Big Data, Proxies, Algorithmic Decision‐Making and the Future of Management Theory

Posted on by

Abstract

The future of theory in the age of big data and algorithms is a frequent topic in management research. However, with corporate ownership of big data and data processing capabilities designed for profit generation increasing rapidly, we witness a shift from scientific to ‘corporate empiricism’. Building on this debate, our ‘Point’ essay argues that theorizing in management research is at risk now. Unlike the ‘Counterpoint’ article, which portrays a bright future for management theory given available technological opportunities, we are concerned about management researchers increasingly ‘borrowing’ data from the corporate realm (e.g., Google et al.) to build or test theory. Our objection is that this data borrowing can harm scientific theorizing due to how scaling effects, proxy measures and algorithmic decision-making performatively combine to undermine the scientific validity of theories. This undermining occurs through reducing scientific explanations, while technology shapes theory and reality in a profit-predicting rather than in a truth-seeking manner. Our essay has meta-theoretical implications for management theory per se, as well as for political debates concerning the jurisdiction and legitimacy of knowledge claims in management research. Practically, these implications connect to debates on scientific responsibilities of researchers.

An Econometric Study on Volatility Clusters, Dynamic Risk Return Relationship, and Asymmetry in Bitcoin Returns

Posted on by
Business Perspectives and Research, Ahead of Print.
The most sought-after cryptocurrency sector is facing dicey environment in India due to stringent ideology of its government that put Indian investors in dilemma in envisaging this sector as a virtuous investment avenue. The investors are very curious for this sector and their curiosity aroused the need for its evaluation in terms of risk-return dynamics in contemporary scenario. The present study is an endeavor to econometrically explore volatility clusters, dynamic risk return relationship, and asymmetry in Bitcoin return series covering the period from August 2010 to February 2022. The results of Augmented Dickey–Fuller test, Ng–Perron tests, Ljung Box Q test, Engle’s ARCH, and White test asserted that the Bitcoin return series is stationary and has apparent volatility clusters in it. The estimates from GARCH-M model confirmed the absence of risk return relationship and the estimates from ARMA-EGARCH model confirmed the presence of asymmetry (leverage effect) in Bitcoin return series. However, the results of ARMA-TARCH model confirmed the absence of asymmetry in the series and further diagnostic checking asserted that ARMA- TARCH model is the best fitted model. These estimations may help the investors in comprehending risk-return dynamics of investment in Bitcoins for framing better hedging strategy in contemporary scenario.

Climate risk and audit fees: An international study

Posted on by

Abstract

Using a comprehensive global sample, we find that climate risk positively relates to audit fees. Specifically, auditors charge higher fee premiums when firms are located in countries with more stringent auditing regulations, higher information opacity and less adaptive capacity for climate risk. Audit fee premiums are also higher when firms are incentivised to manipulate earnings, less important to auditors, and audited by short-tenured and industry-specialised auditors. Our study provides worldwide evidence that climate risk induces more earnings management and increases the efforts of auditors in the auditing process, resulting in higher audit fees.

Investor attention and the predictability of the volatility of CNY‐CNH spreads: Evidence from a GARCH‐MIDAS model

Posted on by

Abstract

Combining the four aspects of self-, macro, environmental, and policy attention, using backward-looking rolling regressions, we construct novel international and domestic investor-attention indices using the search volume index from Google Trends together with Baidu Index to investigate how investor attention affects the CNY-CNH spreads volatility. Moreover, comparing different GARCH-MIDAS models and conventional GARCH-type models is conducted concerning the out-of-sample volatility forecasting capability. Our results show that: (i) international and domestic investor attention has a positive impact; and (ii) the GARCH-MIDAS models involving investor attention improve forecast accuracy. In particular, the model with domestic investor attention has an advantage in forecasting.

Institutional investors’ corporate site visits and resource extraction: Evidence from China

Posted on by

Abstract

This study examines the effect of corporate site visits on resource extraction. Taking advantage of China's mandatory disclosure of detailed investors' site visits information, we find that firms with more investors' site visits have lower levels of managerial private consumption and tunnelling. This association is more pronounced when the monitoring effect of corporate site visits is more efficient, and the agency problem is more severe. We utilise the two-stage least squares (2SLS) estimation approach to demonstrate the robustness of our results. Collectively, our findings highlight the external monitoring role of investors' site visits in reducing corporate agency conflicts.

Arbitrage across different Bitcoin exchange venues: Perspectives from investor base and market related events

Posted on by

Abstract

This paper examines the impact of market related events and investor base on the spread of Bitcoin prices between two exchange platforms, Coinbase and Binance. Based on high-frequency data samples collected from 2019 to 2021, we show how investors from different bases react differently to market related events, which create the price spreads between exchange platforms. We also identify the arbitrage opportunities these spreads create and establish arbitrage strategies for all identified events to exploit the variations in Bitcoin prices traded on both platforms. Findings indicate arbitrage offers profits that are higher overall than holding Bitcoin on either platform.