Overall Statistics
Total Orders
222
Average Win
0.47%
Average Loss
-0.61%
Compounding Annual Return
-10.220%
Drawdown
7.000%
Expectancy
-0.060
Net Profit
-4.380%
Sharpe Ratio
-0.584
Sortino Ratio
-0.518
Probabilistic Sharpe Ratio
10.679%
Loss Rate
47%
Win Rate
53%
Profit-Loss Ratio
0.77
Alpha
-0.141
Beta
0.323
Annual Standard Deviation
0.117
Annual Variance
0.014
Information Ratio
-2.154
Tracking Error
0.136
Treynor Ratio
-0.211
Total Fees
$854.74
Estimated Strategy Capacity
$12000000.00
Lowest Capacity Asset
AAPL R735QTJ8XC9X
Portfolio Turnover
145.65%
#region imports
    using System;
    using System.Collections;
    using System.Collections.Generic;
    using System.Linq;
    using System.Globalization;
    using System.Drawing;
    using QuantConnect;
    using System.Text.RegularExpressions;
    using QuantConnect.Algorithm.Framework;
    using QuantConnect.Algorithm.Framework.Selection;
    using QuantConnect.Algorithm.Framework.Alphas;
    using QuantConnect.Algorithm.Framework.Portfolio;
    using QuantConnect.Algorithm.Framework.Execution;
    using QuantConnect.Algorithm.Framework.Risk;
    using QuantConnect.Algorithm.Selection;
    using QuantConnect.Parameters;
    using QuantConnect.Benchmarks;
    using QuantConnect.Brokerages;
    using QuantConnect.Util;
    using QuantConnect.Interfaces;
    using QuantConnect.Algorithm;
    using QuantConnect.Indicators;
    using QuantConnect.Data;
    using QuantConnect.Data.Consolidators;
    using QuantConnect.Data.Custom;
    using QuantConnect.DataSource;
    using QuantConnect.Data.Fundamental;
    using QuantConnect.Data.Market;
    using QuantConnect.Data.UniverseSelection;
    using QuantConnect.Notifications;
    using QuantConnect.Orders;
    using QuantConnect.Orders.Fees;
    using QuantConnect.Orders.Fills;
    using QuantConnect.Orders.Slippage;
    using QuantConnect.Scheduling;
    using QuantConnect.Securities;
    using QuantConnect.Securities.Equity;
    using QuantConnect.Securities.Future;
    using QuantConnect.Securities.Option;
    using QuantConnect.Securities.Forex;
    using QuantConnect.Securities.Crypto;   
    using QuantConnect.Securities.Interfaces;
    using QuantConnect.Storage;
    using QCAlgorithmFramework = QuantConnect.Algorithm.QCAlgorithm;
    using QCAlgorithmFrameworkBridge = QuantConnect.Algorithm.QCAlgorithm;
#endregion


using QuantConnect.DataSource;

namespace QuantConnect.Algorithm.CSharp.AltData
{
    public class BenzingaNewsDataAlgorithm : QCAlgorithm
    {
        private Symbol _aapl;
        private Symbol _benzingaSymbol;
        private int _currentHoldings = 0;
        private int _targetHoldings = 0;
        private Dictionary<string, int> _wordScores = new Dictionary<string, int>(){
            {"good", 1}, {"great", 1}, {"best", 1}, {"growth", 1},
            {"bad", -1}, {"terrible", -1}, {"worst", -1}, {"loss", -1}
        };
        
        public override void Initialize()
        {
            SetStartDate(2021, 1, 1);
            SetEndDate(2021, 6, 1);
            SetCash(100000);
            
            // Requesting data
            _aapl = AddEquity("AAPL", Resolution.Minute).Symbol;
            _benzingaSymbol = AddData<BenzingaNews>(_aapl).Symbol;
            
            // Historical data
            var history = History<BenzingaNews>(_benzingaSymbol, 14, Resolution.Daily);
            Debug($"We got {history.Count()} items from our history request");
        }
        
        public override void OnData(Slice slice)
        {
            if (slice.ContainsKey(_benzingaSymbol))
            {
                // Assign a sentiment score to the news article
                var contentWords = slice[_benzingaSymbol].Contents.ToLower();
                var score = 0;
                foreach (KeyValuePair<string, int> entry in _wordScores)
                {
                    score += (Regex.Matches(contentWords, entry.Key).Count * entry.Value);
                }
                _targetHoldings = Convert.ToInt32(score > 0);
            }
            
            
            // Ensure we have AAPL data in the current Slice
            if (!(slice.ContainsKey(_aapl) && slice[_aapl] != null && !slice[_aapl].IsFillForward))
            {
                return;
            }
            
            // Buy or sell if the sentiment has changed from our current holdings
            if (_currentHoldings != _targetHoldings)
            {
                SetHoldings(_aapl, _targetHoldings);
                _currentHoldings = _targetHoldings;
            }
        }
    }
}