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The purpose of this paper is to explore the effect of venture capital (VC) funding as a form of ownership on lobbying strategies of venture-backed companies.

The sample consists of venture-backed IPO companies between 1999 and 2014. The authors collected IPO data from the Thompson Securities Data Company (SDC) database. The authors collected VC data from SDC VentureXpert database and lobbying data from the Center for Responsive Politics database (opensecrets.org).

Consistent with the hypotheses, the authors find that VC-backed companies spend less on lobbying compared to non-VC-backed counterparts. However, this relationship is moderated by companies’ R&D intensity. R&D intensive VC-backed companies choose to spend more on lobbying.

The research indicates that although VC backing has a negative impact on lobbying efforts, R&D intensity creates an incentive for VC-backed companies to spend more on lobbying in order to shape public policy to their benefit. The study consists of VC-backed companies that are public. The authors believe that future research can explore political strategies of VC-backed companies during their pre-IPO stage.

The authors believe that political strategies are powerful yet underutilized resources that VC-backed companies can rely on to shift industries and invest in innovative products that challenge norms and fight the status quo. Lobbying and other forms of political involvement can help them shape public policy.

To the best of the authors’ knowledge, the study makes a unique contribution to the literature by exploring the political strategies of VC-backed companies.

The purpose of this study is to investigate how proximity to metropolitan areas and local creative talent impact a company’s access to venture capital (VC). We analyze the interplay between these factors and test our hypotheses using USA county data.

This empirical study uses multivariate regression analyses to analyze VC investment distribution across the USA at the county level between the years 1990–2011.

Our findings suggest that an increase in the local creative workforce correlates with higher levels of VC funding, regardless of metro location, but has a more significant impact in metro areas, indicating the complementary nature of these factors. Furthermore, the tech industry benefits more from the local creative workforce and is less sensitive to geographic location. Our results suggest that non-metro locations with a rich local creative culture can be as effective in attracting VC as metro locations with a mediocre local creative culture. This study contributes to our understanding of the optimal geographic location for companies seeking VC.

One of the limitations of our research is the research timeline. Since “creative class” was not measured by the U.S. Department of Agriculture (USDA) after 2011, we cannot analyze the recent effects of creative class on VC. However, given the fact that technology-related industries increasingly dominated the VC industry in recent years, our results on tech-related industries can shed light on the future expectations of the creative class in the VC industry moving forward.

Some companies might find it advantageous to locate outside metro areas where the creative workforce is more abundant and accessible. Our results support this trend by demonstrating that companies must consider the tradeoff between these two factors and recognize that locating in metro areas may not always be the optimal choice for every company. A tradeoff may exist between location and the cost of accessing creative talent.

Our results suggest that non-metro locations with a rich local creative culture can be as effective in attracting VC as metro locations with a mediocre local creative culture.

The existing literature emphasizes the importance of studying various factors that can help distribute VC and entrepreneurial activities across the country instead of just being concentrated in specific areas like metro regions. Although previous studies have examined broader institutional and country-level factors, local creative culture has not been considered in the context of its impact on the geographical distribution of VC. Our research highlights creative culture as a new local factor that affects VC distribution among USA counties.

The purpose of this paper is to analyze the implications of the target valuation uncertainty on the wealth distribution between the target and acquirer firms in successful mergers. The paper specifically analyzes the division of the total dollar gains between the two parties and also whether the target and/or the acquirer experience a positive/negative gain in mergers when valuation of the target company is more uncertain.

The analyses contrast the implications of the uncertainty in three well‐known merger hypotheses; the market‐for‐corporate‐control, hubris and synergy.

The results are supportive of the implications of the synergy hypothesis. As target valuation uncertainty decreases, it is more likely that both parties experience positive gains from the transaction although more of the gains from the merger significantly shift towards the target company.

Results suggest that both parties are bargaining on the synergy gains and the target is able to negotiate a greater portion of the synergy gains when the value of the target becomes more predictable.

This study examines the prediction power of investor sentiment on Bitcoin return.

We construct a Financial and Economic Attitudes Revealed by Search (FEARS) index using search volume from Google's search engine to reveal household-level (“bankruptcy”, “unemployment”, “job search”, etc.) and market-level sentiment (“bankruptcy”, “unemployment”, “job search”, etc.).

Using a variety of quantitative methodologies such as the transfer entropy model as well as threshold regression and OLS, GLS and 2SLS estimations, we find that (1) investor sentiment has strong predictive power on Bitcoin, (2) household-level sentiment has larger effects than market-level sentiment and (3) the impact of sentiment is greater in low sentiment regimes than in high sentiment regimes. Based on these information, we build a hypothetical trading strategy that outperforms a simple buy-and-hold strategy both on an absolute and risk-adjusted basis. The results are consistent across cryptocurrencies and regions.

The findings contribute to the ongoing debate in the literature on the efficiency of cryptocurrency markets. The results reveal that the Bitcoin market is not efficient in the sense of the efficient market hypothesis – asset prices do not fully reflect all available information and we were able to “beat the market”. In addition, it sheds further light on the debate whether Bitcoin can be considered a medium of exchange, i.e. a currency or an investment product. Because investors are reallocating their Bitcoin holdings during times of increased market sentiment due to liquidity needs, they obviously consider bitcoin an investment product rather than a currency.

This study is the first to examine the impact of investor sentiment measured by FEARS on Bitcoin return.