Bitcoin cyclicality and investment strategy

Abstract

Purpose: To investigate Bitcoin’s cyclic price behavior around scheduled halving events, develop a technical‑analysis‑based active investment strategy tailored to these cycles, and rigorously assess its performance relative to a passive buy‑and‑hold benchmark.

Design/Methodology/Approach: This research employs historical daily BTC /USD price series (June 2012–May 2025), applies a suite of technical indicators to define systematic, halving‑anchored entry and exit rules, and then conducts rigorous statistical evaluations to test whether Bitcoin’s protocol‑driven supply cycles yield reproducible, actionable investment signals.

Findings: Over thirteen overlapping sample windows, the active strategy outperforms passive BTC holding in ten, with positive “alpha” coefficients that are statistically significant at the conventional 5% level in each of those windows (and, in most cases, with p-values below 2.5%). It captures outsized gains in post-halving bull runs (e.g. 2013, 2017, 2021) and meaningfully limits drawdowns in bear phases (e.g. 2014, 2018, 2022). Equity curve simulations demonstrate compounded account growth that markedly surpasses passive returns.

Practical Implications: Crypto asset managers and individual investors can implement the halving‑centric strategy using readily available charting tools and API‑accessible price feeds to automate buy/sell signals, thereby enhancing return potential and mitigating drawdowns without requiring deep on‑chain analytics expertise. This framework also provides a transparent risk‑management overlay—leveraging predefined exit rules—that can be calibrated to varying risk tolerances and seamlessly integrated into broader multi‑asset portfolios.

Originality/Value: This study is among the first to integrate Bitcoin’s protocol‑driven halving schedule with a multi‑indicator technical framework and to validate its efficacy through extensive statistical tests over four market cycles (including the 2024 halving). It offers practitioners a replicable, data‑driven strategy for navigating crypto’s unique cyclical dynamics.

Paper Type: Research Paper