Research articles for the 2020-09-17
arXiv
Pursuing three important elements including economic, safety, and traffic are the overall objective of decision evaluation across all transport projects. In this study, we investigate the feasibility of the development of city interchanges and road connections for network users. To achieve this goal, a series of minor goals are required to be met in advance including determining benefits, costs of implement-ing new highway interchanges, quantifying the effective parameters, the increase in fuel consumption, the reduction in travel time, and finally influence on travel speed. In this study, geometric advancement of Hakim highway, and Yadegar-e-Emam Highway were investigated in the Macro view from the cloverleaf inter-section with a low capacity to a three-level directional intersection of the enhanced cloverleaf. For this purpose, the simulation was done by EMME software of INRO Company. The results of the method were evaluated by the objective of net present value (NPV), and the benefit and cost of each one was stated precisely in different years. At the end, some suggestion has been provided.
SSRN
We consider in detail an investment strategy, titled “The Bounce Basketâ€, designed for someone to express a bullish view on the market by allowing them to take long positions on securities that would benefit the most from a rally in the markets. This investment concept combines macroeconomic views with characteristics of individual securities to beat the market returns. The central idea of this theme is to identity securities from a regional perspective that are heavily shorted and yet are fundamentally sound with at least a minimum buy rating from a consensus of stock analysts covering the securities. We discuss the components of creating such a strategy including the mechanics of constructing the portfolio. Using simulations, in which securities lending data is modeled as geometric brownian motions, we provide a few flavors of creating a ranking of securities to identity the ones that are heaving shorted.
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Congress should......work with the president to reform the federal agencies that were responsible for the country’s fragmented and ineffective response to COVID-19;...ensure that the Strategic National Stockpile is supplied at a level sufficient to meet the immediate needs for medical equipment and supplies that an epidemic such as COVID-19 can be expected to generate;...fund financial incentives that encourage people to be tested for COVID-19, to seek available treatments, to selfâ€â€‹quarantine, and to participate in contract tracing efforts; and...reject efforts to adopt Medicare for All in response to COVID-19 and instead eliminate the tax subsidies that encourage people to obtain health insurance through their employers and let people purchase health insurance that covers only catastrophes.
SSRN
Cultural differences in thought processes (i.e., holistic versus analytic thinking) have been suggested as an explanation for different susceptibility to framing effects. To test this, we conducted an experiment which investigates several framing problems and various measures of cognitive modes of thinking in two countries: Germany and Vietnam. We end clear evidence that holistic thinking style reduces the framing effect in specific tasks while in others it does not. Indeed, this is the primary factor (but maybe not the only one) explaining cultural differences in framing between Germans and Vietnamese. We suggest a theoretical model predicting the task-dependence of this effect. More- over, we observe that demographics can also affect the susceptibility to framing effects. Additional data from Taiwan confirms our results.
arXiv
We discuss a concept denoted as Conformal Prediction (CP) in this paper. While initially stemming from the world of machine learning, it was never applied or analyzed in the context of short-term electricity price forecasting. Therefore, we elaborate the aspects that render Conformal Prediction worthwhile to know and explain why its simple yet very efficient idea has worked in other fields of application and why its characteristics are promising for short-term power applications as well. We compare its performance with different state-of-the-art electricity price forecasting models such as quantile regression averaging (QRA) in an empirical out-of-sample study for three short-term electricity time series. We combine Conformal Prediction with various underlying point forecast models to demonstrate its versatility and behavior under changing conditions. Our findings suggest that Conformal Prediction yields sharp and reliable prediction intervals in short-term power markets. We further inspect the effect each of Conformal Prediction's model components has and provide a path-based guideline on how to find the best CP model for each market.
arXiv
We develop a general class of noise-robust estimators based on the existing estimators in the non-noisy high-frequency data literature. The microstructure noise is a parametric function of the limit order book. The noise-robust estimators are constructed as plug-in versions of their counterparts, where we replace the efficient price, which is non-observable, by an estimator based on the raw price and limit order book data. We show that the technology can be applied to five leading examples where, depending on the problem, price possibly includes infinite jump activity and sampling times encompass asynchronicity and endogeneity.
arXiv
This paper investigates the impact of COVID-19 epidemic on the Chinese stock market crash risk. We first estimate conditional skewness of the return distribution from the GARCH-S model as the proxy of the equity market crash risk for the Shanghai Exchange Stock Market. Then, we construct a fear index for COVID-19 using the data from Baidu Index. Our findings show that the conditional skewness reacts negatively to daily growth in total confirmed cases, indicating that the epidemic increases the crash risk of stock market. Furthermore, we find that the fear sentiment also exacerbates the crash risk. In particular, the fear sentiment plays a significant role in the impact of COVID-19 on the crash risk. When the fear sentiment among people is high, the stock market crash risk is affected by the epidemic more seriously. Evidence from the daily deaths and global cases shows the robustness.
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Central banks sometimes evaluate their own policies. To assess the inherent conflict of interest, we compare the research findings of central bank researchers and academic economists regarding the macroeconomic effects of quantitative easing (QE). We find that central bank papers report larger effects of QE on output and inflation. Central bankers are also more likely to report significant effects of QE on output and to use more positive language in the abstract. Central bankers who report larger QE effects on output experience more favorable career outcomes. A survey of central banks reveals substantial involvement of bank management in research production.
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Grandparenting duties can affect the well-being of the elderly both positively and negatively. This paper disentangles the interactions between grandparenting, quality of life, and life satisfaction in China. Using a panel dataset of 3,205 respondents in three waves of the China Health and Retirement Longitudinal Study (CHARLS) in 2011, 2013, and 2015, we find that grandparents who look after grandchildren are less at risk of depression, receive more financial and in-kind transfers from their children, and report greater life satisfaction than grandparents who do not look after grandchildren. These benefits vary across gender and rural-urban status, however. The positive effect of grandparenting is driven mainly by the direct effect with negligible mediating effect attributable to better quality of life.
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Economic activities have always been organized around certain ideologies, yet little is known about how ideology shapes corporate behavior and how it is different from other political forces. We investigate the impact of politicians’ ideology on corporate policies by exploring a unique setting of ideological change in China from Mao’s ideology to Deng’s around 1978. Using textual analysis based on keywords in People’s Daily, we find a discontinuity in ideological exposure among people who later became city mayors. Those who were at least 18 years old in 1978 and had joined the Chinese Communist Party (CCP) are more likely to have adopted Mao’s ideology, and those who did not join by 1978, due to age limit, but joined soon thereafter were more likely to have adopted Deng’s ideology. This ideological difference has had an enduring effect on contemporary firm and city policies. Firms in cities governed by mayors with Mao’s ideology have made more social contributions, lowered within-firm pay inequality, and pursued less internationalization than those with Deng’s. These effects are stronger in firms with political connections, less state ownership, and more government subsidies as well as in regions that are more market-oriented and not “revolutionary bases.†Our results are robust to OLS regressions with various pair fixed effects besides regression discontinuity. We further find that corporate policies promoted by Mao’s ideology are associated with slower firm growth but greater stakeholder engagement.
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This paper investigates how politicians’ patronage connections affect privatizations in China. The connections to top political leaders (i.e., Central Committee of the Communist Party of China) make local politicians engage more in rent-seeking by selling state-owned enterprises (SOEs) at substantial discounts. These connected local politicians are also more protected in anti-corruption investigations, thus extracting more rents by selling SOE assets at substantial discounts. Consequently, the privatizations conducted by the local politicians with patronage connections achieve significantly lower gains in efficiency and performance. To identify the role of patronage connection in privatization, we use the mandatory retirement age cut-offs of Central Committee members in the regression discontinuity design. We find drops in price discounts of privatization deals and jumps in efficiency for privatized SOEs when local politicians lose connections to Central Committee members around the retirement age cut-offs.
SSRN
In the presence of inter-industry wage differentials, the value of portfolio choice varies across otherwise identical households employed in different industries. I solve a dynamic portfolio choice model for 72 industries using 30 years of data and investigate the impact of the joint distribution of earnings growth and stock returns on certainty equivalent consumption. I find that inequality in certainty equivalent consumption mirrors inequality in initial earnings. Cross-sectional heterogeneity in certainty equivalent consumption is explained by variation in the covariance structure of earnings growth and stock returns and kurtosis of earnings growth. Cyclical variation in industry-specific earnings risk is inconsequential.
arXiv
Cryptocurrencies (CCs) have risen rapidly in market capitalization over the last years. Despite striking price volatility, their high average returns have drawn attention to CCs as alternative investment assets for portfolio and risk management. We investigate the utility gains for different types of investors when they consider cryptocurrencies as an addition to their portfolio of traditional assets. We consider risk-averse, return-seeking as well as diversificationpreferring investors who trade along different allocation frequencies, namely daily, weekly or monthly. Out-of-sample performance and diversification benefits are studied for the most popular portfolio-construction rules, including mean-variance optimization, risk-parity, and maximum-diversification strategies, as well as combined strategies. To account for low liquidity in CC markets, we incorporate liquidity constraints via the LIBRO method. Our results show that CCs can improve the risk-return profile of portfolios. In particular, a maximum-diversification strategy (maximizing the Portfolio Diversification Index, PDI) draws appreciably on CCs, and spanning tests clearly indicate that CC returns are non-redundant additions to the investment universe. Though our analysis also shows that illiquidity of CCs potentially reverses the results.
SSRN
I look at the cryptocurrency market through the prism of standard multifactor asset-pricing models with particular attention to the downside market risk. The analysis for 1,700 coins reveals that there is a significant heterogeneity in the exposure to the downside market risk, and that a higher downside risk exposure is associated with higher average returns. The extra downside risk is priced with a statistically significant premium in cross-sectional regressions. Adding the downside risk component to the CAPM and the 3-factor model for cryptocurrencies improves the explanatory power of the models significantly. The downside risk is orthogonal to the size and momentum risks and constitutes an important forth component in the multifactor cryptocurrency pricing model.
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Corporate dividends cluster on increments of 5, like 25, 50, and 75. Firms that pay dividends on these `prominent' amounts have lower operating performance and five-factor alphas 60 b.p. per year lower. Consistent with agency frictions that reduce managerial effort and lead to lazy decisions, we find that clustering effects are stronger for entrenched firms, with more market power, and low levels of shareholder activism. Dividend increases also tend to cluster more than cuts, consistent with saliency bias. Our results complement a number of recent studies showing the economic importance of simple decision heuristics.
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We study financial returns on alternative collectible investment assets â€" toys - using LEGO sets as an example. Such iconic toys with diminishing over time supply and high collectable values appear to yield high returns on the secondary market. We find that LEGO investments outperform large stocks, bonds, gold and other alternative investments, yielding the average return of at least 11% (8% in real terms) in the sample period 1987-2015. LEGO returns are not exposed to market, value, momentum and volatility risk factors, but have an almost unit exposure to the size factor. A positive multifactor alpha of 4-5%, a Sharpe ratio of 0.4, a positive return skewness and a low exposure to standard risk factors make the LEGO toy and other similar collectibles an attractive alternative investment with a good diversification potential.
SSRN
This paper develops a theory in which heterogeneity in bank capital choices arises in a general equilibrium despite ex ante identical banks. In a future state, the credit market is partially frozen in a crisis - high-capital banks have continued access to funding liquidity but low-capital banks do not. Inter-bank trading in legacy assets allows some frozen banks to sell assets to banks with “financial muscle†to obtain funding. Consequently, there is a reallocation of access to market funding from low-capital to high-capital banks. Inter-bank trading unfreezes the market without government intervention.
arXiv
It is argued that Marxism, being based on contradictions, is an illogical method. More specifically, we present a rejection of Marx's thesis that the rate of profit has a long-term tendency to fall.
arXiv
This paper studies a variation of the continuous-time mean-variance portfolio selection where a tracking-error penalization is added to the mean-variance criterion. The tracking error term penalizes the distance between the allocation controls and a refe\-rence portfolio with same wealth and fixed weights. Such consideration is motivated as fo\-llows: (i) On the one hand, it is a way to robustify the mean-variance allocation in case of misspecified parameters, by "fitting" it to a reference portfolio that can be agnostic to market parameters; (ii) On the other hand, it is a procedure to track a benchmark and improve the Sharpe ratio of the resulting portfolio by considering a mean-variance criterion in the objective function. This problem is formulated as a McKean-Vlasov control problem. We provide explicit solutions for the optimal portfolio strategy and asymptotic expansions of the portfolio strategy and efficient frontier for small values of the tracking error parameter. Finally, we compare the Sharpe ratios obtained by the standard mean-variance allocation and the penalized one for four different reference portfolios: equal-weights, minimum-variance, equal risk contributions and shrinking portfolio. This comparison is done on a simulated misspecified model, and on a backtest performed with historical data. Our results show that in most cases, the penalized portfolio outperforms in terms of Sharpe ratio both the standard mean-variance and the reference portfolio.
SSRN
Mutual funds are captives of the investment management firms, also known as fund sponsors, that bring them into existence and provide for their day-to-day operations. Because fund sponsors exercise complete control over the operations of their funds, the possibility arises that a fund sponsor will use its position of control to obtain advisory fees that are greater than those that would have been established by arm’s length bargaining. A fundamental responsibility of independent mutual fund directors, which serve as watchdogs over the interests of mutual fund shareholders, is to ensure that advisory fees are reasonable in light of, among other factors, economies of scale and profitability realized by a fund sponsor. Yet, despite oversight by independent directors, this paper shows that many mutual fund sponsors have been able to maintain high advisory fees, and have realized increasing levels of economies of scale and profitability, as industry assets increased more than 600% between 1995 and 2018. The nub of the issue is that the methodologies used to calculate profitability have largely evaded meaningful scrutiny by fund boards, which are typically advised that there is no “right answer†when it comes to a methodology. Yet, sponsors are keenly aware that litigation risk arising from excessive profitability could force advisory fee decreases on large and highly profitable funds, and therefore are incentivized to use inappropriate cost allocation methods to understate profit margin. Vigilant fund directors should recognize this potential conflict and rectify the situation, but this has not happened. This paper explores profit margins, scale economies, cost allocation methodology and case law in depth. It identifies two large fund complexes with unambiguously inappropriate cost allocation methodologies and presents circumstantial evidence of widespread use of such practices in the industry.
SSRN
This paper discusses the determinants of corporate environmental disclosure by industrial Saudi listed firms. Using a sample of 63 industrial firms listed in Saudi Arabia between 2016 and 2018 and a fixed effect panel data, we test the effect of corporate governance variables, firms' characteristics and CEOs’ financial education on the level of environmental information disclosure. Two measures of corporate environmental disclosure are used based on Global Reporting Initiative and the content analysis technique. Our results show that the presence of environmental committee and the firm’s age are the most relevant factors that can influence the corporate environmental disclosure in annual reports in the Saudi context. In order to urge Saudi firms to pay more attention to the environment and adopt strategies to conserve it as well as disclose environmental information, it is suggested that decision makers change the nature of the environmental committee from an optional committee to a mandatory committee.
arXiv
Optimal execution, i.e., the determination of the most cost-effective way to trade volumes in continuous trading sessions, has been a topic of interest in the equity trading world for years. Electricity intraday trading slowly follows this trend but is far from being well-researched. The underlying problem is a very complex one. Energy traders, producers, and electricity wholesale companies receive various position updates from customer businesses, renewable energy production, or plant outages and need to trade these positions in intraday markets. They have a variety of options when it comes to position sizing or timing. Is it better to trade all amounts at once? Should they split orders into smaller pieces? Taking the German continuous hourly intraday market as an example, this paper derives an appropriate model for electricity trading. We present our results from an out-of-sample study and differentiate between simple benchmark models and our more refined optimization approach that takes into account order book depth, time to delivery, and different trading regimes like XBID (Cross-Border Intraday Project) trading. Our paper is highly relevant as it contributes further insight into the academic discussion of algorithmic execution in continuous intraday markets and serves as an orientation for practitioners. Our initial results suggest that optimal execution strategies have a considerable monetary impact.
arXiv
In behavioural economics, a decision maker's preferences are expressed by choice functions. Preference robust optimization (PRO) is concerned with problems where the decision maker's preferences are ambiguous, and the optimal decision is based on a robust choice function with respect to a preference ambiguity set. In this paper, we propose a PRO model to support choice functions that are: (i) monotonic (prefer more to less), (ii) quasi-concave (prefer diversification), and (iii) multi-attribute (have multiple objectives/criteria). As our main result, we show that the robust choice function can be constructed efficiently by solving a sequence of linear programming problems. Then, the robust choice function can be optimized efficiently by solving a sequence of convex optimization problems. Our numerical experiments for the portfolio optimization and capital allocation problems show that our method is practical and scalable.
arXiv
We use an optimization procedure based on simulated bifurcation (SB) to solve the integer portfolio and trading trajectory problem with an unprecedented computational speed. The underlying algorithm is based on a classical description of quantum adiabatic evolutions of a network of non-linearly interacting oscillators. This formulation has already proven to beat state of the art computation times for other NP-hard problems and is expected to show similar performance for certain portfolio optimization problems. Inspired by such we apply the SB approach to the portfolio integer optimization problem with quantity constraints and trading activities. We show first numerical results for portfolios of up to 1000 assets, which already confirm the power of the SB algorithm for its novel use-case as a portfolio and trading trajectory optimizer.
SSRN
We consider how state income tax changes affect the demand for municipal bonds by in-state investors. A tax increase (decrease) makes investing in municipal bonds more (less) desirable, and theory predicts a change in demand by investors until the yields on municipal bonds reach a new equilibrium. Using a sample of state-specific municipal bond funds, we find states with tax decreases have net outflows in the following year of almost 1.54% per percentage point drop in tax rates, while tax increases lead to inflows around 0.58%. We find that the response to tax changes is not the immediate reallocation predicted in perfect markets with no frictions.
arXiv
Systemic liquidity risk, defined by the IMF as "the risk of simultaneous liquidity difficulties at multiple financial institutions", is a key topic in macroprudential policy and financial stress analysis. Specialized models to simulate funding liquidity risk and contagion are available but they require not only banks' bilateral exposures data but also balance sheet data with sufficient granularity, which are hardly available. Alternatively, risk analyses on interbank networks have been done via centrality measures of the underlying graph capturing the most interconnected and hence more prone to risk spreading banks. In this paper, we propose a model which relies on an epidemic model which simulate a contagion on the interbank market using the funding liquidity shortage mechanism as contagion process. The model is enriched with country and bank risk features which take into account the heterogeneity of the interbank market. The proposed model is particularly useful when full set of data necessary to run specialized models is not available. Since the interbank network is not fully available, an economic driven reconstruction method is also proposed to retrieve the interbank network by constraining the standard reconstruction methodology to real financial indicators. We show that the contagion model is able to reproduce systemic liquidity risk across different years and countries. This result suggests that the proposed model can be successfully used as a valid alternative to more complex ones.
SSRN
The end of communism in the 1990s probably is the most fundamental restructuring of institutions witnessed in recent history. At its core was the large-scale redistribution of previously state-owned companies. We construct a unique firm-level dataset to study this redistribution in East Germany where the entire state-owned economy was either privatized or liquidated within less than five years. We examine whether the privatization authority followed its mandate to privatize competitive firms using initial labor productivity to indicate firms’ competitiveness. Our results highlight that firms with higher baseline productivity are more likely to be privatized, yield higher sales prices, are more often acquired by West German investors, and are more likely to remain in business even 20 years after leaving public ownership. The privatization agency plausibly contributed to these outcomes by rating and prioritizing productive firms.
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Shadow insurance is a regulatory loophole exploited by certain insurance groups to increase risk exposure, potentially destabilizing the financial system. In this paper, we evaluate the contribution of shadow insurance to systemic risk of the global financial sector using a sample of 215 international insurance entities covering the 2004-2017 period. We detect shadow insurance by examining every reinsurance agreement on the Schedule S filings. Using both DCoVaR and SRISK measures, we find that the practice of shadow insurance is a significant driver of global systemic risk.
SSRN
We provide a comprehensive study on the cross-sectional predictability of corporate bond returns using big data and machine learning. We examine whether a large set of equity and bond characteristics drive the expected returns on corporate bonds. Using either set of characteristics, we find that machine learning methods substantially improve the out-of-sample predictive power for bond returns, compared to the traditional linear regression models. While equity characteristics produce significant explanatory power for bond returns, their incremental predictive power relative to bond characteristics is economically and statistically insignificant. Bond characteristics provide as strong forecasting power for future equity returns as using equity characteristics alone. However, bond characteristics do not offer additional predictive power above and beyond equity characteristics when we combine both sets of predictors.
SSRN
This study investigates the impact of corporate bonds issued by Greek listed firms on employment. Even though external financing and the effects on employment has been studied in the literature, we extend the existing literature by focusing for the first time on the specific role of corporate bonds on employment. Our empirical analysis is based on a panel dataset from 2001 to 2014 and we examine the effect of corporate bonds in the pre- and post-period of the Greek economic crisis, in which the banking system is vulnerable and unable to provide financing to the firms. The results suggest that corporate bonds have a positive effect on employment in the pre-crisis sample, denoting that firms hire employees and proceed to investment choices. On the contrary, during the recession, corporate bonds have a negative effect on employment. Firms reduce their costs and try to control their debt obligations by issuing corporate bonds.
SSRN
This paper uses granular data on syndicated loans to analyse the impact of international reforms for Global Systemically Important Banks (G-SIBs) on bank lending behavior. Using a difference-in-differences estimation strategy, we find no effect of the reforms on overall credit supply, while at the same time documenting a substantial decline in borrower- and loan-specific risk factors for the affected banks. Moreover, we detect a significant decline in the pricing gap between interest rates charged by G-SIBs and other banks, which we interpret as indirect evidence for a reduction in funding cost subsidies. Overall, our results suggest that the G-SIB reforms have helped to mitigate moral hazard problems associated with systemically important banks, while the consequences for the real economy have been limited.
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A crucial decision for large corporations is how profits created by corporate activity should be distributed among different corporate stakeholders. This article posits that public policy should recognize employees as key contributors to corporate value-creation. One approach is to require the creation of Employee Ownership Funds (EOFs), mandatory employee equity ownership trusts established at large corporations, which would pay employees dividends and establish a collective employee voice in corporate governance. The EOFs may reduce economic inequality while improving firm performance and macroeconomic stability. This article provides an original estimate of employee dividends, illustrating the potential of Employee Ownership Funds. Based on historic dividend payments and employee counts in public 10-K filings, I find that, if EOFs held twenty percent of outstanding equity, the average employee dividend across this sample would be $2,622 per year, while the median is $1,760. This indicates that employee dividends can be a small but meaningful form of redressing wealth inequality for the low-wage workforce, though it should emphatically not be seen as a replacement for fair wages.
SSRN
The main purpose of this research is to find out the relationship between capital structure (debt-equity) as and Profitability of the listed cement companies in Pakistan Stock Exchange. Further specific objective is to find out relation of debt equity with gross profit, earning per share, and return on capital and return on equity. The sample is taken from 10 cement companies which are listed on Pakistan stock exchange. The secondary data is taken from 2011 to 2018 (i.e. 8 years). Mean and standard deviation of all ratios and Pearson product correlation analysis is performed with the help of Eviews 9 to find the relationship between capital structure and profitability. This research determines that debt / equity (Capital Structure) is adversely linked with the profitability, it suggests that decrease in the profitability of the organizations is due to increase in debt capital & vice versa
SSRN
We examine the role of female leadership in reducing the incidence of workplace sexual harassment. We estimate the incidence rate of sexual harassment through textual analysis of employees’ job reviews, published online during the period 2011-2017. We find that firms with a higher proportion of women on the board of directors experience less sexual harassment. An increase of one female director is associated with an 18.2% decrease in the sexual harassment rate. The effect is both statistically and economically significant and is not limited to female directors as we find similar results with female CEO and executives. The mechanism for reduced sexual harassment is linked to overall improved social policies. Our results are robust to several adjustments for endogeneity concerns.
arXiv
Using machine learning and alternative data for the prediction of financial markets has been a popular topic in recent years. Many financial variables such as stock price, historical volatility and trade volume have already been through extensive investigation. Remarkably, we found no existing research on the prediction of an asset's market implied volatility within this context. This forward-looking measure gauges the sentiment on the future volatility of an asset, and is deemed one of the most important parameters in the world of derivatives. The ability to predict this statistic may therefore provide a competitive edge to practitioners of market making and asset management alike. Consequently, in this paper we investigate Google News statistics and Wikipedia site traffic as alternative data sources to quantitative market data and consider Logistic Regression, Support Vector Machines and AdaBoost as machine learning models. We show that movements in market implied volatility can indeed be predicted through the help of machine learning techniques. Although the employed alternative data appears to not enhance predictive accuracy, we reveal preliminary evidence of non-linear relationships between features obtained from Wikipedia page traffic and movements in market implied volatility.
SSRN
Mergers and Acquisitions (M&A) have become a central instrument of organizational development. Consequently, research on M&A has developed into a complex research area of management science in recent years. However, the different perspectives are so heterogeneous that a holistic view is often difficult to achieve. The present research paper aims to take a holistic view of M&A research and, based on a bibliometric analysis, to allocate the various studies to research clusters, to map interrelationships between documents, authors, countries, and institutions and to trace the development of M&A research over time. For this purpose, a sample of 580 articles from 9 leading management science journals was bibliometrically examined and a total of 42,630 citations and 18,734 unique references were considered for the years 1963â€"2019.
