Click on a help topic for more information

What are the interactive features and how do I use them?


    The sample graphic on the left shows an "unzoomed" chart and the one on the right shows the chart once it has been zoomed.

What is standard deviation and why is it used in so many of your charts?


    Standard deviation shows the amount of variation there is from the average (or mean) for a data series. A low standard deviation indicates that the data points are typically close to the mean, whereas a high standard deviation indicates that the data series is volatile and the data points are spread out over a large range of values. One standard deviation equals the average variance, two standard deviations equals twice the average variance and so forth.

    The following two charts show how useful standard deviation is when trying to compare series with wide differences in volatility. Both charts show the annual change in housing starts and retail sales since 1961. The first shows how difficult it can be to make sense out of the two indicators when compared on just an annual percentage change basis. The second chart uses standard deviation to give context and compare the "significance" of peaks and valleys in relative terms.

    Since the standard deviation is calculated after the other transformations are done (i.e. year-over-year change and/or inflation-adjustment), the series are now directly comparable both against each other as well as against themselves over time.

    MacroTrends charts are uniquely designed to take advantage of the standard deviation calculation. We recognize that the calculation itself is meaningless to most people and is already reflected in the vertical y-axis labels on each chart. Therefore we use the calculated standard deviation value as the basis for the chart plotting, but keep the original data value (i.e. level, annual % change, etc...) intact and display it in the graphical "balloons" that display when you move your mouse over the chart area.

    You can find out more about standard deviation by clicking here.

What economic and market data do you use and where does it come from?


    The focus of is on the economic indicators that have the greatest impact on the equity, bond, commodity and currency markets. There are tens of thousands of detailed economic data series available through multiple sources, but only a small fraction have real market-moving potential. These market-moving indicators are the foundation of our charts.

    Our sources include:

  • Bureau of Labor Statistics
  • Federal Reserve
  • Bureau of the Census
  • Labor Department
  • Federal Housing Finance Administration
  • Institute for Supply Management
  • University of Michigan

How often is the data updated?

    List of Market-Moving Economic Releases (Updated within 3 hours of release):
  • Employment Report - Non-Farm Payrolls, Unemployment Rate
  • Weekly Unemployment Claims - Initial and Continuing
  • ISM Manufacturing Index
  • Consumer Price Index (CPI)
  • Producer Price Index (PPI)
  • Retail Sales
  • Housing Starts, Housing Permits, New Home Sales
  • Gross Domestic Product
  • Industrial Production and Capacity Utilization
  • Our charts contain numerous other economic indicators which are always updated the same day as the data release
  • Market Indicators Updated Nightly with Last Closing Value
  • Stock Market Indicators - DJIA, S&P 500, NASDAQ, FTSE, Nikkei, Hang Seng, Shanghai, Bovespa
  • Commodity Market Indicators - Gold, Oil, Silver, Reuters/CRB

How many years of historical data do you have?


    Our charts use market index and economic data as far back as 1913. Our oldest series are:

  • Dow Jones Industrial Average - 1913
  • Consumer Price Index - 1913
  • Producer Price Index (All Commodities) - 1913
  • S&P 500 Index and Earnings - 1926
  • Dow Jones Transportation Average - 1929
  • Gross Domestic Product - 1929
  • Dow Jones Utility Average - 1930
  • Non-Farm Payrolls - 1939
  • Most other time series start in 1948 or later. We attempt to provide all historical data made available by the original source.


    Since we inflation-adjust all of our dollar-denominated data, we don't publish DJIA data before 1913, the start of the headline CPI data series.

Why do you adjust your dollar-denominated data for inflation?


    The mission of is to enable not only a comparison between different indicators at any point in time but also valid comparisons of any single indicator with data from the past.

    Since inflation or deflation changes the relative value of a dollar, it is critical to use an appropriate inflation indicator to adjust your historical dollar-denominated data. In this way, the impact of general price changes is removed and a comparison can be made on the changes to the indicator itself.

    You can find out more about adjusting for inflation here.

What methods do you use for inflation-adjusting your data?


    The Consumer Price Index, published by the Bureau of Labor Statistics, is the premier indicator of U.S. inflation. We use this as the primary basis for inflation-adjustment on the site. We use a slightly different approach for two other series:

    Retail Sales

    Since retail sales are non-service purchases, it is important to remove the services portion of the CPI when adjusting this index. We use the CPI commodities index, which is a goods-only subset of the CPI, to adjust the retail sales data.

    Housing Prices

    The housing price-rent index is adjusted by the CPI rental index. As the title implies, the price-rent index charts the relationship between the growth in housing prices and the growth in rental rates. The two tend to move at the same rate on average over time so spikes in prices drive the index upwards. The "headline" CPI would not be appropriate as it containes price movements for numerous other products and services outside of housing.

If an update to a particular inflation-adjusted indicator occurs before the CPI release for that month, what method do you use to adjust the series until the new CPI number is published?


    The CPI is not released until the middle of each month. This means that any inflation-adjusted series that releases earlier in the month will not have a CPI number yet to use for adjustment.

    We work around this by using the inflation rate for the previous month to adjust any impacted series until the new data is released. So for the first two weeks of any given month, series like the Dow, S&P 500 and NASDAQ will reflect an adjustment for the previous month's inflation rate.

    A special case are the consensus earnings estimates for the S&P 500. These projections extend out eight quarters into the future so we use the most recent month's inflation rate to adjust these numbers as well.

Why do you use moving averages for some data series but not for others?


    There are a number of time series that demonstrate significant month-to-month volatility. It becomes difficult to identify a trend in data like this when only viewing single-month data points.

    The use of a simple moving average is the best solution to this problem. The simple moving average calculation takes the average of the preceding X number of days,weeks,months or quarters and displays that average value as the value for the current month. This smooths out the intra-month volatility and allows clear visibility into trend changes.

    We also use moving averages to smooth out charts with time horizons of 30 years or more. Once again, this helps to iron out volatility in the data that isn't relevant to the long term trend

    Click here for more background on moving averages.

How do you decide what moving average to use for a particular time series?


    The government statistical agencies recommend the use of specific moving average ranges for certain of their indicators. follows those recommendations to maintain adherence to commonly accepted standards.

    In situations where there is no official recommended interval, we use the moving average that most clearly identifies trends and smooths out false tops and bottoms. The six month moving average is the most common for monthly indicators.

How do you convert a daily index like the S&P 500 or DJIA into a monthly number that you can use to compare with other indicators?


    The bulk of the economic indicators on this site are published on a monthly basis. This can pose a challenge when the goal is to accurately compare these monthly indicators with a more granular series that changes on a daily or weekly basis. All daily or weekly market indicators are shown as the last available value of each month.

How do you convert a quarterly data series like GDP into a monthly number that you can use to compare with other indicators?


    The base freqency for the site is monthly, so data series with a quarterly release frequency can pose a challenge when attempting comparisons. Our solution was to take the quarterly values and place that value in each month for a given quarter.

    So for example, if GDP is $14 trillion for the first quarter of a given year, the $14 trillion value would be placed in the January, February and March months. This can lead to a "stair-step" look if the graph line isn't modified so we typically use a 3-month moving average to smooth out the choppiness in the data. The benefit of the 3-month MA is that it still displays the unmodified value for the last month of each quarter.

A chart hasn't updated even though the new data has been released. What can I do?


    This could be a result of several things:

    The new data has not yet been updated in the database.

    It can take up to ten minutes for market-moving indicators to be updated and several hours for minor indicators. Please allow enough time for the database to be updated and then try again.

    Your browser is not correctly refreshing the data file.

    Click the "Reload Data" button in the top left corner of the chart window to make sure you have the latest data displayed in the chart.

    Your browser is caching old data.

    Access your browser settings file and clear your browser cache. Instructions for all major browsers are located here.

    You are located behind a corporate proxy server and the proxy server has cached old data for the chart.

    If the above methods do not resolve the issue, please contact your network administrator to find out how to get an exception entered for this site.

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All charts and data are provided 'as is' for informational purposes only and are not intended to be used for trading or as investing advice.