Research articles for the 2020-07-14
arXiv
Generalizing earlier works of Delbaen & Haezendonck [5] as well as [18] and [16] for given compound mixed renewal process S under a probability measure P, we characterize all those probability measures Q on the domain of P such that Q and P are progressively equivalent and S remains a compound mixed renewal process under Q with improved properties. As a consequence, we prove that any compound mixed renewal process can be converted into a compound mixed Poisson process through a change of measures. Applications related to the ruin problem and to the computation of premium calculation principles in an insurance market without arbitrage opportunities are discussed in [26] and [27], respectively.
arXiv
Credit ratings are one of the primary keys that reflect the level of riskiness and reliability of corporations to meet their financial obligations. Rating agencies tend to take extended periods of time to provide new ratings and update older ones. Therefore, credit scoring assessments using artificial intelligence has gained a lot of interest in recent years. Successful machine learning methods can provide rapid analysis of credit scores while updating older ones on a daily time scale. Related studies have shown that neural networks and support vector machines outperform other techniques by providing better prediction accuracy. The purpose of this paper is two fold. First, we provide a survey and a comparative analysis of results from literature applying machine learning techniques to predict credit rating. Second, we apply ourselves four machine learning techniques deemed useful from previous studies (Bagged Decision Trees, Random Forest, Support Vector Machine and Multilayer Perceptron) to the same datasets. We evaluate the results using a 10-fold cross validation technique. The results of the experiment for the datasets chosen show superior performance for decision tree based models. In addition to the conventional accuracy measure of classifiers, we introduce a measure of accuracy based on notches called "Notch Distance" to analyze the performance of the above classifiers in the specific context of credit rating. This measure tells us how far the predictions are from the true ratings. We further compare the performance of three major rating agencies, Standard $\&$ Poors, Moody's and Fitch where we show that the difference in their ratings is comparable with the decision tree prediction versus the actual rating on the test dataset.
SSRN
This paper studies how a bank regulatorâs aggregate and bank-specific information dis-closure policy affects social welfare. We apply global games to studying an economy where depositors, with strategic complementarities among them, face uncertainties about both aggregate and bank-specific information of a bank. Then we examine how disclosure policy of a bank regulator on the bankâs aggregate and bank-specific information affects welfare. With the assumption that bank depositors rely on the bank regulator to collect aggregate bank performance information but have precise private information about bank-specific in-formation, we find that more precise aggregate information disclosed by the bank regulator improves welfare when bank fundamentals are either extremely strong or weak, but tends to reduce welfare when the fundamentals are in the intermediate range where coordination plays a key role. In contrast, more precise bank-specific information disclosed by the regulator tends to increase welfare, even when the fundamentals are in the intermediate range.
arXiv
Volatility is a key variable in option pricing, trading and hedging strategies. The purpose of this paper is to improve the accuracy of forecasting implied volatility using an extension of genetic programming (GP) by means of dynamic training-subset selection methods. These methods manipulate the training data in order to improve the out of sample patterns fitting. When applied with the static subset selection method using a single training data sample, GP could generate forecasting models which are not adapted to some out of sample fitness cases. In order to improve the predictive accuracy of generated GP patterns, dynamic subset selection methods are introduced to the GP algorithm allowing a regular change of the training sample during evolution. Four dynamic training-subset selection methods are proposed based on random, sequential or adaptive subset selection. The latest approach uses an adaptive subset weight measuring the sample difficulty according to the fitness cases errors. Using real data from SP500 index options, these techniques are compared to the static subset selection method. Based on MSE total and percentage of non fitted observations, results show that the dynamic approach improves the forecasting performance of the generated GP models, specially those obtained from the adaptive random training subset selection method applied to the whole set of training samples.
SSRN
Studies document an unexplained wage gap between male and female workers even as female workers have increased their human capital through skill and education. At the executive level, where skill and education are similar, the results on gender-based pay gap persist and are primarily attributed to career interruptions and differences in risk preferences. Tracing the compensation contracts of Execucomp firms (1992-2018), this study observes a nonexistent gap in compensation between genders among CFOs. In fact, female CFOs earn more than male CFOs in the later sample years. This paper offers several explanations for this phenomenon e.g. new evidence on risk preferences of females with financial expertise and changes in the social and regulatory climate.
SSRN
Assessing dependence within extreme co-movements of financial instruments has been of much interest in risk management. Typically, indices of tail dependence are used to quantify the strength of such dependence, although many of the indices that we find in the literature underreport the strength due to equal treatment of the instruments in the tail of their loss distributions. When this becomes an issue, we advocate the use of a procedure designed to estimate the maximal strength of dependence that can possibly occur among the co-movements. We illustrate the performance of the procedure and its implementation using simulated and real data-sets. Detailed analyses of foreign currency exchange rates, stock market indices, and treasury notes are given.
SSRN
Asset heterogeneity is widely believed to hurt the liquidity in markets of many important fixed-income assets such as corporate and municipal bonds. We develop a model in which heterogeneous assets are traded with search friction to study the impact of a quasi-consolidated (QC) trading design in which a cohort of heterogeneous assets are sold at the same price. In the model, asset heterogeneity results in market fragmentation and exacerbates search frictions, thereby undermining market liquidity. We show that QC trading reduces market fragmentation and improves the overall market liquidity by pooling multiple sellers and buyers together. Nevertheless, because of asset heterogeneity, QC trading in general hurts some traders and cannot fully eliminate market fragmentation. Integrating QC contracts for multiple types of assets improves (hurts) overall market liquidity when these types of assets differ slightly (significantly) in value distribution.
SSRN
This paper documents a negative cross-transmission of bank-idiosyncratic credit risk events to the equity value of peers comprising other banks, insurance and real estate firms inter alia. Large jumps in the idiosyncratic component of bank CDS spreads significantly reduce the equity value of peers, particularly on the event day. The negative externality does not hinge on the âinformation connectednessâ between the two entities as proxied by characteristics such as common core line of business, common country or region, and inter-country common legal tradition. The negative externality is stronger in turmoil market conditions when risk-aversion levels are higher and/or investors are subject to pessimism. The more fragile the risk profile of the event bank and peer firm prior to the event the stronger the cross-transmission. The findings lend support to the wake-up call paradigm at micro level, and are insightful towards a better assessment of the vulnerability of the financial system.
RePEC
We study the impact of disclosure about bank fundamentals on depositors' behavior in the presence (and absence) of economic linkages between financial institutions. Using a controlled laboratory environment, we identify under which conditions disclosure is conducive to bank stability. We find that bank deposits are sensitive to perceived bank performance. While banks with strong fundamentals benefit from more precise disclosure, an opposing effect is present for solvent banks with weaker fundamentals. Depositors take information about economic linkages into account and correctly identify when disclosure about one institution conveys meaningful information for others. Our findings highlight both the costs and benefits of bank transparency and suggest that disclosure is not always stability enhancing.
SSRN
We investigate firm-level determinants of capital structure using a large sample of 4,284 Japanese firms over a nineteen-year period (i.e., over 61,000 firm-year observations), a hitherto less examined sample for this purpose. We conduct our analysis and interpret our findings predominantly within the pecking order, the trade-off and the agency theoretical frameworks. We uncover three new findings. First, our evidence indicates that insights derived from the extant literature on capital structure are cross-national and are applicable in the context of Japan, despite the unique characteristics of Japanese firms. Second, financial crisis significantly impacts the relationship between leverage and firm-level determinants, particularly accentuating the effect of asset tangibility and growth. Third, product market competition significantly impacts the observed relationship between firm-level determinants and leverage. Our results are robust, controlling for the joint effects of competition and crisis.
SSRN
The purpose of this paper is to propose a collaborative value chain financing (CVCF) approach whereby the manufacturer/supplier, bank, and SME/buyer collaborate for their mutual benefit. Under the CVCF approach, all parties involved in the transaction engage in risk-taking. The supplier provides the necessary materials to the SME for sale or further value addition while the bank evaluates and monitors credit risk. The trilateral risk-sharing aids in better working capital management, higher turnover for suppliers, and lower default risk for the bank. Currently, a lack of trust between those involved in the value chain results in high financing costs to SMEs due to expected default risk and lower turnover for suppliers in the value chain. We present a CVCF model with a zero percent financing/mark-up rate based on the practice of a steel company listed on the Saudi Arabian stock exchange.
SSRN
A considerable amount of accounting, economics and finance studies have investigated the link between corporate governance (CG) and performance in profit and non-profit organisations. This paper departs from the existing literature by investigating the relationship between CG structures and both financial performance (FP, measured as return on assets (ROA) and equity (ROE)) and non-financial performance, measured as league points won (NFP-Points), of sports organisations with specific focus on UK premier leaguesâ football (soccer) teams.We collect data relating to CG structures, FP and NFP-Points of football clubs playing in the four UK premier leagues in England, Northern Ireland, Scotland and Wales along with the English Championship teams over the 2011-2016 period. We analyse our data relating to 80 football clubs over a 6-year period (generating 397 club-year observations) by running a number of multivariate analyses to test our hypotheses. Our findings are as follows. First, we find that NFP-Points is higher in clubs with larger boards, non-executive directors (NED), CEO role duality, and higher percentage of foreign and/or younger directors, but lower in firms with higher percentage of female directors. Second and by contrast, we find that the relationship between these same set of variables and FP is, however, insignificant except for boards with NED that remained significant and negatively related to ROA. Our findings appear to reflect the prioritisation of on-the-field performance over off-the-field performance by sports organisations. Our evidence is largely robust to using alternative measures and estimation models.
SSRN
The development of credit information sharing schemes in developing countries has gained significant attention in recent times along with ongoing financial sector reforms. In this paper, we provide first-hand evidence of the effect of credit information sharing on credit intermediation cost in these countries, and consequently ascertain the extent to which the credit information sharingâ"credit intermediation cost nexus may be accentuated by banking market concentration and governance quality. Using a large dataset covering 272 banks from 27 African countries over the 2004-2012 period, we uncover four new findings. First, we find that credit information sharing does reduce credit intermediation cost. Second, we show that the relationship between credit intermediation cost and credit information sharing is conditional on banking market concentration. Third, our findings suggest that governance quality moderates the effect of credit information sharing on credit intermediation cost. Finally, we find that banking market concentration reduces credit intermediation cost, but the effect is moderated by credit information sharing. Overall, our findings suggest that credit information sharing may serve as a useful policy tool for achieving financial sector stability in developing countries.
SSRN
We provide new empirical evidence on the implications of public information arrival for investors' beliefs, using a daily measure of dispersion (uncertainty) of beliefs about firm underlying return distribution. Consistent with convergence in beliefs (less disagreement), the arrival of public firm-specific information reduces beliefs dispersion. The effect is stronger for events that are salient, have media coverage, and attract institutional investors' attention. The effect of macroeconomic announcements is weaker than the effect of firm-specific events. In contrast, events involving frictions between firm stakeholders increase beliefs dispersion.
arXiv
Education has traditionally been classroom-oriented with a gradual growth of online courses in recent times. However, the outbreak of the COVID-19 pandemic has dramatically accelerated the shift to online classes. Associated with this learning format is the question: what do people think about the educational value of an online course compared to a course taken in-person in a classroom? This paper addresses the question and presents a Bayesian quantile analysis of public opinion using a nationally representative survey data from the United States. Our findings show that previous participation in online courses and full-time employment status favor the educational value of online courses. We also find that the older demographic and females have a greater propensity for online education. In contrast, highly educated individuals have a lower willingness towards online education vis-\`a-vis traditional classes. Besides, covariate effects show heterogeneity across quantiles which cannot be captured using probit or logit models.
arXiv
Higher life expectancy and rapidly aging populations in developing countries, especially in the last three decades, have created the need for policymakers to introduce pension programs in developing countries. China launched the New Rural Pension Scheme (NRPS) in 2009 to ease internal demographic pressures and concerns about old-age poverty. Using data from the introduction of the NRPS in China, we estimate the effects of pension benefits, due to participation in the NRPS, on individual cognition, measured by episodic memory and intact mental status, among individuals aged 60 and above. We find large negative effects of the provision of pension benefits on cognitive functioning among the elderly. We detect the most substantial impact of the program to be on delayed recall, a measure implicated in neurobiological research as a significant predictor of the onset of dementia. We show suggestive evidence that the program leads to stronger negative impacts among the female sample. Our findings support the mental retirement hypothesis, that decreased mental activity results in atrophy of cognitive skills. We show that retirement plays a significant role in explaining cognitive decline at older ages.
SSRN
New technology promises to expand the supply of financial services to borrowers poorly served by the banking system. Does it succeed? We study the response of FinTech and nonbank lenders to financial services demand created by the introduction of the Paycheck Protection Program (PPP). Online banks and nonbank financial institutions are disproportionately used in ZIP codes located with fewer bank branches, and in industries with little ex ante small-business lending. Their role in filling this lending gap is also magnified in counties where the economic effects of the COVID-19 pandemic were greater. Using the predicted responsiveness of banks to the program, we show that borrowers were more likely to get a FinTech-enabled loan if they are located in ZIP codes where local banks were unlikely to originate PPP loans.
arXiv
We perform a large scale analysis of a list of fintech terms in (i) news and blogs in English language and (ii) professional descriptions of companies operating in many countries. The occurrence and co-occurrence of fintech terms and locutions shows a progressive evolution of the list of fintech terms in a compact and coherent set of terms used worldwide to describe fintech business activities. By using methods of complex networks that are specifically designed to deal with heterogeneous systems, our analysis of a large set of professional descriptions of companies shows that companies having fintech terms in their description present over-expressions of specific attributes of country, municipality, and economic sector. By using the approach of statistically validated networks, we detect geographical and economic over-expressions of a set of companies related to the multi-industry, geographically and economically distributed fintech movement.
arXiv
In the presence of monotone information, stochastic Thiele equations describing the dynamics of state-wise prospective reserves are closely related to the classic martingale representation theorem. When the information utilized by the insurer is non-monotone, classic martingale theory does not apply. By taking an infinitesimal approach, we derive generalized stochastic Thiele equations that allow for information discarding. The results and their implication in practice are illustrated via examples where information is discarded upon and after stochastic retirement.
arXiv
We study the value and the optimal strategies for a two-player zero-sum optimal stopping game with incomplete and asymmetric information. In our Bayesian set-up, the drift of the underlying diffusion process is unknown to one player (incomplete information feature), but known to the other one (asymmetric information feature). We formulate the problem and reduce it to a fully Markovian setup where the uninformed player optimises over stopping times and the informed one uses randomised stopping times in order to hide their informational advantage. Then we provide a general verification result which allows us to find the value of the game and players' optimal strategies by solving suitable quasi-variational inequalities with some non-standard constraints. Finally, we study an example with linear payoffs, in which an explicit solution of the corresponding quasi-variational inequalities can be obtained.
SSRN
We examine the effect of economic policy uncertainty (EPU) on the dynamics of the capital structure for U.S.-listed firms from 1985 to 2017. EPU has a negative and significant effect on the firms' speed of capital structure adjustment. EPU tends to increase the cost of external financing and reduce manager sentiment. Besides, the effect is only pronounced for under-levered firms, especially during high EPU period. Further analyses show that the effect is pronounced in firms with high financial constraints and asset specificity. Our findings highlight the important role of EPU in the capital structure dynamics of firms.
SSRN
We investigate the effect of line-of-business diversification on asset risk-taking in the U.S. property-liability industry. The coordinated risk management hypothesis (Schrand and Unal, 1998) implies a negative relation between underwriting risk and investment risk. Consistent with this hypothesis we find that diversified insurers take more asset risk than non-diversified insurers, and that the degree of asset risk-taking is positively related to diversification extent. Our results are robust to corrections for potential endogeneity bias, selectivity bias, and alternative diversification and asset risk measures. We also provide event study evidence that further supports the coordinated risk management hypothesis. Specifically, we find that when a focused firm diversifies, it increases its asset risk relative to firms that remain focused, and when a diversified firm refocuses, it reduces its asset risk relative to firms that remain diversified.
SSRN
This paper investigates how economic policy uncertainty and ownership structure affect the decisions of US firms to raise capital. We use a three-step sequential framework involving the decisions to raise capital and, depending on the decision to raise capital, the choice of financing instrument, and the volume of capital. The simultaneous equation framework not only treats the three decisions sequentially but also removes endogenous selection bias. By using a sample of 45,635 firm-year records of publicly listed non-financial firms for the period starting from 2000 to the end of 2018, we find that during periods of higher economic policy uncertainty, firms engage in external financing more frequently with a preference toward debt-based instruments. In addition, ownership by institutional investors is associated with a tendency to raise capital through debt financing and in lower volumes, supporting ownership control hypothesis. Our results from economic policy uncertainty provide evidence of pecking order theory and market timing theory in raising capital.
arXiv
We experimentally evaluate the comparative performance of the winner-bid, average-bid, and loser-bid auctions for the dissolution of a partnership. The analysis of these auctions based on the empirical equilibrium refinement of Velez and Brown (2020) arXiv:1907.12408 reveals that as long as behavior satisfies weak payoff monotonicity, winner-bid and loser-bid auctions necessarily exhibit a form of bias when empirical distributions of play approximate best responses (Velez and Brown, 2020 arXiv:1905.08234). We find support for both weak payoff monotonicity and the form of bias predicted by the theory for these two auctions. Consistently with the theory, the average-bid auction does not exhibit this form of bias. It has lower efficiency that the winner-bid auction, however.
SSRN
How do firms manage their operational leverage? We study this question in the context of U.S. multinationals facing changes to foreign labor market protection laws. We find that U.S. firms facing higher labor protection in foreign countries are more likely to replace their integrated business relations with arm's-length relations in those nations. This is consistent with the idea that when firms find it harder to terminate their workers in integrated operations, they change their operating model to one where it is easier to replace or discontinue business partners instead of employees. We also find that when foreign labor protection increases, firms are more likely to reshore their operations, face increased competition in foreign countries, and reduce their overall capital expenditures. However, they do not adjust their financial leverage in response. Our findings showcase that firms offset the inflexibility from rigid labor market regulations by restructuring their real-side operations.
SSRN
We introduce an approach to forecast individual bond liquidity and apply it to the U.S. corporate bond market. Our model combines three dynamic prediction models to get the most accurate estimate for future bond liquidity. We compare the new prediction methodology with the literatureâs current approach to use a bondâs liquidity of today as the best estimate for its liquidity tomorrow. Our approach generates significantly lower forecasting errors and is much better able to capture the premium for expected liquidity in bond yields. We provide evidence that investors in corporate bond funds actively anticipate liquidity deterioration in underperforming funds and sell their shares in advance to secure a first-mover advantage.
SSRN
Capital mobilization is a traditional business of commercial banks and is one of the core foundations for the development of a bank. Capital mobilization is the main input in the operation of a bank, and this is also the basis for generating output for credit activities as well as other banking activities. This study aims to determine the main factors that affect the decisions of individual customers to put savings deposit in Vietnamese commercial banks. Survey data collected from 403 individual customers were analyzed to provide evidence. The results from the multiple regression analysis by using SPSS software revealed that all scales in this study were reliable, and there were six components impacting the savings deposit decision of individual customers from the strongest to the weakest in the following order: the form of promotion, bank brand, service quality, interest rate policy, and employee knowledge and attitude. Besides, the finding showed customers who have high income tend to have a stronger decision on savings deposits in commercial banks. The main findings of this article provide some empirical implications for marketers in banks and serve as a suggestion to improve these factors in order to retain and attract individual customersâ savings deposit decisions.
SSRN
I discover that investors' preferences for gambling mainly involve stocks that have performed poorly in the past three months, as lottery-like stocks with poor performance are much more likely to generate large payoffs than those with good performance (61.53% vs. 40.17%). Furthermore, lotto investors tend to believe that lottery-like stocks with poor performance may have a vigorous rebound shortly, while those with good performance may be less likely to produce a highly positive return given their high prices. Therefore, lottery-like stocks with poor performance have a highly effective lottery-like look, and thus they attract lotto investors. On the other hand, loser stocks without lottery-like features may continue to perform poorly. Overly optimistic (pessimistic) beliefs about stocks with (without) lottery-like features result in a pronounced lottery premium among loser stocks.
SSRN
We describe general multilevel Monte Carlo methods that estimate the price of an Asian option monitored at m fixed dates. For a variety of processes that can be simulated exactly, we prove that, for the same computational cost, our method yields an unbiased estimator with variance lower than the variance of the standard Monte Carlo estimator by a factor of order m. We show how to combine our approach with the Milstein scheme for processes driven by scalar stochastic differential equations, and with the Euler scheme for processes driven by multidimensional stochastic differential equations. Numerical experiments confirm that our method outperforms the conventional Monte Carlo algorithm by a factor proportional to m.
SSRN
French Abstract: Après avoir présenté les grands indicateurs environnementaux existants et leurs limites, nous proposons une définition des caractéristiques dâun indicateur pertinent et efficace dans une approche holistique : embrassant lâensemble des enjeux environnementaux, analysant le cycle de vie complet, utilisant des mesures physiques, portant sur un périmètre dâanalyse mondial, pouvant être calculé sur les différentes classes dâactifs, étant modulable, opérationnel, lisible, neutre, transparent, stable dans le temps et utilisant les informations déjà disponibles compte tenu de lâurgence environnementale. Nous rappelons enfin les principales méthodes dâagrégation dâindicateurs environnementaux et présentons leurs avantages et inconvénients.English Abstract: After presenting the main existing environmental indicators and their limitations, we propose a definition of the (non-exhaustive) characteristics of a relevant and efficient metric in a holistic approach: encompassing all environmental issues, analyzing the entire life cycle, using physical measures, covering a global scope of analysis, being computable across all asset classes, being modular, operational, readable, neutral, transparent, stable over time and using the information already available, given the environmental emergency. Finally, we review the main available methods for aggregating environmental indicators with their advantages and drawbacks.
SSRN
Usually screening in microcredit is a very opaque process, because borrowers seldom have verifiable information or collateral. We explore the relationship between traditional screening variables and a new screening variable (Job Experience) for a Brazilian fintech microcredit firm. Unlike traditional microcredit providers in Latin America, this firm developed a strategy that targets poor workers by using the clients' job contracts as collateral and by implementing a 100% online application system with a low level of bureaucracy. A total of 911 contracts were analyzed. Unlike previous studies, we show that the main variable used for screening is Job Experience: borrowers with longer experience in their current jobs received larger loans with lower interest rates while maintaining smaller delinquency. Thus, we show that financial technology can change the field of microcredit.
SSRN
This paper examines security design in imperfectly competitive markets in which assets clear separately rather than jointly. Derivatives are generally nonredundant even with zero asset supply. We characterize the scope for introducing nonredundant derivatives and examine the welfare effects of new assets. We compare welfare effects of derivatives vs. innovation in trading technology.
SSRN
The Fed has responded to sharp drops in stock prices for two decades by pumping massive amounts of liquidity into the economyâ"creating a not-so-unreasonable expectation that future declines may elicit a similar response. Field and experimental evidence supports the price-raising effect of increased money supply.
SSRN
We evaluate how the aggressiveness of merger and acquisition (M&A) is associated with stock price crash risk from 2007 to 2017 in China. We construct a compressive measure of M&A aggressiveness and find that it is positively associated with stock price crash risk, and the effect is mainly driven by excessive bidding premiums and accumulated goodwill. In addition, M&A aggressiveness predicts failure to deliver performance commitment, and such effect is exaggerated for deals involving related party transaction and major asset restructuring. Mediation analysis identifies valuation uncertainty as the mediating factor due to conflict of interests and information asymmetry, and cash and mutual compensation scheme help alleviate these consequences. Overall, our findings highlight the important role of performance commitment clauses for the financial risk of M&A activities.
SSRN
Risk forecasting is crucial for informed investment decision-making. Moreover, the salience of investment risk increases during economically uncertain times. In this paper, we study how sell-side analysts form expectations of firm risk, under different macroeconomic conditions (low versus high uncertainty) and by distinguishing between quantitative and qualitative information inputs. We find that analysts jointly consider quantitative and qualitative information but that their reliance on qualitative information - in particular, disclosure tone - increases when macroeconomic uncertainty is high. We also find that analysts mostly rely on disclosure tone when it contradicts quantitative information. These findings highlight how narrative disclosures can provide context for quantitative information. Finally, we find that analysts' specific use of quantitative/qualitative information improves their forecasts as predictors of firm risk. Together, our results illuminate analysts' risk forecasting process - what information they use and how.
SSRN
This paper provides a mis-pricing-based explanation for the negative relation between firm-level productivity and stock returns. Investors appear to under-price unproductive firms and overprice productive firms. We find evidence consistent with the speculative overpricing of productive firms driven by investor sentiment and short sale constraints. Investors erroneously extrapolate past productivity growth and its associated operating performance and stock returns, despite their subsequent reversals. Such mis-pricing is perpetuated because of limits to arbitrage and is partially corrected around earnings announcements when investors are surprised by unexpected earnings news. Decomposition analysis indicates that extrapolative mis-pricing and limits to arbitrage explain most of the return predictability of firm-level productivity.
arXiv
Extracting previously unknown patterns and information in time series is central to many real-world applications. In this study, we introduce a novel approach to modeling financial time series using a deep learning model. We use a Long Short-Term Memory (LSTM) network equipped with the trainable initial hidden states. By learning to reconstruct time series, the proposed model can represent high-dimensional time series data with its parameters. An experiment with the Korean stock market data showed that the model was able to capture the relative similarity between a large number of stock prices in its latent space. Besides, the model was also able to predict the future stock trends from the latent space. The proposed method can help to identify relationships among many time series, and it could be applied to financial applications, such as optimizing the investment portfolios.
arXiv
We propose a stochastic model allowing property and casualty insurers with multiple business lines to measure their liabilities for incurred claims risk and calculate associated capital requirements. Our model includes many desirable features which enable reproducing empirical properties of loss ratio dynamics. For instance, our model integrates a double generalized linear model relying on accident semester and development lag effects to represent both the mean and dispersion of loss ratio distributions, an autocorrelation structure between loss ratios of the various development lags, and a hierarchical copula model driving the dependence across the various business lines. The model allows for a joint simulation of loss triangles and the quantification of the overall portfolio risk through risk measures. Consequently, a diversification benefit associated to the economic capital requirements can be measured, in accordance with IFRS 17 standards which allow for the recognition of such benefit. The allocation of capital across business lines based on the Euler allocation principle is then illustrated. The implementation of our model is performed by estimating its parameters based on a car insurance data obtained from the General Insurance Statistical Agency (GISA), and by conducting numerical simulations whose results are then presented.
SSRN
Drawing on institutional theory, we examine the impact of corporate governance (CG) on corruption. The interaction effects of national culture and CG on corruption are also examined. By employing a dataset of 149 countries, our baseline findings indicate that the quality of CG practices reduces the level of corruption. Findings also show that three cultural dimensions, namely, power distance, individualism and indulgence moderate the CG-corruption nexus. Our findings indicate that CG and national culture explain the level of corruption among societies, with national culture appearing to matter more than the quality of CG. Our findings remain unchanged after controlling for endogeneities, country-level factors, CG and corruption proxies.
SSRN
Media dissemination plays an important role in facilitating price discovery. Political pressure that restricts media dissemination can hinder this function and affect investorsâ perceptions. This paper studies the magnitude of newspaper censorship in China and its economic consequences using a setting of âtunnelingâ scandals. We find significant evidence of censorship of tunneling-related negative news at the national and local level. We further show that news that survives censorship reduces information asymmetry and improves pricing efficiency. We find that censorship blocks informative tunneling news and delays incorporation of tunneling reporting into prices.
SSRN
The progressive integration of Environmental, Social and Governance (ESG) issues into the corporate decision making is a cultural change process, which can be described, planned, measured. It speeds up sustainable transformation of governance, strategies and business models of companies. The first edition of this Report analysed the changes in some key behaviours of the company organisation and of the board of directors (BoDs) in the occasion of the first year of implementation of the Directive 2014/95/UE, transposed in Italy by the Legislative Decree no. 254/2016 (the Decree). This second edition of the Report measures the progression of behaviours analysed in 2019 and surveys additional actions considered important for the transformation. The first section focuses on non-financial reporting and on the abstracts of Strategic plans presented to investors in order to study the evolution of corporate culture and organisation towards ESG/multicapital integration. Subsequently, the Report explores whether companies consider non-financial issues relevant also at the board level, through both a documental analysis (based on the examination of the guidelines issued by companies prior to the 2019 board appointment and of the corporate governance reports; second section) and a Survey involving directors and statutory auditors that are members of Nedcommunity, the Italian Association of non-executive and independent directors, carried out for the fourth year by Nedcommunity and Methodos (third section). In order to track the progression of the cultural transformation, the information collected in this Report was clustered in three stages: Awareness, Capabilities and Engagement (see the chart below). Awareness is the precondition for change. It gathers behaviours of the company structure and the BoDs that are coherent with a first acknowledgement of the importance of ESG issues and that could kick-off the transformation process. Compared to 2018, the number of companies acting the different behaviours in the Awareness cluster is unchanged or has in some cases increased. The area Capabilities is intermediate in the transformation journey, when new skills, behaviours and mindsets are trained to accelerate the process. Compared to the previous year, this area records improvements, which in some cases are significant. This is the case of the behaviours linked to stakeholder engagement in the materiality analysis: external stakeholder engagement is indeed described in 70 cases (44 last year); engagement with the top management rose from 47 to 69 cases. There is also a slight increase in the number of companies integrating their reporting tools (from 9 to 11). With regards to boards, improvements are found in the integration of ESG into board renewal guidelines and in the board self-evaluation. The integration of remuneration packages with ESG criteria is also included in this intermediate phase because it is considered a driver towards change. The area Engagement is the most advanced in the ESG/multicapital transformation of strategies and business models. In this phase new behaviours are spontaneously carried out by the boards and the corporate organisation. This part of the analysis covers the abstracts of the Strategic plans presented to investors in the road shows, published in the Investor Relation section of the websites of the companies, in order to verify how and to what extent they describe a strategy that integrates financial and non-financial issues. Five companies (all in the Energy/Oil and Gas industry) fully integrate in their strategy issues that generate value in the short and long term and describe the connections between financial and non-financial matters. Among these companies, one mentions the materiality analysis as a pillar of its Strategic plan.
arXiv
In this paper we continue the research of our recent interest rate tree model called Zero Black-Derman-Toy (ZBDT) model, which includes the possibility of a jump at each step to a practically zero interest rate. This approach allows to better match to risk of financial slowdown caused by catastrophic events. We present how to valuate a wide range of financial derivatives for such a model. The classical Black-Derman-Toy (BDT) model and novel ZBDT model are described and analogies in their calibration methodology are established. Finally two cases of applications of the novel ZBDT model are introduced. The first of them is the hypothetical case of an S-shape term structure and decreasing volatility of yields. The second case is an application of the ZBDT model in the structure of United States sovereign bonds in the current $2020$ economic slowdown caused by the Coronavirus pandemic. The objective of this study is to understand the differences presented by the valuation in both models for different derivatives.
SSRN
Using a novel source of quasi-experimental variation in the revenue of the local government from housing purchase limits policy, we investigate the mechanism of "rent-tax substitution" from 2008 to 2015. The "rent-tax substitution" refers to the substitute relationship between the tax revenue and the land grant premium (rent of land use rights) of local government in China. Our findings indicate that contrary to other cities, the cities implementing housing purchase limits policy (HPLP) have 48.28% less land grant premium but 14.96% more tax revenue. We also examine how the HPLP affect the firm. The results show that the implementation of the HPLP increases the tax burden of local firms, particularly the burden arising from corporate income tax. Furthermore, HPLP negatively influences firms in different aspects concerning investment, employment, and wage.
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Our study focuses on the impact of shareholder activism, which is gaining momentum and which is an expected-to-evolve phenomena in the near future. Mostly, we firstly aim to demystify the effects of such a controversial style of investment, that is perceived in a highly critical way, especially in Europe, where it nevertheless constitutes a considerable upward trend. Then, we intend to explore defense mechanisms implemented against this phenomenon, originally inspired by the mechanisms used to protect against hostile takeovers, but also immediately applied to tackle active investors. In fact, despite the potential creation of value, managers may wish to preserve the company from activist campaigns because such campaigns attract unfavorable public opinion and raise corporate governance issues that take time and attention away from the executives.In Sections I through III of the paper, after defining and framing the phenomenon also with respect to the literature that covered this topic, we will outline the patterns of shareholder activism in the US and in the EU. The most important differences between the two markets will then be drawn, as well as the facets of the latter and in particular the United Kingdom, Italy, Germany, Spain, Sweden and Ireland. An empirical analysis of the main issues concerning the phenomenon in the two geographical contexts considered and case studies relating to the different countries mentioned above will follow. Specifically, with regard to the United States, the trends that characterize the evolution of the phenomenon itself will be identified and some correlations will be quantitatively assessed, while, as far as Europe is concerned, the research aims to give a comprehensive framework, as no systematic studies are available due to the absence of even remotely similar data to the ones regarding the overseas scenario.In Sections IV through VII of the paper, instead, the defensive phenomenon is examined with respect to shareholder investor techniques. This perspective is substantially unexplored in the literature and lacks any strong empirical evidence, although it must be clarified that there are some studies relating to its first phase of implementation. Despite this, the issue is of great concern and interest, as the defense mechanisms at stake are now a service being provided for by the largest investment banks, which currently have a dedicated advisory team for this very specific aspect. So, if activism threatens companies, it provides an opportunity for investment banks to make a profit from their defense activities and build stronger relationships with companies. First, it is widely held that these tools are considered to promote the entrenchment of managers, destroy value or prevent the creation of value for shareholders. However, these conclusions derive from empirical research, which exclusively covered takeovers. Secondly, the few empirical studies about the subject focused only on the use of poison pills, staggered boards and dual-class shares in decreasing the likelihood of being targeted or on the removal by activist investors. Thus, it is not clear whether they are effective in pursuing their agendas.We aim to develop the existing literature considering: (i) the impact that the presence of defense mechanisms has on the equity value created by activist investors in the long-term; and (ii) the degree of effectiveness of such instruments in preventing active shareholders from succeeding in their agenda. This will be examined more closely in the context of the U.S. market, since it is not possible to examine the phenomenon in light of the available data for Europe, although it would be worthwhile to further explore this. Moreover, it should be noted that this study is limited to considering poison pills and staggered board defense mechanisms with reference to events that took place between January 2004 and December 2015 as far as companies operating in any industry are concerned, again due to the limited availability of data. The findings are very significant since they refute the (prevailing) statement according to which activists tend to target companies that generate little profit. On the contrary, target companies tend to outperform because of their high-risk profile. The results of the study also identify a negative correlation between the likelihood that an activist campaign is successful and the presence of defense mechanisms, which, this time, are in line with the academic trend developed up to now.In addition, we will briefly delve into index funds and their relation to activist campaigns. In light of the substantive investments held by index funds in their portfolio companies, any potential support by passive managers for activist campaigns is paramount in order for the relevant hedge fund to secure victory against the incumbent management. Index funds are characterized by significant incentives to keep a deferential stance towards managers, but there is mixed evidence among scholars on whether such deference translates into an actual unwillingness to support activists.The outcomes of this study are not only relevant in the eyes of activists, but also of shareholders, managers, and hopefully of potential investors seeking to replicate strategies pursued by activist investors themselves.
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Venture capital (VC) investments are pro-cyclical in nature, making it much more difficult for startups to attract investments during periods of economic recession than during economic growth. To mitigate the negative effects of the coronavirus crisis on the economy, countries are being forced to invest an unprecedented amount of financial resources in the economy, which in turn requires certain priorities. Therefore, in this article, we will look at which startup categories countries should support first during this crisis and what support instruments should be used for this purpose.
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Do firms with liquid stocks hold more cash? If so, why? We show that liquidity has a positive effect on the level and value of cash holdings. Using a regression discontinuity design based on the Russell 1000/2000 index reconstitution, we also show that there is a causal link between liquidity and cash holdings. These findings are consistent with a view predicting that high liquidity generates the complementarity between external financing and cash holdings. Furthermore, we show that the positive effect is more pronounced for firms with more growth opportunities, suggesting that liquidity increases cash holdings by expanding investment opportunities.
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Public science firms generate positive outcomes, but transitions for their private startup counterparts across the so-called ``Valley of Death'' remain challenging. Like other new ventures, they use modern tools to raise capital, such as crowdfunding and simplified convertible debt instruments, but these strategies have been poorly studied for the economically important niche of early-stage science firms. New data from a ``deep technology'' equity crowdfunding (EC) platform show that those investors make different decisions than their offline counterparts. Debt and a related instrument, the Simple Agreement for Future Equity (SAFE), are used successfully in both channels as early-stage vehicles, but selection and funding outcomes differ. Relative to life sciences and data sciences, engineering or hardware firms experience a significant penalty if they elect to offer convertible debt instruments. Equity crowdfunding investors strongly prefer the SAFE to a traditional debt instrument, but are relatively insensitive to the specific terms. These findings impact the understanding of entrepreneurial finance and the policy associated with science-based ventures.
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We investigate the impact of investor attention, proxied by Google search volume, on target abnormal returns and liquidity measures around M&A announcements. Investor attention slightly increases before and exhibits a sharp incline at the announcement date, with elevated levels of attention subsequent to the announcement. In line with common models of investor attention, we find that investor attention significantly and positively contributes to target abnormal returns at announcement date and leads to timelier incorporation of information, with potential leakage reducing abnormal returns on announcement date. We provide evidence of a share price anomaly as targets which do not attract attention at announcement date have median abnormal returns of more than 4% the following day. High and low attention at announcement date lead to over- and under-reaction in share price returns at announcement date, respectively, either of which is reversed over the subsequent month. Further, liquidity measures improve after M&A announcements, the decrease in bid-ask spread being significantly correlated with attention at announcement. These effects are more profound for smaller targets. The results are robust after controlling for relevant variables and causality concerns.
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When and how do entrepreneurs sell their inventions? To address this issue, we develop an endogenous entry-sale asymmetric information oligopoly model. We show that lowquality inventions are sold directly or used for entry. Inventors who sell post-entry use entry to credibly reveal information on quality. Incumbents are then willing to pay high prices for high-quality inventions to preempt rivals from obtaining them. Using Swedish data on patents granted to small firms and individuals, we find evidence that high-quality inventions are sold under preemptive bidding competition, post entry.
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This paper studies information sharing between strategic investors with private information of different precision about the asset fundamental. We find that a coarsely informed investor would always share her information "as is'' if her counterparty investor is well informed about the fundamental. In this way, the coarsely informed investor invites the well informed investor to trade against her information, thereby offsetting her informed order flow and reducing the price impact. The coarsely informed investor gains from the information sharing but the well informed investor loses from it. Our model offers an explanation for why the masses of investors express investment opinions on social media and sheds new light on information networks in financial markets and institutional investors' sentiment trading strategy.
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We analyze why some merger and acquisitions (M&A) deals are withdrawn paying particular attention to the economic freedom and legal environment of countries. We use a large dataset based on deals worldwide from over 140 countries during the period 1977 to 2014. Our core finding is that the likelihood of a dealâs withdrawal tends to increase if the economic freedom/ quality of legal environment of the acquiring (target) firmâs country is higher (lower). These core findings matter more for the non-financial sector, during non-crisis years, and in developed financial markets. We also report that the deals have higher tendency to be withdrawn if the target firmâs size is larger or its profitability is lower; and the acquiring firmâs size is smaller. Furthermore, our analyses reveal that deal characteristics (i.e., deal attitude, means of payment, deal size, ownership sought) also matter in affecting the outcome of announced M&A deals.
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This paper provides an up-to-date and comprehensive systematic literature review (SLR) of the existing research on women on corporate boards (WOCBs) and corporate financial and non-financial performance. The aim is to synthesise and extend current understanding of both the existing (i) theoretical (i.e., economic, psychological and social) perspectives and (ii) empirical evidence on the (a) multi-level (i.e., individual-, social-, firm- and country-level) antecedents of WOCBs, and (b) the effects that WOCBs have on a wide range of corporate financial and non-financial performance. We achieve this by adopting a three-step SLR approach to analyse/review one of the largest SLR datasets to be employed to date, consisting of 634 mixed, qualitative, quantitative and theoretical studies conducted in over 100 countries from more than 10 disciplines (e.g., accounting, finance, economics and governance) from 1981 to 2019 and published in 270 top-ranked journals. Our findings are as follows. First, a large number of existing studies are descriptive and/or they draw on single rather than multi-theoretical perspectives. Second, existing studies have focused on firm-level rather than country-level antecedents of WOCBs. Third, observable methodological limitations include the dearth of qualitative, mixed-methods and cross-cultural/country studies. Finally, we outline opportunities for future WOCBs research.