Technical Indicator¶

Overview¶

Build the technical indicator dataset for OHLCV per fetch component

Specification:

Calculated on the flight
Reduced the time that serialization dataset
Supported over 200 indicators

Design¶

Technical Component¶

Endpoint¶

There are 3 endpoints

Endpoint: `/quote/technical/indicator`¶

Method: GET

Has authenticated: Yes

Params:

Param	Type	Description
ticker	required, string	Ticker for calculated the dataset
from_date	datetime	Datetime in ISO8601 format
to_date	datetime	Datetime in ISO8601 format
function	list[str]	The targeted functions of technical indicators to fetch

Note: to_date >= from_date

Example:

/quote/technical/indicator?ticker=AAA&function=SMA
        &argument=value&from_date=20231007&to_date=2023111
        |
        |__> If not exist, override by the default configuration()

Endpoint: `/reference/technical/indicator`¶

Method: GET

Has authenticated: Yes

Source: https://ta-lib.org/functions/

Schema:

Column	Type	Description
code	string	The code in upper case
description	string	The description of related function method

Returned:

Params:

Param	Type	Description
code	string	The code to search
keyword	string	The keyword can search on code or description

/reference/technical/indicator?code=SMA
/reference/technical/indicator?keyword=SMA

Transfer to component¶

Table: quote_technical

Schema:

Column	Type	Description
ticker	string	The ticker component
ts	timestamp	The datetime component in float mode
open	float	The open price
high	float	The high price
low	float	The low price
close	float	The close price
volume	float	The volume price

Design for small fetch the dataset component

Note: Inherit from fact_ohlcv_eod

Flow for calculation the design dataset¶

Flow to calculated the functional component dataset

flowchart LR

  %% Component
  params[Handle parameters]
  query[Query ticker quote with OHCLV\nwith full period]

  %% Flow
  params -- transfer --> query -- calculate --> on_the_flight

For code flow:

[0] Design mapping function

mapping_function: dict[str, Callable] = {
    "SMA": talib.sma(**args),
    "AD": tablib.build_ad,
}

[1] Query OHLCV (ticker) for full-period (event exists from_date and to_date)

For handle params:
Upper all case of functional

[2] Based on function list of user query, use mapping_function to fetch the callable to calculate the dataset

Parse related argument on Talib with supported function

Example: SMA | OBV | VMA | CCI | Momentum | RSI

Note: This package come with C && numpy a

Using related talib function to calculated
Append to output dataset

[3] Filter on default component if available. E.g. filter by datetime

[4] Return with JSONResponse model instead using pydantic model because the different on calculated functions results

ticker, date, close -> SMA
ticker, date, close -> function: AD, upper_case, lower_case, ...

Note: Not returned the OHLCV element, just returned the calculated component

[1] Build dataset on marts at quote_technical on Lakeprep

[2] Schedule transfer into quote_technical on Spectrum

Source Reference¶

[1] C++ implement with TaLib at Official TALib documentation