def test_calculate_investment_value__max():
wallet = Wallet(0.01, 3) # min recomended investment = 300
wallet.money = 10000
max_fraction = 5
expected_result = 2000
result = calculate_investment_value(wallet, max_fraction)
assert expected_result == result
def test_calculate_investment_value__invest_all():
wallet = Wallet(0.01, 3) # min recomended investment = 300
wallet.money = 2000
wallet.buy('CCC', 20, 50) # cost = 1010
max_fraction = 2
expected_result = 990
result = calculate_investment_value(wallet, max_fraction)
assert expected_result == result
def simulation(*args, **kwargs):
wallet_history = pd.DataFrame(columns=['Date', 'Wallet state'])
stocks_to_buy = []
stocks_to_sell = []
for day in time_range:
day_str = day.strftime('%Y-%m-%d')
# Buy selected day before. Loop over list, order can be important here.
# Strategy can sort relevant stocks - high priority first.
for tck in stocks_to_buy:
if not wallet.get_volume_of_stocks(tck):
price = traded_stocks[tck].ohlc['Open'].get(day, None)
if price:
total = calculate_investment_value(
wallet, max_positions)
total = total - wallet(
total) # needs some money to pay commission
volume = math.floor(total / price)
if volume > 0:
wallet.buy(tck, volume, price)
print(
info_str(day_str, 'B', tck, volume, price))
# make sure to not sell it the same day
if tck in stocks_to_sell:
stocks_to_sell.remove(tck)
# Sell selected day before. List to set, we dont care here about the order.
# Set will remove duplicates.
for tck in set(stocks_to_sell):
if wallet.get_volume_of_stocks(tck):
price = traded_stocks[tck].ohlc['Open'].get(day, None)
if price:
print_color = determine_print_color_from_prices(
price,
wallet.get_purchase_price_of_stocks(tck))
volume = wallet.sell_all(tck, price)
print_color(
info_str(day_str, 'S', tck, volume, price))
# call decorated function - strategy function
stocks_to_buy, stocks_to_sell = func(
day=day, traded_stocks=traded_stocks, *args, **kwargs)
# if auto trading is active, check if price of any stock in the wallet crossed
# take proffit or stop loss price; if yes then sell it immediately
if auto_trading:
for tck in wallet.list_stocks().copy():
price_max = traded_stocks[tck].ohlc['High'].get(
day, None)
if price:
wallet.update_price(tck, price_max)
if wallet.change(tck) > take_profit:
price = wallet.get_purchase_price_of_stocks(
tck) * (1 + take_profit
) # selling it immediately
price = round(price, 2)
volume = wallet.sell_all(tck, price)
print_green(
info_str(day_str, 'TP', tck, volume, price))
continue
price_min = traded_stocks[tck].ohlc['Low'].get(
day, None)
if price:
wallet.update_price(tck, price_min)
if wallet.change(tck) < -stop_loss:
price = wallet.get_purchase_price_of_stocks(
tck) * (1 - stop_loss
) # selling it immediately
price = round(price, 2)
volume = wallet.sell_all(tck, price)
print_red(
info_str(day_str, 'SL', tck, volume, price))
for tck in wallet.list_stocks():
# update the price to the closing price and calculate relative price change
ohlc = traded_stocks[tck].ohlc
price = ohlc['Close'].get(day, None)
if price:
wallet.update_price(tck, price)
# if auto trading is not active, then take profit / stop loss the next day
if not auto_trading:
# take profit the next day
if take_profit and wallet.change(tck) > take_profit:
stocks_to_sell.append(tck)
# stop loss the next day - price below purchase price
if stop_loss and wallet.change(tck) < -stop_loss:
stocks_to_sell.append(tck)
# save history of the wallet
wallet_history = wallet_history.append(
{
'Date': day,
'Wallet state': wallet.total_value
},
ignore_index=True)
return wallet_history