Trade log 5/22/17

Closed /zn (10y treasury futures) for substantial profit. Didn’t expect to make $ on this trade. Happy. Looking to get long again once I’m back to max equity risk. Currently running half sail…

Quants…

As someone who has been attempting to code trading systems for a rather long time, reading this article makes me think that some of these hedge funds are selling a “quant” marketing image so their clients won’t be tempted away… The quants are here. And they are very quiet. The louder these new quants talk the more desperate and behind they sound. Just my take… but it’s a great read. 

https://www.wsj.com/articles/the-quants-run-wall-street-now-1495389108

Big read. Huge consequences. Transportation as a service.

https://static1.squarespace.com/static/585c3439be65942f022bbf9b/t/591a2e4be6f2e1c13df930c5/1494888038959/RethinkX+Report_051517.pdf

Summary–

 The impacts of TaaS disruption are far reaching:
Savings on transportation costs will result in a permanent boost in annual disposable income for U.S. households, totaling $1 trillion by 2030. Consumer spending is by far the largest driver of the economy, comprising about 71% of total GDP and driving business and job growth throughout the economy. Productivity gains as a result of reclaimed driving hours will boost GDP by an additional $1 trillion.
ê As fewer cars travel more miles, the number of passenger vehicles on American roads will drop from 247 million to 44 million, opening up vast tracts of land for other, more productive uses. Nearly 100 million existing vehicles will be abandoned as they become economically unviable.
ê Demand for new vehicles will plummet: 70% fewer passenger cars and trucks will be manufactured each year. This could result in total disruption of the car value chain, with car dealers, maintenance and insurance companies suffering almost complete destruction. Car manufacturers will have options to adapt, either as low-margin, high- volume assemblers of A-EVs, or by becoming TaaS providers. Both strategies will be characterized by high levels of competition, with new entrants from other industries. The value in the sector will be mainly
in the vehicle operating systems, computing platforms and the TaaS platforms.
ê The transportation value chain will deliver 6 trillion passenger miles in 2030 (an increase of 50% over 2021) at a quarter of the cost ($393 billion versus $1,481 billion).
ê Oil demand will peak at 100 million barrels per day by 2020, dropping
to 70 million barrels per day by 2030. That represents a drop of 30 million barrels in real terms and 40 million barrels below the Energy Information Administration’s current “business as usual” case. This will have a catastrophic effect on the oil industry through price collapse
(an equilibrium cost of $25.4 per barrel), disproportionately impacting different companies, countries, oil elds and infrastructure depending on their exposure to high-cost oil.
ê The impact of the collapse of oil prices throughout the oil industry value chain will be felt as soon as 2021.
ê In the U.S., an estimated 65% of shale oil and tight oil — which under a “business as usual” scenario could make up over 70% of the U.S. supply in 2030 — would no longer be commercially viable.
ê Approximately 70% of the potential 2030 production of Bakken shale oil would be stranded under a 70 million barrels per day demand assumption.
ê Infrastructure such as the Keystone XL and Dakota Access pipelines would be stranded, as well.
ê Other areas facing volume collapse include offshore sites in the United Kingdom, Norway and Nigeria; Venezuelan heavy-crude elds; and the Canadian tar sands.
ê Conventional energy and transportation industries will suffer substantial job loss. Policies will be needed to mitigate these adverse effects.

Assessing the state of the market 5/20/17

 The main things to see here are that the long-term trend remains up. Also SNP earnings are above their 12 month average. Unemployment continues downward although we are reaching the limit of what to expect. And finally that rates are still effectively stimulative in real terms. Once the fed funds rate gets close to or exceeds the two-year bond you will know that the Fed is announcing the end of the party. 


Here you see that reviewing internals through the summation indexes reveals that /nq or ndx remains the place to be.


Dow theory is really old school and I only follow it out of nostalgia. But notice the 8% difference in performance between the industrials and the transport. Hmmmm…


Finally. Yield spread. Orderly. 


Risk appetite spread…

More to come…

Finger-tape Chronicles

Confession: I am in an abusive relationship. I’ve been obsessed with Brazilian Jiu-Jitsu for six years. It ranks right up there with surfing and rock-climbing in terms of people willing to live in a van in order to do it full-time. I tell stories here about the struggle. For the struggle is real…

Trade Log

This blog is for entertainment only. I am NOT recommending you to trade futures. Hire a pro. Do not pay 2 and 20.

5/19/17 Partially closed /nq positions — booking profits — still long oriented. Breadth is thinning.

5/10/17 Bought some AAPL puts. Got to hedge. Mr. Market gets carried away with coke and strippers. Expect to lose $. Still. Don’t call it a hedge fund if it doesn’t hedge.

5/2/17 Long /zn as a static hedge against geopolitical craziness. Currently enjoying some return. But I don’t care if I lose here. I’ve got to sleep at night and America is in grip of an intemperate blowhard. Character is destiny.

3/28/17 Long /nq again. Back to max risk exposure

3/13/17 Partially closed /nq — booking profits

1/17/17 Long /nq — reentered after booking profits from early nov election rip, which I did not believe in and had to hold my nose to buy.

 

 

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The goal is to ride winners, not pick winners. Because unless we have opportunity to get in early, in the first rounds of the capital structure, our money is not locked up. We can switch horses in the middle of the race. Admittedly, most of us fail to do well here. But that is the goal. So currently the race all about

1.) Internet of things

2.) Machine learning (think AI or robotics)

3.) CRISPR and related genomic fields (nearly impossible to find easy trades because of government regulatory involvement.)

4.) Monetizing big data