When Can You Trust Bitcoin? Value-Dependent Block Confirmation to Determine Transaction Finalit

TL;DR

This paper tackles Bitcoin transaction finality by linking fork risk to block depth, transaction value, and user risk tolerance. It models loss and risk using Prospect Theory, deriving a loss function $L(v)$ and a loss threshold LT(v) = $e^{L(v)/c}$, and posits that finality is achieved when $P_{\text{rev}}(d) \leq LT(v)$. Through QUANTAS simulations and analysis of real Bitcoin data, it shows that higher network delays necessitate deeper confirmations, with concrete examples linking value and depth (e.g., $v=\$15$ requiring more blocks under greater delays). The work provides a practical, risk-aware method to determine minimum confirmation depth and suggests real-time monitoring and cross-chain applicability as future directions.

Abstract

We study financial transaction confirmation finality in Bitcoin as a function of transaction amount and user risk tolerance. A transaction is recorded in a block on a blockchain. However, a transaction may be revoked due to a fork in the blockchain, the odds of which decrease over time but never reach zero. Therefore, a transaction is considered confirmed if its block is sufficiently deep in the blockchain. This depth is usually set empirically at some fixed number such as six blocks. We analyze forks under varying network delays in simulation and actual Bitcoin data. Based on this analysis, we establish a relationship between block depth and the probability of confirmation revocation due to a fork. We use prospect theory to relate transaction confirmation probability to transaction amount and user risk tolerance.

Figures (4)

• Figure 1: Simulation. Number of switches of particular lengths depending on the network delay.
• Figure 2: Simulation. Minimum confirmation depth vs dollar value for various network delays.
• Figure 3: Actual Bitcoin Data. Probability of revocation vs. depth.
• Figure 4: Actual Bitcoin Data. Minimum confirmation depth vs dollar value for various network delays.