TrendDetectionSMA: Current Trend Detection using Simple Moving Average
In candlesticks: Candlestick Pattern Recognition

Description Usage Arguments Details Value Author(s) See Also Examples

Uses the SMA of n periods to determine whether a price series is in uptrend or downtrend

1	TrendDetectionSMA(TS, n=20)

`TS`	xts Time Series containing OHLC prices
`n`	number of periods for the SMA to average over

This function assumes that a price series is in uptrend (downtrend) when a period's price closes above (below) the simple moving average of n periods.

A xts object containing the columns:

`UpTrend`	TRUE if uptrend detected (Close > SMA(n))
`NoTrend`	TRUE if sideward trend detected (Close == SMA(n))
`DownTrend`	TRUE if downtrend detected (Close < SMA(n))
`Trend`	+1 for uptrend, 0 for sideward trend, -1 for downtrend

Andreas Voellenklee

TrendDetectionChannel

## Not run: 
  getSymbols("YHOO", adjust=TRUE)
  
  # create chart of YAHOO
  chartSeries(YHOO, subset="last 1 year", TA=NULL)
  
  # visualize the result of trend detection in a indicator box
  addTA(TrendDetectionSMA(YHOO)[,4])
  
  # filter YHOO for Hammer Candlestick Patterns that occur in downtrends
  Hammer <- CSPHammer(TS) & TrendDetectionSMA(TS)[,"DownTrend"]
  
  # how frequent are these hammers?
  colSums(Hammer, na.rm=TRUE)

## End(Not run)