The growth rate of private credit has been so rapid (growing to nearly $2 trillion by the end of 2023, roughly ten times larger than it was in 2009), that concerns about there being a bubble have been raised.
By quantifying how non-performance-based fees dominate the cost structure, this research questions whether current fee models effectively align with investor interests, which could influence future fee arrangements and industry standards.
The authors of the research discussed developed a machine learning model that can accurately predict trading volume for individual stocks. They then demonstrated how this model can be used to construct a portfolio that outperforms a traditional market-cap weighted portfolio.
An index-tracking approach generally lacks flexibility, which detracts from performance, leaving returns on the table. Intelligent design can overcome such issues. For example, an S&P 500 Index could choose to rebalance one month ahead of the scheduled reconstitution, minimizing the impact of reconstitution. Direct index funds are already engaging in such strategies with ETFs.
This paper provides new evidence on the efficacy of prioritizing transactions so as to focus portfolio turnover on the trades that offer the strongest signals and hence the highest potential performance impact.
Transaction costs have a first-order effect on the performance of currency portfolios. Proportional costs based on quoted bid–ask spread are relatively small, but when a fund is large, costs due to the trading volume price impact are sizable and quickly erode returns, leaving many popular strategies unprofitable.
Trading costs, discontinuous trading, missed trades, and other frictions, along with asset management fees can cause a shortfall between live and paper portfolios. The focus of this paper is to test an effective rebalancing method that prioritizes trades with the strongest signals to capture more of the factor premia while reducing turnover and trading costs.
Higher volatility is associated with faster, initially stronger reversals, while lower turnover is associated with more persistent, ultimately stronger reversals
New research reveals that the performance of the hedge fund industry has not been as bad as the results from studies that relied on hedge fund data providers.
Short term return anomalies are generally dismissed in the academic literature "because they seemingly do not survive after accounting for market frictions.” In this research, short term “factors” are taken seriously and the authors argue the standard parameters may not apply for short horizons.
Wall Street’s product machine is continuously pumping out fairy tales; structured products should be avoided.
This article discusses what academic research says about the relationship between the demand for leverage and management fees.
This article examines ETF creations and redemptions around price deviations and finds that the expected arbitrage trades are relatively rare in a broad sample of equity index ETFs. In the absence of these trades, price deviations persist much longer. Creation and redemption activity appears to be constrained when exchange conditions would lead to a costlier arbitrage trade, and the size of the price deviations mainly impact the likelihood rather than the amount of trading. The authors also find some evidence that creations and redemptions are less likely to trade on price deviations when they would be required to trade the underlying stocks against broad market movements. Their results suggest that several factors may discourage the built-in ETF arbitrage mechanism and that investors may receive poorer trade execution in these conditions as a result.
We find that exchange-traded fund (ETF) lending fees are significantly higher than stock lending fees. Two institutional features unique to ETFs play significant roles in explaining the high fees. First, regulations restrict investment companies, such as mutual funds and ETFs, from owning ETFs. As these institutions are key lenders, their absence reduces the lendable supply in the ETF loan market. Second, while the create-to-lend (CTL) mechanism alleviates supply constraints when borrowing demand increases, its efficacy is limited by the associated costs and frictions. Our results speak to the limits to arbitrage in the ETF markets.
In this blog we discuss the academic research surrounding the question of cryptocurrency liquidity. How to Measure the Liquidity of Cryptocurrency? Brauneis, Mestel , Riordan [...]
Liquidity risk and exchange-traded fund returns, variances, and tracking errors Kyounghun Bae, Daejin KimJournal of Financial EconomicsA version of this paper can be found hereWant to [...]
Trading out of sight: An analysis of cross-trading in mutual fund families Alexander Eisele, Tamara Nefedova, Gianpaolo Parise, Kim Peijnenburg, Journal of Financial EconomicsA version [...]
Transaction Costs of Factor-Investing Strategies Feifei Li, Tzee-Man Chow, Alex Pickard & Yadwinder GargFinancial Analysts JournalA version of this paper can be found hereWant to read [...]
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