Methodology for estimating the capacity limit for investment strategies
Following on from my initial capacity paper (Managing the file line between funds under management growth and alpha decay), this blog outlines various capacity methodologies that have been proposed through academic research. It is important to note this is not a recommendation of one over another per se although, as this blog will show, greater weight has been given to the stock liquidation method as this is the one currently most used by the industry.
Previous research papers have outlined various methods to calculate the capacity limit. In determining an appropriate capacity methodology to use, I examined the methods discussed in these research papers and assessed their appropriateness in capacity calculations.
For those wanting more detail a list of some of these research papers is contained at the end of this paper.
1 – Stock Liquidation Method
The Stock Liquidation Method is the capacity approach commonly used across the industry. This approach uses the following measures:
- the weighted average daily trading value (‘WADTVAL’) of the strategy, weighted by each stock’s holding;
- the maximum percentage of ADTVAL that can be traded efficiently each day; and
- the average number of days it takes to efficiently establish the maximum position.
Assessing these three variables together enables the determination of the maximum position size, on average, that can be established when trading efficiently. This number is then multiplied by the number of stocks held and then adjusted for the weight held in cash to obtain the capacity limit of the strategy.
Stock Liquidation Method formula:
A key step in the Stock Liquidation Method is determining the WADTVAL of the strategy. This was calculated by finding the average ADTVAL of each stock in the strategy over a set period and weighting them by the exposure to each.
This part of the process is important, as it specifically incorporates the strategy’s portfolio construction decisions. The strategy emphasises the need to hold liquid stocks, which theoretically should reduce transaction costs and increase capacity. This relationship is accurately captured and accounted for in the methodology; stocks which the strategy has higher exposure to have their ADTVAL values assigned more weight. This means if the strategy pursues more liquid stocks its capacity will increase.
Maintaining a conservative approach to estimating the capacity limit is important and can be emphasised throughout the capacity estimation and analysis process using this methodology.
A conservative approach to managing a fund’s capacity is important as it enables investment strategies to be managed efficiently throughout the bottom of the economic cycle, when market conditions can change and reduce capacity quicker than a manager can adjust their funds under management limits.
To implement a conservative approach many investment managers who use this methodology apply a buffer to their capacity calculation. This has the effect of reducing the risk of exceeding the true capacity limit across the market cycle, which would likely result in failing to meet performance targets.
2 – Maximum ownership method
The ‘maximum ownership’ method is based on the level of stock concentration of the strategy. This approach constrains the total percentage ownership in each stock to a maximum of 4% of the stock’s market cap.
This approach is based on the premise that a fund manager should not manage more than 5% of the voting capital of a company to negate submitting substantial shareholding notices[1], which may reveal its stock positions and by default trading intentions to the market.
An investor required to provide substantial holding statements may reveal their own identity and trade on that stock to the market before the trading is complete. The risk is, that if the trading is not complete, other market participants can front-run the manager by trading the same stock in the same direction and in amounts that significantly change the stock’s price. Hence the investment manager may pay a higher price, or sell at a lower price, than the current market price for part of its trades, thereby increasing the market impact costs for the strategy.
Therefore, unless a manager’s trading of a stock is someway concealed, it will be in the manager’s interest to maintain stock holdings below 5% of voting capital to conceal their trading.
3 – Portfolio turnover method
The ‘portfolio turnover’ method estimates the maximum total daily trading volume, efficiently tradable by one manager based on market liquidity, portfolio holdings and transaction cost constraints. It then estimates total capacity by considering the portfolio turnover as a given, which is required to achieve the investment objectives.
Portfolio turnover is highly correlated to the market conditions and market turnover. Current market conditions indicate that market turnover has deteriorated somewhat over the past 10 years.
Furthermore, turnover volatility has surged during this period, reflecting the increased volatility in average daily trading value and market capitalisation. The underlying cause of the increase in turnover volatility can be attributed to global issues such as trade wars.
With uncertainty in the market, portfolio turnover can be expected to decline and hence is less relevant as a constraint to capacity.
4 – Market turnover method
The ‘market turnover’ method assumes that the manager can efficiently trade a certain percentage of the total market trading value, and that this percentage captures all the required portfolio trades over the course of trading, given a required level of portfolio turnover.
This method requires the assumption of the percentage a manager can efficiently trade of the total index volume. Since it is difficult to estimate this value, an arbitrary assumption must be made which makes it the least accurate method in determining capacity. Hence, I would deem the market turnover method least appropriate for capacity calculations.
Finally, as promised below are the reference papers. Worth a read if you would like more detail.
References
Berk, J. B. and Green, R. C., 2004, “Mutual Fund Flows and Performance in Rational Markets”, Journal of Political Economy 112, 1269-1295.
Chan, H., Faff, Robert W., Gallagher, David R. and Looi, Adrian, Fund Size, Fund Flow, “Transaction Costs and Performance: Size Matters!” (April 3, 2005).
Chen, J., Hong, H., Huang, M. and Kubik, J.D., 2004, “Does Fund Size Erode Mutual Fund Performance? The Role of Liquidity and Organization”, American Economic Review 94, 1276-1303.
Gallagher, D., 2003. “Investment manager characteristics, strategy, top management changes and fund performance”. Accounting & Finance 43, 283-309.
Gallagher, D. R. and Martin, K. M.., 2005, “Size and Investment Performance: A Research Note”, Abacus 41, 55-65.
Grinblatt, M., Titman, S., 1994. “A study of monthly fund returns and performance evaluation techniques”. Journal of Financial and Quantitative Analysis 29, 419-444.
Sawicki, J. and Finn, F., 2002, “Smart Money and Small Funds”, Journal of Business Finance and Accounting, 29, 825-846.
Serbin, V., Bull, P.M., and Zhu, H., 2009. “The Capacity if
Liquidity-Demanding Equity Strategies”. The Journal of Portfolio Management,
Fall 2009.
[1] Section 671B (1) of the Australian Corporations Law requires that information on substantial holdings be submitted to company, responsible entity and relevant market operator when holdings reach 5% of voting capital and when there is a movement of at least 1% in their holding thereafter.
Chris Robertson
Associate Director