Technical factors used in our statistical models
The logic of our long term market timing system is built around
the computerized analysis of certain technical market factors. The
system analyzes the factors for two fundamental purposes:
- Trend Identification – the system uses several stock
market indexes as input factors for analysis of trend direction
as well as for a component of gauging the risk of trend-change.
- Supply and Demand Analysis – the system evaluates a
variety of factors that are indicators of the underlying supply
and demand conditions within the stock market. Changing supply/demand conditions help us gauge the risk of trend-change and also provide a predictive element in the model's logic.
Many market timing systems are simply based upon trend
identification logic and use stock market index prices as their only
data input. These systems can be fairly effective but invariably
suffer from lagging the market’s actual twists and turns. For that
reason, system designers like to build in “predictive” logic that
can pick out the market’s important trend changes more
accurately—with less lag.
- However, maintaining an element of pure trend-following
logic is important as a fail-safe because the predictive logic
will not precisely catch every change in trend.
Predictive logic was designed around an analysis of the
conditions of supply and demand in the stock market can boost effectiveness
Market timing system designers have created many different
approaches to building effective predictive logic. The different
methodologies incorporate a very wide range of different factors.
- Our predictive logic is designed around an analysis of the
conditions of supply and demand in the stock market.
Stock market prices move up and down responding to changes in the
demand for, and supply of, stocks. To better understand the changing
health of that demand/supply relationship, we analyze certain
underlying factors that have a statistically predictive record.
The factors are:
- Market volume statistics – based on New York Stock
Exchange volume
- Market breadth statistics – such as the number of
advancing issues versus declining issues
- Monetary indicators – indicating the relative cost of
money and its impact on the demand for stocks
- Momentum indicators – which decipher how the market’s
rate-of-change feeds back to effect supply and demand
- Credit market indicators – the market’s view of U.S.
corporate creditworthiness impacts investor demand for stocks
- Cross-market relationships – which analyze the
inter-relatedness of different markets based upon historical
patterns
Taken together, the analysis of this battery of factors can help
predict the likelihood of a change-in-trend.
- The analysis of the risk of trend-change is an important
component of the market timing based logic in our system that dynamically changes
portfolio allocations in our Model Portfolios.
Trend following logic makes sure we don’t miss
The trend-following logic within our system makes sure we don’t miss
a Bull Market or Bear Market, even if the trend identification may
occur at a lag. The market factors used as input for trend-following
are simply the changing prices of certain market indexes.
Specifically, our system analyzes the following market indexes:
A time proven statistical model
Combined, the
trend-following and
predictive elements of our system
work together and form an effective market analysis tool. The
long
term market timing model was originally developed in the early
1990’s and has been used live successfully since the mid-1990’s.
- The statistical logic in the system was developed through
the computerized analysis of historical data back to 1970.
Our historical analysis of market data incorporated the:
- devastating bear market of the 1970’s, the
- booming bull market of the 1980’s, and the
- market crash of 1987.
Since then, the long term market timing model has captured every
major trend-change. It accurately identified the:
- massive bull market during the 1990’s, the
- technology stock bubble
and burst, and the
- launch of a new bull market in 2003.
Take a look at a chart showing the model’s exact timing signals. It shows the model’s actual, live market timing signals signifying when we completely exited the stock market (Sell) or
bought back into the market (Buy).
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After seeing how accurate this model has been, you will
wonder how you ever got along without it.
