Stock Market Forecast and Trading

Parabolic SAR (SAR stands for Stop-And-Reverse) is a trend-following indicator that has been used by many traders for decades. Its major application is in trading systems to define a trailing stop, i.e., to protect profit when a price trend changes. The term “parabolic” appeared to characterize the indicator parabola shape that is due to using an accelerating factor in the formula. SAR is especially effective in a trending market. To make it more effective in a sideways market, it is often used in conjunction with other indicators.

SAR indicator gives a strong signal when a price trend is about to reverse, therefore, this indicator can be used for prediction. To compare the predictive ability of SAR with other indicators, it has been implemented into the technical analysis module of Fundamental-Technical Analyzer FTA-2. SAR calculations have been used to collect statistics based on the forecast simulations for major indexes and ETFs during August-October 2011 period. As a result, SAR’s position was mostly in “top ten” indicators list.

The research and presented chart are made by Fundamental-Technical Analyzer FTA-2, one of the software modules that enables composing Neural Network forecasts of many indicators with weights accordingly to each indicator’s predictive ability.

Omitting logical rules for accelerating factor and reversal conditions, a recurring core formula for SAR is the following:

SAR (current point) = AF * [EP – SAR (previous point)] + SAR (previous point)

where:
AF – Acceleration Factor (normally starts from 0.02 and increases by 0.02 if each next point reaches a new extreme, saturates until 0.2);
EP – Extreme Point (lowest low or highest high).

To summarize, Parabolic SAR can be enriched by combining it with Neural Network and successfully used for predicting stock market prices. Combing it with Neural Network allows extracting more statistically stable patterns and, therefore, providing a better accuracy in the forecast. As simulations showed, improved results can be achieved if SAR is transformed into more sensitive indicator by subtracting it from close price (it indicates the degree of SAR and price convergence).

The charts below show potential behavior of S&P-500 Index, ^GSPC, for the next week, March 28 – April 1, 2011. The first chart is pattern similarity forecast, the second one – neural network forecast. Both methods predict an uptrend after Monday.

The chart shows S&P-500 forecast for the period from November 1 to November 5, 2010. The calculation has been performed using Neural Network Stock Trend Predictor NNSTP-2. The forecast is a fluctuation with eventual downside move.

The charts below show S&P-500 forecast for the period from October 18 to October 22, 2010. The forecast is a possible slight uptrend.

The forecasts have been calculated using Neural Network Stock Trend Predictor NNSTP-2 and Investment Analyzer InvAn-4 (pattern similarity).

The chart shows S&P-500 forecast for the period from September 13 to September 17, 2010. The calculation has been performed using Neural Network Stock Trend Predictor NNSTP-2. The forecast is a slight uptrend.

The chart shows S&P-500 forecast for the period starting from August 30. The calculation has been performed using Stock Market Predictor SMAP-3 (cycle analysis). The forecast is a possible uptrend until September 3, then downtrend.

Chart represents S&P-500 forecast for August 23-27, 2010. The prediction has been performed using Investment Analyzer InvAn-4 (pattern similarity). The forecast is a possible slight uptrend.

Chart represents S&P-500 forecast for August 16-20, 2010. The prediction has been performed using Investment Analyzer InvAn-4 (pattern similarity). The forecast is almost flat.

The first chart represents S&P-500 forecast for the first week of June. The calculation has been performed using Neural Network Stock Trend Predictor NNSTP-2. The forecast is a sideways fluctuation.

The second chart represents S&P-500 forecast for June. The calculation has been performed using Stock Market Predictor SMAP-3 (cycle analysis). The forecast is the following: fluctuation for a few days and then a possible uptrend at the end of the month.

Chart represents S&P-500 forecast for April 26-30, 2010. The calculation has been performed using Neural Network Stock Trend Predictor NNSTP-2. The forecast is a slight uptrend.