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.

Global Financial data has added 20 new indices aggregating the data from its proprietary bond indices to create global fixed income series using data from over 50 countries. A price index and return index is provided for each aggregate. These additions provide a significant increase in the historical coverage of GFD’s bond indices. The starting date for the previous World Government Bond Index was 1923, but the updated World Bond Index begins in 1700. The new bond indices include

• World Government Bond Index (begins in 1700)
• World x/USA Government Bond Index (begins in 1700)
• G7 Government Bond Index (begins in 1700)
• Developed Countries Government Bond Index (begins in 1700)
• Developed x/USA Government Bond Index (begins in 1700)
• Emerging Markets Government Bond Index (begins in 1722)
• Asia Government Bond Index (begins in 1722)
• Europe Government Bond Index (begins in 1700)
• North America Government Bond Index (begins in 1786)
• Latin America Government Bond Index (begins in 1822)

These bond indices are weighted by GDP, rather than by the value of outstanding government debt. Given the period of 300 years that is covered, we determined that GDP weighting provided the most consistent methodology. Using debt outstanding as a weighting methodology was impractical not only because of the lack of historical data on bonds outstanding, but also because of the numerous ways in which the outstanding amount of bonds could change. The value of government debt outstanding fluctuated more dramatically than GDP over time, sometimes falling to zero as governments paid off their debts or inflated their way out of their debt. In other cases, governments defaulted on their debt, converted their external debt into internal debt, defaulted on their internal debt but not their external debt, reorganized their debt, forcing bondholders to take a haircut, and so forth. Wars caused sudden increases in outstanding debt while defaults wiped out a large portion of the debt. Central governments could accept responsibility for state debts, or repudiate them. The United States provides several examples of how dramatically the amount of outstanding debt could fluctuate. The US reorganized its debts under Alexander Hamilton in the 1790s issuing new bonds, some of which did not pay any interest for ten years. The United States Federal Government completely paid off its debts in the 1830s, but individual states still had debt and issued bonds. After the Civil War, the Federal Government gradually paid down its debts, but railroads raised enormous amounts of debt. Several countries, such as Imperial Russia, the Confederacy, and others completely defaulted on their debt. During the 1800s, Great Britain gradually paid off the debts it had accumulated during the Napoleonic Wars, while France added to its debt. Germany inflated its way out of its internal debts during its hyperinflation in the 1920s, and was in default on its foreign debt during World War II. Some countries, historically, did not have a central government at all. Italy and Germany didn’t exist as countries in 1850, so any calculation of “national” debt would have to aggregate the debt of individual states. The same is true of South Africa and Australia. If you include state debt for these countries, why not include state debt for the United States, Canada and other decentralized countries? The United States took on the debt of individual states after the Revolutionary War, but refused to take on the debt of individual states and the Confederacy after the Civil War. Although most aggregate bond indices today rely upon the value of outstanding debt as a weighting factor, the dramatic differences in debt from one country to another can create problems. US GDP is about three times Japan’s GDP, but the United States’ federal government debt is only about 50% greater than Japan’s government debt. Consequently, S&P’s World Government Bond Index gives about one-third of its weight to the United States, one-third to Europe and one-fourth to Japan. Since Japan has had significantly lower interest rates than the rest of the world for the past 25 years, weighting by debt outstanding creates a lower average government bond yield than weighting by GDP. There is also a “free float” problem with weighting by outstanding debt. In order to keep interest rates low, central banks in developed countries have bought government debt and added this debt to its balance sheet. About one-third of Japan’s government debt is currently held by the Japanese government itself. For many years, the Chinese government has held hundreds of billions of dollars of United States debt, and since Greece’s default, almost all of Greece’s debt has been owned by governments or central banks, not by the private sector. If government bond indices were to only include the amount available to investors and not held by governments, additional adjustments would have to be made in the weighting of each country. For all these reasons, the returns to a GDP-weighted bond index differ from the returns to a capitalization-weighted bond index. In particular, countries, like Japan, which have a high level of government debt will impose an outsize influence on the index. Since Japan’s bond yields have been consistently lower than bond yields in other countries, a value-weighted Bond Index will provide lower returns than a GDP-weighted Index. The World Government Bond Index and the World x/USA Government Bond Index are provided to all subscribers to the GFDatabase. The other indices are available through a subscription to either the GFD Indices or the Fixed Income Securities Database. 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.