Invest Without Emotions
NASDAQ OMX indices are a great way to get same currency, apples-to-apples datasets. Here are the country specific total-return index returns (key) for 2018:
And here are returns relative to the NASDAQ Global TR Index (NQGIT):
Russia, dinged by US sanctions and a stalling economy, surprisingly put in one of the best equity returns.
Code and charts are on github.
In the book The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It (Amazon,) Scott Patterson provides a peek into the world of quantitative finance with the meltdown of 2007/2008 as a backdrop.
The book is gripping. It almost reads like a whodunit. It is like a modern-day update to Schwager’s Market Wizards series. However, I am not sure I agree with the book’s narrative that quantitative models caused and made volatility worse. In reality, an unwind of any crowded trade can trigger a doom loop of volatility. And in a margin call, the most liquid assets are the first to go. Secondly, for a book that covers statistical arbitrage, long/short value and momentum strategies and capital structure arbitrage using credit default swaps, missing Bridgewater and their risk-parity model is a big one.
Recommendation: Worth a read.
Quantitative momentum investing is fairly new in India. To compare different strategies, you need real-world data spanning a complete cycle. The best proxy for this turns out to be US listed ETFs – they have one price (unlike mutual fund share classes) and their adjusted prices can be easily downloaded. Here, we take a look at two momentum ETFs, DWAQ and MTUM, to highlight why investors should go beyond just running a screen for “momentum” and investing in whatever comes up first.
DWAQ, the Invesco DWA NASDAQ Momentum ETF, was listed back in May 2003. QQQ is a plain vanilla market cap ETF based on the Nasdaq-100 Index. Here are the descriptions from their issuer websites:
The Invesco DWA NASDAQ Momentum ETF is based on the Dorsey Wright® NASDAQ Technical Leaders Index. The Index is comprised of approximately 100 securities from an eligible universe of approximately 1,000 securities of large capitalization companies from the NASDAQ US Benchmark Index. All securities in the universe are ranked using a proprietary relative strength (momentum) measure. Each security’s score is based on intermediate and long-term price movements relative to a representative market benchmark and the other eligible securities. The top 100 securities are selected for the Index. (Invesco)
The Invesco QQQ is an exchange-traded fund based on the Nasdaq-100 Index®. The Index includes 100 of the largest domestic and international nonfinancial companies listed on the Nasdaq Stock Market based on market capitalization. (Invesco)
Here are their relative returns:
Not the torch bearer for momentum that we had hoped for.
MTUM, the iShares Edge MSCI USA Momentum Factor ETF, came a good 10 years after DWAQ. Not constrained just to the Nasdaq, it provides wider exposure to large- and mid-cap U.S. stocks exhibiting relatively higher price momentum. (iShares) It is only fair that we compare it to VONE, which is Vanguard’s Russell 1000 ETF. Russell 1000 covers most of the US large- and mid-cap universe. (Vanguard)
Here are their relative returns:
Not bad! That’s almost a 4% difference in annualized returns.
DWAQ trailed MTUM by about 5% in annualized returns for the period. Probably because it has a more diversified portfolio compared to MTUM’s. This should have lead to shallower drawdowns but that is not the case – DWAQ returns are a lot more volatile than MTUM’s. Will MTUM’s volatility adjusted price momentum continue to out-perform DWAQ’s “proprietary relative strength” momentum? Who knows?
If you think it is a tough job deciding between the two, consider this: there are over 40 momentum ETFs currently listed in the US. Each one slices the data a bit differently, making it absolutely essential that you peek under the hood before you click that buy button!
Charts created using the StockViz Compare Tool.
In Part I of this series, we saw that it is very rare for two consecutive down months to be followed by a third one. Here, we present a simple backtest that goes long NIFTY 50 for a month if the previous two months were negative.
The shallow drawdowns of this strategy makes it ideal for leveraged trades. NIFTY futures are about 7x levered. That should transform the 190% gross return to about 1330%, beating buy and hold by a wide margin. The MIDCAP 100 index behaves similar to this between the 2005 through 2018 time-frame. However, the results are not so great if you include data prior to 2005.
This looks like a case of severe data-mining and should be discounted as such. But it is an interesting result nevertheless.
Code and charts are on github.
A streak of returns is an unbroken set of up or down days, weeks or months. For example, if the market went up on each of the last four days, then it is a streak of 4 daily returns. Can streaks predict the direction of subsequent returns? Before we answer that, let us look at the density plots of up and down streaks over different periods of time. In the charts below, green lines represent positive returns and red represent the negative ones.
Distribution of NIFTY 50 daily return streaks:
Distribution of NIFTY 50 weekly return streaks:
Distribution of NIFTY 50 monthly return streaks:
Looks like something could be done with monthly returns. Click through to Part II for a quick backtest!
Code and images are on github.