AlexStav commited on
Commit
2c8064e
1 Parent(s): 1566530

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +5 -4
app.py CHANGED
@@ -41,15 +41,16 @@ def main():
41
  # Introduction
42
  st.markdown("""
43
  ## Welcome to the Stock Forecasting App!
44
- This app uses the Prophet time series forecasting model to predict future stock prices based on historical data.
45
- Simply enter a stock ticker symbol, choose the start and end dates for the analysis, select your forecast horizon,
46
- and hit the "Forecast Stock Prices" button to see the predictions.
47
 
48
  ### How to Use:
49
  1. Enter the **ticker symbol** of the stock you're interested in (e.g., 'AAPL' for Apple Inc.).
50
- 2. Choose the **start and end dates** for historical data analysis.
51
  3. Select the **forecast horizon** from the dropdown to predict 1, 2, 3, or 5 years into the future.
52
  4. Click the **"Forecast Stock Prices"** button to generate the forecast.
 
 
53
 
54
  Scroll down to view the forecast results and performance metrics of the model.
55
  """)
 
41
  # Introduction
42
  st.markdown("""
43
  ## Welcome to the Stock Forecasting App!
44
+ This app leverages the Prophet forecasting model, developed by Meta (formerly Facebook), to predict future stock prices.
45
+ Prophet is designed for analyzing time series data with strong seasonal effects and several seasons of historical data.
 
46
 
47
  ### How to Use:
48
  1. Enter the **ticker symbol** of the stock you're interested in (e.g., 'AAPL' for Apple Inc.).
49
+ 2. Choose the **start and end dates** for historical data analysis. It is recommended to include as much historical data as possible to enhance the accuracy of the forecast.
50
  3. Select the **forecast horizon** from the dropdown to predict 1, 2, 3, or 5 years into the future.
51
  4. Click the **"Forecast Stock Prices"** button to generate the forecast.
52
+
53
+ The more historical data provided, the more accurately Prophet can capture and forecast seasonal patterns in the data.
54
 
55
  Scroll down to view the forecast results and performance metrics of the model.
56
  """)