The Capacity of Trading Strategies

Sticky Expectations and the Profitability Anomaly

“…That items 1 through 3 of Proposition hold in the data has been shown in the extensive empirical literature on asset pricing. Novy‐Marx () shows that the Sharpe ratio of the profitability anomaly is high, while Landier, Simon, and Thesmar () document that it is indeed a large anomaly, in the sense that large amounts can be invested in it without being eaten up by transaction costs. Novy‐Marx () documents that changes in earnings also forecast returns.…”

“…The corresponding long‐short arbitrage strategy features high Sharpe ratios, no crash risk (Lemperiere et al. ()), and very high capacity due to the high persistence of the profitability signal (e.g., operating cash flows to asset ratio on which the strategy sorts stocks (Landier, Simon, and Thesmar ()). Our goal in this paper is to test whether the profitability anomaly can be directly related to a simple model of sticky expectations in which investors update their beliefs too slowly.…”

Evaluating fund capacity: issues and methods

“…Rising FUM can also result in greater implementation shortfall (Perold, 1988). Illiquidity tends to limit capacity through its impact on execution costs, although this may be offset by impacts of increased liquidity on excess return potential (Chordia et al, 2014;Akbas et al, 2015;Kokkonen and Suominen, 2015;Landier et al, 2015;NovyMarx and Velikov, 2016).…”

“…Loeb, 1991;Knez and Ready, 1996;Beckers and Vaughan, 2001;Lesmond et al, 2004;Bettman et al, 2009Bettman et al, , 2010. Capacity is generally found to be lower for high turnover signals such as momentum, relative to 'slow' signals such as value (see Indro et al, 1999;Korajczyk and Sadka, 2004;Chen et al, 2005;Frazzini et al, 2012;Landier et al, 2015;Novy-Marx and Velikov, 2016). This research highlights how capacity estimates can vary depending on the how it is modelled with respect to aspects such as transaction costs, portfolio construction, trading discretion, constraints and performance evaluation.…”

“…It does not explicitly account for the OC associated with deferring or failing to trade. Landier et al (2015) undertake capacity analysis using multi-period dynamic optimisation, drawing on the model of Gârleanu and Pedersen (2013). Capacity is modelled as a function of baseline expected performance in the absence of transaction costs, described by a Sharpe ratio, a quadratic transaction cost function, an alpha signal with a constant rate of decay, and a target net Sharpe ratio target of 0.3.…”