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Model Overview

This API uses a neuro-symbolic approach to analyse high-frequency tick data, identifying patterns to predict future market trends. Its modular base architecture enables efficient fine-tuning across different time horizons, significantly reducing model development time.

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Supported Markets

Bonds

Commodities

Cryptocurrencies

Derivatives

Equities

Foreign Exchange

Indices

REITs

Tokenised Assets

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Base URL

 https://www.sumtyme.com/shared

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Request Endpoint

POST /auth/ti-tick

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Model Details

Mandatory Time Periods

1 - 501

Optional Time Periods

502 - 3000

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Request Header

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Content-Type
string
required

Must be set to application/json

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Api-Key
string
required

The API key used to authenticate requests to the API

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Request Body

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Timestamp
list
required
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Price
list
required

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Response Fields

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timestamp
string

Trade opportunity timestamp

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trend_identified
string

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Request Example

When forecasting future price trends, a future date must be specified (e.g. Jan 2nd at 11:28:00) and unknown values be filled with zeros (0):

{
    'Timestamp': ["2025-01-01 09:32:00.352", "2025-01-01 09:32:00:478",..., "2025-01-02 11:28:00.000"],
    'Price': [194.33, 195.19, ..., 0]         # Unknown future value
}

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Example - API Request


# Import necessary libraries
import pandas as pd
import requests
import json

# Define function to create json for API 
def tick_data_dict(df):
    # Convert DataFrame to dictionary format
    return {
        "Timestamp": df['Timestamp'].tolist(),
        "Price": df['Price'].tolist()
    }

# Import Data
df = pd.read_csv("")[['Timestamp','Price']]

# Create JSON payload for API request
data = tick_data_dict(df)

# Specify Base URL & API KEY
BASE_URL = ""
API_KEY = ""

# Set API endpoint URL
api_url = f"{BASE_URL}/auth/ti-tick"

# Set header for API request
headers = {"Api-Key": f"{API_KEY}", 'Content-Type': 'application/json'}

# Send POST request to API
response = requests.post(api_url, json=data, headers=headers)

data = json.loads(response.text)

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Example - API Response

{

"2025-01-01 09:32:00.352": {
      "trend_identified": null
    },
    
"2025-01-01 09:32:00:478": {
      "trend_identified": null
    },

...

"2025-01-02 11:28:03.733": {
      "trend_identified": "1"
    }

}
Reset PasswordTime Series Data