Wednesday, January 15, 2014

Starting IPython notebook from windows file exlorer

I organize my IPython notebooks by saving them in different directories. This brings however an inconvenience, because to access the notebooks I need to open a terminal and type 'ipython notebook --pylab=inline'  each and every time. I'm sure the ipython team will solve this in the long run, but in the meantime there is a pretty descent way to quickly access the notebooks from the file explorer.

All you need to do is add a context menu that starts ipython server in your desired directory:




A quick way to add the context item is by running this registry patch.  (Note: the patch assumes that you have your python installation located in C:\Anaconda . If not, you’ll need to open the .reg file in a text editor and set the right path on the last line).

Instructions on adding the registry keys manually can be found on Frolian's blog.

Monday, January 13, 2014

Leveraged ETFs in 2013, where is your decay now?

Many people think that leveraged etfs in the long term underperform their benchmarks. This is true for choppy markets, but not in the case of trending conditions, either up or down. Leverage only has effect on the most likely outcome, not on the expected outcome. For more background please read this post.

2013 has been a very good year for stocks, which trended up for most of the year. Let's see what would happen if we shorted some of the leveraged etfs exactly a year ago and hedged them with their benchmark. 
Knowing the leveraged etf behavior  I would expect that leveraged etfs outperformed their benchmark, so the strategy that would try to profit from the decay would lose money.

I will be considering these pairs:

SPY 2 SSO -1 
SPY -2 SDS -1
QQQ 2 QLD -1
QQQ -2 QID -1
IYF -2 SKF -1

Each leveraged etf is held short (-1 $) and hedged with an 1x etf. Notice that to hedge an inverse etf a negative position is held in the 1x etf.

Here is one example: SPY vs SSO. 
Once we normalize the prices to 100$ at the beginning of the backtest period (250 days) it is apparent that  the 2x etf outperforms 1x etf.



 Now the results of  the backtest on the pairs above:
All the 2x etfs (including inverse) have outperformed their benchmark over the course of 2013. According to expectations, the strategy exploiting 'beta decay' would not be profitable.

I would think that playing leveraged etfs against their unleveraged counterpart does not provide any edge, unless you know the market conditions beforehand (trending or range-bound).  But if you do know the coming market regime, there are much easier ways to profit from it. Unfortunately, nobody has yet been really succesful at predicting the market regime at even the very short term.


Full source code of the calculations is available for the subscribers of the Trading With Python course. Notebook #307

Thursday, January 2, 2014

Putting a price tag on TWTR

Here is my shot at Twitter valuation. I'd like to start with a disclaimer: at this moment a large portion of my portrolio consists of short TWTR position, so my opinion is rather skewed. The reason I've done my own analysis is that my bet did not work out well, and Twitter made a parabolic move in December 2013. So the question that I'm trying to answer here is "should I take my loss or hold on to my shorts?".

At the time of writing, TWTR trades around $64 mark, with a market cap of 34.7 B$. Up till now the company has not made any profit, loosing 142M$ in 3013 after making 534M$ in revenues. The last two numbers give us yearly company spendings of 676M$.

Price derived from user value

Twitter can be compared with  with Facebook, Google and LinkedIn to get an idea of user numbers and their values. The table below summarises user numbers per company and a value per user derived from the market cap. (source for number of users: Wikipedia, number for Google is based on number of unique searches)
users [millions]user value [$]
FB1190113
TWTR250139
GOOG2000187
LNKD259100
It becomes apparent that the market valuation per user is very similar for all of the companies, however my personal opinion is that:
  • TWTR is currently more valuable per user thatn FB or LNKD. This is not logical as both competitors have more valuable personal user data at their disposal. 
  • GOOG has been excelling at extracting ad revenue from its users. To do that, it has a set of highly diversified offerings, from search engine to Google+ , Docs and Gmail. TWTR has nothing resembling that, while its value per user is only 35% lower thatn that of Google.
  • TWTR has a limited room to grow its user base as it does not offer products comparable to FB or GOOG offerings. TWTR has been around for seven years now and most people wanting an accout have got their chance. The rest just does not care.
  • TWTR user base is volatile and is likely to move to the next hot thing when it will become available.
I think the best reference here would be LNKD, which has a stable niche in the professional market. By this metric TWTR would be overvalued. Setting user value at 100$ for TWTR would produce a fair TWTR price of 46 $.

Price derived from future earnings

There is enough data available of the future earnings estimates. One of the most useful ones I've found is here.
Using those numbers while subtracting company spendings, which I assume to remain constant , produces this numbers:
banksindependents
2013-51-43
2014292462
20156121120
Net income in M$

With an assumption that a healthy company will have a final PE ratio of around 30, we can calculate share prices:
banksindependentsaverage
2013-2.81-2.37-2.59
201416.0825.4520.76
201533.7161.6947.70
TWTR price in $ based on PE=30

Again, average price estimate is around 46-48 $ mark which is what it was around the IPO. Current price of 64$  is around 36% too high to be reasonable.


Conclusion

Based on available information, optimistic valuation of TWTR should be in the 46-48 $ range. There are no clear reasons it should be trading higher and many operational risks to trade lower.
My guess is that during the IPO enough professionals have reviewed the price, setting it at a fair price level. What happened next was an irrational market move not justified by new information. Just take a look at the bullish frenzy on stocktwits,  with people claiming things like 'this bird will fly to $100'. Pure emotion, which never works out well.

The only thing that rests me now is to put my money where my mouth is and stick to my shorts. Time will tell.