def test_ma_strat(ticker, start, end, periods):
# load data
stock = get_ohlcv("", [ticker], start, end, "1mo", save=False)[ticker]
# generate moving average
stock["MA"] = stock["Adj Close"].ewm(span=6, min_periods=6).mean()
# set up portfolio
# strategy portfolio
PORTFOLIO = Portfolio()
values = []
# buy and hold portfolio
SIMPLE_PORTFOLIO = Portfolio()
simple_values = []
# execute strategy
for i in range(len(stock)):
if i == 0:
SIMPLE_PORTFOLIO.add_position(ticker, stock["Adj Close"][i],
SIMPLE_PORTFOLIO.get_cash())
# update prices
PORTFOLIO.advance(ticker, stock["Adj Close"][i])
SIMPLE_PORTFOLIO.advance(ticker, stock["Adj Close"][i])
# determine actions
# is trend bearish?
if stock["Adj Close"][i] < stock["MA"][i]:
if PORTFOLIO.have_position(ticker):
PORTFOLIO.close_position(ticker, stock["Adj Close"][i])
else:
# we are bullish!
if PORTFOLIO.get_cash() > 0:
PORTFOLIO.add_position(ticker, stock["Adj Close"][i],
PORTFOLIO.get_cash())
# update historical values
values.append(PORTFOLIO.get_total_value())
simple_values.append(SIMPLE_PORTFOLIO.get_total_value())
# analyze results
# simple portfolio
d = {'Date': list(stock.index), 'value': simple_values}
df_simple = pd.DataFrame(data=d)
df_simple.set_index("Date", inplace=True)
# quant portfolio
d = {'Date': list(stock.index), 'value': values}
df = pd.DataFrame(data=d)
df.set_index("Date", inplace=True)
print_strategy_summary("Simple",
periods,
df_simple,
price_col_name="value")
print()
print_strategy_summary("Quant", periods, df, price_col_name="value")
