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Kim

CMLviz Trade Machine

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I think this is called "curve fitting".

If you think otherwise, then pull up a monthly chart of KO going back 8 years.

What you will see is beginning in March 2009 (8 years), KO has gone straight up without any down moves that would change the outcome of this backtest.

Now, try the same back test, exact same parameters, during ANY other 1,2,3, year period PRE March 2009.

Let's see the results.

And, of course, if you backtest any time period during this 8 year period, you would always get similar outcomes.

These results are not surprising .

The only thing that would be surprising is if this test produced any other results than the one that it did.

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Well, there were periods of downward movement in KO.  Apr - Nov 2016 had a 15% decline, and several other 10% declines in 5yrs.

 

AMBA is up 100% in 3 years, but it had a VERY wild ride in the middle of those 3 years.  It first ran up 400%, then dropped nearly all the way back down, then doubled, dropped 30% again, then back up a bit.

 

But I fully agree.  One need to be very consciousness of curve fitting when using this tool.  If, like most stocks in the past 3 years, has had a tear up, of course bullish strategies are going to perform well.  (Bull put credit spreads, bull call debit spreads, naked puts, long calls, etc.)

 

I've been having a little fun with backtesting naked strangles and straddles (the TastyTrade style).  It's a little more interesting now that some of the bugs have been fixed in the software, but there's still a few others which makes it hard to believe the results without going over the individual trades with a fine toothed comb.

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For example, here's what I find a bit interesting.

DE, naked straddle.

http://tm.cmlviz.com/index.php?share_key=UYejzl3gnZBTTBfG

30 day rollover

Avoid earnings (custom, close 5 days before, open 1 day after)

Close when trade >25% gain, or >200% loss.  (Sell spread for $2, close for $0.50 profit, or for $400 loss - 200% of $2.00 x 100)

Open next trade immediately.

 

Results on just a 1-lot, 3 years:

Capture.JPG

 

And while the risk is $3807, the Portfolio Margin on that is about one-third of that.  If that's too much risk, you can butterfly it off.  Reduce the risk in half, and even increase your ROI% by almost double (50/10d).

Capture.JPG

Edited by ChadK

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50 minutes ago, cuegis said:

I think this is called "curve fitting".

If you think otherwise, then pull up a monthly chart of KO going back 8 years.

What you will see is beginning in March 2009 (8 years), KO has gone straight up without any down moves that would change the outcome of this backtest.

Now, try the same back test, exact same parameters, during ANY other 1,2,3, year period PRE March 2009.

Let's see the results.

And, of course, if you backtest any time period during this 8 year period, you would always get similar outcomes.

These results are not surprising .

The only thing that would be surprising is if this test produced any other results than the one that it did.

 

This is not curve fitting. 

 

Here is Twitter -- an utter disaster on earnings: Same strategy over 3-year with a 100% stop loss.

http://tm.cmlviz.com/index.php?share_key=ZiD5GyhkrYKM8vD8

TWTRpost3yrs.PNG

 

And over one-year:

http://tm.cmlviz.com/index.php?share_key=6D1Ebjv0J2brzKEG

TWTRpost.PNG

 

And the actual stock chart with the earnings disasters.

twtrcharts2.PNG

 

5 times out of the last 8 it has been a literal gap down, but still, do this trade, use a stop, avoid the gap (bc we wait until after earnings), and the return are rather large.

 

Cynicism is at the heart of every good trader, but the unwillingness to welcome new data is at the heart of every failed trader.

 

A portfolio of these short put spreads, even when earnings are awful, has worked exceedingly well. A bear market will not change this, as long as the stops are tight and the trades avoid the risk of earnings -- that's critical. In a bear we will see higher premium, making up for the added risk -- in fact, that's why the vol is higher.

 

 

 

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@Ophir Gottlieb Can you describe what "1 day after earnings" means to you/CMLviz?  In the case of TWTR, February's earnings was before market open on Feb 9th.  So, earnings happened before the market opened, and options traded all day.  The following day was Feb 10th.  I'd call that the day after earnings.  CMLviz opens the trade on Feb 13th (after the weekend).  It's previously been said that the option prices used are at the end of the day, so there was 3 full days of trading before the trade was placed.  It would seem that Feb 10th would have been the most appropriate "1 day after earnings".

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1 hour ago, Ophir Gottlieb said:

 

This is not curve fitting. 

 

Here is Twitter -- an utter disaster on earnings: Same strategy over 3-year with a 100% stop loss.

http://tm.cmlviz.com/index.php?share_key=ZiD5GyhkrYKM8vD8

TWTRpost3yrs.PNG

 

And over one-year:

http://tm.cmlviz.com/index.php?share_key=6D1Ebjv0J2brzKEG

TWTRpost.PNG

 

And the actual stock chart with the earnings disasters.

twtrcharts2.PNG

 

5 times out of the last 8 it has been a literal gap down, but still, do this trade, use a stop, avoid the gap (bc we wait until after earnings), and the return are rather large.

 

Cynicism is at the heart of every good trader, but the unwillingness to welcome new data is at the heart of every failed trader.

 

A portfolio of these short put spreads, even when earnings are awful, has worked exceedingly well. A bear market will not change this, as long as the stops are tight and the trades avoid the risk of earnings -- that's critical. In a bear we will see higher premium, making up for the added risk -- in fact, that's why the vol is higher.

 

 

 

I agree this is most definitely not curve fitting, however it seems you are reducing the amount risked to equal that of the stop loss, is that correct? Therefore, it's likely the margin requirement (and true capital at risk as a stop loss is far from guaranteed in the option markets) is probably about four times the amount than is being shown in the P&L calculations, true?

Edited by SBatch

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5 minutes ago, SBatch said:

I agree this is most definitely not curve fitting, however it seems you are reducing the amount risked to equal that of the stop loss, is that correct? Therefore, it's likely the margin requirement (and true capital at risk as a stop loss is far from guaranteed in the option markets) is probably about four times the amount than is being shown in the P&L calculations, true?

 

The amount risked uses the margin requirements as defined by Reg T (in this case for a short spread) which are not affected by stop losses, so to answer the question directly: no.

 

Here's more on that:

Measuring 'Amount Risked' With Options 
The details behind Reg T, margin requirements, and how "amount risked" is calculated by TradeMachine.

Edited by Ophir Gottlieb

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This is fascinating stuff

Ophir, has the engine been updated to do custom strategies yet?

 

so what i am getting here is that earnings trades done just after earnings are consistently profitable with much less risk.

 

I have  been working on manually backtesting something similar- seeing that calendar spreads expiring in 1-2 days on facebook did extremely well the next day after earnings.

Edited by Davidkot81

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11 hours ago, ChadK said:

But I fully agree.  One need to be very consciousness of curve fitting when using this tool.  If, like most stocks in the past 3 years, has had a tear up, of course bullish strategies are going to perform well.  (Bull put credit spreads, bull call debit spreads, naked puts, long calls, etc.)

 

I've been having a little fun with backtesting naked strangles and straddles (the TastyTrade style).  It's a little more interesting now that some of the bugs have been fixed in the software, but there's still a few others which makes it hard to believe the results without going over the individual trades with a fine toothed comb.

When you say "The Tasty Trade Style", you must only be a seller of premium in your backtests, right? They are vehement that never, under any conditions, would they ever buy premium. They are ONLY premium sellers and that is what they drill over and over.

They offer a lot of valuable information and new insights but, especially in an area such as options, to be 100% black and white, and say that you would NEVER buy premium is pretty closed minded, and I am sure it is preventing them from having many great new discoveries.....especially with all of the tools, data, and staff they have working for them.

But, back to your "TastyTrade" backtest....I assume you are a seller of straddles and strangles.

My question is, they do have some rules about "when" to be a seller, and it is when IV is very high.

They use IV percentile/rank to first determine their candidates.

I was wondering how you first chose your candidates for what to sell in your backtest?

Are you arriving at them by using any tool that screens for high IV rank?

Are you using the filters and removing earnings exposure?

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33 minutes ago, cuegis said:

When you say "The Tasty Trade Style", you must only be a seller of premium in your backtests, right? They are vehement that never, under any conditions, would they ever buy premium.

 

That's not 100% true.  They do occasionally do calendars, and in low IV rank candidates that you want to go directional on, they do prefer buying a vertical over selling one.  But yet, they greatly prefer selling premium to capture the decay.

 

36 minutes ago, cuegis said:

But, back to your "TastyTrade" backtest....I assume you are a seller of straddles and strangles.

My question is, they do have some rules about "when" to be a seller, and it is when IV is very high.

They use IV percentile/rank to first determine their candidates.

I was wondering how you first chose your candidates for what to sell in your backtest?

Are you arriving at them by using any tool that screens for high IV rank?

Are you using the filters and removing earnings exposure?

 

Yes, I do screen by both IV rank and earnings.  In addition, I try to stick to candidates that have some reasonable option volume, as well as priced over about $40 (higher options premium).  TastyWorks website allows you to filter by earnings and IV rank.  I've also written a scan for Thinkorswim to do something similar, but include options volume, price, Market Cap, etc.

 

Tastytrade also does a lot of earnings trades, but I shy away from them.  I don't like binary events...seems too much like gambling which isn't my style.

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27 minutes ago, ChadK said:

 

That's not 100% true.  They do occasionally do calendars, and in low IV rank candidates that you want to go directional on, they do prefer buying a vertical over selling one.  But yet, they greatly prefer selling premium to capture the decay.

 

 

Yes, I do screen by both IV rank and earnings.  In addition, I try to stick to candidates that have some reasonable option volume, as well as priced over about $40 (higher options premium).  TastyWorks website allows you to filter by earnings and IV rank.  I've also written a scan for Thinkorswim to do something similar, but include options volume, price, Market Cap, etc.

 

Tastytrade also does a lot of earnings trades, but I shy away from them.  I don't like binary events...seems too much like gambling which isn't my style.

I agree with you about the binary event nature. Especially in the way that they go about trading them. There is only so  many ways that you can hold a position through earnings and still remain conservative. In the end, it still is pure speculation on a 1 day event. I think their approach to earnings is much more on the "gambling" side.

They claim that they never trade "direction" , they call is pure gambling and always attribute 50/50 probabilities to it, which is probably correct.

Then, all day long, on their show, they are just outright getting long or short, and day trading direction, at the same time they are speaking negatively about it.

I do recall hearing them say they would not ever "buy" verticals, only sell them. But , really, what is the difference? Just look at a P/L profile of each, they are just a mirror of each other.

I use the code they supply, that you can input into TOS,that visually  shows where the IV rank is at the bottom of any chart.

But, you have to first bring up a chart to see that info.

I am looking for a way to automate that process via a scanner/screener.

I didn't know that they created a TastyWorks site with that info.

I have not opened an account with them. I have been with IB since they first started and, along with loyalty, I'm just so used to their platform after all of these years, it would probably be more disruptive for me to change unless the commission difference was much greater than it is.

Are you open to sharing your TOS scan?

Edited by cuegis

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I haven't had good luck with the TOS "sharing" feature (where you can just load it up), so here's a screenshot of my scan:

Capture.JPG

 

Tastytrade believes that selling options with 45 days to expiration is a sweet spot.  You can see that my earnings filter is set to 20 days.  I always double-check earnings dates.  I try to avoid earnings in those ~45 days, but won't always.  I do exit a few days before earnings, but usually, if I waited that long, results aren't so good as the IV goes up, taking away profits.  That said, many times my 45 day trades close in around 20 days.  In fact, out of my last 84 trades, they were closed in an average of 19.29 days, with an average of 6.0% return on Reg-T margin figures.  Out of those 84 trades, 11 were losers, for a 86.9% win rate.  44 trades were naked strangles, 5 naked straddles, 13 iron butterflies, 15 verticals, 4 iron condors, and a couple misc.

 

Also, I don't believe that you need a TastyWorks funded account to use their tools.  Here's what their screener looks like:

Capture.JPG

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8 minutes ago, ChadK said:

I haven't had good luck with the TOS "sharing" feature (where you can just load it up), so here's a screenshot of my scan:

Capture.JPG

 

Tastytrade believes that selling options with 45 days to expiration is a sweet spot.  You can see that my earnings filter is set to 20 days.  I always double-check earnings dates.  I try to avoid earnings in those ~45 days, but won't always.  I do exit a few days before earnings, but usually, if I waited that long, results aren't so good as the IV goes up, taking away profits.  That said, many times my 45 day trades close in around 20 days.  In fact, out of my last 84 trades, they were closed in an average of 19.29 days, with an average of 6.0% return on Reg-T margin figures.  Out of those 84 trades, 11 were losers, for a 86.9% win rate.  44 trades were naked strangles, 5 naked straddles, 13 iron butterflies, 15 verticals, 4 iron condors, and a couple misc.

 

Also, I don't believe that you need a TastyWorks funded account to use their tools.  Here's what their screener looks like:

Capture.JPG

Oh , this is the same screener that they had on their old "Dough" site.

I thought they closed down Dough, but didn't know they just moved it to a different place.

It really is more of a "list" than a scanner.

I do agree with them about many of the things they say (ex selling with 45 DTE is a sweet spot).

But, they contradict themselves very often, and they definitely use "curve fitting" at times when they want to prove a point that they are trying to perpetuate.

The most notable example is when they tried to prove, through one of their backtests, that you cannot make money through buying IV in the period leading up to earnings.

Kim has that story somewhere in his archives.

I think , to prove their point, they bought a straddle, on a big name like GOOG, but it was significantly out of the money when they put it on, and, as we approached earnings, the price moved so that the straddle would up at the money the day before earnings, so it was a big loser.

And, they said.."this proves that you can only lose money buying IV before earnings".

They chose the outcome they wanted to arrive at, then secondly, did a study that would have to prove their point.

They are very good for people who are more experienced, because those people have enough knowledge to know how to separate the BS from the things of value.

But, I think they do a disservice to beginners, who just follow everything they say, because they don't know any better.

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23 minutes ago, ChadK said:

I haven't had good luck with the TOS "sharing" feature (where you can just load it up), so here's a screenshot of my scan:

Capture.JPG

 

Tastytrade believes that selling options with 45 days to expiration is a sweet spot.  You can see that my earnings filter is set to 20 days.  I always double-check earnings dates.  I try to avoid earnings in those ~45 days, but won't always.  I do exit a few days before earnings, but usually, if I waited that long, results aren't so good as the IV goes up, taking away profits.  That said, many times my 45 day trades close in around 20 days.  In fact, out of my last 84 trades, they were closed in an average of 19.29 days, with an average of 6.0% return on Reg-T margin figures.  Out of those 84 trades, 11 were losers, for a 86.9% win rate.  44 trades were naked strangles, 5 naked straddles, 13 iron butterflies, 15 verticals, 4 iron condors, and a couple misc.

 

Also, I don't believe that you need a TastyWorks funded account to use their tools.  Here's what their screener looks like:

Capture.JPG

I don't this on the tastyworks.com website. Where are you getting this from?

Is it part of the trading platform?

If so, can you just download, and use the platform without having an account?

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2 minutes ago, cuegis said:

It really is more of a "list" than a scanner.

It's a list, but with filtering capability.  As the top line shows, I've filtered out candidates with earnings within the next 0-36 days, and IV Rank less than 22.  There's also a liquidity filter.  You can also filter the inverse...only showing stocks with earnings within the next xxx days, etc.  I'm not sure if any of their "lists" include the universe of stocks.  I like using the default "Notable Stocks", as they are the most liquid.

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2 minutes ago, cuegis said:

I don't this on the tastyworks.com website. Where are you getting this from?

Is it part of the trading platform?

If so, can you just download, and use the platform without having an account?

Yeah, it used to be available through dough.com.  I think now you have to sign up for an account on TastyWorks.  But I don't think you actually have to fund the account to use the tools.  Maybe the use of the word "account" is too strong here.  I think you can get login credentials for the website, without having to open a brokerage account.

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2 minutes ago, ChadK said:

It's a list, but with filtering capability.  As the top line shows, I've filtered out candidates with earnings within the next 0-36 days, and IV Rank less than 22.  There's also a liquidity filter.  You can also filter the inverse...only showing stocks with earnings within the next xxx days, etc.  I'm not sure if any of their "lists" include the universe of stocks.  I like using the default "Notable Stocks", as they are the most liquid.

Yes ...I just found my way to this place. You can't download the TastyWorks platform unless you have a funded account.

But, using you TD login info, you can still use the Dough page that you are showing me.

I never could figure out which was the best choice of stocks to use and mostly used "stocks with most liquid options"

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12 hours ago, Ophir Gottlieb said:

 

The amount risked uses the margin requirements as defined by Reg T (in this case for a short spread) which are not affected by stop losses, so to answer the question directly: no.

 

Here's more on that:

Measuring 'Amount Risked' With Options 
The details behind Reg T, margin requirements, and how "amount risked" is calculated by TradeMachine.

@Ophir Gottlieb  That's good to hear.  The issue is in the current extremely low IV environment, the risk/reward is nowhere near the historical.  In fact, in TSLA, AMBA and FB, one would be currently looking at a 4:1 risk:reward ratio if these trades were put on the session after earnings.  I agree this a very good strategy when volatility is higher which would make the risk:reward much more favorable, but we have to trade the market we have not the one we want.  Therefore, have you looked at more of a directional strategy on these underlying?  Perhaps debit call verticals and diagonals? With the extremely low IV, it's inexpensive to be a buyer of 30 day premium as opposed to selling low 30 day premium. Thoughts?

Edited by SBatch

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On 4/28/2017 at 0:48 PM, Ophir Gottlieb said:

 

I found monster edge in Google.

Watch the video here

 

@Ophir Gottlieb  I have been trading straddles into earnings to ride the ramp for several years and really like the concept so I was happy to see you add this feature to the TradeMachine. However, I have a concern regarding how the number of days before earnings is being calculated.  It seems you are using calendar days.  This can be extremely problematic.  Let's use AMD as an example as I like to use them for a pre-earnings straddle.  If I test for an open 10 days prior to earnings and a close 0 days prior to earnings (as AMD reports AMC) we get very varied results with regard to trading days which should absolutely be the focus here. For example, the back-test for the 10/16 cycle will show 9 trading days.  However, if we compare it to the 5/17 cycle we get 7 trading days.  This is a massive differential for such a short term trade.  We are supposed to be comparing apples to apples but in this simple example one trade is on for over 25% more trading days than the other even though we are attempting to solve for a constant with regard to days before earnings.  Can this feature be adjusted to use trading days rather than calendar days?

Edited by SBatch

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23 minutes ago, SBatch said:

@Ophir Gottlieb  I have been trading straddles into earnings to ride the ramp for several years and really like the concept so I was happy to see you add this feature to the TradeMachine. However, I have a concern regarding how the number of days before earnings is being calculated.  It seems you are using calendar days.  This can be extremely problematic.  Let's use AMD as an example as I like to use them for a pre-earnings straddle.  If I test for an open 10 days prior to earnings and a close 0 days prior to earnings (as AMD reports AMC) we get very varied results with regard to trading days which should absolutely be the focus here. For example, the back-test for the 10/16 cycle will show 9 trading days.  However, if we compare it to the 5/17 cycle we get 7 trading days.  This is a massive differential for such a short term trade.  We are supposed to be comparing apples to apples but in this simple example one trade is on for over 25% more trading days than the other even though we are attempting to solve for a constant with regard to days before earnings.  Can this feature be adjusted to use trading days rather than calendar days?

 

We can take a look at that, but remember, options do decay over weekends as well (not like weekdays, but it's still a real factor).

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37 minutes ago, Ophir Gottlieb said:

 

We can take a look at that, but remember, options do decay over weekends as well (not like weekdays, but it's still a real factor).

I have considered that, however that is another constant (theta).  In the AMD example, the two extra trading days is a very large variable (rather than a constant that can be accounted for) because of how much the stock can move and how much IV can rise or fall in those two days.

Edited by SBatch

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@Ophir Gottlieb  I've asked several questions over the last few days.  Could you please answer?

 

On 5/5/2017 at 9:32 PM, ChadK said:

@Ophir Gottlieb Can you describe what "1 day after earnings" means to you/CMLviz?  In the case of TWTR, February's earnings was before market open on Feb 9th.  So, earnings happened before the market opened, and options traded all day.  The following day was Feb 10th.  I'd call that the day after earnings.  CMLviz opens the trade on Feb 13th (after the weekend).  It's previously been said that the option prices used are at the end of the day, so there was 3 full days of trading before the trade was placed.  It would seem that Feb 10th would have been the most appropriate "1 day after earnings".

 

Quote

On 5/5/2017 at 6:16 PM, Ophir Gottlieb said:

Rules 
* Open short put spread one day after earnings 
* Close short put spread 29 days later 
* Use the 30-day options 

 

  On 5/5/2017 at 6:16 PM, Ophir Gottlieb said:

Short Put Spread * Monthly Options

@Ophir Gottlieb  How do you specify using only the monthly options?

If I put in a 30 day rollover, then it looks for options that are 30 days to expiration on the day after earnings.  In the case of AMBA, the most recent earnings was AMC 2/28.  The trade was opened on 3/2, but it chose the Mar31 expiration.  The cycle before, earnings was on 12/1, trade opened on 12/5, but chose the Jan6 expiration.  So, how do you get it to do only monthly options?

 

Have you considered having an option to disable weeklies?  Some of the weeklies are so thinly traded that backtesting on them may not make sense.  Being able to turn them off would be helpful.

 

 

Quote

 

On 5/2/2017 at 6:15 PM, Ophir Gottlieb said:

Yep. Been looking.

Any update on those potential bugs?

 

 

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Lots of good questions coming up, as I've noticed some nuances as well.  I've played around with the tool quite a bit (and am looking forward to support for calendars and custom trades as a large portion of my trades have the calendar and diagonal structures).  It's powerful and easy to use, but don't take the stats in the summary window at face value.  The summary is a great starting point but download the trade details into a spreadsheet for a deeper dive - you may have to play with the data to get the backtest data to fit your needs.  A few things to lookout for:

  • Unequal dollar allocations for each trade iteration.  Your only tuning knob is to specify how many contracts in the settings.  As stock prices move and if you include earnings periods (when options prices are higher), for some stocks the dollar amount for each trade iteration can differ by factors of 4x or more - which means those trades count a lot more to the overall averages.  I like to see equal weight for each iteration so I wind up using the trade details to get a percentage gain/loss for each trade iteration and then average them all out.
  • What option series are selected for each trade (I see some questions regarding this).  I have to play with that Rollover value to fully understand how it works in relation to what option expirations are selected for the trades.
  • For credit spreads, look at the credits received.  For some of the lower IV stocks when you exclude earnings and get farther OTM with your strikes, sometimes the amounts collected can be so low that you wouldn't trade them in a real trade.

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@Ophir Gottlieb  It seems that several of my questions are getting lumped together.  I will separate each with a numbered list, and would appreciate an answer for each.  You had mentioned looking at my question regarding earnings dates, but really there's about 3 questions regarding earnings dates (two in #1 below, and #2).

 

0.  Yes, the limit/stop price bug seems to be fixed this week.  Thanks.  (No need to answer this one.)

 

1.  On May 2nd, Ceugis shared some results on testing TSLA.  I had looked at the results and saw some potential bugs that are different than the stop/limit bug:

Quote

And here's where it gets interesting...

Next position opened is March 3rd.  But earnings was on 2/22.  So it entered a trade this time 7 days after earnings, not 1.  Looks like potential bug #1, or wrong earnings date data.

Then, instead of stopping the weekly trades after a month (~5 trades like in other cycles), it just kept going and going until today, 9 trades later.  This would appear to be bug #2.

 

 

2. I would like clarification as to what "days before" and "days after" earnings is defined as in CMLviz.

Quote

Can you describe what "1 day after earnings" means to you/CMLviz?  In the case of TWTR, February's earnings was before market open on Feb 9th.  So, earnings happened before the market opened, and options traded all day.  The following day was Feb 10th.  I'd call that the day after earnings.  CMLviz opens the trade on Feb 13th (after the weekend).  It's previously been said that the option prices used are at the end of the day, so there was 3 full days of trading before the trade was placed.  It would seem that Feb 10th would have been the most appropriate "1 day after earnings".

 

3. On May 5, on your post about AMBA, you stated use "Monthly Options".  My question is:

Quote

How do you specify using only the monthly options?

If I put in a 30 day rollover, then it looks for options that are 30 days to expiration on the day after earnings.  In the case of AMBA, the most recent earnings was AMC 2/28.  The trade was opened on 3/2, but it chose the Mar31 expiration.  The cycle before, earnings was on 12/1, trade opened on 12/5, but chose the Jan6 expiration.  So, how do you get it to do only monthly options?

 

 

4.  Not really a question, but some feature requests.  I would like to echo Yowster's suggestions for trade amount in dollars, a minimum credit received (or debit for debit trades?), and a way to turn off selecting expirations that are weeklies.

 

I suppose I could pose these questions directly in an email to support, but thought it's best to do it here, so others can benefit.

 

Thanks,

Chad

 

 

Edited by ChadK

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On 5/3/2017 at 2:50 PM, cuegis said:

It makes a lot of sense except I think that, way the stock moves, it could blow right through the short strike before the week is over. Certainly way before June expiration.

$3 is nothing to AAPL.

But, you would be VERY lucky if that happened as you would collect the full June premium now, But , the delta on the Sept 135 is only .78 and you would be short 100 shares (100 deltas) vs your long 78 deltas until you can buy back the short stock and sell some higher strike.

It probably could be done pretty quickly though.

I was thinking of following the exact trades that came out of the backtest..or close to it.

Long 50/ short 20 delta verticals that expire in 2-3 weeks.

If the stock just has a slow grind up, the theta actually works to your advantage. Alot of those trades made money on BOTH legs, which is quite unusual, but is what would happen with a 2-3 week spread and a slow grind up.

 

My trade needs to be more actively traded though

Closed the spread for a quick 10% gain.

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29 minutes ago, SBatch said:

Closed the spread for a quick 10% gain.

I followed the backtest results. Not simply because they showed such a good result. But, just as much because it made sense to me.

The day after earnings, I bought the May 19 147/150 vertical calls.

On friday, at 149, I rolled them up the 149/152.50 vertical .

Today I have an offer to sell the 149/150 call spread, which would just rollup my 149's by $1 and secure more gains.

This has been a monster.

The backtests showed some crazy number, like 900+% over 3 years.

Hey, a guy can dream, can't he?

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42 minutes ago, cuegis said:

I followed the backtest results. Not simply because they showed such a good result. But, just as much because it made sense to me.

The day after earnings, I bought the May 19 147/150 vertical calls.

On friday, at 149, I rolled them up the 149/152.50 vertical .

Today I have an offer to sell the 149/150 call spread, which would just rollup my 149's by $1 and secure more gains.

This has been a monster.

The backtests showed some crazy number, like 900+% over 3 years.

Hey, a guy can dream, can't he?

 

Perfectly done.

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15 hours ago, ChadK said:

@Ophir Gottlieb  It seems that several of my questions are getting lumped together.  I will separate each with a numbered list, and would appreciate an answer for each.  You had mentioned looking at my question regarding earnings dates, but really there's about 3 questions regarding earnings dates (two in #1 below, and #2).

 

0.  Yes, the limit/stop price bug seems to be fixed this week.  Thanks.  (No need to answer this one.)

 

1.  On May 2nd, Ceugis shared some results on testing TSLA.  I had looked at the results and saw some potential bugs that are different than the stop/limit bug:

 

2. I would like clarification as to what "days before" and "days after" earnings is defined as in CMLviz.

 

3. On May 5, on your post about AMBA, you stated use "Monthly Options".  My question is:

 

4.  Not really a question, but some feature requests.  I would like to echo Yowster's suggestions for trade amount in dollars, a minimum credit received (or debit for debit trades?), and a way to turn off selecting expirations that are weeklies.

 

I suppose I could pose these questions directly in an email to support, but thought it's best to do it here, so others can benefit.

 

Thanks,

Chad

 

 

 

The days after earnings discrepancy was actually a time zone issue by user. It has been fixed and behaves as expected.

By monthly options, I mean options as close as 30-days to expo, not the actual "monthlies."

 

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This Option Trade After Twitter Inc Earnings Has Been a Winner


 

TWTR_buiding_logo.png



Date Published:  
Written by Ophir Gottlieb 

LEDE 
One option trade after Twitter Inc (NYSE:TWTR) posts earnings has been a consistent winner and takes no earnings risk and very little stock direction risk. 

Twitter Inc Earnings 
While most of the focus is on the actual earnings move for a stock, that's the distraction when it comes to the option market. For Twitter Inc, irrespective of whether the earnings move was up or down, if we waited on day after the stock move, and then sold an out of the money put spread, the results were simply staggering. 

We can examine this, objectively, with a custom option back-test. Here is our earnings set-up: 
 

setup_2_29_after_custom_e.PNG



Rules 
* Open short put spread 2 days after earnings 
* Close short put spread 29 days later 
* Use the 30-day option 

Here are the results over the last year: 
 

TWTR_1yrs_poste_sps.PNG



That's a 41.4% return, with 4 winning trades and 0 losing trades. The total holding period was less than 4 full months, meaning the annualized return was over 120%. No earnings risk was taken -- this is not a coin flip over earnings. 

The Logic 
This strategy works beautifully in Facebook, but with Twitter Inc, even naysayers can't criticize this strategy as only working because we're in a bull market. Twitter Inc stock has performed awfully post earnings. Here is a 2-year stock chart, where the earnings dates are designated by a "E" icon and circled in red: 
 

twtrcharts2.PNG



It's the exception, not the rule, when Twitter Inc (NYSE:TWTR) doesn't gap down off of earnings. But the logic behind this trade follows a narrative that even after a bad earnings release, if we wait two days after, we find the stock at a point of equilibrium. 

If it gapped down -- that gap is over. If it beat earnings, the downside move is already likely muted. Here's how this strategy has done over the last 6-months: 
 

TWTR_6mos_poste_sps.PNG



That's a 11.5% return, on 2 winning trades and 0 losing trades. Since this is a total of a two-month holding period, that 11.5% is actually a 70% annualized. 

If you're curious, yes, this also produced positive returns over the last 3-years, even though the stock has so under-performed as a buy and hold investment, and done so poorly on earnings calls. 

WHAT HAPPENED 
There are patterns to stock behaviors before and after earnings and those patterns reveal opportunities in the option market, without taking the actual risk of earnings. You can find them, stock by stock, like Apple and Google before and after earnings. 

This is how people profit from the option market -- it's preparation, not luck. 

To see how to do this for any stock and for any strategy with just the click of a few buttons, we welcome you to watch this quick demonstration video: 
Tap Here to See the Tools at Work 

Thanks for reading. 

Risk Disclosure 
You should read the Characteristics and Risks of Standardized Options. 

Past performance is not an indication of future results. 

Trading futures and options involves the risk of loss. Please consider carefully whether futures or options are appropriate to your financial situation. Only risk capital should be used when trading futures or options. Investors could lose more than their initial investment. 

Past results are not necessarily indicative of future results. The risk of loss in trading can be substantial, carefully consider the inherent risks of such an investment in light of your financial condition. 

The author has no position in Twitter Inc (NYSE:TWTR) as of this writing. 

Back-test Link (does require custom earnings settings).

 

 

 

 

 

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On the TWTR study, why pick entering 2 days after earnings?  Sounds suspiciously like a curve fit parameter with limited robustness, especially if entering say 1 day or 3 days after earnings don't give similar results.  But, the tool does look powerful for certain purposes as long as robustness of settings is verified.

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8 hours ago, craigsmith said:

To me, this, most certainly is curve fitting, as well as, some of the other posts. Kim, you have endorsed this platform, can you give us some of your thoughts on these trade ideas?

I don't see how this is curve fitting. When we do our earnings trades, don't we do the same? We look at Dustin charts and select the best day to enter. For example, HD straddle historically produced the best results if entered 2-3 trading days before earnings. And it worked for us very well most of the time.

I think the tool provided a starting point to do the research. It does not guarantee results, it shows probabilities. To me, the ability to play with parameters in terms of when to enter, which deltas to use etc. is very powerful, and I stand behind my endorsement.

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57 minutes ago, Kim said:

I don't see how this is curve fitting. When we do our earnings trades, don't we do the same? We look at Dustin charts and select the best day to enter. For example, HD straddle historically produced the best results if entered 2-3 trading days before earnings. And it worked for us very well most of the time.

I think the tool provided a starting point to do the research. It does not guarantee results, it shows probabilities. To me, the ability to play with parameters in terms of when to enter, which deltas to use etc. is very powerful, and I stand behind my endorsement.

 

My 2 cents on this:
 
I'm an engineer and armature user of statistics based models in my day to day work for using past data to predict future data (and yes, it is probabilistic as Kim mentioned).  To me, this is most certainly "curve fitting" here, or if you don't like that term, he's come up with a model for prediction of profitably playing post-earnings events in TWTR by selling put spreads.  The obvious parameters of the model are option expiration, short option delta, long option delta, entry date, and exit date- so 5 parameters. 
 
If he's training that 5-parameter model based on 8 data points (2 years of earnings events), that's n-1 degrees of freedom, or 7 (n-1 since it doesn't include the entire population of earnings events).  In analysis of variance (stats 101) for regression modeling, and assuming your errors are normally distributed, you use up one degree of freedom for each parameter, and the rest are left over for calculating error (i.e., confidence intervals for each parameter and error in the overall model).  
 
So, with only 3 degrees of freedom left over for computing confidence intervals, it is very unlikely the interval would be very tight around any one parameter.  Hence, that's why I'm very skeptical the confidence interval around entry date is less than +/- 1 day.  
 
So basically, in my opinion, it's wise not to focus too much on the specifics of any one setting CML is predicting based on such a small sample size (as a previous poster mentioned), and just focus on what's actually going on here:  implied volatility in the options is in reversion to the mean after earnings announcement to a level that still provides edge over the realized volatility in this time frame, and there's a slight bullish tilt to price (again, for a very small sample size).

 

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It would be better to have at least 20-30 data points before concluding anything.

Dustin's charts approach this, and prospectively arrived at data (5 years of forward pointing, good results) show it is a promising strategy.  After several years of data, that's what brought me here.  It would be interesting to do a subcategory analysis (what worked, and what didn't) here.

 

It would be helpful for the viz software to look at randomly arrived at criteria and compare them to specified criteria for many data points. Then you would have a better idea at the validity and usefulness of the tool (also a lot of work)

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I'm not a statistician , so I don't know the universally accepted rule for this.

Maybe someone else can give the correct answer.

What is the "official" size of a data set, in the field of statistics, to legitimize a study into being "statistically significant?"

 

Common sense tells me it is not 4, or 8, or even 100!

Edited by cuegis

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There is something else that I think many people here, and in other , similar, places have taken so far out of context that it has reached the point of "abusing" the concept.

Here is the most extreme example, but you will get my point.

I bought an option for .10 cents, and sold it the next day for .12 cents.

That is a 20% return, and if you "annualize" this, it comes out to (pick a number) 35,000%.

There comes a point where .02 cents = .02 cents!

 

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40 minutes ago, cuegis said:

What is the "official" size of a data set, in the field of statistics, to legitimize a study into being "statistically significant?"

I think it depends upon what you are trying to prove, and with what confidence ("confidence level").  Therefore, there is no one correct answer.  It would seem that @luxmon might be better qualified to answer this.

 

That said, in my line of work, I've always heard that 30 data points is a good starting point.

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Well, theoretically, the more data points, the better. The question is how relevant is the data from 8-10 years ago, and how much effort will it require to analyze such large amounts of data.

In our earnings trades we look at the last 4 cycles. is it perfect? No, but it worked pretty well for us. Call it data curve fitting or whatever you want, but numbers don't lie. Our calendars produces average return of over 20% in the last 5 years, and we based on entry and exit targets on 4 last cycles of data. This is what I call probability trading.

So again, I'm not dismissing other methods, and I'm not saying that looking at 10-15 data points is wrong. It all comes to time and effort, and to me, this is 80/20 principle. 

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23 minutes ago, cuegis said:

There is something else that I think many people here, and in other , similar, places have taken so far out of context that it has reached the point of "abusing" the concept.

Here is the most extreme example, but you will get my point.

I bought an option for .10 cents, and sold it the next day for .12 cents.

That is a 20% return, and if you "annualize" this, it comes out to (pick a number) 35,000%.

There comes a point where .02 cents = .02 cents!

 

@cuegis You raise a good point... and illustrate why you should always look in the trade details to see what exactly went into the backtest.  In the TWTR example, the 4 trades in the 1 year backtest had:

  • collect 0.51 credit on short put spread witdh of 2.5
  • collect 0.75 credit on short put spread width of 3
  • collect 0.32 credit on short put spread width of 2
  • collect 0.12 credit on short put spread width of 2.5

While the first 2 trades make some sense, would anybody really want to trade the last two where the credit received is such a low percentage of the spread width???   One losing trade will take multiple winners to make up for - and why if you extend the backtest to 2 years it comes up a loser.

 

BTW, @Ophir Gottlieb when I extended the test to 2 years I think I found a bug.   Look at these trade details:

 

Date             Desc     Size     Symbol             Price      PNL     Stock
30-Jul-15    Open    -1    TWTR Aug28`15     $1.05         $31.47
    DaysAfterEarnings        31 Put            
    Short Puts                    
30-Jul-15    Open    1    TWTR Aug28`15     $0.21         $31.47
    DaysAfterEarnings        27.5 Put            
    Long Puts                    
26-Aug-15    Close    1    TWTR Aug28`15     $6.62    ‑$559     $25.03
    DaysAfterEarnings        31 Put            
    Short Puts                    
26-Aug-15    Close    -1    TWTR Aug28`15     $2.46     $225     $25.03
    DaysAfterEarnings        27.5 Put            
    Long Puts                    


The opening trade collected 0.84 credit on width of 3.5.   The closing trade paid 4.16 to close the spread of width 3.5 - this is obviously wrong.  Deep ITM options have wider bid/ask spreads but in practice you should never have to pay more than the width of the vertical spread to close it.

 

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16 minutes ago, ChadK said:

I think it depends upon what you are trying to prove, and with what confidence ("confidence level").  Therefore, there is no one correct answer.  It would seem that @luxmon might be better qualified to answer this.

 

That said, in my line of work, I've always heard that 30 data points is a good starting point.

 

This answer most certainly depends on how much confidence you desire, or "alpha level".  Getting into this is beyond the scope of the thread and my expertise for sure.   Just to throw out a broad brush answer, in the research studies I've done and if the sampling plan is unbiased (a huge assumption in this analysis since it's only the last 8 events, not 8 randomly sampled from all earnings events in the entire population), I've found to that in order to test significance of a single parameter (i.e., calculate a "p-value" in the vernacular), I've needed at least 20 samples for estimating each parameter in the model.  And this is just to check the significance of the main effect of each parameter (not interactions between those parameters which add another level of complexity - say if entry date is set to one, does the significance and sensitivity of the optimum short delta change, etc).    
 
Again, my main point was to not read so much into the precise settings of these studies and slap that particular trade on blindly, but consider what's going on in IV, RV, and possibly technical analysis that's fundamentally leading to these undoubtedly strong trends that appear to have good edge.   
 
Tim

 

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7 minutes ago, Kim said:

Well, theoretically, the more data points, the better. The question is how relevant is the data from 8-10 years ago, and how much effort will it require to analyze such large amounts of data.

In our earnings trades we look at the last 4 cycles. is it perfect? No, but it worked pretty well for us. Call it data curve fitting or whatever you want, but numbers don't lie. Our calendars produces average return of over 20% in the last 5 years, and we based on entry and exit targets on 4 last cycles of data. This is what I call probability trading.

So again, I'm not dismissing other methods, and I'm not saying that looking at 10-15 data points is wrong. It all comes to time and effort, and to me, this is 80/20 principle. 

 

So, I am a "real statistician" or mathematician as it were. My application of machine learning to finance was endorsed by the head of Germany's artificial intelligence arm. I am also in SSRN. My background stems from my graduate work at Stanford University. 

 

I have also been a market maker on the NYSE ARCA and CBOE (remotely) floors,
 

I am, and have been, considered one of the pioneers of ML in finance and was the earliest to note that neural networks worked better than the prevailing literature dictated, which, believe it or not, was a controversial back then. I showed unquestionably that NN did outperform SVM with enough data, which, to translate into English by using a different industry's own "ah ha" moment would be like proving that battery powered auto engines have greater torque and substantially more power than a combustion engine. It's obvious now, but I assure you it was not obvious before.
 

I love cynicism! It brings intelligent discussion and an evolution to thought processes.
 

I also know that back and forth discussions with non-scientists also brings out a form of cynic that is in fact,  not cynical,  but rather angry.
 

I cannot, and choose not, to change an angry man's mind. 
 

The cynic that looks at the results and says, "hey, this feels like curve fitting," has a winning approach. The cynic that uses Stats 101 to prove a point, is one that assumes the counter party is foolish. Don't be that person. 

 

First, for people that really want to learn, one example of a back-test is not what we do.
 

We publish thousands, yes thousands,  a day to Google News. It is the accumulation of tens of thousands of back tests that inspire and power the facility to begin an analysis of backtests. 
 

A stat cynic that has cognition would know that one backtest, in and of itself, even if it was 1000 years of data, is not sufficient to say very much at all. That entire backtest is one data point, and thousands of data points,  all at the same time.

A trader inside the body of a mathematician would also note that going further back, say more than 2-years, is often less robust than a shorter time period.
 

The pre earnings trades and the post earnings trades, are an amalgamation of analysis, that together deliver robustness. If one where to employ a trade strategy the idea is to create a portfolio of the trades, not one.
 

As Kim does with Steady Options, no month is based on one trade, it’s based on a portfolio of trades.
 

It's not in my nature to interfere with the learning process, so in that vein, I observe responses. I have read the forum broadly not just this thread.
 

I can see traders at various levels, it's really wonderful what Kim has built here. 
 

I chime in now not to change the conversation, but to reassure the cynics that are on their path to improvement to feel confident in their questions but to note that there are people here who are not appropriate to add to your knowledge base.
 

Good luck to all, friends. A quant back-tester is not a product for everyone. That's OK. I wish everyone success in trading.  Our goal is to empower everyone with the tools and information the top 0.1% have so we can break the information asymmetry that has benefited the few at the expense of the many for far too long.

 

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5 minutes ago, Ophir Gottlieb said:

 

So, I am a "real statistician" or mathematician as it were. My application of machine learning to finance was endorsed by the head of Germany's artificial intelligence arm. I am also in SSRN. My background stems from my graduate work at Stanford University. 

 

I have also been a market maker on the NYSE ARCA and CBOE (remotely) floors,
 

I am, and have been, considered one of the pioneers of ML in finance and was the earliest to note that neural networks worked better than the prevailing literature dictated, which, believe it or not, was a controversial back then. I showed unquestionably that NN did outperform SVM with enough data, which, to translate into English by using a different industry's own "ah ha" moment would be like proving that battery powered auto engines have greater torque and substantially more power than a combustion engine. It's obvious now, but I assure you it was not obvious before.
 

I love cynicism! It brings intelligent discussion and an evolution to thought processes.
 

I also know that back and forth discussions with non-scientists also brings out a form of cynic that is in fact,  not cynical,  but rather angry.
 

I cannot, and choose not, to change an angry man's mind. 
 

The cynic that looks at the results and says, "hey, this feels like curve fitting," has a winning approach. The cynic that uses Stats 101 to prove a point, is one that assumes the counter party is foolish. Don't be that person. 

 

First, for people that really want to learn, one example of a back-test is not what we do.
 

We publish thousands, yes thousands,  a day to Google News. It is the accumulation of tens of thousands of back tests that inspire and power the facility to begin an analysis of backtests. 
 

A stat cynic that has cognition would know that one backtest, in and of itself, even if it was 1000 years of data, is not sufficient to say very much at all. That entire backtest is one data point, and thousands of data points,  all at the same time.

A trader inside the body of a mathematician would also note that going further back, say more than 2-years, is often less robust than a shorter time period.
 

The pre earnings trades and the post earnings trades, are an amalgamation of analysis, that together deliver robustness. If one where to employ a trade strategy the idea is to create a portfolio of the trades, not one.
 

As Kim does with Steady Options, no month is based on one trade, it’s based on a portfolio of trades.
 

It's not in my nature to interfere with the learning process, so in that vein, I observe responses. I have read the forum broadly not just this thread.
 

I can see traders at various levels, it's really wonderful what Kim has built here. 
 

I chime in now not to change the conversation, but to reassure the cynics that are on their path to improvement to feel confident in their questions but to note that there are people here who are not appropriate to add to your knowledge base.
 

Good luck to all, friends. A quant back-tester is not a product for everyone. That's OK. I wish everyone success in trading.  Our goal is to empower everyone with the tools and information the top 0.1% have so we can break the information asymmetry that has benefited the few at the expense of the many for far too long.

 

Sold! Where do I sign?

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23 minutes ago, Yowster said:

@cuegis You raise a good point... and illustrate why you should always look in the trade details to see what exactly went into the backtest.  In the TWTR example, the 4 trades in the 1 year backtest had:

  • collect 0.51 credit on short put spread witdh of 2.5
  • collect 0.75 credit on short put spread width of 3
  • collect 0.32 credit on short put spread width of 2
  • collect 0.12 credit on short put spread width of 2.5

While the first 2 trades make some sense, would anybody really want to trade the last two where the credit received is such a low percentage of the spread width???   One losing trade will take multiple winners to make up for - and why if you extend the backtest to 2 years it comes up a loser.

 

BTW, @Ophir Gottlieb when I extended the test to 2 years I think I found a bug.   Look at these trade details:

 

Date             Desc     Size     Symbol             Price      PNL     Stock
30-Jul-15    Open    -1    TWTR Aug28`15     $1.05         $31.47
    DaysAfterEarnings        31 Put            
    Short Puts                    
30-Jul-15    Open    1    TWTR Aug28`15     $0.21         $31.47
    DaysAfterEarnings        27.5 Put            
    Long Puts                    
26-Aug-15    Close    1    TWTR Aug28`15     $6.62    ‑$559     $25.03
    DaysAfterEarnings        31 Put            
    Short Puts                    
26-Aug-15    Close    -1    TWTR Aug28`15     $2.46     $225     $25.03
    DaysAfterEarnings        27.5 Put            
    Long Puts                    


The opening trade collected 0.84 credit on width of 3.5.   The closing trade paid 4.16 to close the spread of width 3.5 - this is obviously wrong.  Deep ITM options have wider bid/ask spreads but in practice you should never have to pay more than the width of the vertical spread to close it.

 

@Yowster can you send the URL back-test to support@cmlviz.com re: max loss > spread width?

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      How to Profit from Trading Options in Autodesk Inc Right After Earnings
       


      Date Published: 2017-05-18 
      Written by Ophir Gottlieb 

      LEDE 
      While Autodesk Inc (NASDAQ:ADSK) just crushed earnings again, sending shares soaring in the after hours trade, one option trade after earnings has been a consistent winner. It takes no earnings risk, little stock direction risk and over the last year has never lost while returning over 160% annualized returns. 

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      While most of the focus is on the actual earnings move for a stock, that's the distraction when it comes to the option market. For Autodesk Inc, irrespective of whether the earnings move was up or down, if we waited one-day after the stock move from earnings, and then sold an out of the money put spread, the results were very strong. 

      We can examine this, objectively, with a custom option back-test. Here is our earnings set-up: 
       


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      * Close short put spread 29 days later 
      * Use the option that is closest to but greater than 30-days away from expiration 

      Here are the results over the last year: 
       


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      This strategy works beautifully in many companies where heavy stock volume follows the earnings release. The logic behind this trade follows a narrative that even after a bad earnings release, if we wait a day after, we find the stock at a point of equilibrium. 

      If it gapped down -- that gap is over. If it beat earnings, the downside move is already likely muted. Here's how this strategy has done over the last 6-months: 
       


      That's a 21.3% return, on 2 winning trades and 0 losing trades. Since this is a total of a two-month holding period, that 21.3% is actually over 120% annualized. 

      If you're curious, yes, this also produced positive returns over the last 3-years. Here are those results. 
       


      Now we can find some comfort in this approach where is shows 9 winning trades and just 2 losing trades over the last three-years. 

      WHAT HAPPENED 
      There are patterns to stock behaviors before and after earnings and those patterns reveal opportunities in the option market, without taking the actual risk of earnings. You can find them, stock by stock, Apple, Google, Netflix and of course Autodesk Inc are just a handful of examples. There has been edge here with this strategy. 

      To see how to do this for any stock and for any strategy with just the click of a few buttons, we welcome you to watch this quick demonstration video: 
      Tap Here to See the Tools at Work 

      Thanks for reading. 

      Risk Disclosure 
      You should read the Characteristics and Risks of Standardized Options. 

      Past performance is not an indication of future results. 

      Trading futures and options involves the risk of loss. Please consider carefully whether futures or options are appropriate to your financial situation. Only risk capital should be used when trading futures or options. Investors could lose more than their initial investment. 

      Past results are not necessarily indicative of future results. The risk of loss in trading can be substantial, carefully consider the inherent risks of such an investment in light of your financial condition. 

      The author has no position in Autodesk Inc (NASDAQ:ADSK) as of this writing. 

      Back-test Link
       
       
       
       
       
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