Following on from my previous post, the relative strengths of sectors for 1 month compared to the Footsie are as follows:
ALTERNATIVE ENERGY 2 -15.93
FOOD AND DRUG RETAIL 8 -6.13
MOBILE TELECOMMUNICA 4 -5.39
HEALTH CARE EQUIPMEN 6 -5.22
TOBACCO 2 -5.07
INDUSTRIAL METALS AN 5 -3.17
GAS - WATER AND MULT 6 -3.00
ELECTRICITY 6 -2.95
EQUITY INVESTMENT IN 5 -2.88
PHARMACEUTICALS AND 12 -0.38
AEROSPACE AND DEFENC 9 0.17
REAL ESTATE INVESTME 26 0.44
FIXED LINE TELECOMMU 10 0.66
NONLIFE INSURANCE 12 0.86
LEISURE GOODS 2 1.50
INDUSTRIAL TRANSPORT 7 1.60
FOOD PRODUCERS 21 1.66
TRAVEL AND LEISURE 39 2.78
REAL ESTATE INVESTME 14 3.13
SUPPORT SERVICES 57 3.69
CONSTRUCTION AND MAT 14 4.24
FINANCIAL SERVICES 37 4.69
GENERAL INDUSTRIALS 7 4.90
ELECTRONIC AND ELECT 13 5.70
OIL AND GAS PRODUCER 45 6.15
MEDIA 26 6.16
OIL EQUIPMENT - SERV 7 6.48
BEVERAGES 6 6.73
SOFTWARE AND COMPUTE 23 6.83
INDUSTRIAL ENGINEERI 15 6.86
LIFE INSURANCE 11 7.42
GENERAL RETAILERS 27 7.73
FORESTRY AND PAPER 1 7.83
TECHNOLOGY HARDWARE 10 8.00
HOUSEHOLD GOODS AND 10 8.81
MINING 37 10.50
PERSONAL GOODS 3 13.57
CHEMICALS 8 13.68
AUTOMOBILES AND PART 1 13.79
BANKS 7 22.61
The second column gives you the number of companies per subsector. The third column is the relative performance. As you can seem banks have had a blistering run. Things are a little mixed up - for example mining has had a good run overall, but not "industrial metals and mining"
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2 comments:
Hey Mark,
Very nice list, how did you compile it?
Hi Miguel,
I obtained the data from sharelock Holmes. Relative Strength is one of the stats that it produces. The stats were compiled using a Lisp program that I wrote myself. I did have a similar program written in R a few weeks ago - the free stats app for Linux/WIN7/OSX - but I don't have R installed on my system at the moment.
Worth mentioning is that the strengths I quoted are medians, not means. I tend to use medians more than means, as they provide more robust statistics. For relative strength, though, I think that it probably isn't too important.
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