Get Statistics

Retrieve aggregate performance statistics for signals within a specified date range.

Endpoint

GET https://enterprise.guardis.io/v1/signals/statistics

Authentication

Include your API key in the X-API-Key header.

X-API-Key: your_api_key_here

---

Query Parameters

Parameter	Type	Required	Description
from_date	string	Yes	Start of the date range (ISO 8601 format)
to_date	string	No	End of the date range (ISO 8601 format). Defaults to current time if omitted
model_name	string	No	Filter by model name. If omitted, statistics are calculated across all models

---

Example Request

curl -X GET "https://enterprise.guardis.io/v1/signals/statistics?from_date=2025-12-01T00:00:00Z&to_date=2025-12-07T23:59:59Z" \
  -H "X-API-Key: your_api_key_here"

---

Response Format

{
  "from_date": "2025-12-01T00:00:00Z",
  "to_date": "2025-12-07T23:59:59Z",
  "model_name": null,
  "total_signals": 284,
  "roi_statistics": {
    "avg_max_roi": "142.847291635",
    "median_max_roi": "118.293847291",
    "min_roi": "-12.847291635",
    "max_roi": "847.291635000",
    "std_dev_roi": "89.472918473"
  },
  "drawdown_statistics": {
    "avg_drawdown_before_ath": "8.472918473",
    "median_drawdown_before_ath": "5.293847291",
    "min_drawdown": "0.000000000",
    "max_drawdown": "42.847291635",
    "std_dev_drawdown": "7.293847291"
  },
  "market_cap_statistics": {
    "avg_signal_market_cap": "38472.918473650",
    "median_signal_market_cap": "32847.291847365",
    "avg_ath_market_cap": "94728.184736500",
    "median_ath_market_cap": "78472.918473650"
  },
  "liquidity_statistics": {
    "avg_liquidity_usd": "24847.291847365",
    "median_liquidity_usd": "21293.847291847"
  },
  "model_breakdown": [
    {
      "model_name": "influx_high_on_dip",
      "signal_count": 156,
      "avg_max_roi": "158.472918473",
      "median_max_roi": "132.847291847",
      "avg_drawdown_before_ath": "6.847291847"
    },
    {
      "model_name": "smart_money_surge",
      "signal_count": 89,
      "avg_max_roi": "124.293847291",
      "median_max_roi": "98.472918473",
      "avg_drawdown_before_ath": "10.293847291"
    },
    {
      "model_name": "organic_momentum",
      "signal_count": 39,
      "avg_max_roi": "118.847291635",
      "median_max_roi": "102.293847291",
      "avg_drawdown_before_ath": "11.472918473"
    }
  ],
  "daily_breakdown": [
    {
      "date": "2025-12-07",
      "signal_count": 42,
      "avg_max_roi": "148.293847291"
    },
    {
      "date": "2025-12-06",
      "signal_count": 38,
      "avg_max_roi": "139.472918473"
    },
    {
      "date": "2025-12-05",
      "signal_count": 45,
      "avg_max_roi": "152.847291635"
    }
  ]
}

---

Field Reference

Response Wrapper

Field	Type	Description
from_date	string	Start of the requested date range
to_date	string	End of the requested date range
model_name	string | null	Model filter applied, or null if all models
total_signals	integer	Total number of signals in the date range

ROI Statistics

Field	Type	Description
avg_max_roi	string	Average maximum ROI percentage across all signals
median_max_roi	string	Median maximum ROI percentage
min_roi	string	Lowest ROI percentage observed
max_roi	string	Highest ROI percentage observed
std_dev_roi	string	Standard deviation of ROI percentages

Drawdown Statistics

Field	Type	Description
avg_drawdown_before_ath	string	Average maximum drawdown before reaching ATH
median_drawdown_before_ath	string	Median maximum drawdown before ATH
min_drawdown	string	Lowest drawdown percentage observed
max_drawdown	string	Highest drawdown percentage observed
std_dev_drawdown	string	Standard deviation of drawdown percentages

Market Cap Statistics

Field	Type	Description
avg_signal_market_cap	string	Average market cap at signal time (USD)
median_signal_market_cap	string	Median market cap at signal time (USD)
avg_ath_market_cap	string	Average ATH market cap (USD)
median_ath_market_cap	string	Median ATH market cap (USD)

Liquidity Statistics

Field	Type	Description
avg_liquidity_usd	string	Average pool liquidity at signal time (USD)
median_liquidity_usd	string	Median pool liquidity at signal time (USD)

Model Breakdown

Field	Type	Description
model_name	string	Name of the signal model
signal_count	integer	Number of signals from this model
avg_max_roi	string	Average maximum ROI for this model
median_max_roi	string	Median maximum ROI for this model
avg_drawdown_before_ath	string	Average drawdown before ATH for this model

Daily Breakdown

Field	Type	Description
date	string	Date (YYYY-MM-DD format)
signal_count	integer	Number of signals on this date
avg_max_roi	string	Average maximum ROI for signals on this date

Note: Decimal values are returned as strings to preserve precision.

---

Example Usage

JavaScript:

const params = new URLSearchParams({
  from_date: "2025-12-01T00:00:00Z",
  to_date: "2025-12-07T23:59:59Z"
});

const response = await fetch(
  `https://enterprise.guardis.io/v1/signals/statistics?${params}`,
  {
    headers: {
      "X-API-Key": "your_api_key_here"
    }
  }
);

const stats = await response.json();

console.log(`Signal Statistics (${stats.from_date} to ${stats.to_date})`);
console.log(`Total Signals: ${stats.total_signals}`);
console.log(`\nROI Performance:`);
console.log(`  Average: ${parseFloat(stats.roi_statistics.avg_max_roi).toFixed(2)}%`);
console.log(`  Median: ${parseFloat(stats.roi_statistics.median_max_roi).toFixed(2)}%`);
console.log(`  Best: ${parseFloat(stats.roi_statistics.max_roi).toFixed(2)}%`);
console.log(`\nDrawdown:`);
console.log(`  Average: ${parseFloat(stats.drawdown_statistics.avg_drawdown_before_ath).toFixed(2)}%`);
console.log(`  Median: ${parseFloat(stats.drawdown_statistics.median_drawdown_before_ath).toFixed(2)}%`);

console.log(`\nModel Breakdown:`);
for (const model of stats.model_breakdown) {
  console.log(`  ${model.model_name}: ${model.signal_count} signals, ${parseFloat(model.avg_max_roi).toFixed(2)}% avg ROI`);
}

Python:

import requests

response = requests.get(
    "https://enterprise.guardis.io/v1/signals/statistics",
    params={
        "from_date": "2025-12-01T00:00:00Z",
        "to_date": "2025-12-07T23:59:59Z"
    },
    headers={"X-API-Key": "your_api_key_here"}
)

stats = response.json()

print(f"Signal Statistics ({stats['from_date']} to {stats['to_date']})")
print(f"Total Signals: {stats['total_signals']}")

print("\nROI Performance:")
print(f"  Average: {float(stats['roi_statistics']['avg_max_roi']):.2f}%")
print(f"  Median: {float(stats['roi_statistics']['median_max_roi']):.2f}%")
print(f"  Best: {float(stats['roi_statistics']['max_roi']):.2f}%")

print("\nDrawdown:")
print(f"  Average: {float(stats['drawdown_statistics']['avg_drawdown_before_ath']):.2f}%")
print(f"  Median: {float(stats['drawdown_statistics']['median_drawdown_before_ath']):.2f}%")

print("\nModel Breakdown:")
for model in stats["model_breakdown"]:
    avg_roi = float(model["avg_max_roi"])
    print(f"  {model['model_name']}: {model['signal_count']} signals, {avg_roi:.2f}% avg ROI")

---

Error Responses

Status Code	Description
400	Missing required parameter or invalid format
401	Missing or invalid API key
422	Invalid date format or date range
500	Internal server error

{
  "code": 400,
  "message": "Missing required parameter: from_date"
}

{
  "code": 422,
  "message": "Invalid date format. Use ISO 8601 format (e.g., 2025-12-01T00:00:00Z)"
}

{
  "code": 422,
  "message": "Date range too large. Maximum allowed range is 90 days"
}