Theorie und Arbitrage Pricing Theorie Kapitalrückflüsse nach erfolgter Investition auf unterschiedlichen Ebenen: Kapitalgeber versus Asset. Die Entwicklung der Rückflüsse über die Inves-titionszeit bietet Aufschluss, (1) mit welcher âGeschwindigkeitâ der Kapitalgeber Rentabilität erzielt und (2) zu welcher Risikoklasse Kapitalgeber und Asset angehören: das Risiko des Kapitalgebers entwi-ckelt sich diametral zum Risiko der Erwirtschaftbarkeit der Cashflows auf Ebene des Assets. Die Ri-sikomesszahl âNon FYT Indicator (NFI)â in einem zeitstetigen FYT-Modell misst die Abweichung der vom Kapitalgeber erhofften Kapitalvermehrung zu den angebotenen kumulierten Rückflüssen des Assets über die Investitionszeit. Die optimale Kapitalanlage zeigt das NFI-Ergebnis gleich null.English abstract: Risk is often associated with volatility to expected returns under adjusted risk or as a stochastic risk of loss on capital employed. Adjustment through diversification of assets reduces unsystematic risks. In contrast to the Modern Portfolio Theory and Arbitrage Pricing Theory, in this article I observe the return of capital after investing at different levels: investor versus asset. The development of returns over the investment period provides information on (1) the âpaceâ with which the investor achieves return on investment and (2) the risk class of the investor and asset: the risk of the investor develops diametrically to the risk of the profitability of the cashflows at asset level. The risk measure 'Non FYT Indicator (NFI)' in a continuous FYT model measures the difference between the capital increase hoped for by the investor and the accumulated return flows of the asset over the investment period. The optimal capital investment shows the NFI result is zero.
SSRN
We propose a double Poisson claims reserving model with a flexible dispersion structure. The over-dispersed Poisson model is a special case of our proposed model. The maximum likelihood estimates (MLE) of mean coefficients and the residual maximum likelihood (REML) estimates of dispersion coefficients are obtained by the method of scoring. We derive the prediction error for both the incurred but not reported (IBNR) claims of each accident year and the total IBNR claims. By a quasi-likelihood approach, the proposed scoring method can be applied to non-integer or negative incremental claims. The empirical studies show that our proposed model provides a more reasonable result than the over-dispersed Poisson model.
SSRN
Using the daily frequency data for the period from August 9, 2015, to July 7, 2020, this paper re-examines the effects of the Economic Policy Uncertainty (EPU) on returns of four cryptocurrencies: Bitcoin, Ethereum, Litecoin, and Ripple. For this purpose, two new measures of the EPU (Twitter-based Economic Uncertainty and Twitter-based Market Uncertainty) are considered. The results from the Granger Causality test with the Recursive Evolving Window approach show that there is a significant causality from the Twitter-based EPU to the BTC/USD from October 2016 to July 2017. Besides, there is a significant causality from the EPU to the ETH/USD from June 2019 to February 2020, as well as from the EPU to the XRP/USD from January 2020 to February 2020. Mainly, the Twitter-based EPU measures positively affect the returns of related cryptocurrencies during these periods. These results are robust to consider different measures of the Twitter-based uncertainty as well as to apply different econometric techniques. Potential implications, including the COVID-19 era, are also discussed.
SSRN
This paper analyzes the Wirecard AG case from a digital finance perspective. The relatively low pace of digital transformation of financial supervisors and the high speed of advancements in technology increase the technological gaps between supervisors and their responsibility areas and result in a new phenomenon named âasymmetric technologyâ. This transition period's lagged and foggy atmosphere might be very conducive to potential white-collar fraudsters who plan to abuse their TECHs in Finance advantages. Fueled by inconsistent supervisory approaches, national protectionism in reaction to trade wars, fierce competitions among national economies, and unattractive yields at money markets, potential white-collar fraudsters come up with great opportunities to abuse FinTech related companies at capital markets. Therefore, the Wirecard AG case has multiple aspects and causes, not only one. Nevertheless, many aspects of todayâs financial sectors address new FinTech crises and FinTech related scandals, not only in one country but also in every economy, developing or developed ones. Therefore, governments and financial supervisors should brace for FinTech crises and financial scandals in the near future unless they meet structural reform and digital transformation requirements.
arXiv
We analyze social network data from Twitter to uncover early-warning signals of COVID-19 outbreaks in Europe in the winter season 2020, before the first public announcements of local sources of infection were made. We show evidence that unexpected levels of concerns about cases of pneumonia were raised across a number of European countries. Whistleblowing came primarily from the geographical regions that eventually turned out to be the key breeding grounds for infections. These findings point to the urgency of setting up an integrated digital surveillance system in which social media can help geo-localize chains of contagion that would otherwise proliferate almost completely undetected.
SSRN
We consider several economic uncertainty indicators for the United States and the UK before and during the COVID-19 pandemic: implied stock market volatility, newspaper-based economic policy uncertainty, twitter chatter about economic uncertainty, subjective uncertainty about future business growth, and disagreement among professional forecasters about future gross domestic product growth. Three results emerge. First, all indicators show huge uncertainty jumps in reaction to the pandemic and its economic fallout. Indeed, most indicators reach their highest values on record. Second, peak amplitudes differ greatlyâ"from an 80 percent rise (relative to January 2020) in two-year implied volatility on the S&P 500 to a 20-fold rise in forecaster disagreement about UK growth. Third, time paths also differ: implied volatility rose rapidly from late February and peaked in mid-March, falling back by late March as stock prices began to recover. In contrast, broader measures of uncertainty peaked later and then plateaued, as job losses mounted, highlighting the difference in uncertainty measures between Wall Street and Main Street.
SSRN
We provide a detailed holdings-based analysis of investment decisions made by U.S. equity SRI funds. Besides incorporating conventional fundamental factors, such as earnings growth, leverage, dividend yield, stock return and volatility, SRI funds adjust portfolio weights by considering companiesâ relative ESG performance. This holds for all categories of passively and actively managed funds, while for active funds ESG scores have a higher economic impact for value rather than growth funds. The timing of inclusion of companies in active SRI funds or their exclusion is driven primarily by fundamentals rather than by ESG performance. We find that both active SRI and matched conventional funds integrate ESG information as well as financial criteria in their investment decisions, but SRI portfolios exhibit higher average sustainability scores. Finally, we posit that SRI screening criteria effectively guide investment decisions, positive screening resulting in higher active portfolio weights of best performers in a corresponding ESG pillar.
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This paper studies exporting and innovative firms investment sensitivity to days receivable outstanding, days payable outstanding, and cash flow which are found to be financial factors determining financing constraints. We also advance and test the idea that export intensity and innovation intensity are driving channels of exporting and innovative firms investment potential sensitivity or non-sensitivity to financing constraints. Using Provence-Alpes Côte d'Azur firms level panel data collected between 2005-2014, we find that exporting firms investment is significantly and positively sensitive to cash flow and days receivable outstanding, while that of innovative firms is only significantly sensitive to cash flow. Although jointly export and innovation performances vanish firms investment sensitivity to financing constraints. Moreover, exporting firms export intensity is significantly and positively sensitive to days receivable outstanding while innovative firms innovation intensity is not significantly sensitive to financing constraints. Then, export intensity appears to be a driving channel for exporting firms investment sensitivity to days receivable outstanding while innovation intensity is not a driving channel for innovative firms investment sensitivity to cash flow.
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This study investigated the impact of financial sector development on domestic investment in selected Economic Community of West African States (ECOWAS) countries for the years 1985 to 2017. The study employed the Augmented Mean Group procedure which accounts for country specific heterogeneity and cross sectional dependence, and the Granger non-causality test robust to cross sectional dependence. The result reveals that (1) the impact of financial sector development on domestic investment depends on the measure of financial sector development utilized, (2) domestic credit to the private sector has a positive but insignificant impact on domestic investment in ECOWAS while banking inter-mediation efficiency (i.e. ability of the banks to transform deposits into credit) and broad money supply negatively and significant influence domestic investment, (3) cross country differences exist on the impact of financial sector development on domestic investment in the selected ECOWAS countries, and (4) domestic credit to the private sector Granger causes domestic investment in ECOWAS. The study recommends cautiousness in terms of the measure of financial development which is being utilized as a policy instrument to foster domestic investment as well as the importance of employing country-specific domestic investment policies in order to avoid blanket policy measures. Also, domestic credit to the private sector should be given priority when forecasting domestic investment into the future.
SSRN
The âCOVID Crisisâ has accelerated the mainstreaming of SDG-driven investment, with pension board members (trustees) playing an increasingly active role across all asset classes, from Sacramento to Sydney: governments (debt) and CEOs (equity) are having to commit more seriously to pressing environmental, social and societal matters, or face the risk of abrupt divestment (Brazil, Facebook etc.). Beyond financial economics and investment policy, the advent of fiduciary capitalism will have a profound impact on the way we govern our corporations and our nations.
arXiv
One of the impediments in advancing actuarial research and developing open source assets for insurance analytics is the lack of realistic publicly available datasets. In this work, we develop a workflow for synthesizing insurance datasets leveraging CTGAN, a recently proposed neural network architecture for generating tabular data. Applying the proposed workflow to publicly available data in the domains of general insurance pricing and life insurance shock lapse modeling, we evaluate the synthesized datasets from a few perspectives: machine learning efficacy, distributions of variables, and stability of model parameters. This workflow is implemented via an R interface to promote adoption by researchers and data owners.
SSRN
We examine the impact of the COVID-19 pandemic on firm borrowing behavior across 31 countries. We exploit the quasi-experimental properties of this pandemic to investigate how national culture, government preparedness, and response to the pandemic affect corporate borrowing and the structure of financial contracts. We find that firms increase their levels of bank and non-bank debt. Our findings show that firm-level characteristics such as financial flexibility, default risk, and size, along with national culture, government preparedness, and response to the pandemic are crucial determinants of corporate borrowing.
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Purpose â" This paper aims to define a methodology to assess the impact of introducing Islamic finance on financial inclusion.Design/methodology/approach â" The paper is based on a literature review to understand the link between Islamic finance and financial inclusion. The second part of the paper presents a conceptual framework to assess the impact of introducing Islamic finance on financial inclusion in a defined context based on the profiling of people interested in Islamic finance.Findings â" The paper brings an insight on the impact of introducing Islamic finance. Indeed, it could cause a financial migration to Islamic banks that can take many forms and depends on many factors that call for deep analysis.Research limitations/implications â" The paper would help financial authorities and financial institutions to measure the impact of introducing Islamic finance on their businesses and the stability of the whole system.Practical implications â" Islamic finance can not only enhance financial inclusion but also create financial migration. The two implications can vary from one context to another.Social implications â" Islamic finance can contribute in the effort of including âself-excludedâ people with religious concerns as well as people without access to financial services.Originality/value â" This paper promotes the idea that Islamic finance is not exclusively a way to enhance financial inclusion.
SSRN
Leveraged exchange-traded funds (LETFs) that allow investors to over-proportionally participate in abstract markets, such as indices, are studied in this paper. LETFs are found to suffer from a performance lag (negative alpha). The lag is categorized in three ways: fund management fees, compounding effects, and a leverage premium. The leverage premium effect intensified during the recent financial crisis (2008/09). In accordance with the approach put forward by Frazzini and Pedersen [2011], various market neutral long/short trading strategies which are sought to exploit the LETF premium are found to have delivered positive abnormal returns over the past years. While these strategies are not necessarily replicable, they teach us a lot about the relation between risk and expected return of LETFs in general.
SSRN
This Article argues that the frameworks put in place to allow for the orderly resolution of large financial institutions suffer from a liquidity problem. This is because post-crisis reforms enjoined central banks from providing liquidity to financial firms during and immediately after resolution. By creating a bright line rule, which essentially prohibited lender-of-last-resort (LOLR) operations once a firm enters resolution proceedings, there is a risk that short-term debt can no longer be rolled over, thereby increasing financial stability risks. As this Article shows, however, there are important differences between the United States (U.S.) and Europe. While the U.S. Congress at least sought to minimize liquidity gaps in resolution by throwing the fiscal firepower of the U.S.âs in the ring, European lawmakers failed to agree on a genuine, common backstop for the resolution of significant credit institutions, only leaving a small window for national solutions. To ensure that the core objectives of resolution, which include allocating losses to equity and long-term debt holders rather than to taxpayers, the central bank should be given a limited LOLR role to shore up the resolved firmâs funding. This LOLR function ought to be guaranteed by the fiscal authority, subject to ex-ante volume limits, and provide only short-term credit. Moreover, to further mitigate latent moral hazard risks and to create a counterweight to the extended LOLR function, the Article advocates for higher capital requirements.
arXiv
We consider a problem of finding an SSD-minimal quantile function subject to the mixture of multiple first-order stochastic dominance (FSD) and second-order stochastic dominance (SSD) constraints. The solution is explicitly worked out and has a closed relation to the Skorokhod problem. We then apply this result to solve an expenditure minimization problem with the mixture of an FSD constraint and an SSD constraint in financial economics.
SSRN
Motivated by the theory of demand-based option pricing in imperfect markets, we examine the relation between short-sale constraints and equity option returns, conditional on the level of mis-pricing in the underlying stock. We report a monotonic relation between various measures of short-sales constraints and delta-hedged returns of put options on overpriced stocks. This relation is robust to controls for firm attributes and limits to arbitrage proxies. Our findings suggest that while investors drive up the demand for these put options, dealers command a high premium as compensation for the increased market making risk. We do not find a robust relation for either put options on under-priced stocks or call options.
SSRN
Using the introduction of high-speed rail (HSR) as an exogenous shock to costs of information acquisition, we show that reductions in information-acquisition costs lead to (i) a significant increase in information production, evidenced by a higher frequency of analysts visiting portfolio firms, and (ii) improvement in output quality, manifested in higher forecast accuracy and better recommendations. Increases in the difficulty in visiting a firm without HSR and in the importance of soft information lead to these effects becoming more pronounced. Importantly, more information production is also associated with improved price efficiency. We corroborate these findings using a large-scale survey of financial analysts. Finally, both the empirical and survey results highlight the importance of soft information in analystsâ unique-information production.
SSRN
German abstract: GAUà und LEGENDRE entwickelten Ende des 18. Jahrhundert die Methode der kleinsten Quadratfehler und legten den Grundstein für Regression. MARKOWITZ untersuchte in den 1950er Jahren das Zusam-menwirken einzelner Güter im Portfolio und minimierte im Rahmen der Modernen Portfoliotheorie prio-risiert Risiko in Form der Volatilität zur erwarteten Rendite. SHARPE, LINTNER und MOSSIN etablierten in den 1960er Jahren das Capital Asset Pricing Modell. ROSS schrieb in den 1970er Jahren mit dem linea-ren Multifaktormodell Geschichte, das insbesondere FAMA, FRENCH und CARHART in den 1990er Jah-ren, zuletzt im Jahr 2015 mit dem 5-Faktor-Modell, konkretisierten. Da Volatilität nicht allein für Risiko steht, untersuche ich weitere Risikomerkmale: (1) die ganzzeitliche Abweichung erwarteter gegenüber angebotenen Kapitalrückflüssen über die Investitionszeit sowie (2) die Einflüsse-Intensität einzelner, als auch Gruppenvariablen auf Güter-Ebene auf Rendite der Kapitalgeber mit âGeneralized Additive Related Modellâ Regressionen. Die Portfolioanalyse heterogener Güter zum Modell âFuture Yield after Taxesâ in modifizierter Form des Baldwin-Zinses optimiert robuste Allokation.English abstract: At the end of the 18th century GAUà and LEGENDRE developed the method of the smallest square errors and laid the foundation for regression. MARKOWITZ examined the interaction of individual assets in the portfolio in the 1950s and, within the Modern Portfolio Theory, minimized risk in form of volatility to the expected return. SHARPE, LINTNER and MOSSIN established the Capital Asset Pricing Model in the 1960s. ROSS made history in the 1970s with the linear multifactor model, which FAMA, FRENCH and CARHART concretized in the 1990s especially, last modified in 2015 with the 5-factor model. Since volatility does not stand for risk alone, I examine further risk characteristics: (1) the full-time deviation of expected capital returns compared to the offered return of capital over the investment period, and (2) the influence intensity of individual as well as group variables at assets level on the return of the investor with 'Generalized' Additive Related Model 'regressions. The portfolio analysis of heterogeneous assets using the 'Future Yield after Taxes' model in a modified form of the Baldwin interest rate optimizes robust allocation.
arXiv
In this paper, we introduce and develop the theory of semimartingale optimal transport in a path dependent setting. Instead of the classical constraints on marginal distributions, we consider a general framework of path dependent constraints. Duality results are established, representing the solution in terms of path dependent partial differential equations (PPDEs). Moreover, we provide a dimension reduction result based on the new notion of "semifiltrations", which identifies appropriate Markovian state variables based on the constraints and the cost function. Our technique is then applied to the exact calibration of volatility models to the prices of general path dependent derivatives.
SSRN
Using novel data on firmsâ government relations staff, and two distinct empirical settings, we show that political activism enables firms to grow their market power. The documented increases in profit margins and market share persist for up to two years, and are concentrated among large politically active firms. We also utilize firmsâ mandatory lobbying disclosures to identify a broad set of legislative actions lobbied for by sample firms, and analyze their strategic actions around those events. Taken together, our results show that politically active firms gain a competitive advantage through strategically timed investments when policy uncertainty is high.
SSRN
We introduce a model for portfolio selection with an extendable investment universe where the agent faces a trade-off between exploiting existing and exploring for new investment opportunities. An agent with mean-variance preferences starts with an existing investment universe consisting of a risk-free and a number of risky assets. However, rather than being limited to these assets, the agent has the option to devote a part of his/her wealth for exploring new investment opportunities. If this option is exercised, a new risky asset is discovered and the agent subsequently invests in the extended universe. We show that the problem is well-posed when the Sharpe ratio of the newly discovered asset has reasonably asymptotic elasticity, and determine an equation characterizing the optimal amount devoted to exploration. We determine that incremental exploration does not pay off: one must put a significant amount at risk in order to harvest the potential benefits of exploring for new investment opportunities. We further find that the investment performance as measured by the Sharpe ratio is increasing in the initial wealth of the agent indicating that richer agents can make better use of new investment opportunities.
SSRN
We consider a market where traders have asymmetric information regarding the distribution of asset return and study price discovery of derivatives. The informed trader has private information regarding arbitrary higher moments of asset return, such as volatility or skewness, and exploits her private information by trading a complete menu of options. The equilibrium trading strategies of the informed agent in our model reflect those used by traders in the market when trying to exploit higher order moment information, such as the volatility straddle.
SSRN
We propose a new asset-pricing framework in which all securitiesâ signals are used to predict each individual return. While the literature focuses on each securityâs own- signal predictability, assuming an equal strength across securities, our framework is flexible and includes cross-predictabilityâ"leading to three main results. First, we derive the optimal strategy in closed form. It consists of eigenvectors of a âprediction matrix,â which we call âprincipal portfolios.â Second, we decompose the problem into alpha and beta, yielding optimal strategies with, respectively, zero and positive factor exposure. Third, we provide a new test of asset pricing models. Empirically, principal portfolios deliver significant out-of-sample alphas to standard factors in several data sets.
SSRN
The U.S. Consumer Financial Protection Bureau has accepted complaints about banksâ financial products and services since 2011 and has released the complaint database to the public since 2013. We analyze the effectiveness of this public disclosure in protecting mortgage borrowers. We find a greater reduction in mortgage applications to banks that receive more mortgage complaints in local markets after the disclosure. The effect is stronger in areas with more sophisticated consumers and higher credit competition, and for banks receiving more severe complaints. The number of monthly mortgage complaints per bank exhibits faster mean reversion after the publication of the database. Our findings suggest that the public disclosure of banksâ provision of inferior products and services enhances product market discipline and consumer financial protection.
arXiv
In this paper, we investigate whether mixing cryptocurrencies to a German investor portfolio improves portfolio diversification. We analyse this research question by applying a (mean variance) portfolio analysis using a toolbox consisting of (i) the comparison of descriptive statistics, (ii) graphical methods and (iii) econometric spanning tests. In contrast to most of the former studies we use a (broad) customized, Equally-Weighted Cryptocurrency Index (EWCI) to capture the average development of a whole ex ante defined cryptocurrency universe and to mitigate possible survivorship biases in the data. According to Glas/Poddig (2018), this bias could have led to misleading results in some already existing studies. We find that cryptocurrencies can improve portfolio diversification in a few of the analyzed windows from our dataset (consisting of weekly observations from 2014-01-01 to 2019-05-31). However, we cannot confirm this pattern as the normal case. By including cryptocurrencies in their portfolios, investors predominantly cannot reach a significantly higher efficient frontier. These results also hold, if the non-normality of cryptocurrency returns is considered. Moreover, we control for changes of the results, if transaction costs/illiquidities on the cryptocurrency market are additionally considered.
SSRN
In this study, we examine how banksâ stock price crash risk is affected by recourse uncertainty embedded in securitizations. By recourse uncertainty, we mean the difficulty for equity market participants to assess the true extent of risk transfer between securitizing banks and investors in asset-backed securities due to the opacity of securitizations. We argue that this uncertainty facilitates the withholding and accumulation of negative recourse news that is subsequently released at once, resulting in crashes. Using a sample of U.S. bank holding companies for the period of 2002-2015, we find that recourse uncertainty is positively associated with the future crash risk of securitizing banks. The result holds after controlling for bank intrinsic risk. We also predict and find that this association is higher for banks with poorer information environment and for the period before the adoption of SFAS 166/167, which required enhanced disclosure about securitization activities.
SSRN
Should legislation ban the negotiated sales of municipal bonds? What are the costs of forcing public auctions? We compare the offering yields of local governments that are forced by state law to use public auctions to the offering yields of local governments that can choose between auctions and negotiated sales. Using a sample of 369,482 school bonds issued between 2004 and 2014, we find that a restriction on negotiated sales has a negative cost instead of positive. The prohibition benefits issuers on average. The offering yields of constrained issuers are 17 basis points lower than the offering yields of unconstrained issuers. The effect is equivalent to a rating upgrade from non-rated to AA-. Nevertheless, most issuers prefer to use negotiated sales even if they do not maximize bond proceeds.
SSRN
Using unique City of Oakland data during COVID-19, we document that small business survival capabilities vary by firm size as a function of revenue resiliency, labor flexibility, and committed costs. Nonemployer businesses rely on low cost structures to survive 73% declines in own-store foot traffic. Microbusinesses (1-to-5 employees) depend on 14% greater revenue resiliency. Enterprises (6-to-50 employees) have twice-as-much labor flexibility, but face 11%-to-22% higher residual closure risk from committed costs. Finally, inconsistent with the spirit of Chetty-Friedman-Hendren-Sterner (2020) and Granja-Makridis-Yannelis-Zwick (2020), PPP application success increased medium-run survival probability by 20.5%, but only for microbusinesses, arguing for size-targeting of policies.
arXiv
Interactive simulation toolkits come in handy when teaching macroeconomic models by facilitating an easy understanding of underlying economic concepts and offering an intuitive approach to the models' comparative statics. Based on the example of the IS-LM model, this paper demonstrates innovative browser-based features well-suited for the shift in education to online platforms accelerated by COVID-19. The free and open-source code can be found alongside the standalone HTML files for the AD-AS and the Solow growth model at https://gitlab.tu-berlin.de/chair-of-macroeconomics/.
SSRN
Stock price multiple is one of the most well-known equity valuation technique used to forecast equity price. It measures by multiplying âthe ratio of stock price to a value driverâ by a value driver. The value driver can be earning per share (EPS), sales or other financial measurements. The objective of price multiple technique is to evaluate the value of assets and compare how similar assets are priced in the market. Although stock price multiple technique is common in financial filed, studies on the application of the technique in Thailand is still limited. The present study is conducted to serve three major objectives. The first objective is to apply the technique to measure value of firms in banking sector in the Stock Exchange of Thailand. The second objective is to develop composite price multiple index to forecast equity prices. The third objective is to compare valuation accuracy of different value drivers of price multiple (i.e. EPS, Earnings Growth, Earnings Before Interest Taxes Depreciation and Amortization, Sales, Book Value and Composite Index) in forecasting equity prices. Results indicated that EPS is the most accurate value drivers of price multiple used to forecast equity price of firms in baking sector.
SSRN
This paper provides a comparison of the effects of economic uncertainty and geopolitical risks on bank credit growth. We use the World Uncertainty Index (WUI) proposed by Ahir et al. (2018) and Geopolitical Risk Index (GPR) introduced by Caldara & Iacoviello (2018) for the measures of economic uncertainty and geopolitical risks, respectively. Our sample is composed of 2,439 banks from 19 emerging economies for the period of 2010-2019. By using fixed effects and dynamic panel data estimation techniques with GMM estimators, we find that economic uncertainty causes a decrease in overall bank credit growth while no effect of geopolitical risks is documented. Further analysis on the growth of different loan types (consumer, corporate, and mortgage) shows that economic uncertainty hampers the growth of all loan types considered in the paper however, the highest impact is observed on corporate loans. Meanwhile, geopolitical risk dampens consumer and mortgage loans but not corporate loans. Additional analyses on bank ownership and heterogeneity imply that the credit behavior of (1) foreign banks, (2) publicly listed banks, and (3) banks with foreign subsidiaries are immune to economic uncertainties.
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The objective of this paper is to examine the relationship between bank characteristics,in particular value, performance and volatility of bank stock returns, and its exposure to ï¬nancial derivative contracts. The study is based on 109 publicly traded European banks over the period from 2005 to 2010. The database contains both accounting data from Bankscope and manually collected information from the notes to ï¬nancial statements. After controlling for bank-speciï¬c characteristics, time effects and cross-country differences, we ï¬nd that banks efï¬ciently using hedging derivatives have a lower risk and a higher value. However, this relationship becomes less pronounced or is inverse in the post-crisis period and concerns both trading and hedging derivatives.For systemically important banks heavily involved in derivatives, market volatility of stock returns is higher and valuations are lower. We notice, however, that derivatives play second ï¬ddle to bank risk and performance. Our ï¬ndings corroborate the importance of distinction of derivatives by the purpose of use, which becomes less obvious for investors in the post-crisis period. Our results have important policy implications, especially in the light of the recent debate over the necessity of separation of risky banking activities from commercial bank branches (for instance, as proposed in Liikanen report) in an attempt to reduce systemic risk. We emphasise the need for a higher transparency of disclosures regarding hedge accounting and harmonisation of reporting formats across EU.
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This document details the construct validation procedures conducted for the textual measure of the Organizational Culture Assessment Instrument (OCAI), which is used to measure firm-level organizational culture.
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This paper investigates the role of institutional infrastructures in the financial inclusion-growth nexus for a panel of twenty countries in sub-Sahara Africa (SSA).Employing the System Generalized Method of Moments (GMM), the following insightful outcomes are established. First, while there is an unrestricted positive impact of physical access to ATMs and ICT measures of financial inclusion on SSAâs growth but only the former was found significant. Second, the four institutional components via economic, political, institutional and general governances were also found to be growth-spurring. Lastly, countries with low levels of real per capita income are matching up with other countries with high levels of real income per capita. The empirical evidence of some negative net effects and insignificant marginal impacts are indication that imperfections in the financial markets are sometimes employed to the disadvantage of the poor. On the whole, we established positive effects on growth for the most part. The positive effects are evident because the governance indicators compliment financial inclusion in reducing pecuniary constraints hindering credit access and allocation to the poor that deteriorate growth.
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Whereas the callable-bond market used to emphasize primarily public debt - Government Agencies, and both investment grade and non-investment corporate debt - that has changed dramatically over the past twenty years, in part due to the low prevailing rates of interest as well as some systematic changes in the Agency sector. While some Agency and investment grade corporate bonds are still extant, there are more numerous callable bonds of lower ratings categories. In delivering a theoretically-sound practical model, one that does not call for computation or use of an "option-adjusted spread" (OAS), this paper seeks to use a one-factor LogNormal interest-rate model to calibrate the implied-vols of callable and putable bonds in the U. S. bond market, and to relate those implied volatilities to measures of time to call, time from call to maturity, moneyness and the credit-yield spread.