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Do Or Die

List of ETFs for Sector Rotation

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Hi,

 

Sector rotation is one of the easiest and top performing trading strategy. It is easy because you have to track markets only on daily time frame and hence requires little dedicated time. It performs well because other strategies in similar time frame (holding period > 6 months) tend to get whipsawed in current economic mess.

 

cyclicalpic.jpg

 

The strategy is so much in demand that ETFs have been launched entirely to mirror a sector rotation portfolio. The Guggenheim/Zacks Sector Rotation ETF (Ticker: XRO) seeks to provide investment results that correspond generally to the performance of an equity index called the Zacks Sector Rotation Index. However, it is illiquid, and past performance data does not covers a full market cycle.

 

Take past 6 months sector performance for example. The defensive sectors of Consumer Staples, Health Care, and Utilities (XLP,XLV,XLU) are performing much better than the leading sectors of Financials, Technology, Consumer Discretionary and Industrials (XLF,XLK,XLY, XLI). This means money is flowing to the defensive sectors; i.e., the overall market is bearish. The regional banks topped out much earlier than DOW as a sign of warning (also mentioned here). I have also attached the sector scenario for market bottom in 2009, which looks just the reverse of current situation.

attachment.php?attachmentid=25707&stc=1&d=1313173909

attachment.php?attachmentid=25706&stc=1&d=1313173791

 

 

To use the list of ETFs, please keep the following points in mind:

  1. Illiquid ETFs may be used as indicators for market trend but do not use them for actual trading because they have tendency to deviate erratically from benchmark returns.
  2. The Equal weighted Rydex ETFs (first ticker letter R) tends to mirror the broad markets.
  3. The Is and Xs are market-cap weighted, meaning that larger companies have greater representation in the index. So far they have been the best indicators for identifying business cycles.
  4. Small Caps tend to outperform in the last leg of a bull market.
  5. There are also ETFs managed by rule based quantitative analysis by First Trust and Powershares. However, comprehensive information on the selection criteria is not available.
  6. The inverse ETFs or Short ETFs do not actually reverse the returns of their benchmark. You are better off shorting a relevant ETF than buying it’s inverse.

 

SECTOR-WISE LIST

 

XLY Consumer Discretionary Select Sector SPDR

RCD Consumer Discretionary

IYC iShares Dow Jones U.S. Consumer Services Sector Index Fund

PSCD S&P SmallCap Consumer Discretionary Portfolio

AXDI MSCI ACWI ex US Consumer Discretionary Sector Index Fund

 

XLP Consumer Staples Select Sector SPDR 10.84%

RHS Consumer Staples

IYK iShares Dow Jones U.S. Consumer Goods Sector Index Fund

PSCC S&P SmallCap Consumer Staples Portfolio

AXSL MSCI ACWI ex US Consumer Staples Sector Index Fund

 

XLE Energy Select Sector SPDR

RYE Energy

IYE iShares Dow Jones U.S. Energy Sector Index Fund

PSCE S&P SmallCap Energy Portfolio

AXEN MSCI ACWI ex US Energy Sector Index Fund

 

XLF Financial Select Sector SPDR

RYF Financials

IYF iShares Dow Jones U.S. Financial Sector Index Fund

PSCF S&P SmallCap Financials Portfolio

AXFN MSCI ACWI ex US Financials Sector Index Fund

 

XLV Health Care Select Sector SPDR

RYH Health Care

PSCH S&P SmallCap Health Care Portfolio

AXHE MSCI ACWI ex US Health Care Sector Index Fund

 

XLI Industrial Select Sector SPDR

RGI Industrials

IYJ iShares Dow Jones U.S. Industrial Sector Index Fund

PSCI S&P SmallCap Industrials Portfolio

AXID MSCI ACWI ex US Industrials Sector Index Fund 7.89%

 

XLB Materials Select Sector SPDR

RTM Materials

IYM iShares Dow Jones U.S. Basic Materials Sector Index Fund

PSCM S&P SmallCap Materials Portfolio

AXMT MSCI ACWI ex US Materials Sector Index Fund

 

XLK Technology Select Sector SPDR

RYT Technology

IYW iShares Dow Jones U.S. Technology Sector Index Fund

PSCT S&P SmallCap Information Technology Portfolio

AXIT MSCI ACWI ex US Information Technology Sector Index Fund

 

XLU Utilities Select Sector SPDR

RYU Utilities

IDU iShares Dow Jones U.S. Utilities Sector Index Fund

PSCU S&P SmallCap Utilities Portfolio

AXUT MSCI ACWI ex US Utilities Sector Index Fund

 

 

Posting a comment will only take you 2 minutes, but it will be the strongest motivation for me to share something better.

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Edited by Do Or Die
formatting

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HI,

Of the EFTs you noted relative to illiquid, which for trading does not workout well as to pricing, can you some how de-note within your groupings which you believe to be the more illiquid?

Jay

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Hi, Do or die. Great strategy, where do you get your research from? I know there is alot of info out there.How often do you rebalance your portfolio? Thanks

 

Hi,

 

My research comes from my trading experience. I do not use this strategy. I have better cards (see here, here and here).

 

Sector rotation is a significant improvement over any strategy that you are using for broad market. For example, If you buy the SPY on 200 MA crossovers; switching to sector rotation whenever it crosses the MA will make a significant difference. At the most basic level, it will improve returns over buy and hold.

 

I will post a backtested strategy example when get time.

Edited by Do Or Die

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HI,

Of the EFTs you noted relative to illiquid, which for trading does not workout well as to pricing, can you some how de-note within your groupings which you believe to be the more illiquid?

Jay

 

The X's and I's are the most liquid in the list (ticker symbol starting with X or I). The others are mentioned as indicators only.

 

As a general rule keep away from ETFs where avg daily volume is less than 10,000 shares

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OK, I did test two very basic tests of sector rotation on SPDRs (XLB, XLY, XLP, XLE, XLF, XLV, XLI, XLK, XLU). I do not enjoy programming and hopefully some one will improve these tests.

 

Trading Rules:

 

Keep a log of month-to-month performance of the sector ETFs. At the beginning of each month, buy the strongest of 3 sectors based on their past month returns. Alternatively to test a market neutral strategy, at each month buy the strongest and short the weakest of sector ETFs, maintaining 3 positions at all times. There are NO stop losses.

Summary:

A long-only always-in-market strategy shows returns similar to SnP 500.

A market neutral strategy made 63.86% (CAR of 7.23%) comparative to 200 day MA crossover strategy returns on SnP 50029.6% in the same period

These tests are only to show the edge or the advantage sector rotation can give you against a broad market index trading strategy. This is not a trading system.

 

Market-Neutral Performance

No. of Trades 141 Winners 58.16% Losers 41.84%  

attachment.php?attachmentid=25727&stc=1&d=1313412001

attachment.php?attachmentid=25728&stc=1&d=1313412001

Amibroker Code

SetBacktestMode(backtestRotational);
SetOption("UsePrevBarEquityForPosSizing", True);
SetOption("MinShares", 1);
SetOption("AllowPositionShrinking",True);
SetOption("AccountMargin",100);
Totalpositions = 3;
SetOption("WorstRankHeld", Totalpositions + 1);
SetOption("MaxOpenPositions", Totalpositions );
SetOption("SeparateLongShortRank", True ); 
SetOption("MaxOpenLong", 3);
SetOption("MaxOpenLong", 3);
//Monthly Rotation
perf= TimeFrameGetPrice( "C", inMonthly, -1 );
perf1= TimeFrameGetPrice( "C", inMonthly, -2 );
score= 100*((perf- perf1)/perf1);
PositionSize = -100/Totalpositions;
PositionScore = score;
m = Month();
newMonth = m != Ref( m, -1);
PositionScore = IIf(newMonth, PositionScore, scoreNoRotate);

 

Long-Only Performance

No. of Trades 177 Winners 63.84% Losers 36.16%  

attachment.php?attachmentid=25725&stc=1&d=1313412001

attachment.php?attachmentid=25726&stc=1&d=1313412001

Amibroker Code

SetBacktestMode(backtestRotational);
SetOption("UsePrevBarEquityForPosSizing", True);
SetOption("MinShares", 1);
SetOption("AllowPositionShrinking",True);
SetOption("AccountMargin",100);
Totalpositions = 3;
SetOption("WorstRankHeld", Totalpositions + 1);
SetOption("MaxOpenPositions", Totalpositions );
//Monthly Rotation
perf= TimeFrameGetPrice( "C", inMonthly, -1 );
perf1= TimeFrameGetPrice( "C", inMonthly, -2 );
score= 100*((perf- perf1)/perf1) + 100;
PositionSize = -100/Totalpositions;
PositionScore = score;
m = Month();
newMonth = m != Ref( m, -1);
PositionScore = IIf(newMonth, PositionScore, scoreNoRotate);

5aa7109829f12_11_PortfolioEquity.png.1bb87ef76c76d049645accc81cc8df63.png

5aa710982ee79_13_ProfitTable.png.f7aa62f8e6d6a25014784d268e7f0e9c.png

5aa7109832b0e_1_PortfolioEquity.png.3e6108a2ba184f6847e70ca7c4ca831f.png

5aa7109836a28_3_ProfitTable.png.58de0dcccef13730c63e672e2b75d4d3.png

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I have no experience with amibroker / portfolio backtesting.

 

 

Would you be able to test: select the best 3 performing etfs for last 6 months (trailing), sell only when the top 3 drop out of the top 50% of performers. Perform this monthly.

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Would you be able to test: select the best 3 performing etfs for last 6 months (trailing), sell only when the top 3 drop out of the top 50% of performers. Perform this monthly.

 

Please put things in rules when you're asking anyone to program. Assuming we're using the 9 SPDRs to test, do you mean?

 

  1. At each month, buy top 3 based on last six months performance
  2. At each month, sell if any spdr falls below the rank of 4 'past six month performers'

 

Both rules will contradict each other, because if we're buying top 3 performers we need to sell if their performance drops below top 3 (not top 4).

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Interesting article Do Or Die,

I have recently deployed this application in an attempt to validate the theory.

Free stock market forecast. Buy sell emails. Neural network, indexes, technical analysis predictions

The principle is as follow :

- you select a set of reference ETFs (although I set up a predefined one)

- you choose one share to be analysed

The software will first calculate the past inter dependencies between the historical data of the ETF and the historical data of your share.

It will then infer the trend of your share based on the latest data of the set of ETF.

Any thoughts?

Regards,

G.

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