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Depending on portfolio turnover, execution costs often have significant negative impact on a portfolio’s or a trading strategy’s profitability. There is often a trade-off between paper profits from a trading strategy and portfolio turnover: lower-frequency strategies with lower turnover tend to have lower paper profits (without considering costs) and higher-frequency strategies with higher turnover tend to have higher paper profits. For example, traditional value signals such as book to price ratio have very low turnover—often less than 25% annually—and short-term mean reversion strategies have much higher turnover—often as high as 25% daily. For strategies with high turnover, reducing trading costs is crucial. A strategy with a daily turnover of 25% and an assumed trading cost of 10 basis points requires 12.6% annualized before-cost return to break even. High trading costs are the reason why some apparent anomalies are hard to monetize and continue to exist.
Our overall approach has been to choose factors that have good performance and consistency in predicting portfolio returns balanced against turnover.
By design, some factors change slowly from one period to the next, whereas others change rapidly. For example, the size factor stays stable over months or even years. Therefore, the single-factor portfolio constructed using size factor has low turnover. In contrast, values of a short-term reversal factor change rapidly from day to day (if the signal works, recent losers become winners and recent winners become losers). Therefore, a single-factor portfolio constructed using a short-term reversal factor has high turnover. Since the turnover depends on how we use a factor to construct a portfolio, there is no standard approach to estimate turnover. One approach is to directly look at a zero-investment portfolio, e.g., the top quintile minus the bottom quintile, to calculate portfolio turnover. A different approach, independent of portfolio construction, measures the serial correlation of factor scores: the correlation between factor scores of the stocks at t and the factor scores of the same stocks at t + 1. Higher correlation means that factor scores are more stable over time and indicates lower factor turnover.
Factors with high turnover need to be, and sometimes are, compensated with higher predictive power. If we have a reasonable estimation of trading costs, they can be directly incorporated to estimate after-cost returns and information ratios. Mediocre predictable power and high turnover, however, do not automatically make the factor a poor signal. Investors usually use multiple factors in the portfolio construction and the final turnover depends on the interaction of the selected factors.
The hysteresis approach is a valuable tool for reducing turnover as well. After we enter a long position when the stock moves into the top quintile, we do not necessarily exit the position when it moves out of the top quintile. Instead, we only exit the position if the stock falls below the 60th percentile. Although the expected alpha is lower when the stock falls from the top quintile to the fourth quintile, holding the existing long position does not require extra trading and does not incur trading costs. Similarly, after we enter a short position when the stock moves into the bottom quintile, we only exit the position if the stock moves above the 40th percentile. By using different thresholds for entry and exit, we reduce the turnover of fast-moving signals and achieve a better trade-off between raw returns and trading costs.
This is just one of hundreds of active management approaches we use at ActiveAllocator.com to create better portfolios.
Retail investors who are ineligible to invest in quality hedge funds, in hard to access investment vehicles, either because they do not meet minimum levels of wealth or income standard, or the high subscription amounts often needed to participate in such funds gravitate to liquid alternative investments. The rise of liquid alternative investment funds, packaged in mutual fund formats over the past years, as the fastest growing category of “alternative investments” is now well documented. McKinsey & Company suggest “retail alternatives will be one of the most significant drivers of U.S. retail asset management growth over the next five years, accounting for up to 50 percent of net new retail revenues”.
With liquid alternatives beginning to find increasing traction in institutional portfolios too, the question is – are they an effective substitute for hedge funds and other illiquid structures? Little empirical fact based exists and opinions abound.
Our research at ActiveAllocator.com attempts to answer this question and concludes that they are not.
Retail investors in considering hedge funds immediately encounter a wide variety of strategies, organizations and structures. Indeed, hedge funds, rather than being an asset class, are broadly a collection of governance structures and investing techniques with many common structural features. Unfortunately, from an investor’s perspective, it is often difficult to decipher which structural features are useful, which imply tradeoffs and which are simply undesirable. The dearth of empirical research leaves investors to make intuitive judgments about what features they should favor.
We re-examined a sub-set of provisions governing fund investing- liquidity terms. In contrast to alternative mutual funds, which allow investors to redeem their holdings on a daily basis with little or no advance notice, hedge fund investors are subject to a variety of terms that may restrict their ability to access their capital. All things equal, investors prefer more liquid investments to less liquid investments. Liquidity provides investors with a valuable option – specifically the opportunity to trade in and out of investments in order to rebalance a portfolio, respond to unforeseen cash flow requirements or redeploy capital towards other opportunities.
While the benefits that liquidity offers to investors are clear, the costs associated with greater liquidity are less apparent. We explored two related questions:
•Do investors pay a price – in terms of lower investment returns – for better liquidity? In other words, do funds with more favorable liquidity terms underperform less liquid funds?
•If the answer to the question is yes, then what drives this cost? In other words how can one explain the underperformance of more “liquid” funds?
Our research finds that there has been a substantial performance cost from offering increased liquidity. The underperformance cannot be attributed to fee levels or the strategy pursued by a particular fund. We are unable to attribute the liquidity cost to differences in skill across managers; we do not find strong evidence that less skillful managers (whose performance is weaker) offer more attractive liquidity terms. Instead, our results indicate that managers who offer more restrictive liquidity terms are able to outperform more liquid managers because they are able to pursue a broader range of attractive trading opportunities.