Idea – model hourly (ex open/close) stock performance as random variable

Idea that hit me today while driving — there is a lot of timing bias in the behavior of an individual stock due to the fact 1) humans are on a daily cycle and 2) opening prices gap from yesterdays close / close positioning.  There is also the fact of after market hours news to move prices.

Thing that I am looking for — model a stock performance as a random variable that is *normally distributed*  <- we find that modeling the daily return of $AAPL or $MSFT is not normally distributed (because of things like October 1987 <- that is an event that is so many standard deviations off the curve that it olny had a 10^-79 probability event, but it happened anyways).   Hypothesis:  We know daily price movements are NOT normally distributed, but perhaps the price movements from, say 11am to 1pm ARE normally distributed.

Check the correlation of $XXX from daily performance to 11am-1pm performance.   Are they correlated for something like $AAPL?    What is the 1 year return of $AAPL using only 11am-1pm vs full day performance?    Need to test this and report the findings here later.


Countries visited by Hoshi and Nergish Aga

My parents have been to 52 countries. Here is the list:

Argentina 1973, 1998
Australia 1989, 1997, 2014
Austria 1963,
Bahrain 1979
Bolivia 1973 Landed at worlds highest airport La Paz
Brazil 1972, 1973, 1997 (lived here)
Canada 1962, 1966, 2017
Chile 1973, 1998, 2012
China 1978, 1996
Dominican Republic
Egypt 1959, 1965, 1999
India (lived here)
Iran (lived here)
Mexico (lived here)
New Zealand
South Africa
United Kingdom
United States 1959-1963, 1965-1972, 1973-1977, 1979 to present (lives here)
Venezuela 1972 at Caracas airport on way to Brazil
Yemen 1959, 1965
The Netherlands a.k.a Holland
Costa Rica

They have also been to 3 other places that are not UN member states:
Hong Kong
Falkland Islands


For further reading on the subject, pick up a copy of “Such a Wonderful Journey” by Hoshi Aga. It is available on



Countries I have been to

Today during the OU PMBA icebreakers someone stated they have been to 34 different countries. I confidently said, “yeah, I’ve been to at least 34”. I decided to count them up today, with a map for the last year I was in said country.

I was wrong, I have only been to 32. Here is my list:

Canada  (2016)
USA (2018)
Mexico (2018)
Haiti (2010)
Brazil (1973)
Argentina (1973)
UK (1998)
France (1998)
Germany (2014)
Austria (2014)
Switzerland  (2014)
Italy (2014)
Greece (2016)
Bahrain (1980)
Iran (1979)
India (1986)
Singapore (1980)
China (1978)
Japan (1978)
Hong Kong (1978)
Australia (2009)
Fiji (2009)
Monaco  (1973)
Bolivia (1973)
Venezuela (1973)
Oman (1998)
Peru (1973)
Pakistan (1978)
Egypt (1986)
Saint Martin (2012)
Sint Maarten (2012)
Bahamas (2001)

Countries I have been to, by last decade last visited

Green = 2010s
Light green = 2000s
Yellow = 1990s
Orange = 1980s
Red = 1970s

So sorry classmate who has been to 34 (or did you say 36) — you are the real globetrotter!

True Bid/Ask spreads on 3xETF, 9+ months out, out-of-the money calls

Most people like to sell premium and collect money.  Me, I like to buy premium in anticipation of a melt-up.

Today I placed an order to buy TQQQ 76.67C, Jan 2019, and another order to sell the same call option. I did this to see what the true market bid/ask spreads are.

In the morning, Schwab was publishing bid@1.40, midpoint@2.60 and ask at 3.80.   There had been no volume on this contract for several days, and the market has been up over the last few days/weeks.

I started placing orders to buy at $1.40, going up in 20c increments until the bid dropped again when I removed my order. The marketmaker bids rose and stayed elevated to $2.50, at which point my bid became best when my order was in, and the bid dropped to $2.50 when I removed my order.  I got filled at $3.50. I bought 10 contracts.

Then I sold  1 contract. Started at $3.50, got filled at $3.30.

So the real spread was $3.30-$3.50 (about 6%), and not the $1.40-$3.80 (46%)  that the platform said at the beginning of the day.


Compare to QQQ options for the same date (Jan 2019) — the same % out of the money (7% for QQQ, 21% for TQQQ) is 190 strike. Before starting, bid is $3.28 to ask of $3.35  (2%) . Using the same methodology buying 32 contracts and selling 2 I got filled buying at $3.29 and selling at $3.28 (0.3%).

Above is the view before starting QQQ trade

Above is the view after completing both QQQ trades (buying and selling).  Notice I am all of the volume. Started at 405, I bought 32 and sold 2, ending volume is 439.


So, the final analysis is as following:



Larry Kudlow

Sad news that Larry Kudlow suffered a heart attack. Wishing him a speedy recovery.

Larry Kudlow has been one of my favorite TV personalities for years. My favorite is Kudlow and Kramer, when they had their run in the 2000-2010 timeframe. I always appreciate Larry’s optimism and his true, core belief that “free market capitalism is the best path to prosperity”.    Get well quick, Larry.

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.

Wow, the new tax bill is really a substantial reduction

Looking at the proposed new marginal tax rates and brackets on the senate website (   from the current 2017 rates on wikipedia ( 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 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:

distribution days = 960 days (21%)
  average 90 day return = +1.72% 
total days = totals 4,408 days
  average 90 day return = +1.02%
distribution days = 849 days (19%)
  average 90 day return = +1.56% 
total days = totals 4,408 days
  average 90 day return = -0.12%
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 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.