Finance

QMetrics: Financial Behavior Insights and Optimization

Analyze quantum bitstring probabilities and provide optimization recommendations for financial advisors using AI-driven insights.

POSThttps://q.idefi.ai/qmetrics/translate

Body

application/json

Input wallet address and configuration for quantum insights and financial optimization.

walletAddress*string

Client's Ethereum wallet address for analysis.

Example: "0xabcdef1234567890abcdef1234567890abcdef12"

chainsarray of string

List of blockchain networks to query for wallet insights.

tokenMapobject

Mapping of chain names to CoinGecko token IDs for price data.

quantumBackendenum

Quantum backend to use ('aer' for local simulation, 'ibm' for IBM runtime).

Example: "aer"

aeribm

shotsinteger

Number of shots for quantum simulation (higher for more precise results).

Example: 1024

Response

200400401

Successful analysis of quantum bitstring probabilities with AI-driven optimization insights.

Body

application/json

wallet_addressstring

Client wallet address.

Example: "0xabcdef1234567890abcdef1234567890abcdef12"

quantum_backendstring

Quantum backend used for the analysis.

Example: "aer"

total_balance_usdnumber

Total portfolio value across specified blockchains in USD.

Example: 15000.32

quantum_resultsobject

Quantum metrics analysis.

Request

JavaScriptCurlPythonHTTP

const response = await fetch('https://q.idefi.ai/qmetrics/translate', {
    method: 'POST',
    headers: {
      "Content-Type": "application/json"
    },
    body: JSON.stringify({
      "walletAddress": "0xabcdef1234567890abcdef1234567890abcdef12"
    }),
});
const data = await response.json();

Response

200400401

{
  "wallet_address": "0xabcdef1234567890abcdef1234567890abcdef12",
  "quantum_backend": "aer",
  "total_balance_usd": 15000.32,
  "quantum_results": {
    "probabilities": {
      "100": 0.1,
      "101": 0.05,
      "110": 0.03,
      "111": 0.02,
      "000": 0.35,
      "001": 0.2,
      "010": 0.15,
      "011": 0.1
    },
    "mapped_results": {
      "100": {
        "probability": 0.1,
        "behavior": "Client prefers income-generating assets like dividend ETFs."
      },
      "101": {
        "probability": 0.05,
        "behavior": "Client increased cash reserves to reduce exposure."
      },
      "110": {
        "probability": 0.03,
        "behavior": "Client explored ESG-compliant funds."
      },
      "111": {
        "probability": 0.02,
        "behavior": "Client displayed unexpected engagement with speculative assets."
      },
      "000": {
        "probability": 0.35,
        "behavior": "Client prefers low-risk portfolio optimizations."
      },
      "001": {
        "probability": 0.2,
        "behavior": "Client expressed interest in balanced growth assets."
      },
      "010": {
        "probability": 0.15,
        "behavior": "Client adjusted holdings after a market correction."
      },
      "011": {
        "probability": 0.1,
        "behavior": "Client requested tax-loss harvesting information."
      }
    },
    "histogram": "iVBORw0KGgoAAAANSUhEUgAAA...",
    "analysis": "The AI analysis shows that 35% of the client's interactions reflect conservative portfolio adjustments. Engagement with speculative assets is minimal, indicating a preference for stability during market volatility."
  }
}