S&P500 Short Term Market Breadth Analog Forecast Starting May 2, 2016
By Lawrence
Review of Forecast for Apr 25, 2016
2-way trading all week as expected. Ended up with short side winning as expected. Not enough time to develop further drop after 1.5% swing down happened from week high. Volatility picked up as expected. The breadth analog model did an excellent job for the week.
Forecast Starting May 2, 2016
Summary of the S&P500 short-term forecast based on my proprietary market breadth analog model as of the close of Apr 29, 2016:
A sell-off week is expected
A drop of 1.5% will likely lead to 2.5% drop
Beware of the price target for the drop tagged this week which can lead to a very strong bounce. Premium members can refer to MBO special update for the information.
Extreme intraday volatility in both directions expected
Multiple intraday turning points expected with wild swings that has to be identified with real-time breadth
My market breadth based analog model takes into account the short term volatility, daily market breadth readings and a few other intraday breadth data to identify the current market conditions. Using the information, the model then went through the historical data over the past 20 years to generate its statistical analysis. The model has been pretty good at identifying important swing tops and bottoms over the past few years by providing early warnings about potential volatility upticks.
S&P500 Short Term Market Breadth Analog Forecast Starting May 2, 2016
Review of Forecast for Apr 25, 2016
2-way trading all week as expected. Ended up with short side winning as expected. Not enough time to develop further drop after 1.5% swing down happened from week high. Volatility picked up as expected. The breadth analog model did an excellent job for the week.
Forecast Starting May 2, 2016
Summary of the S&P500 short-term forecast based on my proprietary market breadth analog model as of the close of Apr 29, 2016:
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Report Snapshot
Short Explanation About The Model
My market breadth based analog model takes into account the short term volatility, daily market breadth readings and a few other intraday breadth data to identify the current market conditions. Using the information, the model then went through the historical data over the past 20 years to generate its statistical analysis. The model has been pretty good at identifying important swing tops and bottoms over the past few years by providing early warnings about potential volatility upticks.
For the technical explanation of the concept, you can read about it here, Market Breadth Primer: Market Breadth Analog Forecasting Method
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