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Crowd Machine makes it a one-click process. Hosting apps is expensive. Crowd Machine makes it inexpensive. Decentralized apps and smart contracts are limited in what they can do. Crowd Machine removes the limitations.

Author: Alphan Maina (Page 4)

Decentralized apps are locked into a specific blockchain. Crowd Machine is blockchain agnostic. Crowd Machine has a decentralized app marketplace for developers to sell their apps. Get paid to be a member of the Crowd Machine community Crowd Machine is focused on its community. Kurt Pfluger CSO. Ben Gorlick CTO. James Duchenne COO. Camden Dore VP, Economics. Jim Joseph Director, Social Media. Ben Leff Dir. Anthony Barbarino Customer Success Manager. Table , Panel A reports regression results for the subsample that only make partial disclosure commitments. I find some evidence, i. Table , Panel B reports the regression results for the subsample that make full disclosure commitments, and 35 results are consistently significant only in this subsample.

The prediction powers of early investments are also greater in this subsample, as indicated by the F tests. The evidence is consistent with the argument that when ICOs commit to more disclosures, the contents of the disclosure becomes more informative. The evidence helps to explain why investors respond favorably to ICOs that voluntarily make full disclosure commitments.

To further understand the relationship between blockchain information and the ICO outcomes, I split each subsample based on the quintiles of blockchain information in Table , Panel C. The quintiles are calculated based on the full commitment sample. I calculate the mean for the ICO outcomes for each quintile. Panel C does not show a perfect linear relation between the signals and the ICO outcomes.

Instead, the ICO outcomes are generally better in the first quintile than in the second quintile, which is particularly the case in the partial commitment sample. The evidence is consistent with the argument that when a firm commits to an increased level of disclosures, the signal becomes more precise, and it is more difficult to hide bad news. The coefficients on the dummy variable are significantly negative for all ICO outcomes, consistent with the argument that investors on aggregate can identify fraudulent ICOs, and those ICOs, on average, raise fewer funds.

Also, these ICO projects are less likely to survive or to deliver their products or services. First, it might be a concern that the number of team members is a poor proxy for size, and that the amount of raised funds is not properly scaled. A common way to address this concern in the literature is to scale raised amount by the hard cap. It is challenging to implement the procedures for two reasons. On the one hand, some ICOs do not have hard caps. On the other hand, some ICOs express their hard caps in terms of Ethers, and the exchange rate of Ethers to the US dollars fluctuates, making it difficult to measure the hard cap accurately.

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I select a sample of observations whose hard cap can be measured reliably. I run the main tests for this sample and replace the dependent variable with the amount of raised funds scaled by hard caps. The results are presented in Table , Panel A, and are consistent with the main results.

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Then I show that the information value and the prediction power of blockchain disclosure are robust to alternative definitions of blockchain information. I replace token distributions in early ICO periods with token distribution on the first day since ICO starts and rerun the test for hypothesis two. In Table , Panel B, and C, I still find that blockchain information predicts future ICO outcomes, and the prediction power is greater for the subsample that makes full disclosure commitments.

In addition, I show that the dummy variables that identify suspicious ICOs are robust to the choice of threshold. When raising the threshold to 10 percent, I potentially introduce more noise to the measure of suspicious ICO volumes. Finally, previous studies document that ICO analysts can collect relevant information, and their ratings are informative of ICO outcomes.

Therefore, the rating variable should correlate with some other control variables and can mitigate the concerns about measurement errors in the whitepaper variable.

The variable absorbs some explanatory power of social media and team size, suggesting that analysts provide ratings based on information on social media and from ICO firms. The disclosure commitments variables are almost not affected by the inclusion of the analyst rating variables. I argue that smart contracts serve as a tool for disclosure commitments. They can allow investors to observe the token distributions and cryptocurrency investments and to assess the popularity and potential of an ICO project.

Startups that voluntarily commit to disclosing such information on blockchains are more likely to succeed. The disclosed information is indicative of ICO outcomes, and the market on aggregate can identify and punish suspicious ICOs. T-stats in parentheses. How can firms make credible disclosure commitments in practice? Previous studies focus on the following two mechanisms.

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On the one hand, mandatory disclosure provides a credible commitment mechanism. Firms choose accounting standards, e. Firms are also subject to disclosure regulations, e. On the other hand, firms make implicit commitments by following voluntary disclosure policies consistently. Such commitments can be enforced by the market.

For example, firms can provide earnings forecasts on a regular basis, and Chen, Matsumoto, and Rajgopal document negative market reactions when firms discontinue this practice. Blockchain technology provides a new way to make commitments. Conceptually, a blockchain is a system of open and distributed ledgers that record information in a verifiable and permanent way.

One can make a commitment by writing a computer program that specifies some future actions, e. After the program is deployed on blockchains, it becomes immutable and is enforced by the blockchain protocols. As long as the protocols are transparent and well designed, the commitment is credible. ICOs became a popular way to finance startups in In an ICO, investors invest with a well-established cryptocurrency, such as Bitcoins, and in return they receive a new cryptocurrency, a new coin.

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The new coin may have values or entitle its holders to future services. It can perform certain transactions automatically, such as collecting Bitcoins investments and distributing new coins. The disclosure decision, e. Importantly, they write and deploy smart contracts before actual transactions take place. That is, the disclosure decision is made before the entrepreneurs know the outcome of the fundraising, i. If they commit to disclosing transactions on blockchains, such disclosure decisions become irreversible. Meanwhile, entrepreneurs have the option not to commit but rather to make an ex-post disclosure decision, i.

Blockchains differ from traditional commitment mechanisms in the following ways.

First, commitments on blockchains are enforced by computer programs, which, if well-designed, prevent potential violations. Once the program is deployed on a blockchain, no 59 one can stop it from sending out the message.