public static TipRanksResult GetTipRanksResult(string symbol)
{
//Return a data object that contains:
//Aggregated ratings data and ratings providers
//Aggregated insider transactions data, insider names, insider ratings
//Aggregated insitutional transactions data, hedge fund ratings, hedge fund names
//Composite score of the above 3 items
string responseString = String.Empty;
HttpWebRequest request = (HttpWebRequest)HttpWebRequest.Create(TipRanksBaseUrl + "getData/" + symbol);
request.Method = "GET";
try
{
using (HttpWebResponse response = (HttpWebResponse)request.GetResponse())
{
StreamReader reader = new StreamReader(response.GetResponseStream(), Encoding.UTF8);
responseString = reader.ReadToEnd();
response.Close();
}
TipRanksDataResponse trResponse = JsonConvert.DeserializeObject <TipRanksDataResponse>(responseString);
//filter results to the last 3 months
DateTime startDate = DateTime.Now.AddMonths(-3);
List <Insider> insiders = trResponse.insiders
.Where(x => DateTime.Compare(x.rDate, startDate) > 0)
.ToList();
List <ConsensusOverTime> bsns = trResponse.consensusOverTime
.Where(x => DateTime.Compare(x.date, startDate) > 0)
.ToList();
List <Expert> ratings = trResponse.experts
.Where(x => DateTime.Compare(x.ratings.FirstOrDefault().date, startDate) > 0 && x.rankings.FirstOrDefault().stars > 0)
.ToList();
//find the slope of the buy and sell consensuses (net)
List <decimal> bsnYList = bsns
.Select(x => Convert.ToDecimal(x.consensus - 3 + x.buy - x.sell))
.ToList();
List <decimal> bsnXList = new List <decimal>();
int counter = 1;
foreach (decimal bsn in bsnYList)
{
bsnXList.Add(counter);
counter++;
}
decimal bsnSlope = Indicators.GetSlope(bsnXList, bsnYList);
decimal bsnSlopeMultiplier = 10.0M; //TwelveData.GetSlopeMultiplier(bsnSlope);
//find the average rating
List <decimal> ratingNums = ratings
.Select(x => Convert.ToDecimal(x.rankings.FirstOrDefault().stars))
.ToList();
decimal averageRating = ratingNums.Sum() / ratingNums.Count;
decimal priceTarget = Convert.ToDecimal(trResponse.portfolioHoldingData.priceTarget);
decimal lastPrice = Convert.ToDecimal(trResponse.prices[trResponse.prices.Length - 1].p);
decimal ratingsComposite = 0;
ratingsComposite += (averageRating / 6.0M) * 100; //Get score using the average rating as a percentage of (max rating + 1)
ratingsComposite += bsnSlope > 0 ? (bsnSlope * bsnSlopeMultiplier) + 5 : -(bsnSlope * bsnSlopeMultiplier) - 5;
ratingsComposite += priceTarget > lastPrice ? 10 : -10; //Adjust with price target
ratingsComposite = Math.Min(ratingsComposite, 100);
return(new TipRanksResult
{
Insiders = insiders,
Institutions = trResponse.hedgeFundData,
ThirdPartyRatings = ratings,
ConsensusOverTime = bsns,
InsiderComposite = 0.0M,
InstitutionalComposite = 0.0M,
RatingsComposite = ratingsComposite,
PriceTarget = priceTarget
});
}
catch (Exception e)
{
Debug.WriteLine("EXCEPTION CAUGHT: TipRanks.cs GetTipRanksResult for symbol " + symbol + ", message: " + e.Message);
return(new TipRanksResult
{
Insiders = null,
Institutions = null,
ThirdPartyRatings = null,
ConsensusOverTime = null,
InsiderComposite = 0.0M,
InstitutionalComposite = 0.0M,
RatingsComposite = 50.0M,
PriceTarget = 0.0M
});
}
}
public static ShortInterestResult GetShortInterest(string quandlResponse, int daysToCalculate)
{
decimal compositeScore = 0;
JObject response = JObject.Parse(quandlResponse);
JObject dataset = (JObject)response.GetValue("dataset");
JArray data = (JArray)dataset.GetValue("data");
int daysCalulated = 0;
int numberOfResults = 0;
HashSet <string> dates = new HashSet <string>();
Stack <decimal> shortInterestYList = new Stack <decimal>();
decimal shortInterestToday = 0;
decimal totalVolume = 0;
decimal totalVolumeShort = 0;
foreach (JArray result in data)
{
if (daysCalulated < daysToCalculate)
{
decimal shortVal = decimal.Parse(result[1].Value <string>());
decimal shortExemptVal = decimal.Parse(result[2].Value <string>());
decimal shortVolume = shortVal + shortExemptVal;
decimal volume = decimal.Parse(result[3].Value <string>());
decimal shortInterest = (shortVolume / volume) * 100;
if (numberOfResults == 0)
{
shortInterestToday = shortInterest;
}
shortInterestYList.Push(shortInterest);
totalVolume += volume;
totalVolumeShort += shortVolume;
numberOfResults++;
string shortDate = DateTime.Parse(result[0].Value <string>()).ToString("yyyy-MM-dd");
if (!dates.Contains(shortDate))
{
dates.Add(shortDate);
daysCalulated++;
}
}
else
{
break;
}
}
List <decimal> shortXList = new List <decimal>();
for (int i = 1; i <= numberOfResults; i++)
{
shortXList.Add(i);
}
List <decimal> shortYList = shortInterestYList.ToList();
decimal shortSlope = Indicators.GetSlope(shortXList, shortYList);
decimal shortSlopeMultiplier = Indicators.GetSlopeMultiplier(shortSlope);
decimal shortInterestAverage = (totalVolumeShort / totalVolume) * 100;
//Add these bonuses to account for normal short interest fluctuations
bool slightlyBearish = (0.0M <= shortSlope && shortSlope <= 0.5M);
bool moderatelyBearish = (0.5M <= shortSlope && shortSlope <= 1.0M);
//calculate composite score based on the following values and weighted multipliers
compositeScore += 100 - shortInterestAverage; //get score as 100 - short interest
compositeScore += (shortSlope < 0) ? (shortSlope * shortSlopeMultiplier) + 20 : -5;
compositeScore += (shortSlope > 0 && slightlyBearish) ? 15 : 0;
compositeScore += (shortSlope > 0 && moderatelyBearish) ? 10 : 0;
//Return ShortInterestResult
return(new ShortInterestResult
{
TotalVolume = totalVolume,
TotalVolumeShort = totalVolumeShort,
ShortInterestPercentToday = shortInterestToday,
ShortInterestPercentAverage = shortInterestAverage,
ShortInterestSlope = shortSlope,
ShortInterestCompositeScore = compositeScore
});
}
//unused for now
public static decimal GetOBVComposite(JArray resultSet, int daysToCalculate)
{
int daysCalulated = 0;
int numberOfResults = 0;
HashSet <string> dates = new HashSet <string>();
Stack <decimal> obvValueYList = new Stack <decimal>();
decimal obvSum = 0;
foreach (var result in resultSet)
{
if (daysCalulated < daysToCalculate)
{
decimal obvValue = decimal.Parse(result.Value <string>("obv"));
obvValueYList.Push(obvValue);
obvSum += obvValue;
numberOfResults++;
string resultDate = result.Value <string>("datetime");
string obvDate = DateTime.Parse(resultDate).ToString("yyyy-MM-dd");
if (!dates.Contains(obvDate))
{
dates.Add(obvDate);
daysCalulated++;
}
}
else
{
break;
}
}
List <decimal> obvXList = new List <decimal>();
for (int i = 1; i <= numberOfResults; i++)
{
obvXList.Add(i);
}
List <decimal> obvYList = obvValueYList.ToList();
decimal obvSlope = Indicators.GetSlope(obvXList, obvYList);
decimal obvSlopeMultiplier = Indicators.GetSlopeMultiplier(obvSlope);
List <decimal> zScores = Indicators.GetZScores(obvYList);
decimal zScoreSlope = Indicators.GetSlope(zScores, obvXList);
decimal zScoreSlopeMultiplier = Indicators.GetSlopeMultiplier(zScoreSlope);
List <decimal> normalizedScores = Indicators.GetNormalizedData(obvYList);
decimal normalizedSlope = Indicators.GetSlope(normalizedScores, obvXList);
decimal normalizedSlopeMultiplier = Indicators.GetSlopeMultiplier(normalizedSlope);
decimal obvAverage = obvSum / numberOfResults;
//look for buy and sell signals
bool obvHasBuySignal = false;
bool obvHasSellSignal = false;
decimal obvPrev = obvYList[0];
bool obvPrevIsNegative = obvPrev < 0;
for (int i = 1; i < obvYList.Count(); i++)
{
decimal current = obvYList[i];
bool currentIsNegative = current < 0;
if (!currentIsNegative && obvPrevIsNegative)
{
obvHasBuySignal = true;
if (obvHasSellSignal)
{
obvHasSellSignal = false; //cancel the previous sell signal if buy signal is most recent
}
}
else if (currentIsNegative && !obvPrevIsNegative)
{
obvHasSellSignal = true;
if (obvHasBuySignal)
{
obvHasBuySignal = false; //cancel the previous buy signal if sell signal is most recent
}
}
obvPrev = current;
obvPrevIsNegative = obvPrev < 0;
}
//Start with the average of the 2 most recent OBV Normalized Scores
//Only use the normalized scores if average OBV is greater than 0
decimal baseValue;
if (obvAverage > 0)
{
baseValue = ((normalizedScores[normalizedScores.Count - 1] + normalizedScores[normalizedScores.Count - 2]) / 2) * 100;
}
else
{
//ZScore bonus helps us score based on derivatives
//Only add ZScoreBonus if it is positive, divide by 4 instead of 2 (which would be classic mean)
decimal zScoreBonus = ((zScores[zScores.Count - 1] + zScores[zScores.Count - 2]) / 4) * 100;
if (zScoreBonus < 0)
{
zScoreBonus = 15; //pity points
}
baseValue = zScoreBonus;
}
//Add bonus if average OBV is greater than 0
decimal obvAverageBonus = obvAverage > 0 ? 15 : 0;
//Add bonus if OBV slope positive
decimal obvSlopeBonus = (obvSlope > 0) ? 10 : 0;
//calculate composite score based on the following values and weighted multipliers
decimal composite = 0;
composite += baseValue;
composite += obvAverageBonus;
composite += obvSlopeBonus;
composite += (zScoreSlope > 0) ? (zScoreSlope * zScoreSlopeMultiplier) : 0;
composite += (normalizedSlope > 0) ? (normalizedSlope * normalizedSlopeMultiplier) : 0;
composite += (obvHasBuySignal) ? 15 : 0;
composite += (obvHasSellSignal) ? -15 : 0;
return(Math.Min(composite, 100)); //cap OBV composite at 100, no extra weight
}
public static decimal GetMACDComposite(JArray resultSet, int daysToCalculate)
{
int daysCalulated = 0;
int numberOfResults = 0;
HashSet <string> dates = new HashSet <string>();
Stack <decimal> macdHistYList = new Stack <decimal>();
Stack <decimal> macdBaseYList = new Stack <decimal>();
Stack <decimal> macdSignalYList = new Stack <decimal>();
decimal macdTotalHist = 0;
foreach (var result in resultSet)
{
if (daysCalulated < daysToCalculate)
{
decimal macdBaseValue = decimal.Parse(result.Value <string>("macd"));
decimal macdSignalValue = decimal.Parse(result.Value <string>("macd_signal"));
decimal macdHistogramValue = decimal.Parse(result.Value <string>("macd_hist"));
macdHistYList.Push(macdHistogramValue);
macdBaseYList.Push(macdBaseValue);
macdSignalYList.Push(macdSignalValue);
macdTotalHist += macdHistogramValue;
numberOfResults++;
string resultDate = result.Value <string>("datetime");
string macdDate = DateTime.Parse(resultDate).ToString("yyyy-MM-dd");
if (!dates.Contains(macdDate))
{
dates.Add(macdDate);
daysCalulated++;
}
}
else
{
break;
}
}
List <decimal> macdXList = new List <decimal>();
for (int i = 1; i <= numberOfResults; i++)
{
macdXList.Add(i);
}
List <decimal> baseYList = macdBaseYList.ToList();
decimal baseSlope = Indicators.GetSlope(macdXList, baseYList);
List <decimal> signalYList = macdSignalYList.ToList();
decimal signalSlope = Indicators.GetSlope(macdXList, signalYList);
List <decimal> histYList = macdHistYList.ToList();
decimal histSlope = Indicators.GetSlope(macdXList, histYList);
//look for buy and sell signals
bool macdHasBuySignal = false;
bool macdHasSellSignal = false;
decimal macdPrev = histYList[0];
bool macdPrevIsNegative = macdPrev < 0;
for (int i = 1; i < histYList.Count(); i++)
{
decimal current = histYList[i];
bool currentIsNegative = current < 0;
if (!currentIsNegative && macdPrevIsNegative)
{
macdHasBuySignal = true;
}
else if (currentIsNegative && !macdPrevIsNegative)
{
macdHasSellSignal = true;
}
macdPrev = current;
macdPrevIsNegative = macdPrev < 0;
}
decimal histSlopeMultiplier = Indicators.GetSlopeMultiplier(histSlope);
decimal baseSlopeMultiplier = Indicators.GetSlopeMultiplier(baseSlope);
decimal signalSlopeMultiplier = Indicators.GetSlopeMultiplier(signalSlope);
decimal histBonus = Math.Min((macdTotalHist * 5) + 5, 20); //cap histBonus at 20
//calculate composite score based on the following values and weighted multipliers
decimal composite = 0;
composite += (histSlope > -0.05M) ? (histSlope * histSlopeMultiplier) + 25 : 0;
composite += (baseSlope > -0.05M) ? (baseSlope * baseSlopeMultiplier) + 10 : 0;
composite += (signalSlope > -0.05M) ? (signalSlope * signalSlopeMultiplier) + 10 : 0;
composite += (histBonus > 0) ? histBonus : 0; //Add histBonus if macdTotalHist is not negative
composite += (macdHasBuySignal) ? 40 : 0;
composite += (macdHasSellSignal) ? -40 : 0;
return(composite);
}
public static decimal GetAROONComposite(JArray resultSet, int daysToCalculate)
{
int daysCalulated = 0;
int numberOfResults = 0;
HashSet <string> dates = new HashSet <string>();
Stack <decimal> aroonUpYList = new Stack <decimal>();
Stack <decimal> aroonDownYList = new Stack <decimal>();
Stack <decimal> aroonOscillatorYList = new Stack <decimal>();
decimal aroonUpTotal = 0;
decimal aroonDownTotal = 0;
foreach (var result in resultSet)
{
if (daysCalulated < daysToCalculate)
{
decimal aroonUpVal = decimal.Parse(result.Value <string>("aroon_up"));
decimal aroonDownVal = decimal.Parse(result.Value <string>("aroon_down"));
aroonUpYList.Push(aroonUpVal);
aroonDownYList.Push(aroonDownVal);
aroonOscillatorYList.Push(aroonUpVal - aroonDownVal);
aroonUpTotal += aroonUpVal;
aroonDownTotal += aroonDownVal;
numberOfResults++;
string resultDate = result.Value <string>("datetime");
string aroonDate = DateTime.Parse(resultDate).ToString("yyyy-MM-dd");
if (!dates.Contains(aroonDate))
{
dates.Add(aroonDate);
daysCalulated++;
}
}
else
{
break;
}
}
List <decimal> aroonXList = new List <decimal>();
for (int i = 1; i <= numberOfResults; i++)
{
aroonXList.Add(i);
}
List <decimal> upYList = aroonUpYList.ToList();
decimal upSlope = Indicators.GetSlope(aroonXList, upYList);
List <decimal> downYList = aroonDownYList.ToList();
decimal downSlope = Indicators.GetSlope(aroonXList, downYList);
List <decimal> oscillatorYList = aroonOscillatorYList.ToList();
//decimal oscillatorSlope = GetSlope(aroonXList, oscillatorYList);
decimal upSlopeMultiplier = Indicators.GetSlopeMultiplier(upSlope);
decimal downSlopeMultiplier = Indicators.GetSlopeMultiplier(downSlope);
//decimal oscillatorSlopeMultiplier = GetSlopeMultiplier(oscillatorSlope);
//look for buy and sell signals
bool aroonHasBuySignal = false;
bool aroonHasSellSignal = false;
decimal previousOscillatorValue = oscillatorYList[0];
bool previousIsNegative = previousOscillatorValue <= 0;
for (int i = 1; i < oscillatorYList.Count(); i++)
{
decimal currentOscillatorValue = oscillatorYList[i];
bool currentIsNegative = currentOscillatorValue <= 0;
if (!currentIsNegative && previousIsNegative && (upYList[i] >= 30 && downYList[i] <= 70))
{
aroonHasBuySignal = true;
}
else if (currentIsNegative && !previousIsNegative && (upYList[i] <= 30 && downYList[i] >= 70))
{
aroonHasSellSignal = true;
}
previousOscillatorValue = currentOscillatorValue;
previousIsNegative = previousOscillatorValue <= 0;
}
decimal aroonAvgUp = Math.Max(aroonUpTotal / numberOfResults, 1.0M);
decimal aroonAvgDown = Math.Max(aroonDownTotal / numberOfResults, 1.0M);
decimal percentDiffDown = (aroonAvgDown / aroonAvgUp) * 100;
decimal percentDiffUp = (aroonAvgUp / aroonAvgDown) * 100;
decimal bullResult = Math.Min(100 - percentDiffDown, 50); //bull result caps at 50
decimal bearResult = Math.Min(percentDiffUp + 15, 20); //bear result caps at 20
//Add bull bonus if last AROON UP >= 70 per investopedia recommendation
//This is the same as when last AROON OSC >= 50
//Cap bullBonus at 15
decimal bullBonus = (aroonAvgUp > aroonAvgDown && previousOscillatorValue >= 50) ? Math.Min(previousOscillatorValue / 5, 15) : 0;
//Add bear bonus if last AROON UP > last AROON DOWN per investopedia recommendation
//This is the same as when last AROON OSC > 0
//Cap bearBonus at 10
decimal bearBonus = (aroonAvgDown > aroonAvgUp && previousOscillatorValue > 0) ? Math.Min(previousOscillatorValue / 5, 10) : 0;
//calculate composite score based on the following values and weighted multipliers
//if AROON avg up > AROON avg down, start score with 100 - (down as % of up)
//if AROON avg up < AROON avg down, start score with 100 - (up as % of down)
decimal composite = 0;
composite += (aroonAvgUp > aroonAvgDown) ? bullResult : bearResult;
composite += (bullBonus > bearBonus) ? bullBonus : bearBonus;
composite += (upSlope > -0.05M) ? (upSlope * upSlopeMultiplier) + 5 : 0;
composite += (downSlope < 0.05M) ? (downSlope * downSlopeMultiplier) + 5 : -(downSlope * downSlopeMultiplier);
composite += (aroonHasBuySignal) ? 25 : 0;
composite += (aroonHasSellSignal) ? -25 : 0;
return(composite);
}
public static decimal GetADXComposite(JArray resultSet, int daysToCalculate)
{
int daysCalulated = 0;
int numberOfResults = 0;
HashSet <string> dates = new HashSet <string>();
Stack <decimal> adxValueYList = new Stack <decimal>();
decimal adxTotal = 0;
foreach (var result in resultSet)
{
if (daysCalulated < daysToCalculate)
{
decimal adxVal = decimal.Parse(result.Value <string>("adx"));
adxValueYList.Push(adxVal);
adxTotal += adxVal;
numberOfResults++;
string resultDate = result.Value <string>("datetime");
string adxDate = DateTime.Parse(resultDate).ToString("yyyy-MM-dd");
if (!dates.Contains(adxDate))
{
dates.Add(adxDate);
daysCalulated++;
}
}
else
{
break;
}
}
List <decimal> adxXList = new List <decimal>();
for (int i = 1; i <= numberOfResults; i++)
{
adxXList.Add(i);
}
List <decimal> adxYList = adxValueYList.ToList();
decimal adxSlope = Indicators.GetSlope(adxXList, adxYList);
decimal adxSlopeMultiplier = Indicators.GetSlopeMultiplier(adxSlope);
decimal adxAvg = adxTotal / numberOfResults;
List <decimal> adxZScores = Indicators.GetZScores(adxYList);
decimal zScoreSlope = Indicators.GetSlope(adxXList, adxZScores);
decimal zScoreSlopeMultiplier = Indicators.GetSlopeMultiplier(zScoreSlope);
//Start with the average of the 2 most recent ADX values
decimal baseValue = (adxYList[adxYList.Count - 1] + adxYList[adxYList.Count - 2]) / 2;
//Add based on the most recent Z Score * 100 if it is positive
decimal recentZScore = adxZScores[adxZScores.Count - 1];
if (recentZScore > 0)
{
baseValue += (recentZScore * 100) / 2; //to even it out
}
else
{
baseValue += 10; //pity points
}
//Add bonus for ADX average above 25 per investopedia recommendation
decimal averageBonus = adxAvg > 25 ? 25 : 0;
//calculate composite score based on the following values and weighted multipliers
decimal composite = 0;
composite += baseValue;
composite += averageBonus;
composite += (adxSlope > 0.1M) ? (adxSlope * adxSlopeMultiplier) + 10 : -10; //penalty
composite += (zScoreSlope > 0.1M) ? (zScoreSlope * zScoreSlopeMultiplier) + 10 : 0;
return(Math.Min(composite, 100)); //cap ADX composite at 100, no extra weight
}
public static ShortInterestResult GetShortInterest(string symbol, IEnumerable <Skender.Stock.Indicators.Quote> history, int daysToCalculate)
{
decimal compositeScore = 0;
List <FinraRecord> shortRecords = GetShortVolume(symbol, history, daysToCalculate);
int daysCalulated = 0;
int numberOfResults = 0;
HashSet <string> dates = new HashSet <string>();
Stack <decimal> shortInterestYList = new Stack <decimal>();
decimal shortInterestToday = 0;
decimal totalVolume = 0;
decimal totalVolumeShort = 0;
foreach (FinraRecord shortRecord in shortRecords)
{
if (daysCalulated < daysToCalculate)
{
decimal shortVolume = shortRecord.ShortVolume + shortRecord.ShortExemptVolume;
decimal shortInterest = (shortVolume / shortRecord.TotalVolume) * 100;
if (numberOfResults == 0)
{
shortInterestToday = shortInterest;
}
shortInterestYList.Push(shortInterest);
totalVolume += shortRecord.TotalVolume;
totalVolumeShort += shortVolume;
numberOfResults++;
string shortDate = shortRecord.Date.ToString("yyyy-MM-dd");
if (!dates.Contains(shortDate))
{
dates.Add(shortDate);
daysCalulated++;
}
}
else
{
break;
}
}
List <decimal> shortXList = new List <decimal>();
for (int i = 1; i <= numberOfResults; i++)
{
shortXList.Add(i);
}
List <decimal> shortYList = shortInterestYList.ToList();
decimal shortSlope = shortYList.Count > 0 ? Indicators.GetSlope(shortXList, shortYList) : 0.0M; //set to 0 if not found
decimal shortSlopeMultiplier = Indicators.GetSlopeMultiplier(shortSlope);
decimal shortInterestAverage = totalVolume > 0 ? (totalVolumeShort / totalVolume) * 100 : 30.0M; //set to 30 if not found
//Add these bonuses to account for normal short interest fluctuations
//The slope cannot be in both ranges if the ranges do not overlap
//This prevents adding both bonuses
bool slightlyBearish = (SlightlyBearishLowerBound <= shortSlope && shortSlope <= SlightlyBearishUpperBound);
bool moderatelyBearish = (ModeratelyBearishLowerBound <= shortSlope && shortSlope <= ModeratelyBearishUpperBound);
//calculate composite score based on the following values and weighted multipliers
compositeScore += 100 - shortInterestAverage; //get base score as 100 - short interest
compositeScore += (shortSlope < 0) ? (shortSlope * shortSlopeMultiplier) + 10 : -15;
compositeScore += (shortSlope > 0 && slightlyBearish) ? 10 : 0;
compositeScore += (shortSlope > 0 && moderatelyBearish) ? 5 : 0;
//Cap this compositeScore at 100 because we should not give it extra weight
compositeScore = Math.Min(compositeScore, 100);
//Return ShortInterestResult
return(new ShortInterestResult
{
TotalVolume = totalVolume,
TotalVolumeShort = totalVolumeShort,
ShortInterestPercentToday = shortInterestToday,
ShortInterestPercentAverage = shortInterestAverage,
ShortInterestSlope = shortSlope,
ShortInterestCompositeScore = compositeScore
});
}
