Using AI to Pick Stocks in 2026: My Results After 6 Months

{
name: 'Get Historical Stock Data',
operation: {
type: 'alpha_vantage',
method: 'GET',
endpoint: '/query',
parameters: {
function: 'SMA',
symbol: 'AAPL',
interval: 'daily',
outputsize: 'full',
datatype: 'json',
'period1': '2020-01-01',
'period2': '2022-01-01',
},
},
},
{
name: 'Analyze Stock Data',
operation: {
type: 'gpt_4',
method: 'POST',
endpoint: '/analyze',
parameters: {
data: {
text: 'Analyze the historical stock data for AAPL',
},
},
},
},
];

// Run the workflow
const results = await api.runWorkflow(workflow);
console.log(results);

Trading Strategy and Risk Management
To maximize returns, I implemented a trading strategy that included position sizing, stop-loss, and take-profit levels. I used GPT-4 to analyze the stock data and generate trading signals. Here's an example of how I used GPT-4 to generate trading signals:
python
import gpt_4

Define the trading strategy

def trading_strategy(symbol, data):
# Analyze the stock data using GPT-4
analysis = gpt_4.analyze(data)

# Generate a trading signal

if analysis['signal'] == 'buy':

    return 'Buy'

elif analysis['signal'] == 'sell':

    return 'Sell'

else:

    return 'Hold'

Define the stock symbol and data

symbol = 'AAPL'
data = {
'text': 'Analyze the historical stock data for AAPL'
}