Research articles for the 2021-08-04

An Assessment of Correlation between Twitter Sentiments Indicators and Stock Market Indicators, with Reference to BSE and NSE in India
Selvam, Murugesan,Kathiravan, Chinnadurai,Dhamotharan, Dhanasekar
The study aims to reveal the relationship between Twittersentiments indicators and stock market indicators, with referenceto BSE and NSE in India. This study used secondary dailytime-series data, for a period of two years, from 01.01.2018 to31.12.2019. Statistical tools, such as Descriptive Statistics andA correlation Matrix was employed to perform the analysis. It wasfound from the correlation analysis that there was a relationshipbetween Twitter sentiments indicators and stock market indicators.The findings of the study would be useful to the investors and otherparticipants in the stock market, as they seek to understand theinfluence of Twitter on stock returns.

Calibrating the Nelson-Siegel-Svensson Model by Genetic Algorithm
Asif Lakhany,Andrej Pintar,Amber Zhang

Accurately fitting the term structure of interest rates is critical to central banks and other market participants. The Nelson-Siegel and Nelson-Siegel-Svensson models are probably the best-known models for this purpose due to their intuitive appeal and simple representation. However, this simplicity comes at a price. The difficulty in calibrating these models is twofold. Firstly, the objective function being minimized during the calibration procedure is nonlinear and has multiple local optima. Secondly, there is strong co-dependence among the model parameters. As a result, their estimated values behave erratically over time. To avoid these problems, we apply a heuristic optimization method, specifically the Genetic Algorithm approach, and show that it is able to construct reliable interest rate curves and stable model parameters over time, regardless of the shape of the curves.

Corporate Personhood and Limited Sovereignty
Pollman, Elizabeth
This Essay, written for a symposium celebrating the work of Professor Margaret Blair, examines how corporate rights jurisprudence helped to shape the corporate form in the United States during the nineteenth century. It argues that as the corporate form became popular because of the way it facilitated capital lock-in, perpetual succession, and provided other favorable characteristics related to legal personality that separated the corporation from its participants, the Supreme Court provided crucial reinforcement of these entity features by recognizing corporations as right-bearing legal persons separate from the government. Although the legal personality of corporations is a distinct concept from their constitutional treatment, the Court’s nineteenth-century rulings bolstered key features created by corporate law and simultaneously situated the corporation as subordinate to the state in a system of federalism. And, finally, the Essay suggests that the balance of power struck in the first century of Supreme Court jurisprudence on corporate rights has been eroded in the modern era. The Supreme Court’s failure to develop a consistent approach to corporate rights questions and its tendency to reason based on views of corporations as associations of persons have exposed a significant flaw in the Court’s evolving corporate personhood jurisprudence: it lacks a limiting principle.

Corruption Along Supply-Chain Networks
Nguyen, Vinh
I study how the corporate corruption culture of foreign suppliers and customers influences the propensity and magnitude of financial misconducts of US corporations. Using the World Bank Corruption Control Index, I find that firms connected to customers( suppliers) from countries with higher corruption culture are more likely to engage in financial misconduct, earnings management, and option backdating. I find that both the selection channel, where US firms with weaker corporate governance choose customers( suppliers) with high corruption culture, and the propagation channel, where the corruption cultures of foreign customers and suppliers influence US firms, explain the magnitude of the effects.

Data Visualization in Earnings Conference Calls
Xu, Da
As data visualization gains popularity in modern society, it is important to understand how this aspect of presentation affects accounting disclosures. By applying deep learning to create customized image recognition algorithms, I investigate firms’ use of data visualization in earnings conference calls. I hypothesize and find that firms tend to use more data visualization when information demand is higher, financial statement processing costs are higher, and operating performance is better. In addition, data visualization is positively associated with analysts’ information acquisition and earnings call informativeness. Overall, my results provide support for dual-coding theory, which predicts that in a situation where verbal stimuli dominate, an increase of imagery stimuli will enhance the audience’s memory and comprehension of the message.

Does equity mutual fund factor-risk-shifting pay off? Evidence from the US
Mateus, Cesario,Todorovic, Natasa,Sarwar, G
This paper assesses the relationship between risk-shifting of mutual funds, measured as benchmark-adjusted factor-based investment style change following a structural break, and their risk-adjusted performance. We isolate only the breaks in style risk beyond those embedded in the funds’ benchmark index to eliminate any natural style risk changes resulting from varying company fundamentals over time. We group style risk changes into extreme (style rotation), moderate (style drifting), and weak (style-strengthening/weakening) and assess which investment style category is most profitable to shift in to and out of. Our findings show that funds that exhibit breaks generate overall better risk-adjusted performance than those that do not. Funds that are most successful in risk-shifting have statistically and economically distinct risk-adjusted performance, make shifts towards small/large/value/growth style combinations rather than mid-cap and blend style, exhibit breaks less frequently, and have more moderate risk-shifts than funds that are unsuccessful.

Does social trust mitigate insiders’ opportunistic behavior? Evidence from insider trading
Fu, Panpan,Ma, Chaoqun,Tian, Yonggang,Wang, Xiuhua
We investigate whether social trust can mitigate insider trading profitability. Our empirical evidence shows that social trust surrounding corporations’ headquarters is negatively associated with corporate insiders’ ability for trading gains. This relation holds in a range of tests including instrumental variable methods and using social trust value from CEO’s birthplace. We further find that social trust plays a more important role in curbing insiders’ trading profitability when firms have a higher level of information asymmetry, poorer corporate governance, and when firms are non-State-owned. Finally, we show that firms headquartered in high social trust regions tend to engage in more investor communication, have a lower probability to restate financial statements, and have lower stock price synchronicity.

Equity Home Bias When Firms are Indebted
Mesa Toro, Andres,Moreno, Antonio,Sammartino, Julieta,Trani, Tommaso
We reassess one of the major puzzles in international macroeconomics, namely the equity home bias puzzle, to shed some light on how it is affected by financial leverage. As corporate debt is generally key to employment, the analysis can provide interesting insights to the mooted argument according to which equity home bias stems from agents’ attempt to insure against changes in their labor income. In a panel of advanced economies spanning the period 1980 through 2018, we find that the non-financial corporate credit-to-GDP ratio is negatively correlated with a standard equity home bias index. The former has increased over time while the latter has decreased, so we attempt to rationalize the data with a two-country, two-good model where firms face borrowing constraints and these constraints reduce agents’ appetite for domestic equities. We show that this happens because the borrowing constraints hinder employment after positive technology shocks, especially those hitting investment. After examining this result with a tractable framework, we find that it can also be true in an extended model, adding financial shocks, trade in bonds and non-unitary elasticity of substitution between goods.

Exploring Risk Premium Factors for Country Equity Returns
Calice, Giovanni,Lin, Ming-Tsung
In this paper, we study a comprehensive set of risk premia of country equity returns for 45 countries over the sample period 2002 to 2018 in both a single and a multiple factor setting. Using a new three-pass estimation method for factor risk premia by Giglio and Xiu (2021), we find that several factors, including default risk, are also priced in country equity excess returns, controlled by the Fama-French 5-factor and Carhart model. Moreover, we apply a novel approach to investigate the multi-factor impact on country equity returns. We find that the multi-factor information, constructed from the first principal component of the statistically significant single factors, provides a consistent and stronger prediction of anomalies in country equity returns.

Factor Representation and Decision Making in Stock Markets Using Deep Reinforcement Learning
Zhaolu Dong,Shan Huang,Simiao Ma,Yining Qian

Deep Reinforcement learning is a branch of unsupervised learning in which an agent learns to act based on environment state in order to maximize its total reward. Deep reinforcement learning provides good opportunity to model the complexity of portfolio choice in high-dimensional and data-driven environment by leveraging the powerful representation of deep neural networks. In this paper, we build a portfolio management system using direct deep reinforcement learning to make optimal portfolio choice periodically among S\&P500 underlying stocks by learning a good factor representation (as input). The result shows that an effective learning of market conditions and optimal portfolio allocations can significantly outperform the average market.

Impact of Digital learning among students
SV, Mohana Sujana
World has now been sustaining the modern culture with more advancements and developments which makes people to buy, sell, communicate etc., from one place. The reason behind this modernization and advancement of technology and internet paved the way for digitalization. Now a day’s people are totally dependent on technology and internet to fulfill each and every common need of human to be done easily and quickly, this has led to the entrance of digitalization in all fields and sectors of economy which has been occupied with digital concepts. Therefore, we have already entered the zone of digitalization in education sector also through various available sources and that has been accepted among people to a great extent. Digital learning technologies have gained much popularity in education from the past few years; and it was rapidly gone high due to the pandemic situation prevailing in our country. Hence this paper addresses the impact of the digital learning technologies among students which has been highly in practice at present. While the acceptance of some of these new digital learning technologies has been investigated, there are few hurdles faced among students in accepting the technology. One of the hardest drawbacks is - physical interaction which has been affected to an extent due to the current scenario. In this study, we compared digital learning technologies (e-lectures, Classroom response, and classroom chat) and their impact and acceptance level of technology among students.

Is Corporate Governance Priced in the Option Market? Evidence from Shareholder Proposals
Qu, Jimmy Chengyuan
By exploiting the local randomness in close-call votes on governance-related shareholder proposals, this paper finds a negative effect of passing a governance proposal on firms’ ex-ante tail risk measured by the cost of option protection against downside tail risks, which suggests that corporate governance is priced in the option market. In a local regression discontinuity (RD) analysis, firms that narrowly pass the majority threshold show a lower ex-ante tail risk measured by implied volatility smirk and model-free implied skewness than those that narrowly fail. This effect is stronger for firms with weaker corporate governance and higher information transparency and is attenuated when firms perform better. Evidence from a global RD analysis confirms the external validity of results in the local RD analysis. Overall, this paper observes a causal impact of corporate governance on the option market and sheds new light on the cross-sectional determinants of option prices.

Learning about the Consumption Risk Exposure of Firms
Kim, Yongjin,Kuehn, Lars-Alexander,Li, Kai
We structurally estimate an investment-based asset pricing model, where firms' exposure to macroeconomic risk is unknown. Bayesian beliefs about this parameter are updated from firms' and industry peers' comovement between their productivity and consumption growth. The model implies that discount rates rise endogenously with the perceived risk exposure of firms, thereby depressing investment and valuation ratios. We test these predictions in the data and find strong support for them. In particular, we find that cross-sectional learning from peers is crucial in this context and alternative risk estimates, which ignore peer observations, do not predict firm variables.

Naïve Earnings Growth Extrapolation
Cui, Chenyu,Li, Frank Weikai,Zhang, Xinyi
Exploiting the unique financial reporting format in China, we document that stocks with the strongest past year-to-date earnings growth experience a significant price run-up of 1.2% during the five trading days before their quarterly earnings announcements and a significant return reversal of -1.35% in the five trading days afterward. This inverted V-shaped pattern on cumulative return spreads is more pronounced among smaller firms with lower institutional ownership and fewer analyst coverage, and it is less pronounced among foreign B-share. Consistent with investor excess demand driving the price run-up, we find retail investor sentiment and buy-sell order imbalance rise ahead of earnings announcements for firms with high past earnings growth. Our findings support models of fundamental extrapolation and suggest investors naively extrapolate the salient but not-so-informative year-to-date earnings growth when forming expectations about the upcoming earnings.

On Modelling of Crude Oil Futures in a Bivariate State-Space Framework
Peilun He,Karol Binkowski,Nino Kordzakhia,Pavel Shevchenko

We study a bivariate latent factor model for the pricing of commodity fu- tures. The two unobservable state variables representing the short and long term fac- tors are modelled as Ornstein-Uhlenbeck (OU) processes. The Kalman Filter (KF) algorithm has been implemented to estimate the unobservable factors as well as unknown model parameters. The estimates of model parameters were obtained by maximising a Gaussian likelihood function. The algorithm has been applied to WTI Crude Oil NYMEX futures data.

On Option Greeks and Corporate Finance
Chang, Kuo-Ping
This paper has proposed new option Greeks and new upper and lower bounds for European and American options. It shows that because of the put-call parity, the Greeks of put and call options are interconnected and should be shown simultaneously. In terms of the theory of the firm, it is found that both the Black-Scholes-Merton and the binomial option pricing models implicitly assume that maximizing the market value of the firm is not equivalent to maximizing the equityholders’ wealth. The binomial option pricing model implicitly assumes that further increasing (decreasing) the promised payment to debtholders affects neither the speed of decreasing (increasing) in the equity nor the speed of increasing (decreasing) in the insurance for the promised payment. The Black-Scholes-Merton option pricing model implicitly assumes that further increasing (decreasing) in the promised payment to debtholders will: (1) decrease (increase) the speed of decreasing (increasing) in the equity though bounded by upper and lower bounds, and (2) increase (decrease) the speed of increasing (decreasing) in the insurance though bounded by upper and lower bounds. The paper also extends the put-call parity to include senior debt and convertible bond. It specifies the lower bound for risky debt and the conditions under which American put option will not be early exercised.

On optimality of barrier dividend control under endogenous regime switching with application to Chapter 11 bankruptcy
Wenyuan Wang,Xiang Yu,Xiaowen Zhou

Motivated by recent developments in risk management based on the U.S. bankruptcy code, we revisit De Finetti optimal dividend problems by incorporating the reorganization process and regulator's intervention documented in Chapter 11 bankruptcy. The resulting surplus process, bearing financial stress towards the more subtle concept of bankruptcy, corresponds to non-standard spectrally negative Levy processes with endogenous regime switching. In both models without and with fixed transaction costs, some explicit expressions of the expected net present values under a barrier strategy, new to the literature, are established in terms of scale functions. With the help of these expressions, when the tail of the Levy measure is log-convex, the optimal dividend control in each problem is verified to be of the barrier type and the associated optimal barrier can be obtained in analytical form.

On simulation of rough Volterra stochastic volatility models
Jan Matas,Jan Pospíšil

Rough Volterra volatility models are a progressive and promising field of research in derivative pricing. Although rough fractional stochastic volatility models already proved to be superior in real market data fitting, techniques used in simulation of these models are still inefficient in terms of speed and accuracy. This paper aims to present the accurate tools and techniques that could be used also in nowadays largely emerging pricing methods based on machine learning. In particular, we compare three widely used simulation methods: the Cholesky method, the Hybrid scheme, and the rDonsker scheme. We also comment on implementation of variance reduction techniques. In particular, we show the obstacles of the so-called turbocharging technique whose performance is sometimes contra productive. To overcome these obstacles, we suggest several modifications.

On the Parameter Estimation in the Schwartz-Smiths Two-Factor Model
Karol Binkowski,Peilun He,Nino Kordzakhia,Pavel Shevchenko

The two unobservable state variables representing the short and long term factors introduced by Schwartz and Smith in [16] for risk-neutral pricing of futures contracts are modelled as two correlated Ornstein-Uhlenbeck processes. The Kalman Filter (KF) method has been implemented to estimate the short and long term factors jointly with un- known model parameters. The parameter identification problem arising within the likelihood function in the KF has been addressed by introduc- ing an additional constraint. The obtained model parameter estimates are the conditional Maximum Likelihood Estimators (MLEs) evaluated within the KF. Consistency of the conditional MLEs is studied. The methodology has been tested on simulated data.

Peer effects on corporate cash holdings: evidence from Vietnam
Nguyen, Nghia Huu,Li, Wei-Hsien
This research examines the peer effects on cash holdings in Vietnam, an emerging market, and finds a reverse peer effect on them - that is, a firm’s level of cash holdings negatively relates to those of its peers. We also note the reverse peer effects are stronger for firms facing less competition and with low intangibility. Because the Vietnam market has noticeable lower competition and investment in innovation than in developed economics like the U.S., our evidence lend supports for competition and innovation investment positively driving cash holdings’ peer effects and reconciles inconsistencies in the literature. Our findings also support heterogeneity across countries in peer mimicking behavior and contributes to the cash holdings literature for the Vietnam market.

Predicting Stock Index Changes
Wilkens, Sascha
The addition or deletion of companies to/from a stock index has major consequences, with a change in demand from index-tracking investors and funds constituting the most obvious one. Numerous event studies since the 1980s have evidenced the existence of abnormal returns and trading volumes ('index effect') around the announcement and actual change dates for stock indices. This paper presents a model-driven approach to predicting changes in the index membership itself. Index rules are combined with models for the evolution of parameters such as market capitalization that drive a company's potential inclusion or exclusion. Special attention is paid to the inherent model risk. The 2021 revision of Germany's blue-chip and mid-cap indices, DAX and MDAX, both in terms of the number of index members and admission criteria, serves as a case study.

Tax-effect versus income-effect and non-discretionary book to tax differences: Evidence from Tunisia
Kasraoui, Abdelkader,Naoui, Kamel
The difference between the accounting standards and the tax legislation generates a divergence in income calculation process. This study aims to investigate the non-discretionary book to tax differences in the Tunisian context. Using a panel data of 31 Tunisian listed companies on the Tunis Stock Exchange over a period of 2010-2016, we estimate the taxable income for each firm-year to calculate the difference between the book income before tax and the tax income named "Income-effect" and we determine the difference between the theoretical tax on book income before tax and the tax payable named “Tax-effect”.Secondly, we model the book to tax differences by four explanatory variables (Change in Net Sales, Profitability, Change in intangible assets and Dividends received) . Our findings confirm that the “Tax-effect” is a powerful response variable used for the non-discretionary book to tax differences in Tunisia.

Text Semantics Capture Political and Economic Narratives
Elliott Ash,Germain Gauthier,Philine Widmer

Social scientists have become increasingly interested in how narratives -- the stories in fiction, politics, and life -- shape beliefs, behavior, and government policies. This paper provides a novel, unsupervised method to quantify latent narrative structures in text, drawing on computational linguistics tools for clustering coherent entity groups and capturing relations between them. After validating the method, we provide an application to the U.S. Congressional Record to analyze political and economic narratives in recent decades. Our analysis highlights the dynamics, sentiment, polarization, and interconnectedness of narratives in political discourse.

The Development of Financial Economics in France between the Mid-1970s and the Early 1980s: Import or Rediscovery?
Jovanovic, Franck,Numa, Guy
To date, little research has documented the international diffusion of financial economics. Financial economics was supposedly “introduced” in France in the 1970s. Some analysts have argued that it is an American author â€" Leonard J. Savage â€" who allowed French authors to rediscover Louis Bachelier’s work, indicating that “a prophet is not without honor, save in his own country.” The present article challenges this conventional narrative and studies for the first time how financial economics was disseminated in France between the mid-1970s and the early 1980s. It shows that, when financial economics was “imported” from the United States in France in 1970s, some pioneering French contributions have been taught for almost a century. Based on this result, the article explains why the French authors who disseminated these ideas rarely referred to the works of French forerunners. It also clarifies the role of the French economists in this process. All of this suggests that the “import” of financial economics in France was in fact a reintroduction.

The role of relatedness and strategic linkages between domestic and MNE sectors in regional branching and resilience
Mattie Landman,Sanna Ojanperä,Stephen Kinsella,Neave O'Clery

Despite the key role of multinational enterprises (MNEs) in both international markets and domestic economies, there is no consensus on their impact on their host economy. In particular, do MNEs stimulate new domestic firms through knowledge spillovers? Here, we look at the impact of MNEs on the entry and exit of domestic industries in Irish regions before, during, and after the 2008 Financial Crisis. Specifically, we are interested in whether the presence of MNEs in a region results in knowledge spillovers and the creation of new domestic industries in related sectors. To quantify how related an industry is to a region's industry basket we propose two cohesion measures, weighted closeness and strategic closeness, which capture direct linkages and the complex connectivity structure between industries in a region respectively. We use a dataset of government-supported firms in Ireland (covering 90% of manufacturing and exporting) between 2006-2019. We find that domestic industries are both more likely to enter and less likely to leave a region if they are related to so-called 'overlapping' industries containing both domestic and MNE firms. In contrast, we find a negative impact on domestic entry and survival from cohesion to 'exclusive MNE' industries, suggesting that domestic firms are unable to 'leap' and thrive in MNE-proximate industries likely due to a technology or know-how gap. This dynamic was broken, with domestic firms entering MNE exclusive sectors, by a large injection of Brexit diversification funds in 2017-18. Finally, the type of cohesion matters. For example, strategic rather than weighted closeness to exclusive domestic sectors matters for both entries and exits.

Two Investors, Two Trees, Two Goods
Sauzet, Maxime
I characterize the global solution to the portfolio problem of two heterogeneous investors with general preferences, in a two-tree, two-good environment. Investors have recursive preferences and a bias in consumption towards a preferred good. The framework highlights the role of the allocation of wealth across investors for portfolios, asset prices, and risk sharing, an aspect that had received little emphasis in such a setting. The influence of the allocation of wealth grows especially as markets become imperfectly integrated, and as investor heterogeneity rises -- be it through a larger bias in consumption, the introduction of labor income, or asymmetries in preferences -- to the point where it can match or surpass the impact of fundamentals. The framework lends itself to several applications and extensions, e.g. in international or environmental contexts.

Unraveling the Relationship between ESG and Corporate Financial Performance - Logistic Regression Model with Evidence from China
Tian, Lewis
With growing awareness of sustainability, the field of Environmental, Social and Governance (ESG), has been attracting mainstream investors and researchers. Many previous studies have found inconclusive or mixed results on the relationship between ESG ratings and firms’ financial performance, which are mainly attributed to their varied markets, time horizons, and sources of ESG rating. Based on evidence from an emerging market, namely China, this paper examines whether ESG is an adequate indicator for firms’ future financial performance. Given the divergence in ESG rating methodologies, we use ESG data from two ESG rating agencies, one based in China (SynTao) and the other based in Switzerland (RepRisk), for robustness. Specifically, we investigate 377 China A-share companies covered by both agencies and find that ESG rating, albeit divergent due to disparate methodologies, is instrumental in predicting the trend of corporate financial performance (CFP). This work verifies that the forward-looking nature of ESG makes it crucial for firms’ long-term valuation and financial performance in emerging markets. Throughout the research, we observe four issues in the current ESG rating process: the opacity and inaccessibility of source data, the obscurity of ESG rating methodologies adopted by rating agencies, the lack of automated pipeline, and the unannounced historical data rewriting. We believe that the public blockchain ecosystem is promising to address these issues, and we propose future research on the ESG framework for blockchain to call for sustainability focus on this emerging technology.

What do you think about climate finance?
Stroebel, Johannes,Wurgler, Jeffrey
We survey 861 finance academics, professionals, and public sector regulators and policy economists about climate finance topics. They identify regulatory risk as the top climate risk to businesses and investors over the next five years, but they view physical risks as the top risk over the next 30 years. By an overwhelming margin, respondents believe that asset prices underestimate climate risks. We also tabulate opinions about the correlation between growth and climate change; social discount rates appropriate for projects that mitigate the effects of climate change; most influential forces for reducing climate risks; and, most important research topics.