Request URL

https://predict7.p.rapidapi.com/

Request Method

POST

Request Body

The predict API requires a JSON object in the request body. This JSON object must contains the following inputs:

The quantile function of a probability distribution is the inverse of the cumulative distribution function:
→ Q(x) = F^-1(x) = inf{y: x ≤ F(y)} where F(x) = P(X ≤ x)

Here is an example request body:

{
    "data": [518.4, 559.9, 553.19, 524.57, 567.65, 531.75, 576.45, 514.42],
    "horizon": 5,
    "cls": [0.2, 0.5, 0.8, 1]
}

Code Snippets

Here’s an example Python code snippet using the requests library to make a request to the predict API:

import requests

url = "https://predict7.p.rapidapi.com/"

headers = {
    "X-RapidAPI-Key": "your_api_key_here",
    "X-RapidAPI-Host": "predict7.p.rapidapi.com",
    "Content-Type": "application/json"
}

payload = {
    "data": [518.4, 559.9, 553.19, 524.57, 567.65, 531.75, 576.45, 514.42],
    "horizon": 5,
    "cls": [0.2, 0.5, 0.8, 1]
}

response = requests.post(url, headers=headers, json=payload)
print(response.json())

Response

The predict API returns a JSON object in the response body. The JSON object has keys that correspond to the quantiles at confidence levels specified as input.

Here’s an example response body:

{
    "0.2": 435.0025226384971,
    "0.5": 517.4767502538812,
    "0.8": 614.0210958892659,
    "1.0": 953.7644640393268
}

Practical example

Here’s an example code in Python to retrieve quartiles of the 30-day apple stock projection, using 10-year daily history:

import requests
import yfinance as yf

data_df = yf.download("AAPL", start="2012-12-31", end="2022-12-31", interval="1d", progress=False)
data = data_df["Close"].tolist()

horizon = 30
cls = [0.25, 0.5, 0.75]
payload = {
    "data": data,
    "horizon": horizon, 
    "cls": cls
}

print("The number of values in the historical data set is:", len(data))
print("The last value which would be projected is:", data[-1])

url = "https://predict7.p.rapidapi.com/"
headers = {
    "X-RapidAPI-Key": "your_api_key_here",
    "X-RapidAPI-Host": "predict7.p.rapidapi.com",
    "Content-Type": "application/json"
}

response = requests.request("POST", url, json=payload, headers=headers)
quantiles = response.json()["quantiles"]

print(f'The 3 quartiles at horizon {horizon} days are:', [q for cl, q in quantiles.items()])

Here is the result:

The number of values in the historical data set is: 2519
The last value which would be projected is: 129.92999267578125
The 3 quartiles at horizon 30 days are: [124.61287199924642, 133.19434735827977, 142.13910859087554]