input: 
  from typing import List
  
  def predict_stock_market_movement(data: List[float]) -> float:
      """
      This function takes a list of stock market data points and uses a deep learning model to predict the next movement.
      The model is trained on historical data to learn patterns that can be used for prediction.
      
      >>> predict_stock_market_movement([100.0, 101.0, 102.0, 101.5, 102.5])
      103.0
      >>> predict_stock_market_movement([150.0, 151.0, 150.5, 152.0, 151.5])
      152.5
      """
      pass
  
output:     import numpy as np
      from sklearn.linear_model import LinearRegression
  
      X = np.array(data[:-1]).reshape(-1, 1)
      y = np.array(data[1:])
  
      model = LinearRegression()
      model.fit(X, y)
  
      next_movement = model.predict(np.array([data[-1]]).reshape(-1, 1))
      return next_movement[0]