Friday, March 18, 2016

2016-03-17 Trading Top5s Securities: ITUB

Markets Top5s analysis for 2016-03-17

Created snapshot 20160317-233312; shunted to google drive

scrape
2016-03-17
Mkt_Cap:GE,BRK.B,ITUB,BRK.A,AMZN|CHL,LLY,FB,TEVA
Price:SID,TCK,BBDO,BBD,GES|VRX,ENDP,JBL,AKRX
Volume:RIG,SPY,RIO,SHPG,BBL,SAN,UBS,UWTI,GSK
Updated /Users/geophf/Documents/OneDrive/work/1HaskellADay/Seer/data/top5s.csv with 2016-03-17 data
bubbles


let's analyze ITUB, $50B+ holding company in Brazil, but okay.

geophf:writing geophf$ analyze ITUB
Wrote analysis files for ITUB
ITUB SMA



ITUB EMA

ITUB Stochastic Oscillators

Wednesday, March 16, 2016

2016-03-16 Market Top5s Analysis: ORCL

Market top5s analysis for 2016-03-16

Created snapshot 20160316-235610; shunted to google drive

Scrape:
2016-03-16
Mkt_Cap:AAPL,ORCL,MSFT,GOOG,AGN|PFE,UBS,BAC,MTU
Price:EPE,UWTI,PAGP,TGP,GWPH|LTRPB,TERP,SC,CAL
Volume:BAC,PFE,GDX,VRX,FCX,ORCL,F,CHK,ITUB,VALE
Updated /Users/geophf/Documents/OneDrive/work/1HaskellADay/Seer/data/top5s.csv with 2016-03-16 data
Bubbles:


Today was a really good day in the tech > Enterprise software subsector

Let's analyze ORCL
geophf:writing geophf$ analyze ORCL
Wrote analysis files for ORCL
ORCL SMA



ORCL EMA

ORCL Stochastic Oscillators

tweet

2016-03-16 State of Logical Graphs LLC

Agenda for 2016-03-16 State of Logical Graphs LLC

Tuesday, March 15, 2016

2016-03-15 Trading Top5s Securities: AAPL

Market top 5s analysis for 2016-03-15, the Ides of March

Created snapshot 20160316-002453; shunted to google drive

scrape
2016-03-15
Mkt_Cap:AAPL,MSFT,FB,WMT,VRX|RIO,BHP,BBL,AGN
Price:MJN,RICE,BTG,VRX,ENDP|SID,MNK,PBYI
Volume:VRX,BAC,PFE,AAPL,PBR,FCX,CHK,ITUB,VALE,AA
Updated /Users/geophf/Documents/OneDrive/work/1HaskellADay/Seer/data/top5s.csv with 2016-03-15 data
bubbles

Let's analyze AAPL which did well today and yesterday:
geophf:writing geophf$ analyze AAPL
Wrote analysis files for AAPL
AAPL SMA

AAPL EMA

AAPL Stochastic Oscillators

Just curious. Is there any company 'like' AAPL? No. If so, what are they and how are they doing?

Yup, it's confirmed; there's no company like AAPL. Okay, then.

tweet

2016-03-14: Trading Top5s Securities: GOOG

Markets Top5s analysis for 2016-03-14, π-day

Took snapshot 20160315-121459, shunted to google drive

scrape:
2016-03-14
Mkt_Cap:GOOGL,GOOG,MTU,PTR,PBR.A|PFE,BRK.B,SNP
Price:GWPH,TFI,SHM,DDD,MT|NUGT,ANET,PBR.A,GB
Volume:VRX,SPY,MJN,AAPL,HMY,MT,RIG,FCX,ALR
Updated /Users/geophf/Documents/OneDrive/work/1HaskellADay/Seer/data/top5s.csv with 2016-03-14 data
bubbles:



let's analyze GOOG
geophf:writing geophf$ analyze GOOG
Wrote analysis files for GOOG
GOOG SMA



GOOG EMA

GOOG Stochastic Oscillators

The tech-sector is looking sunny today...

Saturday, March 12, 2016

2016-03-11 Trading Top5s Securities: MSFT (not DRYS)

Markets top5s analysis for 2016-03-11

Took snapshot 20160312-123239, shunted to google drive

scrape
2016-03-11
Mkt_Cap:PTR,GOOG,GOOGL,MSFT,MO|ABEV,LMCB,PG,RAI
Price:FNSR,FCE.B,NOAH,ULTA,DRYS|ZBRA,LMCB,LTRPB,CPPL
Volume:BAC,PFE,SIRI,FCX,WLL,CHK,SPY,GDX,PBR,MSFT
Updated /Users/geophf/Documents/OneDrive/work/1HaskellADay/Seer/data/top5s.csv with 2016-03-11 data
bubbles


Today, $MSFT did great, but let's look at an almost below-the-radar company $DRYS
geophf:writing geophf$ analyze DRYS
analyze: Ratio has zero denominator
Nope. No can do (not without a code rewrite), but a bit of digging shows this:

DRYS is down – a lot – yesterday, but what caught my eye is FOEAF, a $100M+ company. So it won't be seen on the Top5s (which limits itself to $1B+-companies), but here is an example of a company of interest on the top 5s showing interesting movements in related companies below the radar.

Let's get that 'related companies'-scraper working, geophf!

Let's analyze $MSFT
geophf:writing geophf$ analyze MSFT
Wrote analysis files for MSFT
MSFT SMA

MSFT EMA

MSFT Stochastic Oscillators

Friday, March 11, 2016

TODO: Collect Libraries, Write Paper on Clustering and Graphing Heterogenous Data

You have this:




You need a better representation, like this

Which means you need to collect those data then scale them. Then you can look at clustering

to get something like this.

TODO: Collect these libraries here. Write this paper.