How Alternate Data Sets Can Present Radically Different Perspectives on the S&P 500 Index
Craig Gregozeski | June 9, 2020
The Standard and Poor’s 500 Index is the benchmark most commonly used by fund managers to measure the success of their funds, and by investors to measure the health of their portfolios and that of the overall market. It is commonly assumed that such a widely used measuring stick would provide universal context. In reality, the information gleaned from the S&P 500 Index depends heavily on how the data is presented.
The Standard and Poor’s 500 Index is a capitalization weighted index of 500 stocks designed to measure performance of the broad domestic economy through changes in the aggregate market value of 500 stocks representing all major industries. It is an unmanaged index which cannot be invested into directly. Past performance is no guarantee of future results.
The existence of three data sets is not a problem. The problem is that the industry uses all three of these data sets interchangeably in a potentially misleading way.
To be clear, Standard and Poor’s and Robert Shiller, creator of the weekly and monthly long dated data sets, never intended for the industry to misuse their information.
This data can be misused by firms by way of presenting historical facts. The volatility and recovery percentage necessary is reduced in the monthly and annual data sets, which poses a major problem.
Week 2: The low is 6 and the high is 11
Week 3: The low is 12 and the high is 17
Week 4: The low is 10 and the high is 22
These are volatile time periods—especially Week 4, during which prices more than doubled. A monthly average, however, compiles these prices into an average of 17.05. This number removes all the volatility and presents a smooth figure that does not reflect the severity of the losses that were incurred or the large percentage necessary for recovery (a low of 6 back up to 23 represents a 73% loss, which takes 283% to recover.)
Financial firms of all sizes use monthly and weekly data sets (known as the Shiller Data set) in their presentations about the successful viability of long term investing to present the S&P 500 Index in the best possible light. By removing the volatility, they present investors with a picture of the market that isn't factual or accurate. Only daily price data can present accurate information with the most realistic estimation of market volatility.
Any time you see a chart that refers to the Shiller Data Set, or even the S&P 500 pre-1957, beware that the product packager using it may well be misrepresenting investing outcomes. Seeing a reference to it in the fine print should signal or blare like a tornado warning siren that you’re about to be waylaid.
The opinions voiced in this material are for general information only and are not intended to provide specific advice or recommendations for any individual. All performance referenced is historical and is no guarantee of future results.
The Standard and Poor’s 500 Index is the benchmark most commonly used by fund managers to measure the success of their funds, and by investors to measure the health of their portfolios and that of the overall market. It is commonly assumed that such a widely used measuring stick would provide universal context. In reality, the information gleaned from the S&P 500 Index depends heavily on how the data is presented.
The Standard and Poor’s 500 Index is a capitalization weighted index of 500 stocks designed to measure performance of the broad domestic economy through changes in the aggregate market value of 500 stocks representing all major industries. It is an unmanaged index which cannot be invested into directly. Past performance is no guarantee of future results.
We’ve found evidence that data from the S&P 500 is presented in three different forms:
-
Daily price data
-
Weekly price data
-
Monthly price data
The existence of three data sets is not a problem. The problem is that the industry uses all three of these data sets interchangeably in a potentially misleading way.
To be clear, Standard and Poor’s and Robert Shiller, creator of the weekly and monthly long dated data sets, never intended for the industry to misuse their information.
This data can be misused by firms by way of presenting historical facts. The volatility and recovery percentage necessary is reduced in the monthly and annual data sets, which poses a major problem.
One Set of Data, 3 Different Outcomes
Data tells a different story to investors depending on how it is presented. Imagine that a sample month of data includes the following 20 prices:- 16, 17, 18, 20, 23
- 8, 7, 6, 9, 11
- 12, 13, 17, 15, 14
- 22, 21, 15, 13, 10
Week 2: The low is 6 and the high is 11
Week 3: The low is 12 and the high is 17
Week 4: The low is 10 and the high is 22
These are volatile time periods—especially Week 4, during which prices more than doubled. A monthly average, however, compiles these prices into an average of 17.05. This number removes all the volatility and presents a smooth figure that does not reflect the severity of the losses that were incurred or the large percentage necessary for recovery (a low of 6 back up to 23 represents a 73% loss, which takes 283% to recover.)
Financial firms of all sizes use monthly and weekly data sets (known as the Shiller Data set) in their presentations about the successful viability of long term investing to present the S&P 500 Index in the best possible light. By removing the volatility, they present investors with a picture of the market that isn't factual or accurate. Only daily price data can present accurate information with the most realistic estimation of market volatility.
Any time you see a chart that refers to the Shiller Data Set, or even the S&P 500 pre-1957, beware that the product packager using it may well be misrepresenting investing outcomes. Seeing a reference to it in the fine print should signal or blare like a tornado warning siren that you’re about to be waylaid.
The opinions voiced in this material are for general information only and are not intended to provide specific advice or recommendations for any individual. All performance referenced is historical and is no guarantee of future results.