By our count, 37 countries hit what could be bear market bottoms in 2016. We excluded eight countries (Ghana, Cyprus, Kenya, Malawi, Portugal, Tanzania, Uganda and Zambia) because these countries failed to rally at least 10% from their market bottom, and so, their bear market could continue into 2017. The Cyprus stock market, for example, has declined 99.45% from its all-time high in November 1999. If you had put a $1000 in the Cyprus stock market in 1999, now you would barely have enough left for a cup of coffee at Starbucks. We also excluded Canada from this list. Even though Canada ended a 24.36% bear market in January and has rallied 29% since then, the Canadian market had only risen 40% from its previous bear market bottom in October 2011. We calculated both the percentage increase in the previous bull market and the decrease in the bear market that ended in 2016. For the 37 countries in our list, the previous bull market had risen by 141% with Mongolia ending the strongest bull run with a 626% increase. The bear markets that ended in 2016 had an average decline of 41%, but since then, most of the markets have shown significant recoveries. By the end of 2016, the average stock market in our list had risen by 31% from its market bottom. Several countries ended bear markets that had lasted over five years (Brazil, Colombia, the Czech Republic, Kuwait, Mongolia, and Oman).   Of the 37 countries that probably hit a bear market bottom in 2016, one-third of them were in Europe. Interestingly, even though most European countries hit their market bottoms in January or February, the MSCI Europe Index hit its bottom on June 27, 2016 after the United Kingdom voted in favor of Brexit. Two other international indices hit bottoms in 2016. The MSCI EAFE Index declined by 25% between July 2014 and February 2016 while the MSCI Emerging Market Index declined by 43% between May 2011 and January 2016. Both of them now appear to have hit a bottom and are moving up again. The MSCI World Index did not suffer a 20% bear market decline primarily because of the strength of the United States stock market. Although a bear would argue that there is no reason why the bear markets these countries endured could not continue and each market hit a lower low in 2017, given the fact that on average the markets have bounced off their bear market bottom by 30%, it seems unlikely that they are all headed for lower lows in 2017. Although some bears may argue that a country like the United States has been in a bull market for almost eight years, which is longer than the historical average, there is no reason why the bull market in the United States cannot continue. The fact that numerous countries hit market bottoms in 2016 at least provides support for a continuance of the current bull market into 2017 and reduces the likelihood that markets are headed for a major top in 2017. The table below provides information on the 37 countries and three international indices that hit bear market bottoms in 2016. The table provides information on the previous market top, when it ended and the size of that bull market; when the bear market decline ended and the amount of the decline; and how much the market has recovered since then. Individual stock markets are measured in local currency while international indices and Venezuela are measured in US Dollars.  

Country	Bull Top	Change	Bear Bottom	Change	2016 Recovery
Abu Dhabi	9/18/2014	144.93	1/21/2016	-28.59	21.66
Belgium	4/13/2015	104.31	2/11/2016	-21.25	16.30
Brazil	11/4/2010	133.58	1/20/2016	-48.43	59.99
China	6/12/2015	165.15	2/29/2016	-48.02	15.53
Colombia	11/5/2010	151.96	1/18/2016	-51.78	28.75
Croatia	2/11/2011	84.84	1/18/2016	-32.55	26.54
Czech Republic	4/15/2010	107.51	6/27/2016	-39.42	16.65
Egypt	9/7/2014	147.67	1/21/2016	-48.26	147.74
France	4/27/2015	92.87	2/11/2016	-25.28	24.47
Germany	4/10/2015	120.19	2/11/2016	-29.00	26.40
Greece	3/1/2014	187.51	2/11/2016	-67.81	45.99
Hong Kong	4/28/2015	75.03	2/12/2016	-35.59	20.09
India	1/29/2015	95.60	2/11/2016	-22.67	16.01
Iraq	10/4/2011	63.50	6/16/2016	-73.18	28.75
Italy	4/15/2015	91.29	6/27/2016	-30.74	22.61
Japan	8/10/2015	143.17	2/12/2016	-29.27	26.91
Kazakhstan	9/3/2014	55.26	1/21/2016	-39.12	69.89
Kuwait	6/24/2008	70.82	1/26/2016	-68.47	16.46
Luxembourg	4/14/2015	73.02	2/11/2016	-34.48	41.39
Mongolia	2/25/2011	626.20	5/5/2016	-68.18	17.09
Namibia	5/5/2015	199.62	1/20/2016	-36.31	38.52
Netherlands	4/13/2015	85.92	2/11/2016	-24.28	24.42
Nigeria	7/9/2014	118.19	1/19/2016	-47.82	19.68
Norway	4/15/2015	72.83	1/20/2016	-26.35	29.50
Oman	1/16/2011	66.38	1/21/2016	-30.74	18.81
Peru	4/2/2012	298.29	1/20/2016	-63.09	75.34
Philippines	4/10/2015	376.85	1/21/2016	-25.14	12.43
Poland	4/28/2011	120.89	1/20/2016	-42.90	16.32
Qatar	9/18/2014	239.24	1/18/2016	-40.65	22.54
Romania	8/10/2015	83.09	1/18/2016	-21.21	17.71
Saudi Arabia	9/9/2014	169.96	10/3/2016	-51.42	33.12
Singapore	5/22/2013	143.72	1/21/2016	-26.50	12.75
Spain	4/13/2015	99.78	2/11/2016	-34.95	20.49
Sweden	4/27/2015	109.56	2/11/2016	-22.84	22.79
Ukraine	8/1/2014	65.89	5/24/2016	-54.63	23.17
Venezuela	6/13/2015	100.40	12/10/2016	-73.34	14.07
Zimbabwe	8/1/2013	133.18	6/17/2016	-59.95	54.76
MSCI EAFE	7/3/2014	52.30	2/12/2016	-25.21	12.84
MSCI Emerging	5/2/2011	153.96	1/21/2016	-42.93	5.24
MSCI Europe	5/21/2015	53.45	6/27/2016	-25.53	12.89

Global Financial Data has introduced commodity indices which have the longest histories available anywhere as part of its family of GFD Indices. These commodity indices begin in the year 1000 and are current through 2016. The data are monthly and are updated on an ongoing basis. The GFD Commodity Indices include a composite index, three commodity indices and eight commodity sub-indices. The Composite Index is broken down into three categories, energy, agriculturals and industrials. There are no sub-indices for energy, but there are five sub-indices for agriculturals (beverages, soft foods, grains, livestock and oils and meal) and three sub-indices for industrials (non-food agriculturals, base metals and precious metals). The energy index begins in 1252, beverages in 1287, softs in 1209, grains in 1000, livestock in 1209, oils and meal in 1306, non-food agriculturals in 1248, base metals in 1268 and precious metals in 1000. Every index has at least 700 years of history. For the agricultural indices, beverages include beer, cocoa, coffee, milk and tea; the soft foods include butter, cheese, eggs, potatoes and sugar; the grains include barley, corn, hay, oats, rice and wheat; livestock includes, hogs, cattle and lambs; the oils and meal include corn oil, cottonseed oil, cottonseed meal, flaxseed, lard, oatmeal, palm oil, soybean meal, soybean oil, soybeans and tallow. For the industrial indices, base metals include aluminum, copper, iron, lead, nickel, steel, tin and zinc; the non-food agriculturals include cotton, rubber, tobacco, wood and wool; and the precious metals include gold, palladium, platinum and silver. The energy index includes coal, coal gas, firewood, natural gas and oil (which includes lamp oil, whale oil and petroleum). Data are taken from the United States and England. Annual data from England use historical series calculated by Gregory Clark in “The Price History of English Agriculture, 1209-1914.” British data is used until the 1700s when data from the United States becomes available. Most U.S. data before 1861 comes from Arthur H. Cole, Commodity Prices in the United States, 1700-1861, Cambridge: Harvard University Press, 1938. Series from the 1900s and 2000s use government and traded spot prices data. The underlying commodities have for each series have changed over time. Whenever a new commodity source was introduced, we chain-linked different series to provide a continuous set of data for the underlying commodity. Composites were created for iron (beginning in 1268), steel (1720), coffee (1708), milk (1287), tea (1673), coal (1259), oil (1272), butter (1261), potatoes (1724), sugar (1265), barley (1209), corn (1756), hay (1258), oats (1209), rice (1000), wheat (1209), hogs (1732), cattle (1209), lambs (1874), cotton (1749), tobacco (1618), wood (1443), wool (1248) and lard (1797). Commodities are weighted based upon the amount of trade and consumption of each component. No exact data are available for the amount traded and consumed before the 1900s, so the weights have been estimated. The GFD Commodity Indices are available to subscribers to the GFD Indices, which include hundreds of proprietary series calculated for commodities, stocks and bonds. To get more information on these indices, or if you would like a list of the indices and the companies that have been added, call today to speak to one of our sales representatives at 877-DATA-999 or 949-542-4200.  

Standard and Poor’s and MSCI recently revised their GICS sector indices, introducing Real Estate as a separate sector, removing it as an industry within Finance. S&P/MSCI also revised several of its sub-indices, both adding and subtracting several of them. The GICS Codes now include 11 Sectors, 24 Industry Groups, 68 Industries and 157 Sub-Industries. Because of these changes, GFD has decided to reorganize and simplify the tickers for its S&P Sector Indices. Until now, the S&P Sector index tickers used abbreviations to name a particular sector. For example, RAIL was used for railroads and AIRL was used for Airlines. The problem was that it was impossible to know which alphabetic abbreviation was used for each sector. Going forward, GFD will use the actual GICS numerical codes in the tickers to make it easier for our subscribers to find the sector index they want. Once they have the GICS Code for any sector or industry, they can easily put together the ticker for the index using a simple formula. An Excel file of the current GICS codes can be found at https://www.msci.com/documents/10199/4547797/GICS+Structure+effective+Sep+1%2C+2016.xls/d8600f87-cc12-4070-912f-08590232441d All S&P tickers used in the GFDatabase begin with an underscore (_), followed by a one or two-digit number indicating whether the index is from the S&P 500 Large Cap (5), S&P 400 Midcap (4), S&P 600 Small Cap (6) or S&P 1500 Supercomposite (15) index. The number is then followed by “SP”, and then the GICS Code. For example, the code for the S&P 500 Energy Sector is _5SP10 using 5SP for the S&P 500 and 10 for the Energy Sector. The code for the S&P 400 Transports Industry Group is _4SP2030 using 4SP for the S&P 500 and 2030 for the Transportation Industry Group. The code for the S&P 600 Health Care Providers and Services Industry is _6SP351020 using 6SP for the S&P 600 and 351020 for the Health Care Providers and Services Industry. The code for the S&P 1500 Electric Utilities Sub-Industry is _15SP55101010 using 15SP for the S&P 1500 and 55101010 for the Electric Utilities Sub-Industry. This methodology eliminates the need to determine the letter suffix for each sector and industry. Because the GICS Sectors and Industries are global codes, some industries may not be available for the United States S&P Indices, but GFD Includes all the indices that are available for the S&P 500 Large Cap Indices, S&P 400 Midcap Indices, the S&P 600 Small Cap Indices and the S&P 1500 Supercomposite Indices. To get more information on these indices, or if you would like a list of the indices, call today to speak to one of our sales representatives at 877-DATA-999 or 949-542-4200.

Avoiding instability in the past is the central driving force of Vision 2030. But what is Vision 2030’s plan to rectify this single-minded confidence in oil? Private sector job creation. In total, across twenty-four different agencies and 543 individual initiatives, the Saudi government is about to pour 296 Billion SAR into its economy to facilitate growth. Converting that to USD gives us a better idea of perspective, equating to $78.92 Billion USD over five years. Out of the 543 separate initiatives, Vision 2030 plans to:

• Create more than 450,000 jobs in the non-governmental sector by the year 2020;
• Open financing and subsidy opportunities for home ownership with a target of 52% of the Saudi population being home owners by 2020;
• Increase non-oil related revenues from 163 Billion SR to 530 Billion SR;
• Overhaul its tax system;
• Enhance the importing and exporting operation & process; and
• Reform and restructuring of primary health care systems.

And again, we go through the same thing we did decades past. GDP falls, prosperity and wages decline, and people cry for blood. The response is typically the same: more jobs. Notably, however, is the focus on jobs in the private sector. One wonders how so many in the US who are swayed to the ideas of socialism don’t investigate why so many countries rely on the private sector for wealth creation rather than the government. Hopefully, for the Saudi’s sake, their stimulus package will inspire their economy to a less oil dependent state.