Efeitos dos ciclos de Halving no preço do bitcoin: análise estatística de eventos passados

Abstract

This paper aims to statistically analyze whether Bitcoin halving cycles significantly influence the asset's price, investigating whether there are consistent patterns of appreciation or decline after these events and contributing to the debate on the relationship between the scheduled block reward reduction and market dynamics. The research problem is based on the lack of academic and practical consensus regarding the direct impact of the halving on Bitcoin's valuation. Although the event is predictable and intrinsically linked to the cryptocurrency's scarcity mechanism, it is unclear whether historically observed price movements result from it or from other external factors, such as global liquidity cycles, regulatory changes, institutional adoption, or even speculation based on market expectations. Thus, the study aims to explore not only the technical functioning of the halving but also its implications for supply and demand, considering the four events that have already occurred in 2012, 2016, 2020, and 2024, analyzing how the price of Bitcoin behaved in each of these periods and to what extent external factors may have amplified or diminished its effects. To this end, the study base includes historical data on Bitcoin prices, trading volumes, and market capitalization between 2010 and 2025, offering a comprehensive perspective on the asset's trajectory. The theoretical framework will be supported by scarcity theory, specifically the Stock-to-Flow model, which links the reduction in supply to the appreciation of rare assets; by the efficient market hypothesis, which suggests that prices would already incorporate known information, such as the halving, in advance; and by behavioral economics, which considers the role of investor expectations and psychology in price formation. The analysis methods include descriptive statistics, evaluating means, volatility, and returns before and after halvings; hypothesis testing to assess the statistical significance of variations; time series to identify recurring patterns; and regression models, which seek to isolate the halving's effect from relevant external variables. Thus, the research seeks to provide empirical evidence on the halving's relevance to Bitcoin pricing, discussing whether its influence is truly decisive or merely a catalyst in a market highly influenced by multiple economic, technological, and behavioral factors.