Technical Indicators: H
Haurlan Index
The Haurlan Index was developed by Peter N. Haurlan in the 1960s as an overbought / oversold indicator. It is made up of three components - short term, intermediate term, and long term.
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The short term component is a 3 day exponential moving average of the net difference between the number of advancing issues and the number of declining issues.
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The intermediate term component is a 20 day exponential moving average of the net difference between the number of advancing issues and the number of declining issues.
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The long term component is a 200 day exponential moving average of the net difference between the number of advancing issues and the number of declining issues.
When the short term component moves above +100 a short term buy signal is generated. It remains in effect until the short term component moves down to -150. At -150 a short term sell signal is reached. Stay short until the indicator reaches +100.
The intermediate component is used to confirm breaks of support and resistance. With confirmation, buy and sell signals are generated. The long term component is used to determine the primary trend in price.
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Herrick Payoff Index
The Herrick Payoff Index determines the amount of money flowing into or out of a futures contract by analyzing volume, price changes, and open interest changes.
When the Herrick Payoff Index is above zero it shows that money is flowing into the futures contract. When the Index is below zero it shows that money is flowing out of the futures contract.
The value of each new day is combined with the value of the previous day using a multiplying factor. Since this is a cumulative indicator the value at the beginning of the data series is zero. The value will primarily increase and decrease with the average price for each day, the amount regulated by the trading volume, changes in the number of open contracts, and changes in the average price.
The primary signal to watch for is a divergence from the price. If prices are increasing and the indicator is decreasing, prices will typically correct to confirm the indicator.
Historical Volatility
No one can accurately predict the future but a knowledge of past behavior can be used as a guide to help make informed decisions of what is likely to happen next. With this idea in mind, Historical Volatility measures the variance of the changes in a security over time.
Traders generally tend to start looking at volatility over a long time, at least ten years. This allows identification of short-term deviations from normal activity. That being said, one should not overlook short-term volatility either. If a commodity has averaged 20% volatility over the last year but only 10% over the past thirty days, it might be wise to adjust the volatility estimates to accommodate the most recent data.
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