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Disclaimer: The information provided on this page is strictly for informational purposes and is not to be construed as advice or solicitation to buy or sell any security. Please see our Risk Disclosure and Performance Disclaimer Statement.

How to access the studies in MotiveWave:

Go to the top menu, choose Study>Study Group>Study Name

or Go to the top menu, choose Study>All Studies> Start typing in the study name until you see it appear in the list> Click on the study name> Click OK.

Gator Oscillator

The Gator Oscillator (GO) was authored by Bill Williams. The GO is based on the Alligator, also written by Bill Williams. It shows the degree of convergence/divergence of the balance lines. The top bar is the absolute difference between the Jaw and Teeth lines. The bottom bar is the absolute difference between the Teeth and Lip lines (with a minus sign to display below 0). The user may change input (midpoint), method (SMMA), period and shift lengths. This indicator’s definition is further expressed in the condensed code given in the calculation below.

Halloween Indicator

The Halloween Indicator was authored by Gerald Gardner in the Stocks And Commodities Magazine Oct,2012. It is a seasonal indicator with a simple strategy. If, in October the price of an instrument is below its 50 period Simple Moving Average, buy it, and in May, sell it. The user may change the input (close), method (SMA) and period length. This indicator’s definition is further expressed in the condensed code given in the calculation below.

How To Trade Using the Halloween Indicator

If the Halloween Indicator (HLWNI) is below the closing price and the month is October a buy signal is generated. If the month is May a sell signal is given.

Calculation

//input = price, user defined, default is closing price //method = moving average, user defined, default is SMA //period = user defined, default is 50 //index = current bar number

Plot: hlwni = ma(method, index, period, price);
// Check for signal events
GregorianCalendar cal = new GregorianCalendar(); 
curBarTime =  getStartTime(index);      
cal.setTimeInMillis(curBarTime);
mth = cal.get(GregorianCalendar.MONTH);
sell = (mth == Calendar.MAY);
buy = (price lessThan hlwni AND mth == Calendar.OCTOBER);

Heikin-Ashi Candles Oscillator Long Term

The Heikin-Ashi Candles Oscillator Long Term was authored by Sylvain Vervoort in the Stocks And Commodities Magazine Aug 2012. For details see the article Long-Term Trading Using Exchange Traded Funds. The user may change the input (WP), methods (TEMA,EMA) and period lengths. This indicator’s definition is further expressed in the condensed code given in the calculation below.

How To Trade Using the Heikin Ashi Candles Oscillator LT

If the Heikin Ashi Candles Oscillator LT (HACOLT) equals 100 buy to take a long position and if the HACOLT is 50 exit the long position. A HACOLT value of 0 provides an opportunity for a short entry.

Calculation

//input = price, user defined, default is weighted price //method1 = moving average, user defined, default is TEMA //temaPeriod = user defined, default is 55 //method2 = moving average, user defined, default is EMA //emaPeriod = user defined, default is 60 //Candle Size Factor = user defined, default is 1.1 //index = current bar number

The Heikin Ashi Candles Oscillator LT code may be available on request

Herrick Payoff Index

The Herrick Payoff Index (HPI) was authored by John Herrick. The HPI is used to analyze futures and commodities. One input parameter called the value of one percent move (pointValue) is required. Herrick recommended 100 for most commodities. A host of highs, lows, opens, closes and volumes are mathematically manipulated to produce a bi-colored histogram. This indicator’s definition is further expressed in the condensed code given in the calculation below.

How To Trade Using Herrick Payoff Index

The Herrick Payoff Index may be used in conjunction with other indicators. No trading signals are calculated.

Calculation

//pointValue = user defined, default is 100 //prev = previous, index = current bar number //abs = absolute value //LT = less than, MT = more than

prevOpen = open[index-1];
prevHigh = high[index-1];
prevLow = low[index-1];
prevClose = close[index-1];
median = (high + low) / 2;
prevMedian = (prevHigh + prevLow) / 2;
i = abs(close - prevClose);
g = min(open, prevOpen);
k = (median-prevMedian) * pointValue * volume;
temp = 1 + ((i/2) / g);
if (median LT prevMedian) temp = 1 - ((i/2) / g);
k = k * temp;
prevK = k[index-1];
PlotHist: hpic = prevK + (k - prevK);

Hilbert Transform Indicator

The Hilbert Transform Indicator was authored by John Ehlers. The Hilbert Transform itself is an all-pass filter used in digital signal processing. By using present and prior price differences, and some feedback, price values are split into their complex number components of real (inPhase) and imaginary (quadrature) parts. The user may change the input (midpoint), and period length. This indicator’s definition is further expressed in the condensed code given in the calculation below.

Click here for more information

How To Trade Using the Hilbert Transform Indicator

The Hilbert Transform Indicator may be used in conjunction with other indicators. No trading signals are calculated in this study. Calculation

//input = price, user defined, default is midpoint price //period = user defined, default is 7 //quad = quadrature = imaginary part of complex number //inPhase = real part of complex number //index = current bar number

iMult = .635;
qMult = .338;

priorPrice = price[index-period];
//v1 = Detrend price
v1 = price - priorPrice;

v2 = v1[index-2]);      
v4 = v1[index-4];      

inPhase3 = inPhase[index-3];      
quad2 = quad[index-2];      

//Hilbert transform complex number components, inPhase (real part), quad (imaginary part)

inPhase = 1.25 * (v4 - (iMult*v2) + (iMult*inPhase3));
quad = v2 - (qMult*v1) + (qMult*quad2); 
Plot1: inPhase;
Plot2: quad;

Historical Volatility

Historical Volatility and Pattern Recognition was authored by Laurence A. Conners and Linda Bradford Raschke, Stocks and Commodities Mag. 08/1996. It uses standard deviation and natural logarithm in its formula. The user may change the input (close), period and annual length. This indicator’s definition is further expressed in the condensed code given in the calculation below.

How To Trade Using Historical Volatility

Historical Volatility may be used in conjunction with other indicators. No trading signals are given.

Calculation

//input = price, user defined, default is close //period = user defined, default is 20 // annual = user defined, default is 365 //prev = previous //log = natural logarithm //std = standard deviation //sqrt = square root //index = current bar number

value = price[index];
prevValue = price[index-1];
temp = log(value/prevValue);
Plot: hv = 100 * std(period, temp) * sqrt(annual);

Hull Moving Average

The Hull Moving Average makes a moving average more responsive while maintaining a curve smoothness. The formula for calculating this average is as follows: HMA[i] = MA( (2*MA(input, period/2) – MA(input, period)), SQRT(period)) where MA is a moving average and SQRT is square root. The user may change the input (close), period length and shift number. This indicator’s definition is further expressed in the condensed code given in the calculation below.

Click here for more information.

How To Trade Using the Hull Moving Average

The Hull Moving Average is a lagging trend indicator and may be used in conjunction with other studies. No trading signals are calculated.

Calculation

//input = price, user defined, default is close //method = moving average (ma), user defined, default is WMA //period = user defined, default is 20 //shift = user defined, default is 0 //wma = weighted moving average, sqrt = square root //index = current bar number, LOE = less or equal

sqp = Math.sqrt(period);
for(i = period; i lessThan size(); i++)
    if (isComplete(i)) continue;
    ma1 = 2*ma(method, i, period/2, input);
    ma2 = ma(method, i, period, input);
    if (ma2 == null) continue;
    MA_TMP[i] = ma1 - ma2;
endFor
end = size()-1;
start = 0;
if (start LOE period+sqp) start = period + sqp;
lastComplete = size()-1;
if (shift lessThan 0) lastComplete += shift;
for(i = start; i LOE end; i++) 
    if (isComplete(i+shift)) continue;
    value = ma(method, i, sqp, MA_TMP);
    if (value == null) continue;
    Plot: MA[i+shift] = value;
endFor

Hurst Cycles

Hurst Cycles or Hurst’s Cyclic Theory was developed in the 1970s by J.M.Hurst, an American engineer.

The theory is based on eight principles that explain the price movement of markets and securities, which are influenced by an infinite series of harmonically related cycles of various sizes. These different cycles represent the overall price action.

The key concept behind this theory is that at the beginning or end of a cycle, the markets often achieve significant lows (or troughs). The troughs (as opposed to the peaks) of these cycles align where prices hit significant bottoms (tops). The theory explains the price movements in a market or individual security by showing how these cycles combine, with allowance for some variations. These cycles can be used to predict market reversals and price trends.

For details on this study, see our Hurst Cycles Guide

How to trade using Hurst Cycles

In general, when the cycles are at troughs (low points), they present buying opportunities and in contrast, the cycles at peaks (high points) suggest selling opportunities. Additionally, sell or buy signals become more reliable when multiple time of cycles align at the same points.

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Last updated 28 days ago