# Research articles for the 2019-10-16

Adverse Selection and Credit Certificates: Evidence from a P2P Platform
Hu, Maggie Rong,Li, Xiaoyang,Shi, Yang
SSRN
Certificates are widely used as a signaling mechanism to mitigate adverse selection when information is asymmetric. To reduce information asymmetry between lenders and borrowers, Chinese peer-to-peer (P2P) lending platforms encourage borrowers to obtain various kinds of credit certificates. As P2P markets continue to develop, it is plausible that certification may play a pivotal role in ensuring investment efficiency. We perform the first empirical investigation of this issue, using unique data from Renrendai, one of the Peopleâ€™s Republic of Chinaâ€™s largest P2P lending platforms. We find that surprisingly, loans with more credit certificates experience a higher rate of delinquency and default. However, lenders remain attracted by higher certificates despite lower loan performance ex post, which results in distorted capital allocation and reduced investment inefficiency. Overall, we document a setting where credit certificates fail to serve as an accurate signal due to their costless nature, where poor-quality borrowers use more certificates to boost their credit profiles and improve their funding success. Possible explanations for this phenomenon include differences in marginal benefit of certificates for different borrower types, bounded rationality, cognitive simplification, and borrower myopia.

Bank Competition and Information Production
De Marco, Filippo,Petriconi, Silvio
SSRN
We show that competition adversely affects information production in the banking industry. In particular, we observe that the positive abnormal return associated with the announcement of a bank loan is reduced in US states that deregulate interstate branching. The negative effect of competition on information production is present only for informationally opaque firms (i.e., firms with few tangible assets and bank-dependent borrowers) and for banks that rely more on "soft" information (i.e., small banks). Moreover, we find that charge-off rates on small business loans are higher in deregulated states. Our results suggest that competition decreases loan quality because it reduces banks' incentives to invest in information.

Becoming Global Billionaires from Mainland China: Theory and Evidence
Xiao, Kezhou
SSRN
The increase in the number of global billionaires from mainland China is a puzzle viewed from the standpoint of extractive institutions''. Guided by a proposed conceptual framework relating socio-political backgrounds of the billionaire entrepreneurs to their observable financing decisions, I show, under conditions of an open economy, grassroots billionaire entrepreneurs (e.g., Jack Ma) could attenuate political economy as well as financial frictions via capital injections from foreign venture capitalists. Building a unique database, I find, using a human equation, that (i) the politically unconnected billionaire entrepreneurs financed by foreign venture capitalists are more likely to float their companies outside mainland China (mainly in Hong Kong and the U.S), use offshore financing vehicles, and enter into innovative sectors; and (ii) the politically connected global billionaire entrepreneurs, however, are strongly associated with a record of state-owned enterprise (SOE) restructuring.

Big Data-Based Peer-to-Peer Lending Fintech: Surveillance System through Utilization of Google Play Review
Pranata, Nika,Farandy, Alan Ray
SSRN
Peer-to-peer lending (P2PL) FinTech is growing rapidly in Indonesia. With its flexibility and simplicity, P2PL reduces the financing gap that cannot be fulfilled by banks. However, the rapid development of P2PL also raises a number of problems that burden users such as unethical debt collection methods and the imposition of excessive interest rate and other costs that potentially threaten national financial system stability. Therefore, by utilizing big data, which in this case is 40,650 reviews from 110 P2PLs obtained from Google Play from March 2016 to August 2018, we build a big data-based P2PL surveillance system based on four aspects: legality, review rating, debt collection methods, and level of interest rates and other costs. By using relational database, structured query language (SQL), and text analysis, we found that (i) the majority of P2PL in Google Play are unauthorized; (ii) on average, authorized P2PL receives a better review rating; (iii) there are a lot of negative reviews related to unethical debt collection methods and excessive imposition of interest rate; and (iv) four P2PLs required special supervision from the Indonesia Financial Service Authority (OJK). Furthermore, the OJK should not passively wait for official reports to be filed by the public regarding violations of P2PL businesses. Through this big data-based system, the OJK can find these violations proactively because the system can act as an early warning system for the OJK in terms of P2PL surveillance.

Han, Seung-Oh,Hsu, Po-Hsuan,Huh, Sahn-Wook
SSRN
After constructing high-frequency measures of informed trading as well as the measure of brand innovation proxied by the number of trademark registrations (TMRs), we first examine how market participants respond to the news about TMRs. The results show that the information on TMRs predicts subsequent stock returns, implying the value-relevance of TMRs. We then provide evidence that investors attempt to capitalize on such information in the financial market. The analyses with the posterior probabilities of informed trading and the directional price impacts suggest that market participants interpret more TMRs as good news, which in turn triggers informed buying. A series of robustness tests confirm that the results are consistent with our main arguments.

Business Creation, Incorporation and the Role of Personal Bankruptcy Protection: Evidence from the BAPCPA
Ribas, Rafael P.
SSRN
This paper investigates how business creation, earnings, and survival are related to incorporation and personal bankruptcy codes. In theory, individual debtor protection might either affect entrepreneurship or just prevent the incorporation of household firms. To examine this issue, I exploit the bankruptcy reform of 2005 as an exogenous reduction in the protection granted by homestead exemptions. Generous exemptions are found to encourage low-skilled entrepreneurs to sustain unincorporated firms. However, these exemptions also encourage high-skilled entrepreneurs to undertake profitable ventures. The evidence is consistent with new entrepreneurs often relying on unincorporated forms as the steppingstone to a successful business.

Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes
Eoghan O'Neill,Melvyn Weeks
arXiv

We examine the household-specific effects of the introduction of Time-of-Use (TOU) electricity pricing schemes. Using a causal forest (Athey and Imbens, 2016; Wager and Athey, 2018; Athey et al., 2019), we consider the association between past consumption and survey variables, and the effect of TOU pricing on household electricity demand. We describe the heterogeneity in household variables across quartiles of estimated demand response and utilise variable importance measures.

Household-specific estimates produced by a causal forest exhibit reasonable associations with covariates. For example, households that are younger, more educated, and that consume more electricity, are predicted to respond more to a new pricing scheme. In addition, variable importance measures suggest that some aspects of past consumption information may be more useful than survey information in producing these estimates.

Challenges in Implementing the Credit Guarantee Scheme for Small and Medium-Sized Enterprises: The Case of Viet Nam
Dang, Le Ngoc,Chuc, Anh Tu
SSRN
Access to credit is still one of the greatest obstacles to the growth of small and medium-sized enterprises (SMEs) in Viet Nam. To date, only 39% of SMEs have bank loans. To cater to SMEsâ€™ need for financial sources, especially formal sources such as the banking system, the Vietnamese government has implemented a large number of supporting programs, including the credit guarantee scheme (CGS) for SMEs, which it established in 2001. Through collecting, synthesizing, and analyzing data, we aim to study the challenges involved in implementing CGSs for SMEs as well as the causes of their poor performance. The fundamental reasons we find include the strict and impractical conditions for issuing credit guaranteed loans; the lack of adequate professional competence of staff involved in the credit guaranteeing task; the fragmented relationship between the credit institution and the CGS; and the lack of a credit database platform that facilitates access to finance for SMEs by providing comprehensive and reliable creditworthiness.

Distress and Default Contagion in Financial Networks
Veraart, Luitgard A. M.
SSRN
We develop a new model for solvency contagion that can be used to quantify systemic risk in stress tests of financial networks. In contrast to many existing models it allows for the spread of contagion already before the point of default and hence can account for contagion due to distress and mark-to-market losses. We derive general ordering results for outcome measures of stress tests that enable us to compare different contagion mechanisms. We use these results to study the sensitivity of the new contagion mechanism with respect to its model parameters and to compare it to existing models in the literature. When applying the new model to data from the European Banking Authority we find that the risk from distress contagion is strongly dependent on the anticipated recovery rate. For low recovery rates the high additional losses caused by bankruptcy dominate the overall stress test results. For high recovery rates, however, we observe a strong sensitivity of the stress test outcomes with respect to the model parameters determining the magnitude of distress contagion.

Do Corporate Governance Ratings Change Investor Expectations? Evidence from Announcements by Institutional Shareholder Services
Guest, Paul M.,Nerino, Marco
SSRN
This paper examines empirically the announcement effect of commercial corporate governance ratings on share returns. Rating downgrades by Institutional Shareholder Services (ISS) are associated with negative returns of â€"1.14% over a 3-day announcement window. The returns are highly correlated with the proprietary analysis of ISS and are decreasing in agency costs, consistent with ratings providing independent information on underlying corporate governance quality. We thus show that the influence and impact of ISS extends beyond proxy recommendations and subsequent voting outcomes. Our findings contrast with the insignificant price impact of Daines, Gow, and Larcker (2010), whose analysis we replicate and successfully reconcile to ours by pooling upgrades and downgrades together.

Do Higher Moments Risk Premia Compensate for Macroeconomic Risk?
Khrashchevskyi, Ian
SSRN
In this paper I investigate whether the risk premia associated with higher moments of stock returns such as variance, skewness and kurtosis bear compensation for macroeconomic risk. I introduce a new measure for kurtosis risk premia and show that the higher moment risk premia are related to macroeconomic risk. The results suggest that higher moment risk premia hegdes against macroeconomic risks, but the relationship appears to be asymmetric. Unlike previous studies, I find evidence that there is a difference between variance and skewness risk premia and that the variation in higher moment risk premia can be explained by two common factors. While the first factor is related to risk aversion and market risk, the second factor may be related to ability of market to absorb liquidity shocks. The paper concludes that risk aversion explanation is not enough alone to explain the variation in higher moment risk premia and that the size of the premia may be related to ability of the market to absorb liquidity shocks

Exchange Rate Movements and Fundamentals: Impact of Oil Prices and the Peopleâ€™s Republic of Chinaâ€™s Growth
Chen, Hongyi,Cao, Shuo
SSRN
We identify five factors that can capture 95% of the variance across 39 United States (US) dollar exchange rates based on the principal component method. We use a time-varying parameter factor-augmented vector autoregressive model to analyze the determinants of movements in these exchange rates, and reveal that their impact on global oil prices and the Peopleâ€™s Republic of Chinaâ€™s growth has increased significantly since 2008. In particular, the variance of US dollar exchange rates has mainly been driven by these two shocks in recent years. The impact of monetary policy shocks on the currency pairs is comparatively small.

Fama and French Meet Datastream: Size, Value, Profitability, and Investment Factors in International Stock Returns
SSRN
Using Datastream database, we calculate the five-factor model for global equity markets and compare the results with the five-factor model of Fama and French (2015, 2017) which is mainly based on data from Bloomberg. The results suggest that Datastream provides similar coverage and yields outcomes qualitatively consistent with the Bloomberg-based sample of Fama and French. Most factor returns are driven by the smallest firms. We demonstrate that virtually no value, profitability, or investment effects are present among the big firms representing most of the total market capitalization around the world. Given the fact that those small firms are not investable by big financial institutions, our findings cast doubt on the applicability of the five-factor models in international markets.

Gender and Corporate Success: An Empirical Analysis of Gender-Based Corporate Performance on a Sample of Asian Small and Medium-Sized Enterprises
SSRN
Within a patriarchal society, women are placed in a precarious societal positioning that leads to a prevalence of gender inequality in education, financial literacy, and access to finance. In the context of Asia, where small and medium-sized enterprises (SMEs) are the backbone of most Asian economies and the financial sector is dominated by banks, women in entrepreneurship are susceptible to facing greater credit constraints relative to their male counterparts, which can compromise their corporate performance. We investigate whether there is a significant association between gender and success or failure of SMEs. Using a statistical analysis technique (principal component analysis) and running econometrics regressions on a random sample of 1,492 exporter SMEs from Iran, the research answers the question: is it plausible to conclude that female-owned SMEs are bound for lower corporate performance relative to those of male counterparts? Empirical results show that indeed, despite showing a good leverage status, female-owned SMEs perform lower relative to male counterparts as they have a higher default ratio and lower profitability, liquidity, and coverage. We provide policy suggestions, such as establishment of credit guarantee funds for easing the female-owned SMEsâ€™ access to finance in Asia. Implementation of supportive policies for female-owned SMEs will have significant contribution to economic growth, employment, and ultimately, to gender equality.

Insider Trading and the Market Abuse Directive: Are Voluntary and Mandatory Takeover Bids Different?
Ferretti, Riccardo,Pattitoni, Pierpaolo,Patuelli, Roberto
SSRN
This study analyzes the effectiveness of the Market Abuse Directive (MAD) in reducing possible profits from insider trading during takeover bids. Exploiting the quasi-experimental setting provided by the introduction of the MAD, our event-study analysis on the Italian market suggests that the new regulation did produce effects, for mandatory offers, on the magnitude of abnormal returns and volumes noted before their announcement. Instead, we find no effect for voluntary offers, which prove to be intrinsically different from the latter ones. Multivariate econometric analyses based on regression and matching methods confirm this result. We interpret our results in light of the choice problem of the optimal amount of insider trading, based on the comparison of marginal costs and benefits of the illegal activity, after considering the differences between voluntary and mandatory offers.

Me, myself and I: CEO Narcissism and Selective Hedging
Bajo, Emanuele,JankensgÃ¥rd, HÃ¥kan,Marinelli, Nicoletta
SSRN
In this paper, we test the hypothesis that CEO narcissism influences firmsâ€™ hedging behaviour. Unlike rare but transformative events like acquisitions, derivative usage offers the narcissistic manager a convenient stage for bold and decisive action that generates a continuous supply of attention. It therefore represents a compelling setting for investigating whether narcissism impacts corporate policies. The empirical evidence, based on hand-collected data on derivative positions in the U.S. oil and gas industry, suggests that firms with a narcissistic CEO hedge more selectively. Furthermore, we also find that these firms reduce selective hedging comparatively more following a sharp and unexpected price collapse that sent the industry into a state of distress. This result is in line with the â€˜narcissistic paradoxâ€™: while scoring high on self-esteem and grandiosity in the normal case, such individuals are also inherently fragile and liable to crumble when faced with adversity.

NEU Meta-Learning and its Universal Approximation Properties
Anastasis Kratsios,Cody Hyndman
arXiv

We introduce a new meta-learning procedure, called non-Euclidean upgrading (NEU), which learns algorithm-specific geometries by deforming the ambient space until the algorithm can achieve optimal performance. We prove that these deformations have several novel and semi-classical universal approximation properties. These deformations can be used to approximate any continuous, Borel, or modular-Lebesgue integrable functions to arbitrary precision. Further, these deformations can transport any data-set into any other data-set in a finite number of iterations while leaving most of the space fixed. The NEU meta-algorithm embeds these deformations into a wide range of learning algorithms. We prove that the NEU version of the original algorithm must perform better than the original learning algorithm. Moreover, by quantifying model-free learning algorithms as specific unconstrained optimization problems, we find that the NEU version of a learning algorithm must perform better than the model-free extension of the original algorithm. The properties and performance of the NEU meta-algorithm are examined in various simulation studies and applications to financial data.

On Positive Solutions of a Delay Equation Arising When Trading in Financial Markets
Chung-Han Hsieh,B. Ross Barmish,John A. Gubner
arXiv

We consider a discrete-time, linear state equation with delay which arises as a model for a trader's account value when buying and selling a risky asset in a financial market. The state equation includes a nonnegative feedback gain $\alpha$ and a sequence $v(k)$ which models asset returns which are within known bounds but otherwise arbitrary. We introduce two thresholds, $\alpha_-$ and $\alpha_+$, depending on these bounds, and prove that for $\alpha < \alpha_-$, state positivity is guaranteed for all time and all asset-return sequences; i.e., bankruptcy is ruled out and positive solutions of the state equation are continuable indefinitely. On the other hand, for $\alpha > \alpha_+$, we show that there is always a sequence of asset returns for which the state fails to be positive for all time; i.e., along this sequence, bankruptcy is certain and the solution of the state equation ceases to be meaningful after some finite time. Finally, this paper also includes a conjecture which says that for the "gap" interval $\alpha_- \leq \alpha \leq \alpha_+,$ state positivity is also guaranteed for all time. Support for the conjecture, both theoretical and computational, is provided.

Optimal Stopping under Model Ambiguity: a Time-Consistent Equilibrium Approach
Yu-Jui Huang,Xiang Yu
arXiv

An unconventional approach for optimal stopping under model ambiguity is introduced. Besides ambiguity itself, we take into account how ambiguity-averse an agent is. This inclusion of ambiguity attitude, via an $\alpha$-maxmin nonlinear expectation, renders the stopping problem time-inconsistent. We look for subgame perfect equilibrium stopping policies, formulated as fixed points of an operator. For a one-dimensional diffusion with drift and volatility uncertainty, we show that every equilibrium can be obtained through a fixed-point iteration. This allows us to capture much more diverse behavior, depending on an agent's ambiguity attitude, beyond the standard worst-case (or best-case) analysis. In a concrete example of real options valuation under volatility uncertainty, all equilibrium stopping policies, as well as the best one among them, are fully characterized. It demonstrates explicitly the effect of ambiguity attitude on decision making: the more ambiguity-averse, the more eager to stop---so as to withdraw from the uncertain environment. The main result hinges on a delicate analysis of continuous sample paths in the canonical space and the capacity theory. To resolve measurability issues, a generalized measurable projection theorem, new to the literature, is also established.

Ownership Network and Firm Growth: What Do Five Million Companies Tell About Chinese Economy
Allen, Franklin,Cai, Junhui,Gu, Xian,Qian, Jun â€œQJâ€,Zhao, Linda,Zhu, Wu
SSRN
The finance-growth nexus has been a central question in interpreting the unprecedented success of Chinese economy. This paper employs an equity ownership network, reflecting the firm-to-firm equity investment relationship, of all the registered firms in China and shows that the network has been expanding rapidly since 2000s, with five million firms being in network by 2017. We find that entering the network and increase in network centrality, both globally and locally, are associated with higher future firm growth. Such effect of network position tends to be more pronounced for high productivity firms and non-state-owned enterprises (non-SOEs). The massive Stimulus Plan, launched by Chinese government in November 2008, crowds out the effect of equity capital. Taken together, our analysis suggests that equity ownership network and bank credit tend to act as substitutes for SOEs, while as complements for non-SOEs in promoting growth.

Performance Differential Between Private and State-Owned Enterprises: An Analysis of Profitability and Leverage
SSRN
We investigate empirically the relationship between ownership identity and the performance of firms in terms of profitability and solvency. Using cross-sectional data covering over 25,000 firms worldwide and by employing various empirical methods, we find robust support for the inferior performance of government enterprises over privately owned firms. Specifically, state-owned enterprises (SOEs) tend to be less profitable than privately owned enterprises. However, they appear to be more dependent on debt for their financial needs and are, thus, better leveraged. Additionally, SOEs are more labor intensive and have higher labor costs. Thus, evidence from this study could be interpreted to mean that privatization could improve the performance of public firms. However, a study over a longer period is needed before these results can be considered conclusive.

Portfolio Cuts: A Graph-Theoretic Framework to Diversification
Bruno Scalzo Dees,Ljubisa Stankovic,Anthony G. Constantinides,Danilo P. Mandic
arXiv

Investment returns naturally reside on irregular domains, however, standard multivariate portfolio optimization methods are agnostic to data structure. To this end, we investigate ways for domain knowledge to be conveniently incorporated into the analysis, by means of graphs. Next, to relax the assumption of the completeness of graph topology and to equip the graph model with practically relevant physical intuition, we introduce the portfolio cut paradigm. Such a graph-theoretic portfolio partitioning technique is shown to allow the investor to devise robust and tractable asset allocation schemes, by virtue of a rigorous graph framework for considering smaller, computationally feasible, and economically meaningful clusters of assets, based on graph cuts. In turn, this makes it possible to fully utilize the asset returns covariance matrix for constructing the portfolio, even without the requirement for its inversion. The advantages of the proposed framework over traditional methods are demonstrated through numerical simulations based on real-world price data.

Portfolio optimization in the case of an exponential utility function and in the presence of an illiquid asset
Ljudmila A. Bordag
arXiv

We study an optimization problem for a portfolio with a risk-free, a liquid risky, and an illiquid asset which is sold in an exogenous random moment of time with a prescribed liquidation time distribution. Problems of such type lead to three dimensional nonlinear partial differential equations (PDEs) on the value function. We study the optimization problem with a utility function of a CARA type, i.e. with negative and positive exponential utility functions (EXPn and EXPp). It is well known that both the LOG and the EXPn utility functions are connected with the HARA utility function by means of a limiting procedure: in the first case the parameter of a HARA utility function is going to zero and in the second case to infinity. In our previous papers devoted to the optimization problem with a HARA and LOG utility functions we proved that also the corresponding analytical and Lie algebraic structures are connected with the same limiting procedure. In this paper we show that the case of EXPn utility function differs from the case of the HARA utility and is not connected to the HARA case by the limiting procedure. We carry out the Lie group analysis of the PDEs for the cases EXPn and EXPp utility functions and proved that they are connected by a one-to-one analytical substitution and are identical from the economical, analytical or Lie algebraic point of view. The complete set of nonequivalent group invariant reductions to two dimensional PDEs is provided for the three dimensional PDE with the EXPn utility function in accordance with an optimal system of sub algebras of the admitted Lie algebra. We prove that in one case the invariant reduction is consistent with the boundary condition. We can use the reduced two dimensional PDE to study the properties of the optimal solution and the investment - consumption strategies.

Price, Cultural Dimensions, and the Cross-Section of Expected Stock Returns
Hammerich, Ulrich
SSRN
We document a nominal stock price effect that is (like momentum) associated with (national) culture. Using the full spectrum of cultural dimensions proposed by Hofstede et al. and the cross-section of stock returns of 41 countries, we not only show a robust predictive and explanatory power of price in conjunction with several cultural dimensions, but of cultural differences in general. Although momentum and price are related investment strategies, we find a broad (escalating) European high-price effect, but a material low-price effect in Asia as well as the most significant and robust low-price effect for the US. Most consistent around the world, high-priced stocks show lower return volatility and market betas than low-priced stocks and lower values for skewness of returns.

Racial Disparities in Debt Collection
LaVoice, Jessica,Vamossy, Domonkos F.
SSRN
A distinct set of disadvantages experienced by black Americans increases their likelihood of experiencing negative financial shocks, decreases their ability to mitigate the impact of such shocks, and ultimately results in debt collection cases being far more common in black neighborhoods than in non-black neighborhoods. In this paper, we create a novel data-set that links debt collection court cases with information from credit reports to document the disparity in debt collection judgments across black and non-black neighborhoods and to explore potential mechanisms that could be driving this judgment gap. We find that majority black neighborhoods experience approximately 40% more judgments than non-black neighborhoods, even after controlling for differences in median incomes, median credit scores, and default rates. The racial disparity in judgments cannot be explained by differences in debt characteristics across black and non-black neighborhoods, nor can it be explained by differences in attorney representation, the share of contested judgments, or differences in neighborhood lending institutions.

Return Cross-Predictability in Firms with Similar Employee Satisfaction
Bian, Xueying,Sarkissian, Sergei,Tu, Jun,Zhang, Ran
SSRN
We study the return predictability of similar employee satisfaction (SES) firms using new firm-ranking data of employee satisfaction from Glassdoor. We find that the returns of firm peers with SES have a predictive power for focal firm returns. A long-short portfolio sorted on the lagged returns of SES firm peers yields a significant Fama and French (2018) six-factor alpha of 135 bps per month. This result is distinct from industry and inter-firm momentum effects and cannot be explained by risk-based arguments. Our tests suggest that investorsâ€™ limited attention is the primary reason of firmsâ€™ underreaction to their SES firm returns.

Stochastic Orderings of Multivariate Elliptical Distributions
Chuancun Yin
arXiv

Let ${\bf X}$ and ${\bf X}$ be two $n$-dimensional elliptical random vectors, we establish an identity for $E[f({\bf Y})]-E[f({\bf X})]$, where $f: \Bbb{R}^n \rightarrow \Bbb{R}$ fulfilling some regularity conditions. Using this identity we provide a unified derivation of sufficient and necessary conditions for classifying multivariate elliptical random vectors according to several main integral stochastic orders. As a consequence we obtain new inequalities by applying it to multivariate elliptical distributions. The results generalize the corresponding ones for multivariate normal random vectors in the literature.

Stock Market Liberalization, Investment Banks, and Analyst Forecast Quality: Evidence From a Quasi-Natural Experiment in China
Pittman, Jeffrey,Qi, Baolei,Sun, Zeyu,Wang, Zi-Tian
SSRN
Capitalizing on a quasi-natural experiment in China where certain investment banks become investible to the global market across different periods, we explore the role that stock market liberalization plays in shaping local analystsâ€™ incentives to provide high quality forecasts. In a staggered difference-in-differences research design to improve identification, we find that analysts affiliated with liberalized banks (i.e., pilot analysts) significantly reduce the errors and bias in their earnings forecasts from the pre-liberalization period to the post-liberalization period, relative to non-pilot analysts whose employers remain under strict capital controls during the same timeframe. Consistent with expectations, this result is concentrated among local investment banks that are smaller, have higher existing institutional ownership, and have stronger tournament incentives. Additionally, we identify three mechanisms through which market liberalization affects the quality of analystsâ€™ forecasts: pilot analysts (i) become more focused by reducing the size of their coverage portfolios; (ii) devote more effort to forecasting; and (iii) become subject to harsher career punishments for making deficient forecasts. Our analysis provides insight on the importance of financial globalization to the institutional environment of a countryâ€™s capital market.

SSRN
We study the difference in expected returns between American and equivalent European put options to understand the asset pricing implications of the possibility to early exercise an option. Neoclassical finance theory suggests that the difference is positive, increases with option moneyness, and decreases with option time-to-maturity and the underlying asset's idiosyncratic volatility. Comparing the returns of exchange-traded single-stock American put options with the returns of equivalent synthetic European put options, our empirical work strongly supports these predictions. Our results are surprising given other studies often find investors' option exercising strategies to be non-rational.

Using Machine Learning to Model Claims Experience and Reporting Delays for Pricing and Reserving
Rossouw, Louis,Richman, Ronald
SSRN
In this paper we review existing modelling approaches for analysing claims experience in the presence of reporting delays, reviewing the formulation of mortality incidence models such as GLMs. We then show how these approaches have traditionally been adjusted for late reporting of claims using either the IBNR approach or the more recent EBNER approach. We then go on to introduce a new model formulation that combines a model for late reported claims with a model for mortality incidence into a single model formulation. We then illustrate the use and performance of the traditional and the combined model formulations on data from a multinational reinsurer. We show how GLMs, lasso regression, gradient boosted trees and deep learning can be applied to the new formulation to produce results of superior accuracy compared to the traditional approaches.

Weighted Monte Carlo with least squares and randomized extended Kaczmarz for option pricing
Damir Filipović,Kathrin Glau,Yuji Nakatsukasa,Francesco Statti
arXiv

We propose a methodology for computing single and multi-asset European option prices, and more generally expectations of scalar functions of (multivariate) random variables. This new approach combines the ability of Monte Carlo simulation to handle high-dimensional problems with the efficiency of function approximation. Specifically, we first generalize the recently developed method for multivariate integration in [arXiv:1806.05492] to integration with respect to probability measures. The method is based on the principle "approximate and integrate" in three steps i) sample the integrand at points in the integration domain, ii) approximate the integrand by solving a least-squares problem, iii) integrate the approximate function. In high-dimensional applications we face memory limitations due to large storage requirements in step ii). Combining weighted sampling and the randomized extended Kaczmarz algorithm we obtain a new efficient approach to solve large-scale least-squares problems. Our convergence and cost analysis along with numerical experiments show the effectiveness of the method in both low and high dimensions, and under the assumption of a limited number of available simulations.

Will Stock Buybacks Cause the Demise of Capitalism?
Mendes, AntÃ³nio Marques
SSRN
Like previous economic systems, the capitalist system may be exposed to built-in mechanisms leading to its demise. One serious candidate to ruin capitalism is the practice of companies repurchasing their own shares. In this paper we extend the famous Warren Buffet analogy on CEO Fred Futile to show how unconstrained share buybacks could cause the demise of capitalism.