input: Write a Python function to predict the trend of stock prices using linear regression.
  assert predict_trend([[50], [55], [53], [57], [52], [49], [54]], [[54]]) == 53.428571429
  assert predict_trend([[10], [12], [14], [16], [18], [20]], [[22]]) == 22.0
  assert predict_trend([[100], [105], [110], [115], [120]], [[125]]) == 125.0
output: def predict_trend(X, y):
      from sklearn.linear_model import LinearRegression
      model = LinearRegression()
      model.fit(X, y)
      return float(model.predict([[X[-1][0] + 1]]))