Concepton

a device that is generating concepts


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Skills network

Anything related can be a network. Any network got a hidden magic inside. Building a network is unleashing another part of the beauty of this world. And when you do this, when you find the secret clusters, when you connect the lonely entities of existence – then this magic is flowing though this network, enlightening and reviving nodes, breaking out over the invisible strings into the life, connecting everything and everyone.

Our skills are shaped by the templates of education and jobs, by human behaviors and to get a glimpse of this bias we can do a simple experiment.

Let’s build s crawler that is getting LinkedIn skills from many people, connect those skills based on cross-correlation and build a network that is based on highly correlated skills.

Even small amount of people I took (about 150), is giving a network of over 400 correlated skills, connected by 3500 links and lots of interesting insights.

skills_network2

So… Mainly pics and less words.

Parts of the network, related to declared programming language-based networks (per language). Pay attention on differences:languages

Design (Since this is a small network, it is biased by my occupation, so the design is mainly represented by word of semiconductors – doing it widely would expose other meanings of design):

design

…with zoom-in on SOC (System On Chip) skills network (pay attention on lack of connection between “microprocessors” and “dsp”  skills. hhhhh…) :soc

Declared Skills, related to “Microsoft”:microsoft

This one is coming from my MBA friends (“Merges” as an anchor):

MnA

Hmm… Interesting positioning for Leadership skill:Leadership

Strategy cluster:

strategy

Those are just several examples, but the applications of this network are giving a big potential value. Amazing HR models and mode of work, Personal effective definition of skills and positioning… It can take the LinkedIn to a whole new level.

And as usually – Do not forget to Enjoy Your Life!

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Annual pattern of Demand for Laptops

As I am working on analysis of Lenovo company (hobby/investment), here is an interesting chart out of the work.

Beautiful pattern of demand for Laptops (relative demand per week, comparing to an annual average of demand) during the last decade:

Demand for Laptops - annual pattern

The pattern is very precise and stable since 2004 during most of the year except maybe some end of the year behavior inconsistency. Though there are expected two peaks of demand at winter holidays, year-to-year  variance during ww48 to ww52 is still high. Extremely high peaks at 2007 holidays, driven by Intel Core 2 Duo products wave.

You can see a clear back-to-school growth towards August from the (-10%) dead-season of Laptops marketing at Spring.


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Annual pattern of jobs searching

Are you looking for a job? Most probably this is not a coincidence. Eventually there is a clear annual pattern in amount of people searching for new opportunities.

Here is a normalized relative pattern of amount of people searching for a jobs for a last decade.

Data is based on worldwide statistics based on millions of people and can be used as a model for Human Resource organizations, headhunters or just people that are part of the trend.

X-axis is weeks (1-52), Y-axis is growth in jobs hunting comparing to the average of the year.

X-axis is weeks (1-52), Y-axis is growth in jobs hunting comparing to the average of the year.

We see a nice and clear behavioral pattern that shows a gradual decline throughout the autumn to the annual minimum of job searches by the end of the year and the slight spike before holidays (people that remind that they need money for presents?). Then enormous spike to the annual maximum at the beginning of the year (motivation to change things in the new year? worldwide layoffs pattern?) and then spring decline followed by growth to a summer “hill”.

Same, but with average profile (Rsq > 0.8):

WW Job Search Profile

What can I say? In my company this profile would be one of base components of HR organization budget. I find it cool.


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Antisemitism and Antiisraelism dependency

Oh, c’mon… Not once more – those Israelis can find the antisemitism everywhere!

Gods know, I hate referring to antisemitism even though it is there. Probably this is some kind of denial. Also, since I am leaving in Israeli bubble, I am less exposed to the entire or opposite side of the informational spectrum that foreigners got to, even though I am reading Russian and English press from time to time. By the way, this is in a very high degree, thanks to Google/Facebook and others that are pushing the boundaries of radicalism due to over-personalization and ghettos of social clustering.  BUT here comes a small check +minimal amount of comments. Data for your consideration:

Google trends for “I hate Israel” (IHI) and for “I hate Jews” (IHJ):

image001

What can we see?

IHI as a constant is kind of new thing (staring ~ end of 2010). For each war there is an IHI peak (for example first big peak is 2006 Lebanon war, second peak is Hamas/Israel war at December 2008 etc).  While previously each war caused peak not only in IHI but in IHJ as well, starting 2011, IHI peaks became less impacting IHJ. So there is some transition in perception.

To clean a bit peak and investigate the trend, I did 3 month averaging and put IHI vs IHJ with a small leg of one month (IHJ after IHI) till 2010:

image003

Since the post perceptional change at 2010, the situation is as following (max Rsq at leg of 3 month now):

image004

Even though it is not a direct dependency, for example spike in IHJ at end of 2011 (red) and high IHI (Operation Pillar of Defense) at end of 2012, overall behavior is common for both.

So if the behavior is not going to change, even though the highest peak of IHI after recent war is going to cause the increase in IHJ in about 2-3 month, overall it is not going to be proportional and fade within a bias of IHJ. Well – we’ll see.

And… how can we finish without good news – the clear dramatic x10 decline of IHJ for the last decade! Always look on the bright side of life!


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Tripadvisor (TRIP) demand and impact on revenues

Analyzing Tripadvisor (TRIP) usage rate, you can observe interesting behavior of people that has direct impact on revenues of the company and I am not talking about growth of usage rate, which is going up all the way to the number one worldwide travel information company:

Tripadvisor usage rate (TRIP)

Tripadvisor usage rate (TRIP)

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Crisis

Well… H.N.Y. fellows! What will be this year? I am optimistic, even though nothing has been conceptually changed in economic, ethical, technological, health, geopolitical and many other conditions of the world. At least a part of the world I am leaving in… At least in my private world… Got a strong feeling of something that is going to be changed though – we have been rested for too long for the exponential world we are leaving in. Speaking of optimism and changes, got an interesting question – Is there going to be a new crisis? Let’s see…

In 2013 we got to the same level of crisis exposure as before 2008 financial crisis and it is trending down:

Image

Interesting is that there is a periodic response to crisis – you can see it even by eye. For those who love math, I can say that Fourier transform of “Crisis” time series clearly shows the peak (skip the chart if you do not care):

Image

The Crisis Cycle period is ~175 days (actually 165-185) throughout last decade.

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Short 2 Long ETF Modeling

Abstract

The obvious relation between Long and Shot ETFs is expected as absolutely opposite, while empiric data analysis is showing interesting duality phenomena of their dependency during rising and falling markets. Drill down into this dependency helps to model ETF price and gain dependencies, see price distortion on gain/loss tails, get insight into ETF behavior during financial crisis and more. This pretty dense work might require explanations and emphasis of details. Welcome to invite me for a drink 🙂 Continue reading