How to Build a Unified Dashboard for Portfolio Tracking and Arbitrage Scanning

Step‑by‑step tutorial on integrating portfolio data with arbitrage alerts, including API setups, UI design, and risk management tips.

Step‑by‑step tutorial on integrating portfolio data with arbitrage alerts, including API setups, UI design, and risk management tips.

How to Build a Unified Dashboard for Portfolio Tracking and Crypto Arbitrage Scanning

Published: June 2026

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Introduction

The rapid expansion of the cryptocurrency market has generated unprecedented opportunities for both long‑term investors and short‑term traders. According to CoinMarketCap, the total crypto market capitalization surpassed $2 trillion in early 2026, while daily trading volume on major exchanges regularly exceeds $150 billion. Simultaneously, price differentials between exchanges—a phenomenon known as arbitrage—continue to create profit potential for agile participants.

A unified dashboard that merges portfolio analytics with real‑time arbitrage alerts can transform a fragmented workflow into a single, data‑driven interface. This article provides a step‑by‑step guide for building such a dashboard, from acquiring market data via APIs to designing a responsive user interface and implementing robust risk‑management controls. The tutorial assumes familiarity with a modern programming stack (e.g., JavaScript/TypeScript, Python, or Swift) and basic cloud services (AWS, GCP, or Azure).

1. Foundations of Portfolio Tracking

1.1 What Is Portfolio Tracking?

Portfolio tracking is the systematic collection, aggregation, and visualization of an investor’s asset holdings. The process delivers metrics such as total market value, unrealized gains, and allocation percentages.

1.2 Key Data Sources

|--------|--------------|----------------------|-----------------|

| DeFi Wallet (e.g., MetaMask) | ERC‑20 token balances | GET /api?module=account&action=tokenbalance | https://api.etherscan.io/api?module=account&action=tokenbalance&address=... |

| Price Aggregator (e.g., CoinGecko) | Spot prices, market caps | GET /api/v3/simple/price | https://api.coingecko.com/api/v3/simple/price?ids=bitcoin,ethereum&vs_currencies=usd |

The reliability of portfolio tracking hinges on synchronizing these disparate sources. A robust implementation stores raw API responses in a time‑stamped database and applies a deterministic transformation pipeline to produce a unified view.

1.3 Core Metrics to Display

1. Total Net Asset Value (NAV) – Sum of all holdings converted to a base currency (usually USD).

2. Weighted Average Cost (WAC) – Average acquisition price weighted by quantity.

3. Performance Ratio – (Current NAV ÷ Historical NAV) × 100 % for any given period.

4. Allocation Heatmap – Visual representation of exposure across asset classes (e.g., Bitcoin, DeFi tokens, stablecoins).

2. Fundamentals of Crypto Arbitrage Scanning

2.1 What Is Arbitrage?

Arbitrage is the simultaneous purchase and sale of an asset on different markets to capture a price discrepancy. In the crypto ecosystem, arbitrage can be classified into three primary categories:

| Category | Description | Typical Spread |

|----------|-------------|----------------|

| Spatial | Buying on Exchange A and selling on Exchange B | 0.2 % – 1.5 % |

| Triangular | Exploiting price loops within a single exchange (e.g., BTC→ETH→USDT→BTC) | 0.1 % – 0.7 % |

| Statistical | Leveraging predictive models to anticipate short‑term mispricings | Variable, often > 1 % |

A statistical study published in The Journal of Digital Finance estimated that 1.8 % of daily crypto trades are driven by arbitrage opportunities, translating to a global profit pool of more than $2.7 billion per year.

2.2 Data Requirements for Arbitrage Scanning

Arbitrage scanners must ingest low‑latency order‑book data, including the best bid and ask for each trading pair. The most critical fields are:

symbol (e.g., BTCUSDT)
bid_price
ask_price
timestamp (UTC)

A well‑engineered scanner aggregates these fields from at least three high‑volume exchanges to increase detection reliability.

2.3 Calculating Arbitrage Opportunities

The fundamental formula for a spatial arbitrage spread is:

\text{Spread (\%)} = \frac{\text{Ask}_{\text{Exchange A}} - \text{Bid}_{\text{Exchange B}}}{\text{Bid}_{\text{Exchange B}}} \times 100

A spread above 0.4 % is generally deemed actionable after accounting for transaction fees, network latency, and slippage.

3. Integrating Portfolio Data with Arbitrage Alerts

3.1 Architectural Overview

A unified dashboard consists of four logical layers:

1. Data Acquisition Layer – Handles API calls to exchanges, price aggregators, and wallet providers.

2. Processing Layer – Normalizes data, computes portfolio metrics, and evaluates arbitrage conditions.

3. Storage Layer – Persists raw and transformed data in a time‑series database (e.g., InfluxDB) and a relational store for user preferences.

4. Presentation Layer – Serves JSON responses via a GraphQL endpoint to the front‑end client.

A typical deployment diagram places the Data Acquisition Layer behind a task queue (e.g., RabbitMQ) to ensure rate‑limit compliance. The Processing Layer runs as a stateless microservice that can scale horizontally during peak market hours.

3.2 Implementing the API Bridge

Below is a concise Python snippet that demonstrates retrieving balances from Binance and price quotes from CoinGecko, then merging them into a consolidated portfolio object.

`python

import requests

import time

import hmac

import hashlib

BINANCE_API_KEY = 'YOUR_KEY'

BINANCE_SECRET = 'YOUR_SECRET'

COINGECKO_URL = 'https://api.coingecko.com/api/v3/simple/price'

def binance_signature(query_string: str) -> str:

return hmac.new(BINANCE_SECRET.encode(), query_string.encode(), hashlib.sha256).hexdigest()

def fetch_binance_balances():

timestamp = int(time.time() * 1000)

query = f'timestamp={timestamp}'

signature = binance_signature(query)

headers = {'X-MBX-APIKEY': BINANCE_API_KEY}

resp = requests.get(f'https://api.binance.com/api/v3/account?{query}&signature={signature}',

headers=headers)

resp.raise_for_status()

return resp.json()['balances']

def fetch_prices(symbols):

ids = ','.join(symbols)

params = {'ids': ids, 'vs_currencies': 'usd'}

resp = requests.get(COINGECKO_URL, params=params)

resp.raise_for_status()

return resp.json()

def build_portfolio():

balances = fetch_binance_balances()

crypto_symbols = [b['asset'].lower() for b in balances if float(b['free']) > 0]

prices = fetch_prices(crypto_symbols)

portfolio = []

for bal in balances:

asset = bal['asset']

amount = float(bal['free'])

if amount == 0: continue

price_usd = prices.get(asset.lower(), {}).get('usd', 0)

value_usd = amount * price_usd

portfolio.append({'asset': asset,

'amount': amount,

'price_usd': price_usd,

'value_usd': value_usd})

return portfolio

if __name__ == '__main__':

print(build_portfolio())

The script adheres to Binance’s signed‑request protocol and gracefully falls back to a price of zero if a token is absent from CoinGecko. Scaling this pattern to dozens of exchanges requires abstracting the authentication logic into reusable adapters.

3.3 Merging Arbitrage Signals with Portfolio Exposure

After the Processing Layer identifies a profitable arbitrage spread, the system must verify that the user holds sufficient capital on the relevant exchanges. The verification algorithm follows these steps:

1. Identify the target pair (e.g., BTC/USDT).

2. Check available balances on both Source A and Destination B.

3. Calculate maximum feasible trade size as the minimum of the balances and the exchange‑specific trade limits.

4. Apply a risk buffer (e.g., 80 % of the feasible size) to accommodate network latency.

A simplified JavaScript function illustrates this logic:

`javascript

function assessArbitrageOpportunity(opportunity, portfolio) {

const { sourceExchange, destExchange, base, quote, maxSpread } = opportunity;

const sourceBal = portfolio[sourceExchange][base] || 0;

const destBal = portfolio[destExchange][quote] || 0;

const feasibleSize = Math.min(sourceBal, destBal / maxSpread);

const riskAdjustedSize = feasibleSize * 0.8; // 20% safety margin

return riskAdjustedSize > 0 ? riskAdjustedSize : 0;

}

The function returns a non‑zero value only when the user’s holdings satisfy the arbitrage prerequisites. This approach prevents the system from generating alerts that cannot be executed, thereby enhancing user trust.

4. Designing the User Interface

4.1 Dashboard Layout Principles

A cohesive UI should present three core sections on a single screen:

Portfolio Summary – Top‑right card displaying NAV, daily change, and allocation donut chart.
Arbitrage Feed – Central scrolling list of live opportunities, each entry showing exchange pair, spread, and suggested trade size.
Risk Controls – Bottom‑left panel with sliders for maximum daily exposure, per‑trade limit, and slippage tolerance.

Responsive design guidelines recommend a minimum width of 1440 px for desktop monitors and a breakpoint at 768 px for tablets. The UI must gracefully collapse the arbitrage feed into a modal on smaller screens to preserve readability.

4.2 Visualizing Real‑Time Data

To render live order‑book updates, WebSocket connections are preferable to polling. The following React code fragment utilizes the useEffect hook to subscribe to Binance’s depth stream:

`jsx

import { useState, useEffect } from 'react';

import { w3cwebsocket as W3CWebSocket } from 'websocket';

const client = new W3CWebSocket('wss://stream.binance.com:9443/ws/btcusdt@depth');

function DepthChart() {

const [depth, setDepth] = useState({ bids: [], asks: [] });

useEffect(() => {

client.onmessage = (message) => {

const data = JSON.parse(message.data);

setDepth({ bids: data.b, asks: data.a });

};

return () => client.close();

}, []);

return (

);

}

The Chart component can be powered by a library such as Chart.js or D3.js, with the bid‑ask spread visualized as a shaded area. Real‑time rendering ensures that traders react to price movements within milliseconds, a critical factor for arbitrage execution.

4.3 Alerting and Notification System

In‑app notifications should be coupled with native push mechanisms (APNs

ArbitrageRadar PRO on the App Store · arbitrageradarpro.com

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ArbitrageRadar PRO on the App Store · arbitrageradarpro.com