input: import numpy as np
  import tensorflow as tf
  
  def create_model():
      """Create a neural network model that takes a trajectory of stock prices and predicts the stock price for the next day.
  
      Example:
      >>> model = create_model()
      >>> input_data = np.array([[10, 10.4, 10.5, 10.6, 10.7, 10.9, 11]])
      >>> predictions = model.predict(input_data)
      >>> print(f"Predicted stock price for the next day is: {predictions[0][0]}")
      "Predicted stock price for the next day is: [predicted price]"
      """
      model = tf.keras.Sequential([
          tf.keras.layers.Dense(64, activation='relu', input_shape=(7, )),
          tf.keras.layers.Dense(1)
      ])
  
      model.compile(loss='mean_squared_error', 
                    optimizer='adam',
                    metrics=['accuracy'])
  
      return model
output:     return model