Stock Charts

Provided by Only Headline

<?php
/**
* Plugin Name: Stock Predictor
* Plugin URI: https://example.com/
* Description: A plugin for predicting small-cap and penny stocks with the most retail investor volume.
* Version: 1.0
* Author: John Doe
* Author URI: https://example.com/
*/

// Load necessary libraries
require_once plugin_dir_path( FILE ) . ‘vendor/autoload.php’;

use \nltk\sentiment\SentimentIntensityAnalyzer;
use \sklearn\preprocessing\MinMaxScaler;

// Load and preprocess data
function preprocess_data() {
// Load stock and sentiment data
$stock_data = pd.read_csv( plugin_dir_path( FILE ) . ‘stock_data.csv’ );
$sentiment_data = pd.read_csv( plugin_dir_path( FILE ) . ‘sentiment_data.csv’ );

// Drop missing values
$stock_data = $stock_data->dropna();
$sentiment_data = $sentiment_data->dropna();

// Perform sentiment analysis
$sia = new SentimentIntensityAnalyzer();
$sentiment_data['compound'] = $sentiment_data['text']->apply( function( $x ) use ( $sia ) {
    return $sia->polarity_scores( $x )['compound'];
} );

// Feature engineering
$scaler = new MinMaxScaler();
$stock_data['volume_norm'] = $scaler->fit_transform( $stock_data['volume']->values.reshape( -1, 1 ) );
$sentiment_data = $sentiment_data->groupby( ['symbol', 'date'] )['compound']->mean()->reset_index();
$features = pd.merge( $stock_data, $sentiment_data, how='left', on=['symbol', 'date'] );
return $features;

}

// Shortcode for displaying predicted stocks
function stock_predictor_shortcode() {
$features = preprocess_data();
$results = ”;

if (isset($_POST['run_scan'])) {
    // Run predictive model and generate results
    // ...

    // Display results
    $results = '<p>Predicted stocks: AAPL, GOOGL, AMZN</p>';
}

// Display form and results
$html = '
    <form method="post">
        <button type="submit" name="run_scan">Run Scan</button>
    </form>
    <div>' . $results . '</div>
';
return $html;

}
add_shortcode( ‘stock_predictor’, ‘stock_predictor_shortcode’ );

Follow me