public ExponentialMovingAverage(IEnumerable <TInput> inputs, Func <TInput, decimal?> inputMapper, int periodCount) : base(inputs, inputMapper)
{
_ema = new GenericMovingAverage(
i => inputs.Select(inputMapper).ElementAt(i),
Smoothing.Ema(periodCount),
inputs.Count());
PeriodCount = periodCount;
}
public RelativeStrength(IEnumerable <TInput> inputs, Func <TInput, decimal?> inputMapper, int periodCount) : base(inputs, inputMapper)
{
PeriodCount = periodCount;
_u = new PositiveDifferenceByTuple(inputs.Select(inputMapper).ToList(), 1);
_d = new NegativeDifferenceByTuple(inputs.Select(inputMapper).ToList(), 1);
_uEma = new GenericMovingAverage(
periodCount,
i => Enumerable.Range(i - PeriodCount + 1, PeriodCount).Average(j => _u[j]),
i => _u[i],
Smoothing.Mma(periodCount),
inputs.Count());
_dEma = new GenericMovingAverage(
periodCount,
i => Enumerable.Range(i - PeriodCount + 1, PeriodCount).Average(j => _d[j]),
i => _d[i],
Smoothing.Mma(periodCount),
inputs.Count());
}
public KaufmanAdaptiveMovingAverage(IEnumerable <TInput> inputs, Func <TInput, decimal?> inputMapper, int periodCount, int emaFastPeriodCount, int emaSlowPeriodCount) : base(inputs, inputMapper)
{
_er = new EfficiencyRatioByTuple(inputs.Select(inputMapper), periodCount);
decimal smoothingFactor(int i)
{
var s = Smoothing.Ema(emaSlowPeriodCount)(i) + _er[i].Value * (Smoothing.Ema(emaFastPeriodCount)(i) - Smoothing.Ema(emaSlowPeriodCount)(i));
return(s * s);
}
_gma = new GenericMovingAverage(
periodCount - 1,
i => inputs.Select(inputMapper).ElementAt(i),
i => inputs.Select(inputMapper).ElementAt(i),
smoothingFactor,
inputs.Count());
PeriodCount = periodCount;
EmaFastPeriodCount = emaFastPeriodCount;
EmaSlowPeriodCount = emaSlowPeriodCount;
}
