The following paper will explain how to build a U. This strategy is therefore different from our Global Sector Rotation strategy, as it only employs US sectors. The addition of the negatively correlated short sector rotation model significantly reduces volatility and drawdowns during difficult market periods.

The result is a meta sector ETF rotation strategy which performed well since in the backtests. The Sector rotation strategy produced an average yearly profit of What makes this sector etf rotation strategy interesting is that it does not rely on either treasuries or bonds to balance out and hedge in times of market stress.

It uses the short US ETF sector strategy as a hedge instead. Industry Indices, have been within the first ETFs on the U.

There are sector ETF available from SPDR, Vanguard, Schwab, iShares. There are also European versions of these sector ETFs as well. These 10 Dow Jones U. Their respective ETFs are highly liquid with small spreads which makes them excellent instruments to build dynamically rebalanced portfolio investment strategies. Using our QuantTrader backtesting software you can therefore modify this strategy to fit the ETF provided by your k or IRA Roth plan sponsor, use our QuantTrader free trial to simulate yours.

Here are the 10 main U. The Select Sector SPDR ETF exist since Only the XLRE ETF for the real estate sector was added later in With the 9 main sector SPDR ETF in existence for nearly 18 years, we can easily perform long-term strategy backtests covering all sorts of economic events, including some important market corrections in , and Due to the small spread of these SPDR ETFs and low fees with good discount brokers we can rebalance our investment monthly at low cost.

For all 10 sectors, we also have inverse SPDR sector ETF. This allows us to short the worst performing sectors.

3 Sector Rotation Strategies for ETF Investors

If you use the inverse ETFs, then you have to take into account the leverage of these ETFs and divide your buy orders by 2x or 3x. Most of our Logical Invest strategies are trend following strategies. US sectors are a very good way to do trend following, because each sector normally over- or under-performs for long periods at a time. This also means that over- or under-performance is due to longer lasting economic cycles, not just short term market fluctuations.

The economy itself is not a linear stable system, but swings between periods of expansion growth and contraction recession. Each market cycle favors a different industry sector, and the goal of a good working sector rotation strategy is to invest always in the best performing sectors while avoiding or even shorting the worst performing sectors. In fact there is not only one single trend following strategy possible, but we have different ways to construct sector rotation strategies.

To backtest these sector rotation model we use our QuantTrader backtesting software. This is probably the most basic trend following strategy.

The strategy ranks the Select Sector SPDR ETF and every month we invest in the top SPDR ETF for the following month. The image below shows the sector rotation model backtest using QuantTrader QT. The backtest starts Oct. QT shows 3 panes. The top pane just shows the different SPDR sector ETFs performances. We did not include the relatively new XLRE ETF sector, but only the 9 basic industry sectors which allows for a longer backtest.

The middle pane shows the monthly changed asset allocation. In fact you see that we only used 6 of the 9 sectors, while more than half of the time the sector rotation strategy was invested in the consumer staples sector XLP ETF and also quite often in the utilities sector XLU ETF. The summary field shows that the sector rotation ETF strategy produced an average yearly profit of 9. These 2 parameters are used to rank the SPDR sector ETFs each month and determine the top sector.

We normalize the returns because we want to rank also the SPDR sectors ETFs with negative return. Normalizing means that we use 1. The volatility is normalized the same way. The volatility attenuator allows us to give a weight to the volatility or risk of an ETF. If the volatility attenuator is 1, then we have a normal Sharpe formula with performance divided by volatility.

If the attenuator is 0, then we always divide by 1, which means that we rank only by performance and we do not consider volatility or risk. A volatility attenuator higher than 1 means that we rather want low volatility SPDR sector ETFs, but still prefer a good return.

For the strategy, we use a volatility attenuator of 5, which means that we want to select the SPDR sector ETFs with low volatility. The result is a volatility of 15 for this strategy which is lower than the volatility of most SPDR sectors ETFs or the SPY ETF. For some bull market cycles, it is probably a little too safe, therefore we construct a second trend following strategy which is selecting well performing sectors a little bit more aggressively. This sector rotation model has a lookback period of only 7 trading days.

This means that each month it will invest in the best performing SPDR sector ETFs of the last 1. Such a stock sector rotation strategy will automatically result in more frequent rebalancing. You see in the middle pane of the chart above, every single one of the 9 SPDR ETFs was used. This strategy however reacts much faster on market changes than the previous one, and about half of the time the strategy is invested in different sector ETFs than the strategy with a long lookback period.

The sector rotation model has a yearly profit of 9. The performance of the two stock sector rotation strategies using long and short lookback periods is nearly identical even if they invest half of the time in different sectors. With our QuantTrader backtesting software, strategies themselves, can be used like ETFs in new strategies. We call such strategies meta-strategies or strategy of strategies.

Now, if you combine the previous two sector rotation strategies in a single sector rotation model you get a higher Sharpe ratio than the two single strategies. If I dynamically allocate between the two strategies, then I get an average annual return of During flat to declining markets, in the below charts you can see that the QuantTrader backtest will allocate most of the investment into the long lookback low volatility strategy.

During bull markets the short lookback strategy seems to work better. So, all together you can say that these two SPDR ETF rotation strategies complement each other quite well and it makes sense to use them together rather than only using one single strategy.

Another way to construct sector rotation strategies is to use mean reversion. When the current market price is less than the average price, the stock is considered attractive for purchase, with the expectation that the price will rise. When the current market price is above the average price, the market price is expected to fall. In other words, deviations from the average price are expected to revert to the mean. Quant trader can be used to build such strategies with sector ETFs.

There are however each month sectors which perform much better or much worse than the average. Normally the market exaggerates to the down- and to the upside moves of the best and the worst sector. There is a good probability that the worst sector will recover slightly from its losses the next month and the best ETF will give away some of its gain due to profit taking. Based on this probability we can now build some mean reversion strategies.

Nearly every month you have to invest in another of the SPDR sector ETFs as you can see in the charts below. The sector rotation model calculates performance differently than for normal momentum strategies. For this strategy the perforance is calculated like this:. The -2x 20 day performance means that the last month performance of the worst SPDR ETF is multiplied by -2x. To this we add the performance of the last 10 days. The result is that an ETF with a positive convexity is preferred.

ETFs For Sector Rotation Strategies

In the chart below you have the performance curve of two SPDR sector ETFs. The green one goes down linearly but the red one oes down and during the last 10 days shows signs of recovery. The strategy has a yearly profit of So, the strategy also performed even slightly better than the two momentum strategies.

This strategy invests in the best momentum SPDR sector ETF which had a small correction during the last 2 weeks. During bull markets, many investors feel they just missed the opportunity to invest in a good performing sector. Since they do not like to buy at all time heights, they wait until there is a small correction of their favorite industry sector.

This is what this strategy does, and it works quite well. The stock sector rotation strategy has a yearly profit of So, the model performed even slightly better than the two momentum models.

This is in fact a short strategy with a negative correlation to the market. Constructing profitable short strategies is very difficult.

I tried to use momentum and short always the worst ETF, but this does not work well because of the mean reversion which I used in the last strategy. The best way to short the market is to sell the best performing sector ETF, betting on the fact that it will probably revert to the mean on profit taking. The sector rotation model has a yearly profit of 1. As you can see, the result is quite poor and it would not make sense to invest in such a strategy alone. If markets begin to move sideways, the sector rotation model already goes up and this accelerates on down going markets.

In fact it is a perfect hedging strategy. A meta-strategy is a strategy composed not of ETFs but of sub-strategies.

QuantTrader calculates the performance of a strategy like an ETF. This way you can build a new U. We use a lookback period of days and rank our 5 strategies. This negative correlation will reduce a lot the volatility of the composed meta-strategy. The chart below shows the result produced by our backtesting software.

The middle pane shows you how the asset allocation between the 5 different US Sector rotation strategies changed. The strategy produced an average yearly profit of These backtest results of our sector rotation strategies emplying SPDR ETF are very promising.

The backtests included many big market corrections and the sectors cover the whole U. The sector rotation models are also quite stable and work with a wide range of parameters with a lot of ETF changes over this long backtest period, so that there is not much danger of overfitting.

I use this stock sector rotation strategy myself since quite some time and I think that the probability is high that this model continues to work also well in the future. You can simply register for it from this link and will receive the monthly allocations by email. Using our QuantTrader backtesting software you can modify this strategy to either fit the ETF provided by your k or IRA Roth plan sponsor, or to contribute to the vivid discussion in our QuantTrader forum to further enhance the strategy.

Use our QuantTrader 30 days free trial to simulate yours. I was just thinking about this the other day, how to build a good US sector strategy, so this was an article with very good timing: Thanks for the flowers, appreciated. Yes, the strategy will be automatically available for our All-Strategies and QuantTrader subscribers. Our QT subscribers will find it also in the next QT release, to be posted over the weekend. Yes, but only after some weeks, need to rebuild part of the tool, sorry.

Also initially I will not recalculate the preconfigured portfolio options, as this might affect some people who do not wish to get to US centric in their portfolio. Hi David and welcome.

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You will also receive an email in your inbox. Please refer to the welcoming email for more useful info. We develop intelligent, rule-based portfolio investment models. About us Contact us On Seeking Alpha On Talking Markets. Facebook Rss Twitter Vimeo Youtube Googleplus Linkedin Email. How to get started. The Logical Invest long-short US Sector Rotation Strategy.

The Logical Invest long-short US Sector Rotation Strategy — A US sector rotation meta strategy combining dynamically 5 different sector strategies based on SPDR ETF The following paper will explain how to build a U. Sector Sector SPDR ETF Inverse Sector SPDR ETF leverage Sector Futures GLOBEX U. Materials Sector XLB ETF SMN ETF -2x IXB Future U. Financial Sector XLF ETF SKF ETF -2x IXM Future U. Industrials Sector XLI ETF SIJ ETF -2x IXI Future U. Technology Sector XLK ETF REW ETF -2x IXT Future U.

Consumer Staples Sector XLP ETF SZK ETF -2x IXR Future U. Real Estate Sector XLRE ETF SRS ETF -2x U. Utilities Sector XLU ETF SDP ETF -2x IXU Future U. Health Care Sector XLV ETF RXD ETF -2x IXV Future U. Sector XLY ETF SCC ETF -2x IXY Future Extended backtest using SPDR ETF since The Select Sector SPDR ETF exist since An overview of different U.

Combining both into one sector rotation strategy The performance of the two stock sector rotation strategies using long and short lookback periods is nearly identical even if they invest half of the time in different sectors. Mean reversion sector ETF rotation strategy Another way to construct sector rotation strategies is to use mean reversion.

For this strategy the perforance is calculated like this: Our formula would select the red chart or sector ETF. Mean reversion can also be combined with momentum. The next strategy will do exactly that: Sector Rotation meta-strategy using SPDR ETF A meta-strategy is a strategy composed not of ETFs but of sub-strategies.

Backtest performance overview year Frank Grossmann Logical-Invest, Frank studied Microtechnics at the Federal Institute of Technology in Lausanne and Business Administration at the Federal Institute of Technology in Zurich. After the Studies in he founded Labocontrol AG. Labocontrol developed high speed film scanners used in most of the photo labs for the production of Photo CD's. In Labocontrol was sold to Digital Now and Frank worked as Chief Scientist and later CTO of this Company.

In Mai Frank founded Colour-Science AG a company specialized in image processing algorithms like face detection or red eye removal. Many of these algorithms could be also used to search for pattern in financial data, so Frank began to develop and back test rule based investment strategies. The main focus was to find strategies, which would allow a positive return also during a financial downturn or major financial crash. Based on this research, logical-invest developed some very successful strategies and due to its solid performance and positive returns, we decided to share our knowledge with you and publish it on a monthly basis through "rent-a-strategy".

Will this strategy also be included in the monthly allocation emails sent to QT-subscribers? This is great news. When will it be added to the Custom Portfolio Builder? Leave A Comment Cancel reply Comment. Check out QuantTrader — Free Trial.

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