Test harness is important to evaluate trading strategy

Simple Way of Evaluating Algorithmic Trading Strategy

Designing a financial trading strategy

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Back-testing is an important step to get the statistics to ensure effective trading strategy. It comes with some of the key points such as profit and loss, net profit and loss, invested capital, number of trades/orders return, Sharpe ratio etc. Here, we will discuss as how to design a financial trading strategy using open source Python tools and we’ll review the results of the back-test by going through some plots generated by pyfolio.

Let us load the data as shown below.

Function to extract data:

def dataExtraction():
  dataset = web.DataReader('^IXIC', data_source = 'yahoo', start = '2010-01-01')
  dataset = dataset.sort_index(ascending=True)
  # Plot the closing prices
  dataset['Adj Close'].plot(grid=True, figsize=(10, 6))
  plt.title('Nasdaq Composite close price')
  plt.ylabel('price ($)')
  plt.show()
  return dataset
dataset = dataExtraction()
print(dataset)