technicalindicators | javascript technical indicators written in typescript | Cryptocurrency library
kandi X-RAY | technicalindicators Summary
kandi X-RAY | technicalindicators Summary
A javascript technical indicators written in typescript.
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Top functions reviewed by kandi - BETA
- Run the build
- Return the available list of available sensors
- Load a model from the initializer .
- Returns the fibonacci retracements of a given start point .
- Interpolate the array into the array
- Reverse digital inputs
- Decode a pattern detector .
- Re - reverse indicator
- overlaginator .
- starts the wild - ghost phantom
technicalindicators Key Features
technicalindicators Examples and Code Snippets
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QUESTION
I have tried to use Technical Indicators library to calculate RSI
(and ROC
) for candlestick's closing prices, but when I compare results from Binance, I am not getting quite accurate results:
I fetch data using this Binance API:
This is example of usage for RSI and ROC indicators:
If I do this:
...ANSWER
Answered 2022-Mar-25 at 21:17( better: When do we get equal outputs on screen ? )
RSI is one of several indicators that include an element of prior data. As such a 14 day RSI based on 15 days or 50 days of underlying data will be significantly different to a 14 day RSI based on 500 days of data.
So, unless all TimeSeries' "observers" compute RSI from (a) the exactly the same TimeSeries and (b) using the very same "length" ( for depth-of-prior DATA dependent underlying computing, here starting with a plain SMA for the very first "observed" period-length bars ) and (c) using the very same numerical properties of computing methods ( having almost all platforms using the same 64-bit IEEE-754 numerical processing, this need not cause problems, using hybrid FPGA/GPGPU/SoC/ASIC algos yet may introduce this class of further incoherencies (causing new breed of differences in results) ),
so,
there is the highest chance to meet both (a) & (b) & (c) if and only if we all start from the very "beginning" of the DATA in the TimeSeries-history ( easy if we all use the same source of data, not so easy, if some use time-zone uncorrected, different history-depths from different (T)OHLC(V)-data sources ) and using the same numerical processing methods.
Some technical-indicators are less susceptible to depth-of-observation, some more ( if this is a core problem ( for sake of shaving latency off / increasing performance / maintaining Quant-models' reproducibility & repeatability of results ),
try to set your "Accuracy" threshold and test all technical-indicators' dependence on the depth-of-prior DATA ( so as the convergence starts to meet your "Accuracy" threshold, making no sense to extend the depth further, if results started to converge and remain stable irrespective of any further extended depth-of-prior DATA re-processing )
In cases, where you happen to reach such "short enough" depth-of-prior DATA, you need not re-process a single bar deeper into past. Not so in all other cases, where DATA-depth dependence cannot be avoided. Pity, there we all need to take the same depth (often the maximum one, see above), if we want to get the same result(s).
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