found a implementation here on stackoverflow but nor sure where to find a package 'package com.perseus.analysis.calculator.technical.trend' that it uses, and also if u know of a good algorithm pls let me know, would eventually like to convert, and implement this in c# here the code and link to where I obtained the code.
link: the post
the interface....
public interface ISupportResistanceCalculator {
/**
* Identifies support / resistance levels.
*
* @param timeseries
* timeseries
* @param beginIndex
* starting point (inclusive)
* @param endIndex
* ending point (exclusive)
* @param segmentSize
* number of elements per internal segment
* @param rangePct
* range % (Example: 1.5%)
* @return A tuple with the list of support levels and a list of resistance
* levels
*/
Tuple<List<Level>, List<Level>> identify(List<Float> timeseries,
int beginIndex, int endIndex, int segmentSize, float rangePct);
}
and also the class....
/**
*
*/
package com.perseus.analysis.calculator.technical.trend;
import static com.perseus.analysis.constant.LevelType.RESISTANCE;
import static com.perseus.analysis.constant.LevelType.SUPPORT;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Date;
import java.util.LinkedList;
import java.util.List;
import java.util.Set;
import java.util.TreeSet;
import com.google.common.collect.Lists;
import com.perseus.analysis.calculator.mean.IMeanCalculator;
import com.perseus.analysis.calculator.timeseries.ITimeSeriesCalculator;
import com.perseus.analysis.constant.LevelType;
import com.perseus.analysis.model.Tuple;
import com.perseus.analysis.model.technical.Level;
import com.perseus.analysis.model.timeseries.ITimeseries;
import com.perseus.analysis.util.CollectionUtils;
/**
* A support and resistance calculator.
*
* @author PRITESH
*
*/
public class SupportResistanceCalculator implements
ISupportResistanceCalculator {
static interface LevelHelper {
Float aggregate(List<Float> data);
LevelType type(float level, float priceAsOfDate, final float rangePct);
boolean withinRange(Float node, float rangePct, Float val);
}
static class Support implements LevelHelper {
@Override
public Float aggregate(final List<Float> data) {
return Collections.min(data);
}
@Override
public LevelType type(final float level, final float priceAsOfDate,
final float rangePct) {
final float threshold = level * (1 - (rangePct / 100));
return (priceAsOfDate < threshold) ? RESISTANCE : SUPPORT;
}
@Override
public boolean withinRange(final Float node, final float rangePct,
final Float val) {
final float threshold = node * (1 + (rangePct / 100f));
if (val < threshold)
return true;
return false;
}
}
static class Resistance implements LevelHelper {
@Override
public Float aggregate(final List<Float> data) {
return Collections.max(data);
}
@Override
public LevelType type(final float level, final float priceAsOfDate,
final float rangePct) {
final float threshold = level * (1 + (rangePct / 100));
return (priceAsOfDate > threshold) ? SUPPORT : RESISTANCE;
}
@Override
public boolean withinRange(final Float node, final float rangePct,
final Float val) {
final float threshold = node * (1 - (rangePct / 100f));
if (val > threshold)
return true;
return false;
}
}
private static final int SMOOTHEN_COUNT = 2;
private static final LevelHelper SUPPORT_HELPER = new Support();
private static final LevelHelper RESISTANCE_HELPER = new Resistance();
private final ITimeSeriesCalculator tsCalc;
private final IMeanCalculator meanCalc;
public SupportResistanceCalculator(final ITimeSeriesCalculator tsCalc,
final IMeanCalculator meanCalc) {
super();
this.tsCalc = tsCalc;
this.meanCalc = meanCalc;
}
@Override
public Tuple<List<Level>, List<Level>> identify(
final List<Float> timeseries, final int beginIndex,
final int endIndex, final int segmentSize, final float rangePct) {
final List<Float> series = this.seriesToWorkWith(timeseries,
beginIndex, endIndex);
// Split the timeseries into chunks
final List<List<Float>> segments = this.splitList(series, segmentSize);
final Float priceAsOfDate = series.get(series.size() - 1);
final List<Level> levels = Lists.newArrayList();
this.identifyLevel(levels, segments, rangePct, priceAsOfDate,
SUPPORT_HELPER);
this.identifyLevel(levels, segments, rangePct, priceAsOfDate,
RESISTANCE_HELPER);
final List<Level> support = Lists.newArrayList();
final List<Level> resistance = Lists.newArrayList();
this.separateLevels(support, resistance, levels);
// Smoothen the levels
this.smoothen(support, resistance, rangePct);
return new Tuple<>(support, resistance);
}
private void identifyLevel(final List<Level> levels,
final List<List<Float>> segments, final float rangePct,
final float priceAsOfDate, final LevelHelper helper) {
final List<Float> aggregateVals = Lists.newArrayList();
// Find min/max of each segment
for (final List<Float> segment : segments) {
aggregateVals.add(helper.aggregate(segment));
}
while (!aggregateVals.isEmpty()) {
final List<Float> withinRange = new ArrayList<>();
final Set<Integer> withinRangeIdx = new TreeSet<>();
// Support/resistance level node
final Float node = helper.aggregate(aggregateVals);
// Find elements within range
for (int i = 0; i < aggregateVals.size(); ++i) {
final Float f = aggregateVals.get(i);
if (helper.withinRange(node, rangePct, f)) {
withinRangeIdx.add(i);
withinRange.add(f);
}
}
// Remove elements within range
CollectionUtils.remove(aggregateVals, withinRangeIdx);
// Take an average
final float level = this.meanCalc.mean(
withinRange.toArray(new Float[] {}), 0, withinRange.size());
final float strength = withinRange.size();
levels.add(new Level(helper.type(level, priceAsOfDate, rangePct),
level, strength));
}
}
private List<List<Float>> splitList(final List<Float> series,
final int segmentSize) {
final List<List<Float>> splitList = CollectionUtils
.convertToNewLists(CollectionUtils.splitList(series,
segmentSize));
if (splitList.size() > 1) {
// If last segment it too small
final int lastIdx = splitList.size() - 1;
final List<Float> last = splitList.get(lastIdx);
if (last.size() <= (segmentSize / 1.5f)) {
// Remove last segment
splitList.remove(lastIdx);
// Move all elements from removed last segment to new last
// segment
splitList.get(lastIdx - 1).addAll(last);
}
}
return splitList;
}
private void separateLevels(final List<Level> support,
final List<Level> resistance, final List<Level> levels) {
for (final Level level : levels) {
if (level.getType() == SUPPORT) {
support.add(level);
} else {
resistance.add(level);
}
}
}
private void smoothen(final List<Level> support,
final List<Level> resistance, final float rangePct) {
for (int i = 0; i < SMOOTHEN_COUNT; ++i) {
this.smoothen(support, rangePct);
this.smoothen(resistance, rangePct);
}
}
/**
* Removes one of the adjacent levels which are close to each other.
*/
private void smoothen(final List<Level> levels, final float rangePct) {
if (levels.size() < 2)
return;
final List<Integer> removeIdx = Lists.newArrayList();
Collections.sort(levels);
for (int i = 0; i < (levels.size() - 1); i++) {
final Level currentLevel = levels.get(i);
final Level nextLevel = levels.get(i + 1);
final Float current = currentLevel.getLevel();
final Float next = nextLevel.getLevel();
final float difference = Math.abs(next - current);
final float threshold = (current * rangePct) / 100;
if (difference < threshold) {
final int remove = currentLevel.getStrength() >= nextLevel
.getStrength() ? i : i + 1;
removeIdx.add(remove);
i++; // start with next pair
}
}
CollectionUtils.remove(levels, removeIdx);
}
private List<Float> seriesToWorkWith(final List<Float> timeseries,
final int beginIndex, final int endIndex) {
if ((beginIndex == 0) && (endIndex == timeseries.size()))
return timeseries;
return timeseries.subList(beginIndex, endIndex);
}
}