Neue Studien – April 2024

Hinweis: Ich veröffentliche die Liste interessanter Studien hier mit einer Verzögerung. Die aktuelle Aufstellung erhalten Sie bei Anmeldung für meine monatliche Rundmail (kostenlos und werbefrei).


Same-Weekday Momentum

We document a new empirical fact about stock momentum. A significant fraction of stock momentum reflects return continuation on the same weekday. […] The net contribution of the same weekday momentum to the overall stock momentum ranges from about 20% to 60%. […] We find within-week seasonality and persistence in institutional trading to be its driver.

Fazit: Der konzentrierte Handel institutioneller Anleger ist ein wichtiger Bestandteil des Momentum-Effekts bei Aktien.


What Drives Stablecoin Growth?

Stablecoin issuers operate in a manner akin to mutual or money market funds – only without paying directly interest back to the stablecoin holders. Stablecoin issuers back their coins with purportedly secure and yield-generating reserves, such as commercial papers, Treasury Bills, government bonds and privately issued bonds, money market funds, and loans.

Fazit: Gewinne aus den Reserven sind ein wichtiger Treiber für das Wachstum von Stablecoins.


Estimating a Network Adoption Curve through Price Trends

Most technologies that have a public market price attached to them are not rolled out on day one. […] The price is hidden until the IPO date, often years after their invention. […] You can think of Bitcoin as a gradual-rollout, new technology that is pre-IPO, but its price is available for all to see.

Fazit: Der steigende Bitcoin-Preis spiegelt seine zunehmende Akzeptanz wider.


10-K Complexity, Analysts‘ Forecasts, and Price Discovery in Capital Markets

We find evidence of 52% more analyst underreaction to 10-K information for high- versus low-complexity 10-Ks. […] We find 46% greater impact of analyst underreaction on market efficiency with respect to high- versus low 10-K information. […] More complex 10-Ks increase investor reliance on analysts for interpretation.

Fazit: Kompliziertere Jahresabschlüsse verringern die Markteffizienz.


Volatility Targeting Is Trendy: How Trend Following Explains Alpha in Volatility-Managed Strategies

Volatility management appears to have alpha over a buy-and-hold investment in equity factors – most importantly, the market factor – over a long history dating back to the 1920’s. […] When return direction and return magnitude are negatively correlated, a volatility targeting strategy will align positioning with a trend following strategy.

Fazit: Der größte Teil des Alphas von Volatility Targeting bei Aktien kann durch Trendfolge erklärt werden.


Shifting Volumes to the Close: Consequences for Price Discovery and Market Quality

We find evidence for significant distortions of the closing price with 14% of the closing auction return being systematically reversed overnight. Increasing closing auction volumes, index rebalancing days, and high intraday returns are the main drivers of these reversals. Our results also show that intraday liquidity decreases due to the shift of trading volumes to the close while volatility improves.

Fazit: Ein Widerspruch zur Theorie, dass Schlussauktionen positive Effekte auf Preisfindung und Liquidität haben.


Outperforming the Market: Portfolio Strategy Cloning from SEC 13F Filings

Replicating the strategies of institutional investment managers from 13F filings aligns with or exceeds the performance of the original funds. […] The upper quartile of original funds show a minimum alpha of 12.8%, while the upper quartile of cloned counterparts exhibit a minimum alpha of 24.3%. This finding signifies that the top 25% of cloned funds do not merely track the performance of its source funds.

Fazit: Die Nachbildung der Fonds kann zu einer vergleichbaren oder sogar besseren Performance führen.


StockGPT: A GenAI Model for Stock Prediction and Trading

A daily rebalanced long-short portfolio formed from StockGPT predictions earns an annual return of 119% with a Sharpe ratio of 6.5. The StockGPT-based portfolio completely spans momentum and long-/short-term reversals, eliminating the need for manually crafted price-based strategies, and also encompasses most leading stock market factors. This highlights the immense promise of generative AI in surpassing human in making complex financial investment decisions.

Fazit: Generative KI ist der Studie zufolge vielversprechend, was komplexe Anlageentscheidungen angeht. Ich bin aber skeptisch.


Who Clears the Market When Passive Investors Trade?

On a dollar basis, active mutual funds and financial institutions clear the market on average, but firms are still the most responsive, with $0.77 of greater share issuance or fewer shares repurchased for every additional $1 of index demand. [..] Our results challenge the assumption in demand-based asset pricing models that the supply of shares is fixed.

Fazit: Die Ausgabe neuer Aktien ist vor allem für passive Investments relevant.


Short-Selling Hedge Funds

Short-selling hedge funds outperform their non-short-selling peers, with a superior performance not explained by known hedge fund skill measures. Therefore, our short-selling measure provides a new predictor of hedge fund skill. […] We find that these funds typically trade in opposition to retail trades.

Fazit: Short-Positionen von Hedgefonds scheinen recht profitabel zu sein (was mich überrascht).

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