Bitcoin

For anyone trading or investing in Bitcoin, a familiar indicator can become a dangerous comfort blanket. Josh Molnar’s Bitcoin Runs on a Clock argues that classic cycle signals—such as MVRV, the Mayer Multiple and Pi Cycle Top—have weakened as Bitcoin’s price swings become less extreme. Thresholds calibrated to earlier cycles may consequently stop triggering, leaving investors waiting for a sell signal that never arrives. The practical takeaway is that a strong historical record does not make an indicator’s settings permanent. If the market changes, the dashboard needs to change with it.

This paper tests whether that rotation in attention leaves a systematic footprint. Using Donchian breakout signals across QQQ and Bitcoin, with cash as a fallback during periods of consolidation, we examine whether investors can harvest momentum without remaining permanently exposed to either asset’s full drawdown profile. The results suggest that the answer is yes: retail attention does not move randomly. It rotates, it concentrates, and—when measured through price breakouts—it can be systematically exploited.

From the trading desk to the portfolio committee, investors face a familiar question: how should alternative stores of value fit into a diversified portfolio? This research explores that question through a systematic dual-momentum framework comparing Bitcoin and physical gold in a rules-based tactical allocation model. Rather than debating ideology, we focus on practical portfolio construction and risk-adjusted returns. The goal is to examine whether “digital gold” can complement its physical counterpart within a disciplined investment process, and whether the distinct behavior of these assets can be used to build a more effective systematic strategy.

The crypto-enthusiast’s mantra—“just add Bitcoin and watch the efficient frontier fly”—runs into a hard empirical wall when you extend the sample, tighten the econometrics, and force the asset to compete on identical risk-adjusted footing with equities. Alistair Milne’s new SSRN paper applies a textbook Markowitz mean–variance framework to a two-asset universe (S&P 500 vs. Bitcoin) and finds that the ex-ante optimal long-term weight on BTC is not merely small; it is outright negative. In other words, a rational, variance-averse allocator who believes expected returns equal historical equity premia plus a fair compensation for BTC’s non-diversifiable volatility should be short, not long, the flagship digital token.

Bitcoin is one of the most widely discussed financial assets of the modern era. Since its inception, it has evolved from a niche digital experiment into a globally recognized investment instrument with institutional adoption and billions in daily trading volume. Despite its inherent volatility, Bitcoin has demonstrated a strong long-term growth trajectory, making it an attractive candidate for trend-based and momentum-oriented trading strategies. In this study, we apply concepts from technical analysis to construct and refine a trend-following strategy for Bitcoin, progressing step by step from a simple MACD setup toward an improved multi-timeframe model.

MicroStrategy has become one of the most polarizing companies in public markets. Once a conventional business intelligence firm, it has transformed into the world’s largest publicly traded Bitcoin proxy, holding over a million BTC on its balance sheet and continuously raising capital to buy more. Supporters praise it as a visionary “Bitcoin ETF with leverage,” while critics argue it is an irrationally overvalued vehicle whose market capitalization regularly trades far above the fair value of its underlying assets. The persistent premium — the gap between MicroStrategy’s equity value and the market value of its Bitcoin holdings — has puzzled analysts, defied traditional valuation logic, and raised the question: why does this spread exist, and why does it not close through arbitrage? A recent academic paper, Valuing MicroStrategy, offers a structural model that explains this phenomenon and sheds light on how the firm’s unique financing mechanics allow its stock price to exceed the value of its assets.