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10 Market Timing Strategies, Compared

Jun. 07, 2017 8:42 AM ETSPY31 Comments
Emmanuel Marot profile picture
Emmanuel Marot


  • As investors, we would all love to be able to invest in the stock market just before it goes up, and exit it just before it goes down.
  • For some investors, ‘Market Timing’ is a well-needed arrow. For others, it is pure hubris.
  • The goal of the present objective analysis is to evaluate the efficiency of 10 different market-timing strategies and to determine if some of them are actually worth following.


Like in my previous articles, we'll try to get a statistically significant, and objective analysis. While examples like 'look how good a 200-SMA worked for Microsoft (MSFT) in 1993' or 'Amazon (AMZN) recent movements show that earnings forecasts don't work' may be amusing stories, but they would be purely anecdotal. We need to focus on a much broader simulation.

First, while the ideal would be to run tests for thousands of different stocks, we will instead focus on the market as a whole, by simulating market-timing strategies on the S&P 500. If we consider stock prices to follow a Brownian motion, then their combination is also Brownian.

Second, the simulations must span a duration as long as reasonably possible. One could argue that the stock market wasn't exactly working the same way a century ago, so we won't try to go as far. As a matter of fact we could, until recently, get S&P 500 data as early as January 3rd, 1950 with the Yahoo! Finance's API . Yahoo! unfortunately stopped the service without warnings a few weeks ago. For more recent data, we can use the wonderfully simple Tiingo.com service, but it doesn't give index prices, only securities. Therefore we'll use SPY, the largest S&P 500 ETF as a proxy. Since the S&P 500 index and SPY ETFs numbers are not exactly the same, we scale the historical Yahoo data to match. The updated data contains almost 17,000 trading day prices and is available, as a CSV file. We'll show performances both for the entire period 1950-2017, but also for the last 10 years only. The last decade is interesting because we had both a huge drop (2008), followed by an impressive but very volatile growth.

For the sake of simplicity, we will ignore both trading costs and dividends

This article was written by

Emmanuel Marot profile picture
Emmanuel Marot graduated from leading French Business School ESCP with a major in Computational Finance and a MBA exchange from the University of Washington. He previously co-founded and managed three startups, all in the Internet field, and all with successful exits; the last one being a mobile search engine that served a billion queries in over 10 countries and was subsequently sold to Microsoft Corp. An ‘accidental quant’, Emmanuel now focuses on merging sound mathematical principles with his Internet data mining experience to create new stock market investment strategies.

Analyst’s Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

Seeking Alpha's Disclosure: Past performance is no guarantee of future results. No recommendation or advice is being given as to whether any investment is suitable for a particular investor. Any views or opinions expressed above may not reflect those of Seeking Alpha as a whole. Seeking Alpha is not a licensed securities dealer, broker or US investment adviser or investment bank. Our analysts are third party authors that include both professional investors and individual investors who may not be licensed or certified by any institute or regulatory body.

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Comments (31)

Lee Bailey profile picture
Interesting and worthwhile intro to the topic, bravo! Market timing is a very difficult thing to do accurately and consistently, which is probably why most people believe its impossible. That and successful market timers do not want more competition, so telling people not to try is a wise business strategy for top firms.

We've been building sophisticated algotrading models for more than two years at https://grizzlybulls.com. They pull data in real-time from dozens or even hundreds of indicators and analyze it using complex heuristics and machine learning to produce actionable signals or biases that can be useful in avoiding corrections and outperforming the market as a whole. As of January 2022, our top algorithmic trading model has averaged annual returns in excess of 75%.

It took us a long time to get a model that was profitable at all, even more time to build one that consistently beat the market, and it's my lifetime most proud achievement to have one returning on par with top systems from Renaissance Technologies and David E. Shaw. Before our success, we were frustrated trying a bunch of simpler systems that would only work occasionally. We realized we needed to build something much more complex, resilient and robust.
Interesting and worthwhile article. Regarding the Zenvestment 30/90 strategy. Do you mean when the 30 day EMA crosses the 90 day EMA? If not please explain how the strategy works in more detail. Thanks.
Scoe profile picture
09 Jun. 2017
Your Sharpe Ratio numbers are not correct...or aren't scaled to standard units. How are you calculating them?

Also, I have met many professional investors who rely on Sharpe. Sortino is better because it eliminates the "upside penalty" that you refer to. But in most cases, this really doesn't matter much if you have enough data.
Emmanuel Marot profile picture
I wondered how long it would take for someone to notice ;-).
It's due to the way I annualized them. I didn't care to fix it since only the relative value was of interest in this analysis.
VR51 profile picture
09 Jun. 2017
Emmanuel Marot -- I suggest that you try another MA approach -- 5/20 Monthly, not daily.
Emmanuel Marot profile picture
Do you mean a moving average of 5 and 20 months?
VR51 profile picture
10 Jun. 2017
Yes, just as you used 5/20 daily MA's, put 5 & 20 MA's on a monthly chart going back 20 years.
Emmanuel Marot profile picture
Since there are 21 market days in a month (252 / 12), that gives a span of 105 days for the short EMA and 420 days for the long one.
Trading every 4 weeks since 1950 gives:

5-20 month EMA crossover
Average Return (annualized) : 7.90%
Total Return (annualized) : 4.72%

Positive Return Ratio : 51.10%
Market Beating Ratio : 7.40%
Not Losing to Market Ratio . : 89.94%
Loss Prevention Ratio : 19.94%

Sharpe Ratio : 0.28
Maximum Drawdown : 27.57%
Modified Martin Ratio : 0.38%
V2 Ratio : -0.02%
Trades per Year : 0.28
Hardog profile picture
I always like when folks talk about Mean reversion. Still trying to find that for the FANG stocks and PCLN.
Individual stock prices are less likely to mean revert. They don't have to. They can go bankrupt or grow by leaps and bounds over decades. Short term mean reversion works best with sector and national market indices. Things like Mexico, Italy, the junk bond market, the energy market, or gold. All are much less efficient markets than the S&P 500.
The best mean reversion strategies I've seen do 2 things:

1) Trade along with the long-term trend. For example, if the market is above the 200-day moving average, they only go long
2) They look for short-term opportunities. Example: buy a 7-day low and sell when it reaches a 7-day high

Larry Connors and Cesar Alvarez have done a lot of work in this area. I'd avoid mean reversion strategies that go against the long-term trend, meaning you shouldn't short very often (if at all). The only other mean reversion that may work is very long term. If stocks are trading at very high valuations (like now), move to a more conservative allocations (more bonds, possibly gold) until this changes. The article I linked earlier on Shiller PE does this.
Emmanuel Marot profile picture
Here's an approximation of the strategy you mentioned (implementing it exactly in my code would take some work):
- Stay in in market if the price is above the 200-days average
- Get in if the price is the lowest since last week
- Sell if it's below the 200-days average and not the lowest since last week.

The results are ok. Not spectacular but ok...

Starting in 1950, trading every week:
- Average Return (annualized): 9.48% (vs 9.76% for buy and hold)
- Max Drawdown: 37.67%
- Modified Martin Ratio: 0.54
- 5.42 trades per year

Starting 10 year ago is not as good:
- Average Return (annualized): 5.67%
- Max Drawdown: 37.67%
- Modified Martin Ratio: 0.29
Market Map profile picture
As many boomer aged investors most likely want preservation of capital and peace of mind during significant declines, those who want to employ dynamic risk management don't need to catch "the top" or "the bottom" tick in order to produce decent risk adjusted results and compounded asset growth.
As the S&P 500 has risen 73% of the years and declined / was flat 27% of years since 1954, if one captures a portion of " the 73%" with equities and avoids portions of the most significant declines ( > -20%, 6 % of the sample ) with investment in "flight to safety" assets, then they've won half the battle.
Movements of a simple econometric measure, the LEI, has correlated with the largest significant declines over the past 60 years.
1) Move to inversely correlated assets * ,"safe" assets, or conduct portfolio hedging during LEI signaling accompanied by the price of the S&P 500 residing below it's 10 period monthly basis and
2) move back into equity based assets on a S&P 500 price cross back above it's 10 period MA.
Constructing a diversified equity asset portfolio including highest premia risk factors ( small cap value, emerging small cap, mid cap growth, and large cap value ) for the equity assets produces added value with highest and most diversified alpha with risk mitigation provided by items 1 & 2 above.
As the LEI represents a decent measure of economic activity with symbiotic relationship to earnings and industrial output, strength or weakness in the market trend goes hand in hand. This is usually coincident with easy availability or tightening of credit which has correlated with lower or higher market volatility. Economic / market trends can be likened to a supertanker; directional change taking some time and effort . Smaller market "corrections" happen, usually by exogenous, news driven events,but don't usually impact the strength of the "direction".
* the price of VUSTX above it's 10 period monthly basis when item #1 occurs instructs the investor towards allocation into intermediate / long duration bond fund; other wise cash / money market equivalents.
. . . .
tinyurl.com/lfx7zhh ( paste links into browser address bar )
Market Map - great post. What you have described I believe is the best timing strategy for the average investor which is basically recession timing.

I use a similar system but incorporate some other economic indicators, principally the 12 month sma for unemployment - together with LEI they make a great system for avoiding real economic weakness in the markets.
What a system such as this does for nervous investors like my self, is it gives me the ability (and emotional strength) to ignore all the doom and gloom articles and let my investments run, knowing that there will come a time to take action..

Authors such as "Ploutos" provide the SA community with a great service by detailing where we can gain advantage in the market. Small and mid cap, embracing the low volaitlity principal seem like a great strategy..
Thanks. Where do you get historical data for the LEI, unemployment, etc?


Awesome website from the FED St Louis, so much data available.
Very interesting article; I appreciated reading it and the work you've done is outstanding. Thank you.
RettW profile picture

The above link shows that similar but more comprehensive research reveals that the 13/48 day EMA is best. So you were too high (50/200) and too low (5/20) in your two point sample.
It would be nice if you could do a local search around the 13/48 day EMA optimum, including the past two years of index returns.
It's actually 13/48.5 and that sounds very curve fit--especially the .5 part. Most likely, it just happened to work well in that test. Like you implied (I think), you'd need to do a parameter sensitivity test--check similar crosses like 12/48, 14/47, etc. I'd also like to see it tested before 1991 (when that backtest started). I'd be very surprised if it performed as well when tested "out of sample."

In addition, I'd like to see it tested on indexes besides the Nasdaq and Nikkei--S&P 500, Dow, Russell 2000, etc.
Emmanuel Marot profile picture
Here are the results with the 13/48 days EMA:

Starting in 1950, trading every 4 weeks:
- Average Return (annualized): 5.05%
- Max Drawdown: 35.14%
- Modified Martin Ratio: 0.22%

Starting 10 year ago results are much better:

- Average Return (annualized): 7.96%
- Max Drawdown: 14.02%
- Modified Martin Ratio: 1.00

Results are similar when trading every week. I agree it smells a bit of over-fitting, I'm a bit wary of something that works great in-sample but not so much outside. Stay tuned for a future article where we'll use artificial intelligence to find the best parameters!
Also, this article shows really good results using Shiller PE or an alternative valuation method for timing:

The drawdowns look unrealistically low, though. Something isn't right IMO.
Emmanuel Marot profile picture
Thanks for pointing out this article. Interesting results, and worthy of a further analysis. Incidentally, it's more about 'asset rotation' than 'market timing'. Which has probably more interest anyhow. But it's also harder to make an objective assessment because, alongside the strategy, the assets you choose to rotate have a huge impact on performances.
Interesting article. Market timing strategies work better when you add some sort of filter to reduce the number of trades. For example, buy/sell based on the 10 month MA (or simply if the S&P 500 is higher than it was 10 months ago). You only check this on the last trading day of the month.

The problem with the 200-day MA is there's so much whipsawing (buy/sell trades) around it. Many people watch this MA, so there's a lot of activity when price starts to touch it. It worked much better before everyone had PCs and web-baesd charting. When Trader Vic mentioned it in his book (early 90s), it had a nice track record.

Cesar Alvarez uses a modified 200-day MA strategy. He requires the price to trade above/below the MA for 10 days before trading:
Emmanuel Marot profile picture
Keep in mind that in my analysis, I'm trading at max once every 4 weeks, so reducing the frequency kinds of smooth out signals.

But to your point, if we take inspiration from the MACD, and trade when the signal line (200-days moving average) is above its smoothed line (10-days), results are similar but slightly better:

Avg return: 8.19%
Max Drawdown: 26.65%
M2 Ratio: 0.56
One of the commonly followed strategy includes volatility in the mix. Allocate certain percentages to two different moving averages and recent volatility of the underlying. It will be interesting to see the success rate of that strategy.
bikeeagle1 profile picture
Vincent makes an interesting point, but I see it the other way. Inefficient markets might be more susceptible to one-off news driven spikes, which are the antithesis of trend following systems. It is precisely because SPY is so heavily traded and "efficient" that it is more reliable for trend following.

I found the article to be very informative. Thanks to the author. For a follow up, perhaps he could investigate various timing strategies at the portfolio level? For example, using an equal-weighted portfolio of SPY, TLT, GLD, and VNQ, what would have been the results of various timing strategies?

I believe there is a fundamental Achilles heel in your approach to a short term trading system. The S&P 500 is the most heavily traded index by far. Daily dollar volume traded in SPY dwarfs all other ETFs. The index is heavily watched and there is heavy participation when it moves. In other words, it's a very efficient market. You will have a greater degree of success with short term trading systems if you seek out more inefficient markets.
07 Jun. 2017
EXACTLY. CAPE systems don't work if you are in the market when CAPE is low and out when it's high. It works if you get in when CAPE is low and hold the assets and ride to the high CAPE. Usually takes almost a decade for that to play out.
There are really only 2 kinds of trading systems: trend following and mean reverting. From my own experiences, I can confirm that inefficient markets are better for a mean reverting system. You take advantage of all those temporary "overbought" and "oversold" conditions. For a long term trend following system like the author seems to desire, I'm not convinced that day to day market efficiency matters, but it will smooth out the ride. I suggest the author explore mean reverting strategies using inefficient volatile markets. The results may be much better than what's presented above.
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