Web-Based Portfolio Risk Analytics JavaScript, React, API

```javascript
// **Project Overview:**
// This project demonstrates a basic web-based portfolio risk analytics tool using React for the front-end, JavaScript for logic, and fetching data from a (mock) API.  It will:
// 1.  Fetch portfolio data (holdings, weights, expected returns, volatility).
// 2.  Calculate basic portfolio statistics (weighted average return, weighted average volatility, Sharpe Ratio).
// 3.  Display the results in a user-friendly React component.

// **Disclaimer:** This is a simplified example. Real-world portfolio risk analysis is much more complex and requires robust data sources and sophisticated risk models.  This code uses placeholder data and basic calculations for demonstration purposes.

// **Assumptions:**
// - You have Node.js and npm (or yarn) installed.
// - You have a basic understanding of React components and JSX.
// - This example uses a mock API for data.  In a real application, you would replace this with calls to a real API endpoint.

// **Steps:**

// 1. **Create a React application:**

//    ```bash
//    npx create-react-app portfolio-risk-app
//    cd portfolio-risk-app
//    npm install react-chartjs-2 chart.js  //optional for graphing.
//    npm start
//    ```

// 2. **Code Implementation:**

// App.js (Main Application Component)

import React, { useState, useEffect } from 'react';
import './App.css'; // Optional CSS file
import PortfolioSummary from './PortfolioSummary'; // Import the child component
//import PortfolioChart from './PortfolioChart'; //Optional chart for visualization

function App() {
  const [portfolioData, setPortfolioData] = useState(null);
  const [loading, setLoading] = useState(true);
  const [error, setError] = useState(null);

  useEffect(() => {
    // Simulate fetching data from an API endpoint
    const fetchData = async () => {
      try {
        // Replace this with your actual API call (e.g., using fetch)
        //const response = await fetch('/api/portfolio'); // Example API endpoint
        //const data = await response.json();

        // Mock data for demonstration
        const mockData = {
          holdings: [
            { ticker: 'AAPL', weight: 0.25, expectedReturn: 0.12, volatility: 0.15 },
            { ticker: 'MSFT', weight: 0.20, expectedReturn: 0.10, volatility: 0.12 },
            { ticker: 'GOOG', weight: 0.15, expectedReturn: 0.14, volatility: 0.18 },
            { ticker: 'AMZN', weight: 0.20, expectedReturn: 0.08, volatility: 0.10 },
            { ticker: 'TSLA', weight: 0.20, expectedReturn: 0.20, volatility: 0.25 }, // Added TSLA for demonstration
          ],
          riskFreeRate: 0.02, // 2% risk-free rate
        };

        setPortfolioData(mockData);
        setLoading(false);
      } catch (err) {
        setError(err);
        setLoading(false);
      }
    };

    fetchData();
  }, []); // Empty dependency array ensures this runs only once on component mount

  if (loading) {
    return <div>Loading portfolio data...</div>;
  }

  if (error) {
    return <div>Error: {error.message}</div>;
  }

  if (!portfolioData) {
    return <div>No portfolio data available.</div>;
  }

  // Function to calculate weighted average return
  const calculateWeightedAverageReturn = () => {
    let weightedReturn = 0;
    portfolioData.holdings.forEach(holding => {
      weightedReturn += holding.weight * holding.expectedReturn;
    });
    return weightedReturn;
  };

  // Function to calculate weighted average volatility (simplified)
  const calculateWeightedAverageVolatility = () => {
    let weightedVolatility = 0;
    portfolioData.holdings.forEach(holding => {
      weightedVolatility += holding.weight * holding.volatility;
    });
    return weightedVolatility;
  };

  // Function to calculate Sharpe Ratio
  const calculateSharpeRatio = () => {
    const portfolioReturn = calculateWeightedAverageReturn();
    const portfolioVolatility = calculateWeightedAverageVolatility();
    return (portfolioReturn - portfolioData.riskFreeRate) / portfolioVolatility;
  };

  const weightedAverageReturn = calculateWeightedAverageReturn();
  const weightedAverageVolatility = calculateWeightedAverageVolatility();
  const sharpeRatio = calculateSharpeRatio();

  return (
    <div className="App">
      <h1>Portfolio Risk Analytics</h1>

      <PortfolioSummary
        holdings={portfolioData.holdings}
        weightedAverageReturn={weightedAverageReturn}
        weightedAverageVolatility={weightedAverageVolatility}
        sharpeRatio={sharpeRatio}
      />

      {/*
       Optional Visualization
      <PortfolioChart holdings={portfolioData.holdings} />
      */}
    </div>
  );
}

export default App;

// PortfolioSummary.js (Child Component to display summary)

import React from 'react';

function PortfolioSummary({ holdings, weightedAverageReturn, weightedAverageVolatility, sharpeRatio }) {
  return (
    <div>
      <h2>Portfolio Summary</h2>
      <p>Weighted Average Return: {weightedAverageReturn.toFixed(2)}</p>
      <p>Weighted Average Volatility: {weightedAverageVolatility.toFixed(2)}</p>
      <p>Sharpe Ratio: {sharpeRatio.toFixed(2)}</p>

      <h3>Holdings:</h3>
      <ul>
        {holdings.map((holding, index) => (
          <li key={index}>
            {holding.ticker}: Weight - {holding.weight}, Expected Return - {holding.expectedReturn}, Volatility - {holding.volatility}
          </li>
        ))}
      </ul>
    </div>
  );
}

export default PortfolioSummary;

// Optional PortfolioChart.js for visualizing the portfolio (requires react-chartjs-2 and chart.js)

/*
import React from 'react';
import { Pie } from 'react-chartjs-2';
import { Chart, registerables } from 'chart.js';
Chart.register(...registerables);

function PortfolioChart({ holdings }) {
  const labels = holdings.map(holding => holding.ticker);
  const data = holdings.map(holding => holding.weight);

  const chartData = {
    labels: labels,
    datasets: [
      {
        label: 'Portfolio Allocation',
        data: data,
        backgroundColor: [
          'rgba(255, 99, 132, 0.6)',
          'rgba(54, 162, 235, 0.6)',
          'rgba(255, 206, 86, 0.6)',
          'rgba(75, 192, 192, 0.6)',
          'rgba(153, 102, 255, 0.6)',
        ],
        borderWidth: 1,
      },
    ],
  };

  const options = {
    plugins: {
      title: {
        display: true,
        text: 'Portfolio Allocation',
      },
    },
  };

  return <Pie data={chartData} options={options} />;
}

export default PortfolioChart;

*/

// App.css (Optional CSS file)

/*
.App {
  text-align: center;
  padding: 20px;
}

h1 {
  color: #333;
}

h2 {
  color: #666;
  margin-top: 20px;
}

p {
  margin: 5px 0;
}

ul {
  list-style: none;
  padding: 0;
}

li {
  margin: 5px 0;
}
*/

// **Explanation:**

// *   **`App.js`:**
//     *   **State Management:** Uses `useState` to manage `portfolioData`, `loading`, and `error`.
//     *   **`useEffect`:**  Fetches data (simulated with mock data) when the component mounts.  The empty dependency array `[]` ensures it only runs once.  This is where you would make an actual API call using `fetch` or `axios`.
//     *   **Error Handling:** Includes `try...catch` for error handling during data fetching.
//     *   **Loading State:**  Displays a "Loading..." message while data is being fetched.
//     *   **Data Validation:** Checks if `portfolioData` exists before rendering the summary.
//     *   **Calculation Functions:**  `calculateWeightedAverageReturn`, `calculateWeightedAverageVolatility`, and `calculateSharpeRatio` perform the calculations.  *Important*: The volatility calculation is greatly simplified and does *not* account for correlations between assets, which is crucial in real-world risk analysis.
//     *   **Component Composition:** Renders the `PortfolioSummary` component, passing the calculated statistics as props.
// *   **`PortfolioSummary.js`:**
//     *   **Receives Props:** Accepts `holdings`, `weightedAverageReturn`, `weightedAverageVolatility`, and `sharpeRatio` as props.
//     *   **Displays Data:** Renders a summary of the portfolio data, including the calculated statistics and a list of holdings.
// *   **`PortfolioChart.js` (Optional):**
//     *   **Uses `react-chartjs-2` and `chart.js`:**  Creates a pie chart to visualize the portfolio allocation (the weights of each asset).  This requires installing those libraries.
//     *   **Formats Data for Chart:** Transforms the `holdings` data into the format required by `react-chartjs-2`.

// **Running the application:**

// 1.  Save all the files.
// 2.  In your terminal, inside the `portfolio-risk-app` directory, run:

//     ```bash
//     npm start
//     ```

//     This will start the development server and open the application in your browser (usually at `http://localhost:3000`).

// **Important Considerations and Improvements:**

// *   **Real API Integration:**  Replace the mock data with actual API calls to a data provider.  You'll need to handle authentication and data parsing.
// *   **Security:**  Be mindful of security when fetching data from APIs, especially if the API requires authentication.  Use environment variables to store API keys.
// *   **Error Handling:** Implement more robust error handling, including logging errors to the console and providing user-friendly error messages.
// *   **Data Validation:** Validate the data received from the API to ensure it's in the expected format.
// *   **User Interface (UI):** Improve the UI with better styling, responsive design, and potentially interactive elements (e.g., allowing users to input their own portfolio data).
// *   **More Sophisticated Risk Metrics:**  Implement more advanced risk metrics like Value at Risk (VaR), Expected Shortfall (ES), beta, and tracking error.
// *   **Correlation Matrix:**  Include a correlation matrix to account for the relationships between asset returns when calculating portfolio volatility. This is critical for accurate risk assessment.
// *   **Backtesting:** Consider adding backtesting functionality to evaluate the performance of different portfolio strategies.
// *   **Stress Testing:**  Implement stress testing to assess how the portfolio would perform under extreme market conditions.
// *   **Optimization:** Add portfolio optimization features to help users find the portfolio allocation that maximizes return for a given level of risk.
// *   **Data Visualization:** Use more sophisticated charting libraries (e.g., D3.js) to create richer visualizations.
// *   **Unit Testing:** Write unit tests to ensure the correctness of your calculations and data processing logic.
// *   **State Management:** For larger applications, consider using a state management library like Redux or Zustand.
// *   **Typescript:**  For a larger and more maintainable application, use Typescript.

// This comprehensive example should get you started with building your portfolio risk analytics tool.  Remember to expand upon this foundation with the considerations mentioned above to create a more robust and useful application.
```