Hey, hey — thanks to let’s encrypt and certbot, I have a full https site for https://football.playoffpredictor.com! Thanks DevNet and Derak Berreyesa!
My IRA option, 2017
2017 was a great year for stocks. I want to use this column to detail one particular trade I made in 2017 — my call option on TQQQ.
So first, why options? I have been trading stocks since in my early twenties, but trading options are new to me, something I have only done for a couple years now. Back in 2016 I spent a lot of time watching Robert Shiller’s OpenYale class on Financial Markets. In that class he talks about the development of options and futures markets. Options and futures are labeled as derivatives markets, but when you step back and think about it the options market IS the real market. Think about a soybean farmer in Texas. On December 1 she will not particularly care about the spot price of soybeans on that day- her land is all harvested and ready for next year’s planting. But she would be very interested in the price of soybeans in October of the following year, when she could bring a crop to market if she decides to plant it now. Same for a company: Delta Airlines does not care so much about the spot price of jet fuel today, but they do care very much about what it will be 1-24 months from now, and getting a predictable price so they can plan their capital expenditures and fare prices accordingly. In a lot of ways the options market is what drives real business and spot prices are not nearly as important. So from that view options are not merely gambling.
I trade almost exclusively in an IRA account, and you can trade options there — just no margin, which is fine for me. In my IRA I am granted level 1 options access, which means I can buy calls and puts. I have been comfortable with owning QQQ (Nasdaq 100) for 10+ years, one day in about 2013 I saw a ticker “TQQQ” pass on the bottom of the CNBC screen. I looked it up and it was 3x the QQQ return. I knew interest rates were ridiculously low then and I naively thought this fund achieved 3x by borrowing cash at low rates and using that to actually buy things like Apple and Cisco. So I went in – and it has done fantastically, returning about 1000% over that period.
In 2017 I decided to try TQQQ as an option. I’m not even sure that an option should be allowed on such a product as it is an option to being with. Sort of an option on an option. The thought was buy an out of the money call. My goal was to buy an instrument that worked as follows — if the market went up 20-30% in 2007 this option would return +700%. That is a significant return on a sizable investment that can potentially be somewhat life-changing. At least enough to buy a new car or along those lines. If the market went up less, say 10%, this option would return -100%. Fortunately I have an overall portfolio where I can stand to lose a few % if the option did not pan out and I was comfortable defining my risk this way so I decided to pull the trigger.
On 3/31/17 the TQQQ option book looked like this:
The underlying spot price was 88.21. I knew I wanted to give myself some time – to me a short term option is more like gambling but a longer term option is a call on the market. So I picked January 2018. (The actual expiration is 1/19/2018). I also knew I wanted an out-of-the-money call. The only real question was how out of the money? I felt there was a chance the Nasdaq could return 25%, which would imply a TQQQ 1 year return of about 75%. How strong was my conviction? A 75% return on an 88.21 price is 154.3 Doing analysis with those number you get the following:
All the numbers above assume an initial investment of $10,000.
If I picked a strike of 130 I would make 1,250%. A strike of 90 would result in a profit of 400%. In either case, if the market was down for 2017 I would have lost -100%.
In the end I debated hard between the 100 and 120 strikes. I really wanted to pull the trigger on the 120 strikes, but I felt there was too much risk there. For example, if the market had returned 10% last year the returns would have looked like this:
It would have been a good year, The market would have been up for most, but that 120 strike option would have returned -100%. A total wipeout in an excellent year for stocks was too painful for me to contemplate, so I pulled the trigger on the 100 strikes.
I bought 16 calls of TQQQ strike 100 / 1/19/2018 on April 11, 2017. The purchase price was $6.00 each contract.
Often when you have a big winner you sell too early. I did a that this time, but I don’t regret it. My goal was to let the $10k bet ride to Jan 18, 2018 and take what it was worth then. Instead after the position doubled (which turned out to be 1 month later on 5/11/2017) I sold half the position. I sold 8 contracts at $12.60, getting back my $10k investment. I would then let the rest of it ride to expiration.
Except I didn’t. On 12/4/2017 I sold another 4 of the contracts, knowing the end of the option period was near and I did not want to lose all my profit. I sold that lot at $36 each.
I let my 4 remaining options ride to the end. Since they were now deep in the money calls near expiration, they trade at almost the exact difference between the underlying price and option strike price – (Delta of 1). I sold those for whatever the market would bear on market open on 1/17/2018, which turned out to be $63 each.
So my profit as it stands today is:
debit of $6 * 16 * 100 = -$9,600
credit of $12.60 * 8 * 100 = +$10,080
credit of $36 * 4 * 100 = +$14,400
credit of $63 * 4 * 100 = $25,200
—————-
Total of $40,080
So a return of 417% in 9 months. That will do pig, that’ll do.
What if I had waited and not sold at all? Based on the absolute final trade of TQQQ on 1/19/2018 expiration (167.94) – that would have been 1032%.
What if I had done the 120 strike? There the return becomes a fantastic 2200%. The calculations to here have been using the ask price of the options, not the midpoint. Another problem with these options are the spreads. Look at the 120 strike- $2.8 to buy and $1.3 to sell. That means as soon as you execute your order your $10,000 position gets cut in half. Even though that would have worked wonders in 2017 it is still a hard call to pull that trigger.
What’s next?
So fo 2018 I am going to keep 10% of my portfolio in options. My thinking is to ladder 4 options, with strikes of 3,6, 9 and 12 months and $5,000 position each. As for the underlying I am sticking with TQQQ – If we are in the last throes of a bull market, that one will go parabolic before crashing — I would not be surprised to see NASDAQ 8600 by the end of March 2018. If that were to happen, that implies TQQQ would be at $260 / share. If you took a position in March 16, 2018 call @ 200 strike which you can buy now for $2.00 each and you could sell them for $60 each, that’s a return of 2,900%. Insane? Yes. Improbable? Yes. Impossible? We’ll know in 54 trading days.
I’ll detail how that works out in 2019.
Bitcoin
apparently if you want to pay me, you can send bitcoin to this address: 1KW14VFn7PxfskufCiSU49ApeAyRcBfH47
Wow, the new tax bill is really a substantial reduction
Looking at the proposed new marginal tax rates and brackets on the senate website (https://www.finance.senate.gov/imo/media/doc/12.2.17%20HR%201.PDF) from the current 2017 rates on wikipedia (https://en.wikipedia.org/wiki/Income_tax_in_the_United_States#Marginal_tax_rates_for_2017) how big a tax break can you expect?
Quick math for a family with $150k annual taxable income with the old (2017) method:
- 10% on $9,325 = $932.50
- + 15% on ($37,950 – $9325) = $4293.75
- + 25% on ($91,900 – 37,950) = $13,487.50
- + 28% on ($150,000 – $91,900) = $16,268.00
- ———————–
- total (2017) = $34,981.75
and now with the new (2018) method:
- 10% on $19,050 = $1,905
- 12% on ($77,400-$19,050) = $7,002
- 22% on ($140,000-$77,400) = $13,772
- 24% on ($150,000-$140,000) = $2,400
- ———————
- total (2018) =$25,079
So basically $10k less in tax, or an overall reduction of around 30%
Of course that does not take into account changes to itemized deductions, but at least its a start to wrap your mind around the new tax bill.
IBD “Distribution Days” backtesting
So I have been going to the Investor Business Daily meetup in OKC. for the last few months. We usually have about 5 people in attendance and we talk stocks for a couple hours. The host, Raylon Rogers, reads a chapter from an IBD book and then we look at the charts to get our investment ideas. This last week he talked about “Redemption Days”. This is an IBD term to look for selling with volume. IBD is pretty much all a technical analysis method (I perfer fundamentals). If at the end of one trading day the price action was a lower close and the volume rose from yesterday than this is a distribution day. Their sell signal is 5 distribution days out of the last 15 trading days.
How often should a redemption day occur? If it is all truly random, you would expect 3.75 distribution days over any rolling 15 day period (volume can either go up or down, price can either go up or down — therefore a .25 probability that both price moves down and volume moves up on any given day).
So I decided to backtest. I wrote a script in PERL and am hosting it on github if you would like to download and try yourself. It uses data from alphavantage.co API to get daily stock data.
What I follow, and what we talked about in class was the NASDAQ index. Using the tool there have been a total of 4,484 trading days since Jan 1, 2000 (where the alphavantage data stops– I would really like to test this for 1997-1999, since I think that will be the best model for how this particular bull market ends). Of those 4,484 days I can use 4,408 of them for backtesting — I can’t use Jan 1-15, 2000 (since I can’t compute the redemption days between Dec 15-31, 1999), and I can’t use anything after July 26th, 2017 (as I can’t compute the 90 day return after that date (yet)). I use 90 days because that gets a single earning release cycle and I think that is a good number to judge — oh yeah, the market tanked, and you can tell over the last 90 days.
So we are analyzing about ~4,400 days. In that period for the NASDAQ there were 932 times we had 5 or more redemption days out of the last 15 trading days. Of those 932 times, 90 days later the index was down 355 times (38%).
OK, seems decent. If I have a formula to keep me protected 38% of the time that might be worth something. Is it? Let’s see the number of days out of those 4,400 when the return was negative 90 days out: we get 1,609 (36%). So in that light 38% is not statistically significant. I can simply use a rule that says always stay out of the market and I will avoid having negative 90 days returns 36% of the time. Seems about as good as saying stay out when you have 5 redemption days over the last 15 and you will avoid negative returns 38% of the time.
OK, what about total return if you follow redemption day theory? Average return 90 days out from our 932 days of 5/15 redemption days is 1.89%. This compares to an average return 90 days out from all 4,404 analyzed days of 1.25% So what this is saying is you are worse than the market (note both returns are positive). You would be better off buying on 5/15 redemption days.
So how about trying 6 or more redemption days out of 15 instead of just 5/15:
times with 6+ redemption days = 320 times with 7+ redemption days = 106 times with 8+ redemption days = 14
8 is the most, no time since 2000 has there been 9 or more redemption days out of 15 in the IXIC (Nasdaq). So analyze those 14 times with 8/15 redemption days. Average 90 day return is highly positive +7.17%: Here are the 14 times it happened and the 90 day forward return:
2000-04-18 = 7.9% 2001-09-24 = 30.8% 2001-09-25 = 31.6% 2004-03-15 = 2.3% 2009-11-06 = 3.1% 2010-06-03 = -3.0% 2010-06-04 = -0.5% 2012-04-18 = -3.5% 2012-04-23 = -3.9% 2012-07-27 = 0.6% 2016-01-22 = 6.5% 2016-01-25 = 7.6% 2016-05-05 = 10.5% 2016-05-06 = 10.3%
Of interest, not only is the 90 day return super positive, you are only saved from -3% moves down three times, and two times you miss 90 day moves of 30%. I definitely want the other side of this trade. Also, following this theory you are not protected against the 2008 financial crisis or the 2000 dot com bubble.
So, safe to say this theory is totally busted as it relates to the NASDAQ index. How about individual stocks? Let’s try a few:
TGT: distribution days = 960 days (21%) average 90 day return = +1.72% total days = totals 4,408 days average 90 day return = +1.02%
CSCO: distribution days = 849 days (19%) average 90 day return = +1.56% total days = totals 4,408 days average 90 day return = -0.12%
AMZN: distribution days = 766 days (17%) average 90 day return = +6.7% total days = totals 4,408 days average 90 day return = +7.08%
note – dividends are considered here for TGT and CSCO, we are using alphavantage.co TIME_SERIES_DAILY_ADJUSTED, not TIME_SERIES_DAILY.
Again, this distribution day theory is busted. In fact, you want the other side of this trade, if anything (buy after a series of distribution days, don’t sell).
Want me to try it for your stock? Let me know what symbol in the comments and I’ll post the results here.
College Football thoughts on the eve of the 1st rankings
playoffpredictor.com has as the computer top 4:
Which really makes sense, if you think about it. Georgia has a super-quality win over ND. Bama’s best win is over #38 Texas A&M. Wisconsin looks solid and Penn State’s one loss (1 point on the road) is a much better loss than tOSUs (15 points at home) or OUs (7 points at home).
I am expecting the committee to come out with:
- Bama #1
- Georgia #2
- Wisconsin #3
- Ohio State or ND #4
Right now there are 2 other unbeatens – UCF and Miami. Miami and Notre Dame play each other on Nov 11. What I am really interested to see is how the committee treats UCF. My computer has them at #5 – they have some very good wins — in fact, their best win is much better than Bama or Wisconsin’s best win. However, I suspect the committee will put them at about #20 in the initial poll. The way this season is shaking out UCF could be the only unbeaten in college football. I will really like to see if a rematch with Memphis and them winning the AAC would be enough to get a mid-major in.
Cisco Live! 2017 Las Vegas
I am fortunate enough this year to get a ticket out to Cisco Live (thanks James and David)! Here are my summary impressions of day 1 of the event
Opening Keynote — Chuck took the stage and had 2 guest speakers: Tim Cook of Apple and the CEO of UnitedHealth. Chuck used the word “security” much more than I have heard at keynotes in the past. You can totally get his head is that IoT will add ~10-20 billion new network connections in the next few years, and without security it will not happen. So a lot of the keynote was around IoT and security.
I like the Cisco messaging and the thought process is solid. However, it is different watching Chuck vs John Chambers — John had an energy to work the crowd and walk through the crowd with piercing eye contact that just draws you in. It will take some getting used to to understand American Tech 2.0 is Tim Cook and Chuck Robbins, not Steve Jobs and John Chambers.
At the world of solutions I gravitated to the new Catalyst 9300 and Catalyst 9400 switching line, as that is what I am going to be presenting to my clients in the next few weeks. From a hardware point of view, the sexiest, coolest thing was the removable fan tray in the new Cat 9400. Designed by the people that design Ferraris, the tray goes all the way from the front of the chassis to the back, so you can remove it from either side. I realize how lame that sounds, and it is. But the reality is that is as sexy and new in hardware thinking goes. Such is the life of hardware (and you suddenly understand why Cisco is going so hard to a software company).
The new part of the cat 9300 / 9400 is DNA Center, a plug in into APIC-EM. One of the highlights is finding malware threats in encrypted traffic. How is that done? Well, DNA Center requires ISE and Lancope Stealthwatch. The cat 9300/9400 sends netflow to stealthwatch and it specifically looks for the metadata of the Initial Data Packet (IDP) and Sequence of Packet Lengths and Arrival Times (SPLT). The guys in the booth tell me that’s all you need to understand if the traffic is malware. They tell me they have this down to something like 99.95% accuracy. Uh-huh. We’ll see how this plays out.
Think we have enough products? Check out how many security vendors exist in the marketplace today.
I got my Shake Shack dinner! I was looking forward to this all week. Good, but $18 bucks for a burger, fries and a shake! Wow! I have no idea how the federal reserve measures inflation, but I can tell you they are quite wrong.
I saw one really good vendor at the World of Solutions — Kentik. This is something one of my customers use. It processes netflow data. What I love is the visitations. I’m doing a 30 day trial. I totally see my customers sending netflow to Kentik and Lancope.
Summer 2017 movie predictions
Rules: winner is determined by correctness of their list against boxofficemojo.com
Season is summer 2017 (memorial day to Labor Day) – winner to be announced on Labor Day
10 points for getting a movie in the correct slot. 9 points for being 1 off, etc. max possible points = 10×10= 100
Austin’s Prediction
1. Despicable Me 3
2. Cars 3
3. Guardians of the Galaxy Vol. 2
4. Baywatch
5. Spider-Man Homecoming
6. Pirates of the Caribbean
7. Wonder Woman
8. The Dark Tower
9. War for the Planet of the Apes
10. Transformers: The Last Knight
Matthew’s Prediction
1. Despicable Me 3
2. Guardians of the galaxy vol 2
3. Cars 3
4. Spider-Man Homecoming
5. Transformers: The Last Knight
6. Wonder Woman
7. Pirates of the Caribbean
8. War for the Planet of the Apes
9. Baywatch
10. Dunkirk
Neville’s Prediction
1. Guardians of the Galaxy 2
2. Pirates of the Caribbean
3. Cars 3
4. Transformers: The Last Knight
5. Spider-Man Homecoming
6. Captain Underpants
7. Diary of a Wimpy Kid
8. All Eyes on Me
9. Alien: Covenant
10. Wonder Woman
Calculate implied move in a stock from earnings based on options prices
Have you ever listened to CNBC on a marquee company earnings day and heard something along the lines of “options are pricing in a 4% move in this stock post-earning, either up or down” and wondered how that was calculated? Here is how I do it:
Yesterday (5-2-2017) Apple (AAPL) reported Q1 earnings of $2.10 per share. It was one of those scenarios where earnings beat expectation, but guidance was weak, so the stock opened the next day down 1.49%. How close did that 1.49% on Wednesday match what the options market told you on Tuesday?
First, start with the shortest term option available. Options always expire on a Friday, so for AAPL you need to look at the options that expire on 5-5-2017. Prior to close on Tuesday AAPL was trading at $147.63 per share. Look at at-the-money calls and puts – so look at the $148 call. That option was trading on 5-2 at $2.41
So that means a bullish speculator (3 day options is definitely speculation, not investing!) believes AAPL will get to at least $150.41 by Friday. There are only two things at play between Tuesday and Friday — 1 is the earnings call (obviously) and 2 is the overall market volatility on Wednesday through Friday. So a speculator believes those 2 forces will equal a total move of 1.88% (the difference between 150.41 and 147.63).
Now look at the way the options were trading on Wednesday morning. With the stock now at $145.31 a call for $146 on Friday expiration was trading at $0.80. Again this implies a break even price of $146.80, or a 1.02% move. The only thing from Wednesday to Friday is normal overall market volatility, so this tells you that Wed-Fri market vol accounts for 1.02%.
Doing the math on the only other force at play (earning announcement) means that the earnings announcement was 1.88% – 1.02% = 0.86%
Let’s do it now for the downside using at-the-money puts. The Tuesday $147 put cost $2.27 implying a break even price of $144.73 or a move down of 1.96%.
On Wednesday the $145 put cost $1.34 implying break even at $143.66 or a move down of 0.92% between Wednesday and Friday.
Doing the math, 1.96%-0.92% = 1.04%
So the options told you to expect a 0.86% move up or a 1.04% move down in AAPL post-earnings.
So really the options did an okay job of predicting the move. The predicted downside move was 1.04% and the actual was 1.49%. Kinda close, but not spot on.
Guess that squshies!
I was a guest on Kawaii Unicorn YouTube channel playing guess that squishie
https://www.youtube.com/watch?v=6q8ZQVz01Os&feature=share