tensortrade.env.default.rewards module

class tensortrade.env.default.rewards.PBR(price: tensortrade.feed.core.base.Stream)

Bases: tensortrade.env.default.rewards.TensorTradeRewardScheme

A reward scheme for position-based returns.

• Let \(p_t\) denote the price at time t.
• Let \(x_t\) denote the position at time t.
• Let \(R_t\) denote the reward at time t.

Then the reward is defined as, \(R_{t} = (p_{t} - p_{t-1}) \cdot x_{t}\).

Parameters:price (Stream) – The price stream to use for computing rewards.

get_reward(portfolio: Portfolio) → float

Gets the reward associated with current step of the episode.

Parameters:portfolio (Portfolio) – The portfolio associated with the TensorTradeActionScheme. Returns:float – The reward for the current step of the episode.

on_action(action: int) → None

registered_name = 'pbr'

reset() → None

Resets the position and feed of the reward scheme.

class tensortrade.env.default.rewards.RiskAdjustedReturns(return_algorithm: str = 'sharpe', risk_free_rate: float = 0.0, target_returns: float = 0.0, window_size: int = 1)

Bases: tensortrade.env.default.rewards.TensorTradeRewardScheme

A reward scheme that rewards the agent for increasing its net worth, while penalizing more volatile strategies.

Parameters:

• return_algorithm ({'sharpe', 'sortino'}, Default 'sharpe'.) – The risk-adjusted return metric to use.
• risk_free_rate (float, Default 0.) – The risk free rate of returns to use for calculating metrics.
• target_returns (float, Default 0) – The target returns per period for use in calculating the sortino ratio.
• window_size (int) – The size of the look back window for computing the reward.

get_reward(portfolio: Portfolio) → float

Computes the reward corresponding to the selected risk-adjusted return metric.

Parameters:portfolio (Portfolio) – The current portfolio being used by the environment. Returns:float – The reward corresponding to the selected risk-adjusted return metric.

class tensortrade.env.default.rewards.SimpleProfit(window_size: int = 1)

Bases: tensortrade.env.default.rewards.TensorTradeRewardScheme

A simple reward scheme that rewards the agent for incremental increases in net worth.

Parameters:window_size (int) – The size of the look back window for computing the reward.

window_size

The size of the look back window for computing the reward.

Type:int

get_reward(portfolio: Portfolio) → float

Rewards the agent for incremental increases in net worth over a sliding window.

Parameters:portfolio (Portfolio) – The portfolio being used by the environment. Returns:float – The cumulative percentage change in net worth over the previous window_size time steps.

class tensortrade.env.default.rewards.TensorTradeRewardScheme

Bases: tensortrade.env.generic.components.reward_scheme.RewardScheme

An abstract base class for reward schemes for the default environment.

get_reward(portfolio) → float

Gets the reward associated with current step of the episode.

Parameters:portfolio (Portfolio) – The portfolio associated with the TensorTradeActionScheme. Returns:float – The reward for the current step of the episode.

reward(env: tensortrade.env.generic.environment.TradingEnv) → float

Computes the reward for the current step of an episode.

Parameters:env (TradingEnv) – The trading environment Returns:float – The computed reward.

tensortrade.env.default.rewards.get(identifier: str) → tensortrade.env.default.rewards.TensorTradeRewardScheme

Gets the RewardScheme that matches with the identifier.

Parameters:identifier (str) – The identifier for the RewardScheme Returns:TensorTradeRewardScheme – The reward scheme associated with the identifier. Raises:KeyError: – Raised if identifier is not associated with any RewardScheme