def main():
args = parser.parse_args()
if args.draw:
# parse arguments and collect data
# price history
if args.use_generated:
gen = args.use_generated[0]
src = args.use_generated[1]
(data, _) = calc.generate_theoretical_data(gen, src)
else:
data = db.build_price_lut(args.draw[0])
dates = [date_obj(date) for date in sorted(data.keys())]
prices = [data[date_str(date)] for date in dates]
# indicators and plot counts
if not args.indicators:
args.indicators = []
plots = 1
indicators = {}
for indicator_code in args.indicators:
if indicator_code[0:4] == 'MACD':
plots = 2
indicators[indicator_code] = calc.get_indicator(indicator_code,
data, True)
# plot main price data
pyplot.subplot(plots * 100 + 11)
pyplot.plot(dates, prices, label='{} price'.format(args.draw[0]))
pyplot.legend(loc='upper left')
# plot indicators
for (indicator_code, series) in indicators.items():
code_parts = indicator_code.split('_')
indicator = code_parts[0]
if len(code_parts) > 1:
period_code = code_parts[1]
if indicator == 'MACD':
pyplot.subplot(plots * 100 + 12)
pyplot.plot(dates, series[0], label=indicator_code)
pyplot.plot(dates, series[1],
label='Signal_{}'.format(period_code))
pyplot.legend(loc='upper left')
else:
pyplot.subplot(plots * 100 + 11)
pyplot.plot(dates, series, label=indicator_code)
pyplot.legend(loc='upper left')
pyplot.show()
if args.generate:
(part, full) = calc.generate_theoretical_data(args.generate[0],
args.generate[1])
tgt_lut = db.build_price_lut(args.generate[0])
src_lut = db.build_price_lut(args.generate[1])
tgt_dates = [date_obj(d) for d in sorted(tgt_lut.keys())]
src_dates = [date_obj(d) for d in sorted(part.keys())]
tgt_gen_part_prices = [part[date_str(d)] for d in src_dates]
tgt_gen_full_prices = [full[date_str(d)] for d in src_dates]
src_prices = [src_lut[date_str(d)] for d in src_dates]
pyplot.subplot(211)
pyplot.plot([date_obj(d) for d in tgt_dates],
tgt_gen_full_prices[-len(tgt_dates):],
label='{}-generated'.format(args.generate[0]))
pyplot.plot([date_obj(d) for d in tgt_dates],
tgt_gen_part_prices[-len(tgt_dates):],
label='{}'.format(args.generate[0]))
pyplot.legend(loc='upper left')
pyplot.subplot(212)
pyplot.plot(src_dates, tgt_gen_part_prices, label='{}-generated'.format(args.generate[0]))
pyplot.plot(src_dates, src_prices, label='{}'.format(args.generate[1]))
pyplot.legend(loc='upper left')
pyplot.show()
if args.portfolio:
# init main objects
my_market = Market()
my_portfolio = Portfolio()
my_trader = Trader(args.portfolio[0], my_portfolio, my_market)
# init simulator
my_monitor = Monitor(my_trader, my_market)
my_sim = Simulator()
my_sim.add_trader(my_trader)
my_sim.use_market(my_market)
my_sim.use_monitor(my_monitor)
(strategy, tickers, indicators) = db.build_strategy(args.strategy[0])
my_trader.add_assets_of_interest(strategy['assets'])
my_trader.set_strategy(strategy['positions'])
my_sim.use_stocks(tickers)
my_sim.use_indicators(indicators)
if args.contribute:
my_trader.set_contributions(args.contribute[0], args.contribute[1])
if args.rebalance:
my_trader.set_rebalancing_period(args.rebalance[0])
if args.use_generated:
for i in range(len(args.use_generated) // 2):
gen = args.use_generated[i * 2]
src = args.use_generated[i * 2 + 1]
(data, _) = calc.generate_theoretical_data(gen, src)
my_market.inject_stock_data(gen, None, None, data)
# run simulation
my_sim.simulate()
# print some stats
print('##################################')
print('# PERFORMANCE SUMMARY')
print('##################################')
print('initial: $' + currency(my_trader.starting_cash))
print('final: $' + currency(my_trader.portfolio.value()))
print('trades: {}'.format(my_portfolio.trades))
print('---------------------------')
print('Sharpe Ratio: {}'.format(
my_monitor.get_statistic('sharpe_ratio')))
print('Sortino Ratio: {}'.format(
my_monitor.get_statistic('sortino_ratio')))
print('---------------------------')
print('CAGR: {}%'.format(
percent(my_monitor.get_statistic('cagr'))))
print('Adjusted CAGR: {}%'.format(
percent(my_monitor.get_statistic('adjusted_cagr'))))
print('---------------------------')
print('best year: {}%'.format(
percent(max(my_monitor.get_data_series('annual_returns')[1]))))
print('worst year: {}%'.format(
percent(min(my_monitor.get_data_series('annual_returns')[1]))))
print('---------------------------')
drawdown = my_monitor.get_statistic('max_drawdown')
print('max drawdown: {}%'.format(percent(drawdown['amount'])))
print(' between {} and {}, recovered by {}'.format(
drawdown['from'], drawdown['to'], drawdown['recovered_by']))
# show plots
(x, y) = my_monitor.get_data_series('portfolio_values')
pyplot.subplot(411)
pyplot.plot(x, y)
pyplot.grid(b=False, which='major', color='grey', linestyle='-')
(x, y) = my_monitor.get_data_series('asset_allocations')
pyplot.subplot(412)
pyplot.stackplot(x, y, alpha=0.5)
pyplot.grid(b=True, which='major', color='grey', linestyle='-')
pyplot.legend(sorted(strategy['assets']), loc='upper left')
(x, y) = my_monitor.get_data_series('annual_returns')
ax = pyplot.subplot(413)
pyplot.bar(list(range(len(x))), y, 0.5, color='blue')
ax.set_xticks(list(range(len(x))))
ax.set_xticklabels(x)
pyplot.grid(b=True, which='major', color='grey', linestyle='-')
(x, y) = my_monitor.get_data_series('contribution_vs_growth')
pyplot.subplot(414)
pyplot.stackplot(x, y, alpha=0.5)
pyplot.grid(b=True, which='major', color='grey', linestyle='-')
pyplot.legend(['Contributions', 'Growth'], loc='upper left')
pyplot.show()
exit()
