Six new strategies have been added. Five new related research papers have been included into existing strategy reviews and two new short free blog posts have been published during last few weeks. Plus, five trading strategies have been backtested in QuantConnect in the previous two weeks.
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.
This article examines the impact of major consumer holidays, Thanksgiving and Christmas, on financial markets. Using historical price data from 2004 to 2024, we analyze daily performance trends in the 10 trading days before and after each holiday to determine whether seasonal spending influences asset prices. Our findings suggest that seasonal consumer spending influences financial markets, with Amazon benefiting around Thanksgiving and gold during Christmas.
Six new strategies have been added. Two new related research papers have been included into existing strategy reviews and three new short free blog posts have been published during last few weeks. Plus, four trading strategies have been backtested in QuantConnect in the previous two weeks.
Cryptocurrencies have matured from experimental curiosities into a viable investable asset class whose return-generation and risk characteristics merit treatment within empirical asset pricing. A recent paper by Nicola Borri, Yukun Liu, Aleh Tsyvinski, Xi Wu summarizes ten facts from the literature that show cryptocurrencies share important similarities with traditional markets—comparable risk-adjusted performance and a small set of cross-sectional factors—while retaining distinctive features such as frequent large jumps and price signals embedded in blockchain data. Key themes include portfolio diversification, factor structure, market microstructure, and the evolving role of regulation and derivatives in shaping market discovery and stability.
The clustering of excess returns on the final trading days of the month constitutes a robust empirical regularity with significant implications for portfolio construction. We document a month-end premium that is both statistically and economically significant, distinct from the canonical turn-of-the-month (ToM) effect. Our strategy highlights systematic style rotations—particularly shifts in value versus growth exposures, as proxied by the IVE–IVW spread—and documents parallel contemporaneous dislocations between real-estate and broad-equity benchmarks, as measured by the IYR–SPY spread.
The U.S. equity market has periodically been dominated by a few technology-driven stocks, most recently the so-called “Magnificent Seven.” Historically, similar dominance occurred during the Nifty Fifty era in the 1960s–1970s and the dot-com boom in the 1990s. These periods of concentrated leadership often led to temporary outperformance, but systematically capturing such gains has proven challenging. Our study investigates the potential to exploit technology sector dominance using momentum-based strategies across Fama–French 12 industry portfolios, analyzing whether long-only, long-short, and rolling-basis approaches can generate persistent alpha, and assessing the limitations of simple timing methods.
Hello all,
What have we accomplished in the last month?
– Parametrization of the One Day Shocks & 100yrs Historical Events, Volatility Targeting, Correlation Analysis, and Portfolio Rebalancing reports
– 20 new Quantpedia Premium strategies have been added to our database
– 5 new related research papers have been included in existing Premium strategies during the last month
– Additionally, we have produced 7 new backtests written in QuantConnect code
– 5 new blog posts that you may find interesting have been published on our Quantpedia blog in the previous month
– Plus you are all invited to a new Quantpedia webinar – Unlocking the Power of Calendar and Seasonal Strategies
Three new strategies have been added. Three new related research papers have been included into existing strategy reviews and three new short free blog posts have been published during last few weeks. Plus, three trading strategies have been backtested in QuantConnect in the previous two weeks.
Gold has been in the headlines lately as it climbs to new highs, prompting many investors to look for ways to benefit from the rally. However, many institutional investors – such as mutual funds and pension funds – face restrictions on buying physical gold or gold-backed ETFs. Instead, they often turn to gold mining stocks to gain indirect exposure to gold’s price. That approach seems logical on the surface: mining stocks typically offer leveraged exposure to gold’s movements. But as highlighted by Dirk G. Baur, Allan Trench, and Lichoo Tay in their recent study “Gold Shares Underperform Gold Bullion”, this strategy can be misleading. The authors demonstrate that, over the long run, gold mining shares structurally underperform physical gold itself.
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