S&P500 Market Breadth Driven Short Term Forecast Starting Nov 7, 2016
By Lawrence
Review of Forecast for Oct 31, 2016
Attempted to bounce on Monday as expected. Dropped to 1.5% and opened the door to 2.5% downside move as forecasted. NFP Friday slowed down the drop but we still get a close at the low of the week. The breadth analog model did a near perfect job last week.
Forecast Starting Nov 7, 2016
Summary of the S&P500 short-term forecast based on my proprietary market breadth analog model as of the close of Nov 4, 2016:
Intraday volatility spikes expected
US election results on Tuesday can swing the markets hard both ways
A bounce is due on Monday
Custom breadth readings point to 2 opposite scenarios with near equal chance
If upside push fails to produce at least 1.5% upside, the down trend will resume falling hard in coming 2 weeks
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 Market Breadth Driven Short Term Forecast Starting Nov 7, 2016
Review of Forecast for Oct 31, 2016
Attempted to bounce on Monday as expected. Dropped to 1.5% and opened the door to 2.5% downside move as forecasted. NFP Friday slowed down the drop but we still get a close at the low of the week. The breadth analog model did a near perfect job last week.
Forecast Starting Nov 7, 2016
Summary of the S&P500 short-term forecast based on my proprietary market breadth analog model as of the close of Nov 4, 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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