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This study aims to integrate entrepreneurship theories and acculturation perspectives into a unified lens to understand opportunity development by transnational entrepreneurs (TNEs).

This study uses a conceptual method, considering how acculturation strategies of TNEs influence cross-cultural arbitrage.

We develop six propositions that define how acculturation strategies relate to different levels of cultural embeddedness of transnational entrepreneurs and ultimately influence the process by which the entrepreneur engages in cross-cultural arbitrage.

We are one of the first to integrate the sociology of immigrants with entrepreneurship to better understand how TNEs engage in cross-cultural arbitrage.

This paper aims to highlight firms' profitability as an alternative channel by which changes in leverage could affect stock returns in an imperfect market setting. The author also analytically argues that the benefits of debt, if any, may accrue beyond the usual tax benefit channel.

The author used multivariate regression models based on firms' characteristics and the models' changes along with a two-stage least-square (2SLS) type procedure to estimate the impact of leverage changes on stock returns. The author controls for the varying arbitrage risk that is measured by forecasted idiosyncratic volatility of stock prices and overcome simultaneous or endogenous determination by using inter-temporal non-synchronous variation in leverage and control variables.

The author finds that increase in leverage increase (decrease) stock returns for firms with the gross operating profitability higher (lower) than the cost of debt. The author also finds that the variation in arbitrage risk does not substitute for the primary effect of leverage changes on stock returns.

The author's findings provide tacit support to the recent literature attempting to resolve the empirically puzzling pattern of the negative relationship between profitability and leverage. The findings suggest inclusion of profitability as a crucial asset-pricing factor in the contemporary empirical models.

The non-trivial role of profitability in determining the effect of leverage on firms' stock returns that may be useful to managers, credit analysts and policy makers to assess the impact of net profitability on any change in leverage and its ensuing consequences on firms' value.

The paper develops analytical insights into the marginal role of profitability in influencing the relationship between firms' financing decisions and firms' stock returns beyond the conventional mechanisms of tax benefits, bankruptcy costs and information asymmetry.

In this study, we investigate what drives the MAX effect in the South Korean stock market. We find that the MAX effect is significant only for overpriced stocks categorized by the composite mispricing index. Our results suggest that investors' demand for the lottery and the arbitrage risk effect of MAX may overlap and negate each other. Furthermore, MAX itself has independent information apart from idiosyncratic volatility (IVOL), which assures that the high positive correlation between IVOL and MAX does not directly cause our empirical findings. Finally, by analyzing the direct trading behavior of investors, our results suggest that investors' buying pressure for lottery-like stocks is concentrated among overpriced stocks.

The study explores the evolution of Indian domestic electronics manufacturing post-economic reforms and also investigates the lack of natural growth stages among Indian start-up/SME electronics manufactures.

The theoretical framework is inspired by Dawar and Frost's survival strategy theory that local companies may follow to overcome competitive threats from MNCs. The study adopts a qualitative methodology, more precisely, a phenomenological approach to walking through policy/regulatory reforms amid market distortions, technological gaps and colonial mindset from the perspective of Indian domestic electronics manufacturers. The study has adopted Gioia method of data analysis to inductively suggest a few research propositions.

The phenomenological approach revealed eight essential structure (essence) narratives to explore the complex issue that plague the industry: make in India, made in India, preferential market access strategy, equitable market access strategy, blue ocean strategy, competitive positioning strategy, technical capability and importance of policy/regulatory arbitrage.

The situation of Indian electronics manufacturing units is comparable to the bonsai tree situation, where natural evolution in business stages does not exist; they are born and die as start-ups/MSMEs. The study advocates for equitable market access by removing market distortions. The long-term solution may lie in making available locally manufactured products as a dependable alternative to the imported products or produced locally by MNC OEMs in terms of cost, quality, technology, volume, after-sale service and integrated supply chain.

While the favorable FDI policies, digital India and make-in India initiatives have strengthened domestic electronics production, it is yet to significantly impact India's position in global trade, including manufacturing and exports.

This study aims to analyze the efficient market hypothesis (EMH) of cryptocurrencies on multiple platforms by observing whether there is a discrepancy in the levels of efficiency between different exchanges. Additionally, EMH is tested in a multivariate way: whether the prices of the same cryptocurrencies traded on different exchanges are temporally related to each other. ADF and KPSS tests, whereas the vector autoregression model of order p – VAR(p) – for multivariate system.

Both Bitcoin and Ethereum show efficiency in the weak form on the main platforms in each market alone. However, when estimating a VAR(p) between prices among exchanges, there was evidence of Granger causality between cryptocurrencies in all exchanges, suggesting that EMH is not adequate due to cross information.

It is essential to assess the cryptocurrency market in a multivariate way, not only to favor its maturation process, but also to promote a broad understanding of its inherent risks. Thus, it will be possible to develop financial products that are actively managed in a more sophisticated cryptocurrency market.

There is a possibility of performing arbitrage on different exchanges and market assets through cross-exchanges. Thus, emphasizing the need for regulation of exchanges in the digital asset market, as an eventual price manipulation on a single platform can impact others, which generates various distortions.

This study is the first to find evidence of cross-information for the same (and other) cryptocurrencies among different exchanges.

This study seeks to investigate role of the coronavirus disease 2019 (COVID-19) pandemic on clean energy stocks for the United States for the period 21 January 2020–16 August 2021.

At the empirical stage, the Fourier-augmented vector autoregression approach has been used.

According to the empirical results, the response of the clean energy stocks to the feverish sentiment, lockdown stringency, oil volatility, dirty assets, and monetary policy dies out within a short period of time. In addition, the authors find that there is a unidirectional causality from the feverish sentiment index and the lockdown stringency index to the clean energy stock returns; and from the monetary policy to the clean energy stocks. At the same time, there is a bidirectional causality between the lockdown stringency index and the feverish sentiment index. The empirical findings can be helpful to both practitioners and policy-makers.

Among the COVID-19 variables used in this study is a new feverish sentiment index, which has been constructed using principal component analysis. The importance of the feverish sentiment index is that it allows us to examine the impact of the aggregate level of fear in the economy on clean energy stocks.

This study analyzes the impact of the information environment (IE) and credit default swap (CDS) transaction costs on information transmission between the stock and CDS markets. Using the daily regression analysis on the Korean firm’s stock and CDS data from 2004 to 2023, the results show that companies with superior IE in the stock market exhibit a larger and more sensitive total information flow from the stock market to the CDS market. Companies with lower transaction costs in the CDS market demonstrate faster information flow. In the case of companies with superior IE, fundamental information is reflected in stock prices with high weight and thus the CDS spreads change reflecting information about stock prices. According to this study’s findings, the primary factor influencing the information flow from the stock market to the CDS market is the information environment of the company in the stock market, rather than transaction costs in the CDS market.

This study aims to examine the relationship between investor gambling preferences and stock returns, using data for all firms listed in Shanghai A-share market during 2016 and 2021.

This study employs price and trading volume data to capture the behavioral characteristics and gambling preferences of investors. Using the Fama-French three-factor and five-factor models to estimate benchmark returns, this study investigates whether investing in gambling stocks can yield positive excess returns.

The study reveals that stocks identified as gambling stocks generate high returns in the month they are identified as such but subsequently experience a significant drop in excess returns compared to non-gambling stocks over the following one to six months. These results are found to be consistent across different methods used to classify gambling stocks and across various industry sectors.

This research provides insights into the risk-return tradeoff of different stock types and the factors that fuel irrational investment behavior. This research underscores the importance of considering the behavioral elements of investment, particularly in emerging markets where individual investors have a significant impact.

This study advises investors to avoid adopting a gambler or speculative mindset and instead make well-informed and calculated investment decisions that are in line with investors financial objectives and risk appetite. This approach can help create a more stable and sustainable financial market.

This study provides new evidence on the relationship between gambling preferences and future stock returns in financial markets and sheds new light on the important role of irrational factors in investment decisions.

The purpose of this paper is to propose a novel and new direct measurement of small investor sentiment in the equity market. The sentiment is based on the individual investors’ internet search activity.

The author measures unexpected changes in the small investor sentiment with AR (1) process, where the residuals capture the unexpected changes in small investor sentiment. The author employs vector autoregressive, Granger causality and linear regression models to estimate the association between the unexpected changes in small investor sentiment and future equity market returns.

An unexpected increase in the search popularity of the term bear market is negatively associated with the following week’s equity market returns. An unexpected increase in the spread (the difference in popularities between a bull market and a bear market) is positively associated with the following week’s equity market returns. The author finds that these effects are stronger for small-sized companies.

By author’s knowledge, the paper is the first that measures the small investor sentiment that is based on the internet search activity for keywords used in the American Association of Individual Investor’s (AAII) survey questions. The paper proposes an alternative small investor sentiment measure that captures the changes in small investor sentiment in more timely fashion than the AAII survey.

The study aims to test prospect theory (PT) predictions in the cryptocurrency (CC) market. It proposes a new asset pricing model that explores the potential of prospect theory value (PTV) as a significant predictor of CC returns.

The study comprehensively analyses a large sample set of 1,629 CCs, representing more than 95% of the CC market. The study uses a portfolio analysis approach, employing univariate and bivariate sorting techniques with equal-weighted and value-weighted portfolios. The study also employs ordinary least squares (OLS) regression, panel data methods and quantile regression (QR) to estimate the models.

This study demonstrates an average inverse relationship between PTV and CC returns. However, this relationship exhibits asymmetry across different quantiles, indicating that investor reactions vary based on market conditions. Moreover, PTV provides more robust predictions for smaller CCs characterized by high volatility and illiquidity. Notably, the findings highlight the dominant role of the probability weighting (PW) component in PT for predicting CC behaviors, suggesting a preference for lottery-like characteristics among CC investors.

The study is one of the early studies on CC price dynamics from the PT perspective. The study is the first to apply a QR approach to analyze the cross-section of CCs using a PT-based asset pricing model. The results shed light on CC investors' decision-making processes and risk perception, offering valuable insights to regulators, policymakers and market participants. From a practical perspective, a trading strategy centered around the PTV effect can be implemented.