Abstract

The statistical concept of gambler’s ruin suggests that gambling has a large amount of risk. Nevertheless, gambling at casinos and gambling on the Internet are both hugely popular activities. In recent years, both prospect theory and laboratory-controlled experiments have been used to improve our understanding of risk attitudes associated with gambling. Despite theoretical progress, collecting real-life gambling data, which is essential to validate predictions and experimental findings, remains a challenge. To address this issue, we collect publicly available betting data from a DApp (decentralized application) on the Ethereum blockchain, which instantly publishes the outcome of every single bet (consisting of each bet’s timestamp, wager, probability of winning, userID and profit). This online casino is a simple dice game that allows gamblers to tune their own winning probabilities. Thus the dataset is well suited for studying gambling strategies and the complex dynamic of risk attitudes involved in betting decisions. We analyse the dataset through the lens of current probability-theoretic models and discover empirical examples of gambling systems. Our results shed light on understanding the role of risk preferences in human financial behaviour and decision-makings beyond gambling.

Highlights

  • ObjectivesWe aim to characterize gamblers in Etheroll, through each of their lifetime bet, bet size, betting probability and cumulative profit distributions

  • The client server model, the most widely used computing network model in the world today, allows devices to request services or resources from other devices

  • We study the behavioural dynamics of gamblers on a decentralized application (DApp) known as Etheroll

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Summary

Objectives

We aim to characterize gamblers in Etheroll, through each of their lifetime bet, bet size, betting probability and cumulative profit distributions. We aim to carefully characterize gamblers who follow a few prescribed types of gambling strategies

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