Capitalogix

Here Are Some Links For Your Weekend Reading -- December 31st, 2016

Any bold predictions for 2017?

 

 

Here are some of the posts that caught my eye recently.

Hope you find something interesting.

 

Lighter Links:

• The Top 10 TED Talks of 2016. (YouTube)
• The Year in Pictures 2016. (Nyti)
• The 12 Key Science Moments of 2016. (TheGuardian)
• How I Process a Massive Amount Of Content. (Medium)
• The Top Jerry Jones Quotes of 2016: Ugly Babies, Jumping off Buildings and Circumcising Mosquitos. (SportsDay)

 

Trading Links:

• Who Benefits from Market Speed Bumps? The Exchanges. (New York Times)
• Where are They Now? the 12 Members of the 1896 Dow Jones Industrial Average. (BizInsider)
• It's So Hard to Get Cash in India that Some People are Ordering It Online. (Money)
• Percentage of Young Americans Living with Parents Rises to 75-Year High. (WSJ)
• Contrarian Views for 2017, Seven Dos and Don’ts for Your Portfolio, and Trump's Market Mirage (Globe and Mail)

Here Are Some Links For Your Weekend Reading - December 25th, 2016

Even Santa was hacked this year.

 

 

So, were you naughty or nice?

  

Here are some of the posts that caught my eye. Hope you find something interesting.

 

Lighter Links:

• The 10X Mindset – Life At an Exponentially Higher Level. (Medium)
• 21 Business Books Worth Reading At Least Once a Year. (Inc)
• Artificial Intelligence and Life in 2030 - Stanford's 100-Year Study on AI. (AI100)
• The Magic and Power of Placebo. (FourHourWorkWeek)
• How to Create a Happy Life with Hacks from Stanford’s Famous ‘Design Your Life’ Class. (Medium)

Trading Links:

• America's next Great Metropolis is Taking Shape in Texas. (Forbes)
• “Moneyball” in Commercial Lending: from Art to Science in Pricing. (BCGPerspectives)
• The Paradox of Quant. (TheReformedBroker)
• Bill Gross Says You Should Start Buying Land and Gold. (Fortune)
• UK ‘Sailing Blindly’ into Financial Meltdown Bigger Than 2008, Think Tank Warns. (RT)

Where Does America Get It's Oil?

When people think oil, they think Middle East.  But, in reality, our biggest importer is Canada (with 3,169,ooo barrels a day imported in 2015).

The chart is a little old, but is interesting nonetheless.

 

see U.S. Energy Information Administration.

Perhaps more surprising is that America gets most of our oil internally ... with 8,796,000 barrels produced last week. 

Meanwhile, we are using approximately 19,400,000 a day.

Crazy numbers. Do you think they'll go up, or down, in 2017?

 

Here Are Some Links For Your Weekend Reading - December 18th, 2016

It was cold in Dallas this weekend ... below freezing.

In contrast, it's officially colder than Mars in Canada

Don't stick your tongue on any flag poles. 

 

 

Here are some of the posts that caught my eye. Hope you find something interesting.

 

Lighter Links:

• Clinton Campaign to Participate in the Wisconsin Recount — Plus Michigan and Pennsylvania If They Happen. (TW)
• America’s Top Spy Talks Snowden Leaks and Our Ominous Future. (Pocket)
• The Strange Psychology of Stress and Burnout. (Pocket)
• A New Program Judges If You’re a Criminal from Your Facial Features. (MotherBoard)
• 3 New, Must-Read Quotes from Tesla Motors, Inc. CEO Elon Musk. (FoxBusiness)

 

Trading Links:

• How Apple Lost China to Two Unknown Local Smartphone Makers. (Bloomberg)
• ‘A Rude Shock’: Indians Describe Life after Narendra Modi’s Currency Ban. (New York Times)
• NASA's New 'Intruder Alert' System Spots an Incoming Asteroid. (NPR)
• Is the Age of Asset Management Over? (FinanceMagnates)
• Immigration, World Poverty and Gumballs. (YouTube)

A Statistically Significant Edge

Last week we discussed that just because a trading system is making money doesn't prove it has an edge.  It means you have both the chance that the system has an edge - and also that it may just be lucky.

One of our advisors wrote back to see if they understood that approach.

 

The odds of flipping a coin and getting heads 25 times in a row is roughly 1-in-33 million. So if we have 33 million flippers and 100 get 25 heads in a row, statistically that is very improbable.  We can deduce that group of 100 is a combination of some lucky flippers, but also that some have a "flipping edge."  We may not be able to say which is which, but as a group our 100 will still consistently provide an edge in future flip-offs.

 

Well, that is correct.  In fact, if we were developing coin-flipping agents that would be as far as we would be able to go.  However, we are in luck because our problem has an extra dimension, which makes it possible to filter-out some of the "lucky" Bots from our trading systems.

 

Determining Which are the Best Systems.

 

There are several ways to determine whether a trading system has a persistent edge.  For example, we can look at the market returns during the trading period and compare and contrast that with our trading results.

This is significant because many systems have either a long or short bias.  That means even if a system does not have an edge, it would be more likely to turn a profit when its bias is in alignment with the market. 

We try to correct that bias using some math and statistical magic, in order to determine whether the system has a predictive edge.

 

It Is a Lot Simpler Than It Sounds.

 
Imagine a system that picks trades based on a roulette spin.  Instead of numbers or colors, the wheel is filled with "Go Long" and "Go Short" selections.  As long as the choices are balanced, the system is random.  But what if the roulette wheel had more opportunities for "long" selections than "short" selections?

This random system would appear to be "in-phase" whenever the market is in an uptrend.  But does it have an edge? 

One Way To Calculate Whether You Have An Edge.
 

Let's say that you test a particular trading system on hourly bars of the S&P 500 Index from January 2000 until today. 

 

1. The first thing you need is the total net profit of the system for all its trades.  
2. The second thing you need to calculate is the percent of time it spent long and short during the test period.
3. Third, you need to generate a reasonably large population of completely random entries and exits with the same percentage of long/short time as your back-tested results (this step can be done many times to create a range of results). 
4. Fourth, use statistical inference to calculate the average profit of these purely random entry tests for that same test period. 
5. Finally, subtract that amount from the total back-tested net profit from the first step.

 

According to the law of large numbers, in the case of the "roulette" system illustrated above, correcting for bias this way, the P&L of random systems would end up close to zero … while systems with real predictive power would be left with significant residual profits after the bias correction.

While, the math isn't difficult … the process is still challenging because it takes significant resources to crunch that many numbers for hundreds of thousands of Bots. 

The good thing about RAM, CPU cycles and disk space is that they keep getting cheaper and more powerful.

What My Dogs Can Teach Us About Markets

 Some dogs run fast; other dogs do tricks … my 100 pound lab, Duke's best talent is his ability to remain immobile in almost any situation (some call it "laziness" … I prefer "calm" or "even-tempered").

At the other end of the spectrum is Boo, our 20 pound mix between a Beagle and a Boston terrier. Let's just say that he has higher metabolism than Duke. 

When Boo hears a noise, he lets out an involuntary, barely audible, sound.  His body becomes rigid and his head cocks.  He becomes alert and carefully tunes his ears to their most sensitive setting, seeking any information that will help identify the "danger." And now he's waiting for the next intrusion.

Usually there are no other disturbances to follow, and the noise is cataloged and soon forgotten. His alertness level slowly subsides over the next 10-15 minutes or so.  He'll go back to napping, a little more fitfully this time … and just a little bit on edge.

Things get a little more interesting when another noise surfaces shortly after the first one.  What could once be dismissed now must be treated as a threat - and just to be safe, a threat of the highest order.  Now the appropriate response is a series of barks, nervous glances, pacing, rushing off in the direction of the noise to investigate, and a barrage of barks meant to sound more menacing than the source of the noise.  Who or what is it? How much harm can they cause? How grave is the threat?

Duke is a different story.  Nothing upsets Duke more than Boo.  The same noise that prompted Boo to become alert does nothing to Duke.  However the first time that Boo makes noise, that makes Duke alert. And the second time Boo makes noise, Duke starts vocalizing, and the third time, well now both of them start yapping and when they both start yapping, then other dogs in the neighborhood start yapping.

I realized that the same thing happens in the market with people.

In the market, it is the second noise - and subsequent noises - that creates the equivalent of the Homeland Security "Red Alert." Once an elevated level of alertness has been established, it takes a long period of relative calm for it to subside.  And when on "Red Alert" … any additional noises (for example, the responses of the other market participants) - big or small - will highlight, magnify and further validate the issue.

But, like in the story "The Boy Who Cried Wolf," even legitimate threats are ignored after too many false alarms (or prolonged periods of constant alert).  So, bad news about the economy isn't as likely to get people excited after the past few weeks.

Here Are Some Links For Your Weekend Reading - November 20th, 2016

Here are some of the posts that caught my eye. Hope you find something interesting.

Lighter Links:

• The Myths Democrats Swallowed that Cost Them the Presidential Election. (NW)
• You Can Have Emotions You Don’t Feel. (Nautil)
• Dalai Lama: Behind Our Anxiety, the Fear of Being Unneeded. (NYTimes)
• For the 4th Time in American History, the President-Elect Lost the Popular Vote. (LATimes)
• Dear Democrats, Read this If You Do Not Understand Why Trump Won. (Medium)

Trading Links:

• Clinton Lost the Economic Argument. (Slate)
• Peter Thiel Joins Donald Trump’s Transition Team. (TheVerge)
• How the Market Responded to Trump's Win Shows Wall St. Learned a Fundamental Lesson. (BI)
• Here’s How the Fed and the ECB Will React to Trump’s Victory. (Fortune)
• Hedge Funds Run by Trump Advisors Made the Most Money off His Election Win. (FB)

Periodic Table of Alternative Investments

As Trump's Presidency starts, I thought it made sense to get an overview of alternative investment options.

 

 via CoInvest.

That reminded me of something else I'd seen recently ... Check out this Periodic Table of Elements that shows what they're commonly used for. 

 

via Discover

Pretty interesting – It gives you some insight into what it takes to keep the world running.

If you ask nicely, perhaps they'll name an element after you?

S&P 500 at Decision Zone

As the country enters its decision zone, the S&P 500 Index is at one too.

Here is a chart that shows we are at a major support-resistance zone.

 

via StockCharts.com.

 

We just saw a long string of down days. U.S. stocks just posted their longest slide since 1980 (nine straight days).

Regardless of what happens here, I expect volatility.

What about you?

Clown Hysteria: 2016 in a Nutshell

This summer, South Carolinians started seeing menacing clowns in the woods.

As a response to clown hysteria,Target pulled clown masks from shelves , McDonalds scaled down use of Ronald McDonald, and people everywhere have been in a fervor.

Not everyone has been affected negatively though ... Surprisingly (to me), Pornhub has seen a massive increase in clown related searches. 

 

via TNW

There you have it ... hard data.

2016 continues to surprise ... Celebrities dying, phones exploding, the election, and this.

It will be interesting to see how 2016 ends, and what the future brings.

The world changes, but human nature remains relatively constant.