Entrepreneurial Finance

This paper examines the operating and financial performance of venture firms conducting initial coin offerings (ICOs) with different types of investors and at different points along a venture’s life-cycle. Relative to purely crowdfunded ICO ventures, institutional investor-backed ICO ventures exhibit weaker operating performance and fail earlier. However, conditional on survival, these ventures financially outperform their peers that do not receive institutional investor support. The diverging effects of investor backing on financial and operating performance are consistent with our theory of "certification exploitation" through a new form of pump-and-dump scheme. Institutional investors exploit their reputation to drive up ICO valuations and quickly exit the venture post-ICO, with the difference in pre- versus post-certification token prices being their exploitation profit in liquid markets for startups. Our findings further indicate that there is an inverted U-shaped relationship between the financial success of an ICO and the timing along a venture’s life-cycle, with the product piloting phase representing the pivotal point.

This paper compares bootstrap simulation approaches in the context of the maximum drawdown (MDD) risk measure for stock market and cryptocurrency returns. Our comparisons are based on the complete distribution of the MDD using stochastic dominance tests. The standard Efron (1979) bootstrap severely underestimates the true MDD. The simulation results of the moving block bootstrap approach are reasonably good as long as the stationarity problem does not become striking. The stationary bootstrap approach of Politis and Romano (1994) provides the best results. Investment practitioners should choose the Politis and Romano (1994) method as their first choice to model MDD risk.

Coordination frictions may prevent the efficient adoption and governance of digital platforms. We document that crypto funds (CFs) create value, inter alia, by smoothing such frictions on blockchain-based decentralized digital platforms (DDPs). CF-backed DDPs obtain higher valuations in the primary market (i.e., in initial coin offerings, ICOs), outperform their peers post ICO, and benefit from token price appreciation around CF investment disclosure in the secondary market. In line with our theory, primary transaction data from the Ethereum ledger shows that the valuations of DDPs with meager adoption and relative centralization benefit more from CF backing. Moreover, the positive valuation and performance effects for CF-backed DDPs are higher for CFs with more central investor networks.

Crypto Funds (CFs) represent a novel investor type in entrepreneurial finance. CFs intermediate Decentralized Finance (DeFi) markets by pooling contributions from crowd-investors and investing in tokenized startups, combining sophisticated venture- and hedge-style investment strategies. We compile a unique dataset combining token-based crowdfunding (or Initial Coin Offerings, ICOs) data with proprietary performance data of CFs. CF-backed startup ventures obtain higher ICO valuations, outperform their peers in the long run, and benefit from token price appreciation around CF investment disclosure in the secondary market. Moreover, CFs beat the market by roughly 2.5% per month. Their outperformance is persistent, suggesting that CFs deliver abnormal returns because of skill, rather than luck. These performance effects for CFs and CF-backed startups are driven by a fund’s investor network centrality. Overall, our study paves the way for research on what some refer to as the “crypto fund revolution” in entrepreneurial finance.

The valuation of start-up firms is challenging, yet highly relevant for entrepreneurs and financiers alike. We reverse-engineer fair-value multiples by comparing the firm value at the time of financing with the firm value at the time of exit. Our framework produces reliable valuation multiples from observed venture capital transactions per industry and financing round. Despite their simplicity, sanity checks confirm that our multiples are highly performant in describing common valuation characteristics. Valuation multiples are higher when more experienced investors are involved, and when the exit occurs through an IPO rather than an M&A. In contrast, later stage financing rounds and larger investment consortia are associated with lower valuation multiples.

The authors examine to what extent the market for initial coin offerings (ICOs) is driven by investor sentiment. Their results, based on a comprehensive set of sentiment and coin price data, suggest that the ICO market is driven by crypto-related sentiment, but is almost unrelated to general capital market sentiment. Among the crypto-related sentiment, social media channels, rather than traditional news channels, are the main source of investor sentiment. The authors find that ICO firms exploit “windows of opportunity” and avoid periods of negative sentiment. Coins listed during periods with negative investor sentiment generate negative returns in the short run. Moreover, returns to investors on the first day of trading predict long-run returns up to six months.

Token offerings or initial coin offerings (ICOs) are smart contracts based on blockchain technology designed to raise external finance without an intermediary. The new technology might herald a revolution in entrepreneurial and corporate finance, with soaring market growth rates over the last two years. This paper surveys the market evolution, offering mechanisms, and token types. Stylized facts on the pricing and long-term performance of ICOs are presented, and practical implications for this young market to thrive are discussed.