In this blog I’ll examine the old “sell in May and go away” seasonal pattern associated with risky assets. It’s timely to consider this pattern since the markets are now entering the seasonally weak period. Furthermore, stock market performance has been relatively weak in a number of recent “strong periods,” such as in January 2016, November 2015 through January 2016, and November 2015 through April 2016, which often provides a foreboding tell of additional weakness during the traditional seasonal weak period of May through October.
Seasonality as a trading edge is also worth considering because trend following has become very trendy these days, with billions of dollars flowing into this discipline every year via managed futures funds. The problem with these flows is that the effectiveness of trend following diminishes as more assets are devoted to the discipline, since trend following is naturally capacity constrained due to high turnover (>200%) and the liquid demanding nature of trading. It seems that trend following is crowded.
At this point in time, it may be interesting to examine other market timing signals as an alternative way to add and reduce risk exposure. One such approach is seasonality, which is probably underutilized by the asset class trading community and thus might be more effective than trend following over the near term.
The seasonal pattern has been well known for decades – the stock market’s best period is from November through April, and its poor-performing period is from May to October. This is not the case every year, but on average this seasonal pattern has held up really well with stock markets around the world for decades.
Academics call this pattern the Halloween effect since the buy signal is generated by buying at the close on October 31 every year and the sell signal is on every April 30. What’s amazing is that seasonality has not been arbitraged away, even though the cost of implementing a seasonal trading system has been low since the 1980s. The old adage of “sell in May and go away” still works! (more…)
A stale pricing edge occurs when a security or fund can be purchased or sold at a price that is stale with respect to current up-to-the-second information. This trading edge is as fleeting as a twenty dollar bill sitting on a busy sidewalk. For instance, if the price of a U.S. equity closed-end fund is sitting at bid $10, ask $10.10 for most of the day without trading activity, and the S&P 500 trades up 2% during the day, the ask price of $10.10 may be too low, and therefore, stale. Then buying at the bid can provide a risk-free profit (if hedged by an S&P 500 short) of at least 10 cents, since the fund should be trading at $10.20/$10.30.
You’ll never find stale prices with liquid large cap equities or ETFs. Only rarely do they occur with securities that don’t trade very often, such as closed-end funds. The stale price edge is not backtestable with price data since simulated orders would have affected prices at the time.
Generally, we’d expect stale price opportunities to occasionally occur with illiquid stocks that trade with a wide bid-ask spread, with very little size offered. Stale prices may also emerge when transaction costs are high (perhaps due to a financial transaction tax), or when markets are highly volatile. In the heat of a stock market crash, when 10% up and down days are the norm, we’d expect a few stale price opportunities to emerge. Getting back to the U.S. equity closed-end fund discussed above, if the S&P 500 ramped 5% in the last hour of the day, and the closed-end fund lagged up only 2%, then perhaps that’s an opportunity to buy at the ask, and expect its price to eventually catch up (possibly the next morning).
Funds are the bread-and-butter tools for asset class traders – ETFs, ETNs, closed-end funds, open-end funds, limited partnerships, etc. There are stale pricing opportunities that can occur with investment funds from time to time.
Most notable was the stale pricing associated with open-end mutual funds. This advantage is no longer available today, but it represented a structural edge from the 1980s to the early 2000s. In his book The New Market Wizards, Jack Schwager profiled one trader, Gil Blake,1 who used this edge in the 1980s to produce an annualized return of 45% per year over 12 years. Mr. Blake actively traded Fidelity sector funds to generate those returns, switching in and out of funds every day. Interestingly, he was unaware of why the strategy worked, when what he was doing was systematically exploiting stale pricing. At that time, mutual fund prices exhibited a daily serial correlation because many of the securities held in the fund had stale prices when used to calculate the daily close-of-business net asset value (NAV). (more…)
Cut your losses short, and let your profits run.
For centuries, that’s probably the number one trader’s adage. This is exactly what the trend following (TF) investment discipline does – using simple rules to be long markets in uptrends and short markets in downtrends. The mathematical rules used to identify uptrends and downtrends are predefined and mechanically implemented to eliminate human emotions in deciding when to be in or out of a market.
The most common way trend following is implemented is with managed futures funds, which are typically placed in the “alternatives bucket” of an investment portfolio, perhaps making up 5% of the total. A good example of such a fund is the AQR Managed Futures Strategy Fund (Symbol: AQMIX). Managed futures funds apply the trend-following discipline to various equity and fixed income markets, along with currency pairs and commodity futures.
In this blog, I’ll examine the trend-following approach applied to asset classes that have a positive risk premium above inflation and T-bills, which are stocks and bonds. In addition, the focus will be to shift into cash when stock and bond trends are down, rather than more aggressively shorting downtrends. This is traditionally the realm of market timing, hence my distinction using the title “Trend-Following Market Timing”.
It’s an open question for me about whether managed futures funds add value over the long term, and this is worthy of a future blog piece. Generally, shorting stocks on a TF signal doesn’t work very well in the long term, but it does reduce managed futures fund correlation to stocks, and provides “bear market insurance” for a diversified portfolio of stocks and bonds. If you believe, as I do, that currency pairs and commodity futures do not deliver a long-term return above T-bills, then what kind of return can we expect from applying a trend-following overlay to these markets? I’m not sure what the answer is, so I won’t be addressing that question in this blog.
Everything I write beyond this point about trend following applies to the market-timing view of shifting between stocks and cash, and asking whether such an approach provides any sort of trading edge. (more…)
An essential component of successful trading is having a good sense of timing. The standard industry tool for getting the timing right is technical analysis, so we need to examine its effectiveness. I’ll assume the reader is familiar with technical analysis, and as an asset class trader, I’ll also assume we control a limited amount of assets such that positions can be bought and liquidated with minimal trading impact costs.
For extremely large asset management firms and hedge funds, technical analysis is not an available tool because all-in trading costs are prohibitively expensive with this approach. These firms are forced to use other approaches such as value investing, which is, ironically, a horrible tool for timing price moves. Even large trend following CTAs are forced to use the most liquid futures contracts to minimize trading impact costs. So perhaps being small and using technical analysis is an advantage for us.
In a nutshell, technical analysis is the analysis of price and trading volume patterns to identify current and future price uptrends, downtrends and trend turning points. Practically all trading “how-to” books rely almost exclusively on technical analysis. Technical analysis techniques and patterns appear to be valid on all time scales and with any tradable security.
I gravitated to TA rather quickly when I first started trading, because as a full-time engineer, trading was a hobby. I didn’t have the time or expertise to dig through how the “fundamentals” influenced prices. I read many books on technical analysis and trading. The classic books are still the best,1-4 while most others fail to provide additional insight. In the next few blog posts I’ll talk about technical analysis, trend following and backtesting issues associated with mechanical trading models. Nowadays, I still look at charts and use basic technical analysis, but I don’t expect too much from it. (more…)