The Economic Surprise Indicator (ESI) from Citigroup is quite popular amongst analysts/traders that want to track how actual economic data compare to expectations. In a way, it measures relative optimism and pessimism amongst professional forecasters regarding the economy, which is a very useful tool for investors.
ESI is constructed daily by taking a weighted average “surprises” (actual release sversus Bloomberg survey median forecasts) observed over the past three months. Older surprises are discounted relative to more recent surprises to prevent the index from becoming stale. A value greater (less) than zero denotes stronger- (weaker)- than-expected data, whereas a value near zero indicates that the data have been coming in as expected. As the Fed paper, points out, (1) there is a high degree of auto-correlation, which suggests that there is stickiness to economists' forecast. The Fed paper doubts such to be the case but we think it is the case (people don't change their views day-to-day), and (2) the weights are based on the historical impact of each data surprise on the U.S. market i.e. payrolls and ISMs have higher weights that others. Such weighting may not be appropriate for the Fed policymakers but it is definitely relevant for investors.
ESI is constructed daily by taking a weighted average “surprises” (actual release sversus Bloomberg survey median forecasts) observed over the past three months. Older surprises are discounted relative to more recent surprises to prevent the index from becoming stale. A value greater (less) than zero denotes stronger- (weaker)- than-expected data, whereas a value near zero indicates that the data have been coming in as expected. As the Fed paper, points out, (1) there is a high degree of auto-correlation, which suggests that there is stickiness to economists' forecast. The Fed paper doubts such to be the case but we think it is the case (people don't change their views day-to-day), and (2) the weights are based on the historical impact of each data surprise on the U.S. market i.e. payrolls and ISMs have higher weights that others. Such weighting may not be appropriate for the Fed policymakers but it is definitely relevant for investors.
As the chart show, the ESI tends to lead the S&P500 variance with its 200-day moving average by about 3-6 months. If this relationship were to hold, then we should see pull-back in the S&P500 towards its 200-day moving average.
