QuanTAlib/docs/readme.md

# QuanTAlib - quantitative technical indicators for Quantower and other C#-based trading platorms

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Quantitative TA Library (**QuanTAlib**) is an easy-to-use C# library for quantitative technical analysis with base algorithms, charts, signals and strategies useful for trading securities with [Quantower](https://www.quantower.com/) and other C#-based trading platforms.

**QuanTAlib** is written with some specific design criteria in mind - some reasons why there is '_yet another C# TA library_':

- Written in native C# - no code conversion from TA-LIB or other imported/converted TA libraries
- No usage of Decimal datatypes, LINQ, interface abstractions, or static classes with tons of methods (all for performance reasons)
- Supports both **historical data analysis** (working on bulk of historical arrays) and **real-time analysis** (adding one data item at the time without the need to re-calculate the whole history)
- Calculate early data right - no hiding of incomplete calculations with NaN values (unless explicitly requested with useNan: true), data is as valid as mathematically possible from the first value
- Usage of events - each data series is an event publisher, each indicator is a subscriber - this allows seamless data flow between indicators)
- Seamlessly integrates with **Polyglot notebooks** (.NET Interactive) and used in Jupyter notebooks - see the examples and documentation.

QuanTAlib does not focus on sources of OHLCV quotes. There are some basic data feeds available to use in learning and strategy exploration: `RND_Feed` and `GBM_Feed` for random data feed, `Yahoo_Feed` and `Alphavantage_Feed` for quick grab of basic daily data of US stock market.

See [Getting Started](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/getting_started.ipynb) .NET interactive notebook to get a feel how library works. Developers can use QuanTAlib in .NET interactive or in console apps, but the best usage of the library is withing C#-enabled trading platforms - see **QuanTower_Charts** folder for Quantower examples.

## Coverage

⭐= Calculation is validated against other TA libraries

✔️= Calculation exists but has no cross-validation tests

⛔= Not implemented (yet)

| **BASIC TRANSFORMS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
|--|:--:|:--:|:--:|:--:|
| ⭐ OC2 - (Open+Close)/2 |️ `.OC2` || CandlePart.OC2 ||
| ⭐ HL2 - Median Price | `.HL2` | MEDPRICE | CandlePart.HL2 ||
| ⭐ HLC3 - Typical Price | `.HLC3` | TYPPRICE | CandlePart.HLC3 ||
| ⭐ OHL3 - (Open+High+Low)/3 | `.OHL3` || CandlePart.OHL3 ||
| ⭐ OHLC4 - Average Price | `.OHLC4` | AVGPRICE |️ CandlePart.OHLC4 ||
| ⭐ HLCC4 - Weighted Price |  `.HLCC4` | WCLPRICE | CandlePart.HLCC4 ||
| ⭐ MIDPOINT - Midpoint value | `MIDPOINT_Series` | MIDPOINT |||
| ⭐ MIDPRICE - Midpoint price | `MIDPRICE_Series` | MIDPRICE |||
| ⭐ MAX - Max value | `MAX_Series` | MAX |||
| ⭐ MIN - Min value | `MIN_Series` | MIN |||
| ⭐ SUM - Summation | `SUM_Series` | SUM |||
| ⭐ ADD - Addition | `ADD_Series` | ADD |||
| ⭐ SUB - Subtraction | `SUB_Series` | SUB |||
| ⭐ MUL - Multiplication | `MUL_Series` | MUL |||
| ⭐ DIV - Division | `DIV_Series` | DIV |||
|||||
| **STATISTICS & NUMERICAL ANALYSIS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
| ⭐ BIAS - Bias | `BIAS_Series` ||| bias |
| ⛔ CORREL - Pearson's Correlation Coefficient || CORREL | GetCorrelation ||
| ⛔ COVAR - Covariance ||| GetCorrelation ||
| ⭐ ENTP - Entropy | `ENTP_Series` ||| entropy |
| ⭐ KURT - Kurtosis | `KURT_Series` ||| kurtosis |
| ⭐ LINREG - Linear Regression | `LINREG_Series` || GetSlope ||
| ⭐ MAD - Mean Absolute Deviation | `MAD_Series` || GetSma | mad |
| ⭐ MAPE - Mean Absolute Percent Error | `MAPE_Series` || GetSma ||
| ⭐ MED - Median value | `MED_Series` ||| median |
| ✔️ MSE - Mean Squared Error | `MSE_Series` || GetSma ||
| ⛔ SKEW - Skewness |||||
| ⭐ SDEV - Standard Deviation (Volatility) | `SDEV_Series` | STDDEV |||
| ✔️ SSDEV - Sample Standard Deviation | `SSDEV_Series` ||||
| ✔️ SMAPE - Symmetric Mean Absolute Percent Error | `SMAPE_Series` ||||
| ⭐ VAR - Population Variance | `VAR_Series` | VAR || variance |
| ⭐ SVAR - Sample Variance | `SVAR_Series` ||| variance |
| ⛔ QUANT - Quantile |||||
| ✔️ WMAPE - Weighted Mean Absolute Percent Error | `WMAPE_Series` ||||
| ⛔ ZSCORE - Number of standard deviations from mean |||||
||||||
| **TREND INDICATORS & AVERAGES** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
| ⛔ AFIRMA - Autoregressive Finite Impulse Response Moving Average |||||
| ⭐ ALMA - Arnaud Legoux Moving Average | `ALMA_Series` || GetAlma ||
| ⛔ ARIMA - Autoregressive Integrated Moving Average |||||
| ⭐ DEMA - Double EMA Average | `DEMA_Series` | DEMA | GetDema | dema |
| ⭐ EMA - Exponential Moving Average | `EMA_Series` || GetEma | ema |
| ⛔ EPMA - Endpoint Moving Average ||| GetEpma ||
| ⛔ FRAMA - Fractal Adaptive Moving Average |||||
| ⛔ FWMA - Fibonacci's Weighted Moving Average |||||
| ⛔ HILO - Gann High-Low Activator |||||
| ✔️ HEMA - Hull/EMA Average | `HEMA_Series` ||||
| ⛔ Hilbert Transform Instantaneous Trendline || HT_TRENDLINE | GetHtTrendline ||
| ⭐ HMA - Hull  Moving Average | `HMA_Series` || GetHma | hma |
| ⛔ HWMA - Holt-Winter Moving Average |||||
| ✔️ JMA - Jurik Moving Average | `JMA_Series` ||||
| ⭐ KAMA - Kaufman's Adaptive Moving Average | `KAMA_Series` | KAMA | GetKama | kama |
| ⛔ KDJ - KDJ Indicator (trend reversal) |||||
| ⛔ LSMA - Least Squares Moving Average |||||
| ⭐ MACD - Moving Average Convergence/Divergence | `MACD_Series` | MACD | GetMacd ||
| ⛔ MAMA - MESA Adaptive Moving Average || MAMA | GetMama ||
| ⛔ MCGD - McGinley Dynamic |||||
| ⛔ MMA - Modified Moving Average |||||
| ⛔ PPMA - Pivot Point Moving Average |||||
| ⛔ PWMA - Pascal's Weighted Moving Average |||||
| ⭐ RMA - WildeR's Moving Average | `RMA_Series` ||| rma |
| ⛔ SINWMA - Sine Weighted Moving Average |||||
| ⭐ SMA - Simple Moving Average | `SMA_Series` | SMA | GetSma | sma |
| ⭐ SMMA - Smoothed Moving Average | `SMMA_Series` || GetSmma ||
| ⛔ SSF - Ehler's Super Smoother Filter |||||
| ⛔ SUP - Supertrend |||||
| ⛔ SWMA - Symmetric Weighted Moving Average |||||
| ⛔ T3 - Tillson T3 Moving Average || T3 | GetT3 ||
| ⭐ TEMA - Triple EMA Average | `TEMA_Series` | TEMA | GetTema | tema |
| ⭐ TRIMA - Triangular Moving Average | `TRIMA_Series` | TRIMA |||
| ⛔ TSF - Time Series Forecast || TSF |||
| ⛔ VIDYA - Variable Index Dynamic Average |||||
| ⛔ VOR - Vortex Indicator |||||
| ⭐ WMA - Weighted Moving Average | `WMA_Series` | WMA | GetWma | wma |
| ⭐ ZLEMA - Zero Lag EMA Average | `ZLEMA_Series` ||| zlma |
||||||
| **VOLATILITY INDICATORS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
| ⭐ ADL - Chaikin Accumulation Distribution Line | `ADL_Series` | AD | GetAdl | ad |
| ⭐ ADOSC - Chaikin Accumulation Distribution Oscillator | `ADOSC_Series` | ADOSC| GetAdl | adosc |
| ⭐ ATR - Average True Range | `ATR_Series` | ATR | GetAtr | atr |
| ⭐ ATRP - Average True Range Percent | `ATRP_Series` || GetAtr ||
| ⛔ BETA - Beta coefficient || BETA | GetBeta ||
| ⭐ BBANDS - Bollinger Bands® | `BBANDS_Series` | BBANDS | GetBollingerBands ||
| ⛔ CHAND - Chandelier Exit ||| GetChandelier ||
| ⛔ CRSI - Connor RSI ||| GetConnorsRsi ||
| ⛔ DON - Donchian Channels ||| GetDonchian ||
| ⛔ FCB - Fractal Chaos Bands ||| GetFcb ||
| ⛔ HV - Historical Volatility |||||
| ⛔ ICH - Ichimoku ||| GetIchimoku ||
| ⛔ KEL - Keltner Channels ||| GetKeltner ||
| ⛔ NATR - Normalized Average True Range || NATR | GetAtr ||
| ⛔ CHN - Price Channel Indicator |||||
| ⭐ RSI - Relative Strength Index | `RSI_Series` | RSI | GetRsi | rsi |
| ⛔ SAR - Parabolic Stop and Reverse || SAR | GetParabolicSar ||
| ⛔ SRSI - Stochastic RSI || STOCHRSI | GetStochRsi ||
| ⛔ STARC - Starc Bands |||||
| ⭐ TR - True Range | `TR_Series` | TRANGE | GetTr | true_range |
| ⛔ UI - Ulcer Index |||||
| ⛔ VSTOP - Volatility Stop |||||
||||||
| **MOMENTUM INDICATORS & OSCILLATORS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
| ⛔ AC - Acceleration Oscillator |||||
| ⛔ ADX - Average Directional Movement Index || ADX | GetAdx ||
| ⛔ ADXR - Average Directional Movement Index Rating || ADXR | GetAdx ||
| ⛔ AO - Awesome Oscillator ||| GetAwesome ||
| ⛔ APO - Absolute Price Oscillator || APO |||
| ⛔ AROON - Aroon oscillator || AROON | GetAroon ||
| ⛔ BOP - Balance of Power || BOP | GetBop ||
| ⭐ CCI - Commodity Channel Index | `CCI_Series` | CCI | GetCci ||
| ⛔ CFO - Chande Forcast Oscillator |||||
| ⛔ CMO - Chande Momentum Oscillator || CMO | GetCmo ||
| ⛔ COG - Center of Gravity |||||
| ⛔ COPPOCK - Coppock Curve |||||
| ⛔ CTI - Ehler's Correlation Trend Indicator |||||
| ⛔ DPO - Detrended Price Oscillator ||| GetDpo ||
| ⛔ DMI - Directional Movement Index || DX | GetAdx ||
| ⛔ EFI - Elder Ray's Force Index ||| GetElderRay ||
| ⛔ GAT - Alligator oscillator ||| GetGator ||
| ⛔ HURST - Hurst Exponent ||| GetHurst ||
| ⛔ KRI - Kairi Relative Index |||||
| ⛔ KVO - Klinger Volume Oscillator |||||
| ⛔ MFI - Money Flow Index || MFI | GetMfi ||
| ⛔ MOM - Momentum || MOM |||
| ⛔ NVI - Negative Volume Index |||||
| ⛔ PO - Price Oscillator |||||
| ⛔ PPO - Percentage Price Oscillator || PPO |||
| ⛔ PMO - Price Momentum Oscillator |||||
| ⛔ PVI - Positive Volume Index |||||
| ⛔ ROC - Rate of Change || MOM | GetRoc ||
| ⛔ RVGI - Relative Vigor Index |||||
| ⛔ SMI - Stochastic Momentum Index |||||
| ⛔ STC - Schaff Trend Cycle |||||
| ⛔ STOCH - Stochastic Oscillator || STOCH | GetStoch ||
| ⛔ TRIX - 1-day ROC of TEMA || TRIX | GetTrix ||
| ⛔ TSI - True Strength Index |||||
| ⛔ UO - Ultimate Oscillator || ULTOSC | GetUltimate ||
| ⛔ WILLR - Larry Williams' %R || WILLR | GetWilliamsR ||
| ⛔ WGAT - Williams Alligator |||||
||||||
| **VOLUME INDICATORS** | **QuanTAlib** | **TA-LIB** | **Skender** | **Pandas TA** |
| ⛔ AOBV - Archer On-Balance Volume |||||
| ⛔ CMF - Chaikin Money Flow |||||
| ⛔ EOM - Ease of Movement |||||
| ⭐ OBV - On-Balance Volume | `OBV_Series` | OBV | GetObv ||
| ⛔ PRS - Price Relative Strength ||||
| ⛔ PVOL - Price-Volume |||||
| ⛔ PVO - Percentage Volume Oscillator |||||
| ⛔ PVR - Price Volume Rank |||||
| ⛔ PVT - Price Volume Trend |||||
| ⛔ VP - Volume Profile |||||
| ⛔ VWAP - Volume Weighted Average Price |||||
| ⛔ VWMA - Volume Weighted Moving Average |||||