38 DTE Iron Condor Results Summary

The introduction to this series, here, described the different variations of SPX iron condors (IC) and exits that were tested at 38 days to expiration (DTE).  Recall, the tests covered 9 IC variations, with short strike deltas at four locations, utilizing 12 exits.  In all, there were 432 test runs (9 variations x 4 deltas x 12 exits). Each test run executed more than 200 SPX IC trades between the Jan-2007 expiration and the Sep-2016 expiration.  I used weekly options for this testing, so there were more than 12 trades per year.  In total, there were 97,416 total trades entered for the 38 DTE testing.

There are six groupings of charts below, with each grouping containing 12 charts.  Each row corresponds to a short delta (row 1 = 8 delta, row 2 = 12 delta, row 3 = 16 delta, row 4 = 20 delta), and each column corresponds to an IC wing width (column 1 = 25 points, column 2 = 50 points, column 3 = 75 points).

Each of the charts contains data for the 12 exits for each of the three primary IC structures (standard balanced - ST, extra long put - EL, delta neutral - DN).

All of the charts are structured similarly:

• Each colored line in a chart represents a particular type of IC structure:
• Blue lines are for standard balanced ICs (ST)
• Red lines are for extra long put ICs (EL)
• Green lines are for delta neutral ICs (DN)
• The lines styles are associated with a particular profit taking approach:
• Solid lines represent profit taking at 50% of the credit received
• Dashed lines represent profit taking at 75% of the credit received
• Dotted lines represent closing the trade at 2 DTE with no profit taking target (NA)
• The X-axis displays the loss taking percentage level in terms of the credit received:
• 100%, 200%, 300%, and no loss taking level / closing at 2 DTE (NA)

Normalized P&L per Day

This first set of charts shows normalized P&L Per Day percentages.  A couple of notes on these charts:

• The Y-axis scale is the same for all the P&L per day charts in this blog post
• The Y-axis displays the average normalized percent P&L per day
• Each of the 432 test runs is represented in the 12 charts below, and each test run had a different average days-in-trade (DIT).  The number DIT obviously impacts the average P&L per day
• The max risk for a 25 point 8 delta IC will be approximately half the max risk for a 50 point 8 delta IC.  The P&L per day values are expressed as a percentage of the max risk for that test run...this is necessary in order to fairly compare the returns of each of the different wing widths

A couple of trends are clear:

1. There is more variability in P&L per day readings in the 25 point wing width ICs
2. As the delta of the short strikes increases, the variability in the P&L per day readings increases
3. The largest reading was 0.18% and was associated with the ST (100:50), 50 point wings, 20 delta
4. The next best reading was 0.17% and was associated with three test runs: 
1. ST (100:50), 25 point wings, 20 delta
2. ST (100:75), 25 point wings, 16 delta
3. DN(100:50), 25 point wings, 20 delta

(click to enlarge)

Normalized P&L per Trade

The normalized P&L per trade charts are organized in the same way as the normalized P&L per day charts.  Also note that these returns are expressed as a percentage of the max risk for a particular test run.  There were 432 test runs, with each test run including 200+ trades.  In a test run, the $ returns for each of these trades varied slightly, as well as the $ max risk for each of these trades.  The $ returns were averaged, and this $ average was divided by the largest $ max risk for all of the 200+ trades in that run.  This is the normalized P&L for that test run...with all 432 of these data points displayed in the 12 charts below.

We see the following in the data:

1. We can see that the variability in normalized P&L per trade again increases as the delta of the short strike increases, and decreases with increasing wing width.
2. The largest normalized P&L per trade was 4.3% for the ST (200:75), 25 point wings, 16 delta
3. The top four P&L per trade variations were all associated with profit taking at 75%, wing widths of 25 points, and short strike deltas of 16
4. The top P&L per day variations came in the following positions in terms of P&L per trade:
1. ST (100:50), 50 point wings, 20 delta came in 7th place -> 3.4%
2. ST (100:50), 25 point wings, 20 delta came in 11th place -> 3.4%
3. ST (100:75), 25 point wings, 16 delta came in 2nd place -> 4.1%
4. DN(100:50), 25 point wings, 20 delta came in 5th place -> 3.5%

(click to enlarge)

Win Rate

The chart structure should be familiar to you by now, so I'll not review the chart layouts.  The win rate trends are clear:

1. Win rates tend to increase as wing widths increase
2. Win rates tend to increase as the delta of the short strike decreases
3. The top win rate was 92%, and was associated with these five strategies:
1. DN (NA:50), wing width 75, 8 delta
2. DN (NA:50), wing width 50, 8 delta
3. ST (NA:50), wing width 50, 8 delta
4. ST (NA:50), wing width 75, 8 delta
5. DN (NA:50), wing width 25, 8 delta
4. The top 10 strategies all had win rates of 91% or better...and all 10 had two variables in common...they took profits at 50%, and none of them used loss exits (they exited at 2 DTE).  8 of these 10 also had short strike deltas of 8.

(click to enlarge)

Largest Loss

The next charts show the normalized largest loss for each of the test runs  These largest losses are expressed as a percentage of the max defined risk number for all of the 200+ trades in a test run.  Here are the trends:

1. The largest loss percentage increases with increasing short strike delta
2. The largest loss percentage increases with increasing loss taking level...surprise! :)
3. The top 24 largest losses all occurred with strategies with 25 point wing widths, and had losses of 95% or greater
4. The top 4 smallest losses all occurred with strategies with 75 point wing widths and 8 delta short strikes:
1. DN (100:50), 75 point wings, 8 delta -> 15% loss
2. DN (100:75), 75 point wings, 8 delta -> 15% loss
3. ST (100:50), 75 point wings, 8 delta ->15% loss
4. ST (100:75), 75 point wings, 8 delta -> 15% loss

(click to enlarge)

Profit Factor

The best 15 profit factors were associated with delta neutral trades with 8 delta short strikes.  The top performers were:

1. DN (NA:NA), 75 point wings, 8 delta -> 2.0
2. DN (NA:75), 50 point wings, 8 delta -> 1.9
3. DN (NA:75), 75 point wings, 8 delta -> 1.9
4. DN (NA:NA), 50 point wings, 8 delta -> 1.9
5. DN (300:75), 50 point wings, 8 delta -> 1.9 

(click to enlarge)

Average DIT For Winning Trades

This metric was derived by averaging all of the DIT for all of the winning trades in test run.  If you are basing your IC trading on one of the 432 variations in my backtesting, you'll want to keep an eye on these DIT numbers.  Adding a DIT exit to your profit and loss exits is worth considering.

Here are a few trends:

1. The larger the delta of your short strikes the longer you'll need to stay in your trades
2. The larger your profit taking level, the longer you'll need to stay in your trade...surprise! :)
3. The 50% profit taking level should have you out of the trade in less than 20 days for a 38 DTE IC
4. The smallest winning trade DITs were associated with 8 delta short strikes, profit taking at 50%, and loss taking at 100%...the structure type (ST, EL, DN) did not matter as seen in the charts

(click to enlarge)

A part two to this article will follow some time next week.

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New Iron Condor Series Introduction

If you've been following my Twitter feed, you know that I have started analyzing Iron Condors (IC) again. I am looking at the same three structures that I've looked at in past posts (standard balanced IC, delta neutral IC, and extra long put IC), but with varying wing widths.  Part of the motivation here is to see if we can get close to short strangle returns, but with defined risk. 

In the screen shots below, are examples of these three structures, with the three different wing widths that will be reviewed (25 point, 50 point, and 75 point).   These screen shots were taken after market close on Monday, December 19th, using the SPX 17-Feb-2017 expiration at 59 DTE.  The standard balanced ICs are all 10 contracts / 10 lot.  The delta neutral IC and extra long put IC modify this 10 lot structure as shown below.


Standard Balanced Iron Condor (ST)

• 25 point wing width 
• Strikes: 2415 / 2390 / 2045 / 2020
• Short Delta: 8 
• Credit: $2,100
• Max Risk: $22,850

(click to enlarge)

• 50 point wing width 
• Strikes: 2440 / 2390 / 2045 / 1995
• Short Delta: 8 
• Credit: $3,600
• Max Risk: $46,400

(click to enlarge)

• 75 point wing width
• Strikes: 2465 / 2390 / 2045 / 1970
• Short Delta: 8
• Credit: $4,700
• Max Risk: $70,300

(click to enlarge)

Extra Long Put Iron Condor (EL)

• 25 point wing width
• Strikes: 2415 / 2390 / 2045 / 2020
• Short Delta: 8
• Credit: $1,565
• Max Risk: $23,435

(click to enlarge)

• 50 point wing width
• Strikes: 2440 / 2390 / 2045 / 1995
• Short Delta: 8
• Credit: $3,145
• Max Risk: $46,855

(click to enlarge)

• 75 point wing width
• Strikes: 2465 / 2390 / 2045 / 1970
• Short Delta: 8
• Credit: $4,340
• Max Risk: $70,660

(click to enlarge)

Delta Neutral Iron Condor (DN)

• 25 point wing width
• Strikes: 2415 / 2390 / 2045 / 2020
• Short Delta: 8
• Credit: $1,525
• Max Risk: $23,475

(click to enlarge)

• 50 point wing width
• Strikes: 2440 / 2390 / 2045 / 1995
• Short Delta: 8
• Credit: $2,675
• Max Risk: $47,325

(click to enlarge)

• 75 point wing width
• Strikes: 2465 / 2390 / 2045 / 1970
• Short Delta: 8
• Credit: $3,575
• Max Risk: $71,425

(click to enlarge)

Over the next several months I will review how these 9 IC variations have performed between the Jan-2007 expiration and the Sep-2016 expiration on the SPX.  Unlike past tests, in this series, I will include weekly options.  This will provide more trade occurrences, thus resulting in more meaningful metrics.

I will look at four different short strike deltas (8, 12, 16, and 20), across several DTE (38, 45, 52, 59, 66, 73, and 80) for the 9 IC variations above.

The following 12 exits will be tested for each of the 9 variations at each delta, for each DTE:

1. NA:NA - exit at 2 DTE.
2. NA:50 - exit if the trade has a profit of 50% of its initial credit OR 2 DTE.
3. NA:75 - exit if the trade has a profit of 75% of its initial credit OR 2 DTE.
4. 100:NA - exit if the trade has a loss of 100% of its initial credit OR 2 DTE.
5. 100:50 - exit if the trade has a loss of 100% of its initial credit OR if the trade has a profit of 50% of its initial credit OR 2 DTE.
6. 100:75 - exit if the trade has a loss of 100% of its initial credit OR if the trade has a profit of 75% of its initial credit OR 2 DTE.
7. 200:NA - exit if the trade has a loss of 200% of its initial credit OR 2 DTE.
8. 200:50 - exit if the trade has a loss of 200% of its initial credit OR if the trade has a profit of 50% of its initial credit OR 2 DTE.
9. 200:75 - exit if the trade has a loss of 200% of its initial credit OR if the trade has a profit of 75% of its initial credit OR 2 DTE.
10. 300:NA - exit if the trade has a loss of 300% of its initial credit OR 2 DTE.
11. 300:50 - exit if the trade has a loss of 300% of its initial credit OR if the trade has a profit of 50% of its initial credit OR 2 DTE.
12. 300:75 - exit if the trade has a loss of 300% of its initial credit OR if the trade has a profit of 75% of its initial credit OR 2 DTE.

For a given DTE, there will be 432 test runs (9 variations x 4 deltas x 12 exits).  As mentioned earlier, each test run will enter as many trades as possible that meet the entry criteria between the Jan-2007 expiration and the Sep-2016 expiration.  For a given DTE, this will result in the backtest of approximately 100,000 trades.  This process will take some time!


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Momentum Rotation System AmiBroker Code

I've received several requests for details on the AmiBroker (AB) code and settings used for the backtest shown in my April post: Momentum Rotation 60 Day ROC System Results. That post used the AmiBroker Formula Language (AFL) code from my article in March 2015.  That was a long time ago, so here is the 60 day momentum rotation system AFL again:

SetBacktestMode( backtestRotational );

// 1 ###### BACKTESTER SETTINGS - 1. GENERAL TAB 
SetOption("InitialEquity", 100000);
SetOption("MinShares", 1);
SetOption("MinPosValue", 0);
SetOption("FuturesMode", False);
SetOption("AllowPositionShrinking", False);
SetOption("ActivateStopsImmediately", False);
SetOption("ReverseSignalForcesExit", False);
SetOption("AllowSameBarExit", False);
RoundLotSize = 0;
TickSize = 0;
MarginDeposit = 0;
PointValue = 1;
SetOption("CommissionMode", 2);
SetOption("CommissionAmount", 7.95);
SetOption("InterestRate", 0);
SetOption("AccountMargin", 100);
SetOption("MarginRequirement", 100);

// 2 ###### BACKTESTER SETTINGS - 2. TRADES TAB 
BuyPrice = SellPrice = ShortPrice = CoverPrice = Close;
SetTradeDelays( 1, 1, 1, 1);

// 5 ###### BACKTESTER SETTINGS - 5. PORTFOLIO TAB 
//SetOption("MaxOpenPositions",   1);
// check the box to "Add artificial future bar..."
// Limit trade size as % - use 10 for live trading
// check the box to "Disable trade size limit..."
SetOption("UsePrevBarEquityForPosSizing", False);
SetOption("UseCustomBacktestProc",  False);

// 6 ###### BACKTESTER SETTINGS - 6. WALK FORWARD TAB
//SetOption("WorstRankHeld",    1);


Totalpositions = 1;
SetOption("WorstRankHeld", 1);
SetOption("MaxOpenPositions", Totalpositions );
PositionSize = -100 / Totalpositions ;

LastDayOfMonth = IIf( (Month() == Ref( Month(), 1) AND (Month() != Ref( Month(), 2)) ), 1, 0);
TradeDay = LastDayOfMonth ;

Score = ROC(Close, 60);
PositionScore = IIf(Score < 0, 0, Score ); // Long only
PositionScore = IIf(TradeDay , PositionScore , scoreNoRotate);

//Exploration
Filter = 1;
AddColumn(Score ,"Score",1.1);
AddColumn(PositionScore ,"PositionScore ",1.1);
AddColumn(PositionSize ,"Position Size",1.1);

You can download the AFL code above from my Google Drive: 00_60DayMomentum.afl

It is fairly straight forward AFL code, but I've highlighted four key areas:

• Line 1 - Rotational trading needs to be activated for this system
• Line 24 - Trade delays are set to 1, which means trades are entered one day after the signal is generated
• Line 43 - The LastDayOfMonth variable actually stores the second to last day of the month.  This causes the rotation ranking signal to be calculated on the second to last day of the month.  Since our trade delay is one, the trade occurs the following day, the last day of the month
• Line 47 - If the ROC(60) is negative, then the PositionScore is set to 0, otherwise the PositionScore is set to the ROC(60)

On the second to last trading day of the month, this strategy calculates the 60 day ROC for each product in the portfolio based on closing prices on that day.  If the 60 day ROC is negative, the system sets the PositionScore to 0 for that product.  It then ranks all of the products in the portfolio, selecting the product with the highest rank.  If all products have a rank of 0, the system will move to cash.  On the last trading day of the month, it executes the buy and sell orders at the close - "market on close" orders in live trading.

In addition to the AFL code above, I used the AB settings shown below.  To replicate my results, you'll need to update your AB settings to match mine.

AmiBroker Backtester Settings - General Tab

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AmiBroker Backtester Settings - Trades Tab

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AmiBroker Backtester Settings - Stops Tab

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AmiBroker Backtester Settings - Report Tab

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AmiBroker Backtester Settings - Portfolio Tab

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AmiBroker Backtester Settings - Walk Forward Tab

(click to enlarge)

AmiBroker Backtester Settings - Monte Carlo Tab

(click to enlarge)

AmiBroker Backtester Filter Settings

(click to enlarge)

To run my AFL in your installation of AmiBroker:

• Download my AFL file
• Open an AB Analysis tab
• Select my AFL file in the Formula field on the Analysis tab
• Update the filter settings (shown above) to only run this strategy against a specific Watch List
• Change the range to "From-To dates", and then select a date range
• Finally, select the Backtest button to run the strategy

After you have backtesting configured and running, the next step is to automate quote updates and signal generation.  I use the Windows Task Scheduler utility to call JS scripts, that in turn launch AB and AmiQuote.  This topic is beyond the scope of this article, but I may discuss it in the future.

Also, since my last blog post, there have been several articles on momentum trading, and the poor performance of these systems lately.  Here are a few worth reading:

• Alpha Architect: Is Momentum Investing Dead? Or Is It Just Painful?
• ETF.com: Why Momentum Is Struggling
• ETF.com: Is Momentum Really Dead?

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Momentum Rotation Multiple System Results

In the last two posts (here and here) we looked at the performance of a simple 60 day momentum rotation system. In this post, we will look at variations on that simple system, and how these variations performed during the same time period, using the same 10 ETF products.  The 10 ETFs used by all of the systems were:

• EEM - iShares MSCI Emerging Markets Index ETF - trade-able April 2003
• EFA - iShares MSCI EAFE Index ETF - trade-able August 2001
• FXI - iShares China Large-Cap ETF - trade-able October 2004
• IEF - iShares 7-10 Year Treasury Bond ETF - trade-able July 2002
• IYR - iShares Dow Jones US Real Estate ETF - trade-able June 2000
• SHY - iShares 1-3 Year Treasury Bond ETF - trade-able July 2002
• SPY - SPDR S&P 500 Trust ETF - trade-able January 1993
• TIP - iShares Barclays TIPS Bond ETF - trade-able December 2003
• UUP - PowerShares DB US Dollar Bullish ETF - trade-able March 2007
• XLV - Health Care Select Sector SPDR ETF - trade-able December 1998

Recall that our simple momentum rotation system only looked at the 60 day/period momentum (ROC) for ranking, and picked the one ETF with the largest positive change.  If all 10 of the ETFs in the group had a negative rate of change...a price today that was lower than the price 60 days ago, then the system moved to cash.  The system only ranked the ETFs in the portfolio on the last trading day of the month.  This is how the system shown in the past posts was structured.  The associated AmiBroker afl code can be found here.

In this post, we will look at six versions of this simple system:

1. 20 period momentum rotation ( ROC(20) )
2. 60 period momentum rotation ( ROC(60) )
3. 120 period momentum rotation ( ROC(120) )
4. 20 period / 120 period momentum rotation ( ROC(20) + ROC(120) )
5. 20 period / 120 period smoothed momentum rotation ( ROC(20) + MA(ROC(120), 20) ) 
6. Weighted momentum rotation ( 0.5*ROC(120) + 0.3*ROC(20) + 0.2*HV(120) )

We will review four variations of each of these six systems, and compare their performance to that of our "standard" 60 period momentum rotation system reviewed in my previous articles.  There are six equity curve charts below, one for each of the six versions listed above.  Each equity curve chart contains the following four variations:

1. No Ftr (No Filter - NF) - select the ETF that has the greatest ROC of the 10 ETFs; positive momentum or the smallest negative momentum (green)
2. Slope Ftr (Slope Filter - SF) - select the ETF that has the greatest positive ROC of the 10 ETFs; do not select any ETF if all 10 ETFs have negative ROC -> go to cash (blue)
3. Brdth Ftr (Breadth Filter - BF) - select the ETF that has the greatest ROC of the 10 ETFs; positive momentum or the smallest negative momentum; if the breadth filter (based on 200 funds) is below a threshold value -> go to cash (gold)
4. Markt Ftr (Market Filter - MA) - select the ETF that has the greatest ROC of the 10 ETFs; positive momentum or the smallest negative momentum; if the S&P 500 is below the 200 day MA on the S&P 500 -> go to cash (purple)

In addition, each of the six equity curve charts contains the equity curves for two additional systems:

• Standard - our standard 60 period momentum rotation system with slope filter; no trades taken with negative momentum (red)
• S&P 500 Index - buy and hold the S&P 500 (orange)

Now let's look at the equity curves for each of the six system variations...

20 Period Momentum ( ROC(20) )

(click to enlarge)

The four systems (No Ftr, Slope Ftr, Brdth Ftr, Mrkt Ftr) use as their core, a momentum system based on the 20 period rate of change (ROC(20)).  The "standard" 60 period momentum system (red) had the greatest overall return, and the four 20 period variations returned about the same as buying and holding the S&P 500 (orange).


60 Period Momentum ( ROC(60) )

(click to enlarge)

In the equity curve chart above, the red curve is the same as the blue curve; the "standard" system is the same as the 60 period system with the slope filter.  Our "standard" system had the lowest overall performance of the 60 period systems, although they all performed better than buy and hold (orange).  The best performance went to the non-filtered system variation (green).


120 Period Momentum ( ROC(120) )

(click to enlarge)

Other than the market filter variation (purple), the other three 120 period variations seem to be recovering from the 2015 performance lull fairly well.  The best performance went to the non-filtered system variation (green).  The "standard" system (red) under performed all 120 period variations.


ROC(20) + ROC(120)

(click to enlarge)

These four variations added the 20 period momentum to the 120 period momentum, yielding a composite momentum score.  The best performance again went to the non-filtered variation, with the breadth filter variation coming in second place.  All variations out performed buy and hold.


ROC(20) + MA(ROC(120), 20)

(click to enlarge)

These four variations added the 20 period momentum to the 20 period moving average of the 120 period momentum.  These variations respond more slowly to the change in the 120 period momentum.  We see the impact of this change on the steep decline in system performance in 2015.  All variations again out performed buy and hold.


Weighted System Components (3)

(click to enlarge)

Lastly, we look at four variations that are based on summing three weighted scores.  These four variations add the 120 period momentum (multiplied by 0.5) with the 20 period momentum (multiplied by 0.3) with the 120 period historical volatility (multiplied by 0.2).  The best performance went to the non-filtered variation, followed by the breadth filter variation.

For me, there were two big take-aways in reviewing these equity curves.  One, all versions and variations experienced poor performance in 2015.  Second, the non-filtered variations, in general, outperformed the other variations.  These same two trends were present in nearly all of the other 30+ product portfolios I tested with these systems.

Finally, I thought it was interesting that just this week the following article was published via Quantpedia: Has Momentum Lost Its Momentum?

In the next post, I will share the AmiBroker system settings that I used for these tests, so that you can replicate the "standard" system results.


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Momentum Rotation 60 Day ROC System Metrics

It's been a while since my last post.  I had planned on writing this particular article about three months ago, but work got in the way of my writing and testing  Over the next few weeks I will try to close out this series on momentum rotation using my 60 day ROC example written for AmiBroker.  After I finish this series, I will get back to option strategy backtesting

I thought it was interesting how poorly the 60 day ROC momentum rotation system performed during 2015.  During this period, there were no consistent uptrends for the products traded by my example system.  I believe this was the primary reason for the poor performance.  I thought this might be reflected in the 250 day correlation between the products (measured at the end of each year in the test period).  The correlation tables are shown below.  Surprisingly, 2015 did not look dramatically different than some of the other years.

2003 - 250 Day Correlation

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2004 - 250 Day Correlation

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2005 - 250 Day Correlation

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2006 - 250 Day Correlation

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2007 - 250 Day Correlation

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2008 - 250 Day Correlation

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2009 - 250 Day Correlation

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2010 - 250 Day Correlation

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2011 - 250 Day Correlation

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2012 - 250 Day Correlation

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2013 - 250 Day Correlation

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2014 - 250 Day Correlation

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2015 - 250 Day Correlation

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2016 - 250 Day Correlation

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Next, I looked at the performance of this system from: 1) 2003 through 2014, 2) 2015 through the first three months of 2016, and 3) 2003 through the first three months of 2016.  These metrics are shown in the table below.

(click to enlarge)

For 2015, there were a few metrics that jumped out at me compared to the 2003 through 2014 period:

1. The win rate was much lower, so fewer winning trades than typical for this system
2. The average bars held was higher for both winners and losers, so we were in the trades longer than usual before a momentum change occurred
3. The maximum consecutive winners and losers was lower, indicating a market with no sectors with strong upward momentum...a zig zagging market
4. The maximum trade drawdown was lower, indicating no persistent down moves before a trade was exited...weak uptrends and weak downtrends

I also reviewed Monte Carlo simulations for this system (using the same ETF products) from 2003 through 2016.  For the Monte Carlo runs, the position sizing utilized 99% of the available capital for each trade.

(click to enlarge)

The actual metrics for this simulation are shown in the table below.  The backtesting and Monte Carlo simulations assumed an initial portfolio equity of $100K.

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90% of the observed annual return values were at or above 9.86%.  Also in 90% of cases the drawdown was less than or equal to 31.84%.  A negative return for the system should occur in less than 1% of the cases based on the data above.  For the actual bactested system, the annual return was 16.9%.  Even when I performed the simulations with a fixed number of shares per trade, rather than 99% of the portfolio equity, there were no negative annual return values in the Monte Carlo metrics tables.  Using a fixed number of shares per trade eliminates the compounding effect.

In the next article I will show the equity curves for several other momentum rotation systems trading the same products.  Do you think they will also perform poorly during 2015?


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