def test_sharpe_ratio(self, net_worths):
scheme = RiskAdjustedReturns(return_algorithm='sharpe', risk_free_rate=0)
returns = net_worths.diff()
sharpe_ratio = scheme._sharpe_ratio(returns)
expected_ratio = returns.mean() / (returns.std() + 1E-9)
assert sharpe_ratio == expected_ratio
def test_sharpe_ratio(self, net_worths):
scheme = RiskAdjustedReturns(return_algorithm='sharpe',
risk_free_rate=0,
window_size=1)
returns = net_worths[-2:].pct_change().dropna()
expected_ratio = (np.mean(returns) + 1E-9) / (np.std(returns) + 1E-9)
sharpe_ratio = scheme._sharpe_ratio(returns)
assert sharpe_ratio == expected_ratio
def test_sortino_ratio(self, net_worths):
scheme = RiskAdjustedReturns(return_algorithm='sortino',
risk_free_rate=0,
target_returns=0)
returns = net_worths.pct_change()
sortino_ratio = scheme._sortino_ratio(returns)
expected_return = returns.mean()
downside_std = returns[returns < 0].std()
expected_ratio = expected_return / downside_std
assert sortino_ratio == expected_ratio
def test_sortino_ratio(self, net_worths):
scheme = RiskAdjustedReturns(return_algorithm='sortino',
risk_free_rate=0,
target_returns=0,
window_size=1)
returns = net_worths[-2:].pct_change().dropna()
downside_returns = returns.copy()
downside_returns[returns < 0] = returns**2
expected_return = np.mean(returns)
downside_std = np.sqrt(np.std(downside_returns))
expected_ratio = (expected_return + 1E-9) / (downside_std + 1E-9)
sortino_ratio = scheme._sortino_ratio(returns)
assert sortino_ratio == expected_ratio
def test_sortino_ratio(self, net_worths):
scheme = RiskAdjustedReturns(
return_algorithm='sortino', risk_free_rate=0, target_returns=0)
returns = net_worths['net_worth'].diff()
sortino_ratio = scheme._sortino_ratio(returns)
downside_returns = pd.Series([0])
returns[returns < 0] = returns ** 2
expected_return = returns.mean()
downside_std = np.sqrt(downside_returns.mean())
expected_ratio = expected_return / (downside_std + 1E-9)
assert sortino_ratio == expected_ratio
def env():
context = {
"base_instrument": USD,
"actions": {
"pairs": [USD / BTC],
"stop_loss_percentages": [0.02, 0.04, 0.06],
"take_profit_percentages": [0.01, 0.02, 0.03],
"trade_sizes": 10,
"trade_side": TradeSide.BUY,
"trade_type": TradeType.MARKET,
"order_listener": None
},
"rewards": {
"return_algorithm": "sharpe",
"risk_free_rate": 0,
"target_returns": 0
},
"exchanges": {
"model_type": "FBM",
"hurst": 0.61,
"timeframe": "1d",
"base_price": 7500,
"base_volume": 12000
}
}
with TradingContext(**context):
action_scheme = ManagedRiskOrders()
reward_scheme = RiskAdjustedReturns()
exchange = Exchange()
portfolio = Portfolio(USD, [
Wallet(exchange, 100000 * USD),
Wallet(exchange, 0 * BTC)
])
env = TradingEnvironment(
portfolio=portfolio,
action_scheme=action_scheme,
reward_scheme=reward_scheme,
window_size=14,
enable_logger=False
)
return env