[WIP] Action order management

docs/source/components/actions/ContinuousActions.md

@@ -1,6 +1,6 @@
 # ContinuousActions
 
-Simple continuous scheme, which calculates the trade amount as a fraction of the total balance.
+Simple continuous scheme, which calculates the trade size as a fraction of the total balance.
 
 ## Key Variables
 
@@ -9,7 +9,7 @@ Simple continuous scheme, which calculates the trade amount as a fraction of the
 - `instrument`
   - The number of bins to divide the total balance by. Defaults to 20 (i.e. 1/20, 2/20, ..., 20/20).
 - `instrument`
-  - The maximum amount above the current price the scheme will pay for an instrument. Defaults to 1.0 (i.e. 1%).
+  - The maximum size above the current price the scheme will pay for an instrument. Defaults to 1.0 (i.e. 1%).
 
 ## Setters & Properties
 

docs/source/components/actions/DiscreteActions.md

@@ -1,6 +1,6 @@
 # DiscreteActions
 
-Simple discrete scheme, which calculates the trade amount as a fraction of the total balance.
+Simple discrete scheme, which calculates the trade size as a fraction of the total balance.
 
 ## Key Variables
 
@@ -9,7 +9,7 @@ Simple discrete scheme, which calculates the trade amount as a fraction of the t
 - `actions_per_instrument`
   - The number of bins to divide the total balance by. Defaults to 20 (i.e. 1/20, 2/20, ..., 20/20).
 - `max_allowed_slippage_percent`
-  - The maximum amount above the current price the scheme will pay for an instrument. Defaults to 1.0 (i.e. 1%).
+  - The maximum size above the current price the scheme will pay for an instrument. Defaults to 1.0 (i.e. 1%).
 
 ## Setters & Properties
 
@@ -40,4 +40,4 @@ from tensortrade.actions import DiscreteActions
 action_scheme = DiscreteActions(n_actions=20, instrument='BTC')
 ```
 
-_This discrete action scheme uses 20 discrete actions, which equates to 4 discrete amounts for each of the 5 trade types (market buy/sell, limit buy/sell, and hold). E.g. [0,5,10,15]=hold, 1=market buy 25%, 2=market sell 25%, 3=limit buy 25%, 4=limit sell 25%, 6=market buy 50%, 7=market sell 50%, etc…_
+_This discrete action scheme uses 20 discrete actions, which equates to 4 discrete sizes for each of the 5 trade types (market buy/sell, limit buy/sell, and hold). E.g. [0,5,10,15]=hold, 1=market buy 25%, 2=market sell 25%, 3=limit buy 25%, 4=limit sell 25%, 6=market buy 50%, 7=market sell 50%, etc…_

docs/source/components/actions/MultiDiscreteActions.md

@@ -1,8 +1,8 @@
 # MultiDiscreteActions
 
-Discrete scheme, which calculates the trade amount as a fraction of the total balance for each instrument provided.
+Discrete scheme, which calculates the trade size as a fraction of the total balance for each instrument provided.
 
-The trade type is determined by `action % len(TradeType)`, and the trade amount is determined by the multiplicity of the action.
+The trade type is determined by `action % len(TradeType)`, and the trade size is determined by the multiplicity of the action.
 For example, `0 = HOLD`, `1 = LIMIT_BUY|0.25`, `2 = MARKET_BUY|0.25`, `5 = HOLD`, `6 = LIMIT_BUY|0.5`, 7 = `MARKET_BUY|0.5`, etc.
 
 ## Key Variables
@@ -12,7 +12,7 @@ For example, `0 = HOLD`, `1 = LIMIT_BUY|0.25`, `2 = MARKET_BUY|0.25`, `5 = HOLD`
 - `_actions_per_instrument`
   - The number of bins to divide the total balance by. Defaults to 20 (i.e. 1/20, 2/20, ..., 20/20).
 - `_max_allowed_slippage_percent`
-  - The maximum amount above the current price the scheme will pay for an instrument. Defaults to 1.0 (i.e. 1%).
+  - The maximum size above the current price the scheme will pay for an instrument. Defaults to 1.0 (i.e. 1%).
 
 ## Setters & Properties
 
@@ -42,4 +42,4 @@ from tensortrade.actions import MultiDiscreteActions
 action_scheme = MultiDiscreteActions(n_actions=20, instrument='BTC')
 ```
 
-_This discrete action scheme uses 20 discrete actions, which equates to 4 discrete amounts for each of the 5 trade types (market buy/sell, limit buy/sell, and hold). E.g. [0,5,10,15]=hold, 1=market buy 25%, 2=market sell 25%, 3=limit buy 25%, 4=limit sell 25%, 6=market buy 50%, 7=market sell 50%, etc…_
+_This discrete action scheme uses 20 discrete actions, which equates to 4 discrete sizes for each of the 5 trade types (market buy/sell, limit buy/sell, and hold). E.g. [0,5,10,15]=hold, 1=market buy 25%, 2=market sell 25%, 3=limit buy 25%, 4=limit sell 25%, 6=market buy 50%, 7=market sell 50%, etc…_

docs/source/components/component_types/action_scheme.md

@@ -12,4 +12,4 @@ from tensortrade.actions import DiscreteActions
 action_scheme = DiscreteActions(n_actions=20, instrument='BTC')
 ```
 
-_This discrete action scheme uses 20 discrete actions, which equates to 4 discrete amounts for each of the 5 trade types (market buy/sell, limit buy/sell, and hold). E.g. [0,5,10,15]=hold, 1=market buy 25%, 2=market sell 25%, 3=limit buy 25%, 4=limit sell 25%, 6=market buy 50%, 7=market sell 50%, etc…_
+_This discrete action scheme uses 20 discrete actions, which equates to 4 discrete sizes for each of the 5 trade types (market buy/sell, limit buy/sell, and hold). E.g. [0,5,10,15]=hold, 1=market buy 25%, 2=market sell 25%, 3=limit buy 25%, 4=limit sell 25%, 6=market buy 50%, 7=market sell 50%, etc…_

docs/source/components/exchanges/Exchange.md

@@ -71,7 +71,7 @@ Inside of the [README](../README.md), you'll have seen the reason why we have th
   - The performance of the active account on the exchange since the last reset.
 - `generated_space`
   - The initial shape of the observations generated by the exchange, before feature transformations.
-- `generated_columns`
+- `observation_columns`
   - The list of column names of the observation data frame generated by the exchange, before feature transformations.
 - `observation_space`
   - The final shape of the observations generated by the exchange, after feature transformations.

docs/source/components/exchanges/live/CCXTExchange.md

@@ -35,7 +35,7 @@ An exchange for trading on CCXT-supported cryptocurrency exchanges.
   - The performance of the active account on the exchange since the last reset.
 - `generated_space`
   - The initial shape of the observations generated by the exchange, before feature transformations.
-- `generated_columns`
+- `observation_columns`
   - The list of column names of the observation data frame generated by the exchange, before feature transformations.
 - `observation_space`
   - The final shape of the observations generated by the exchange, after feature transformations.

docs/source/components/exchanges/live/InteractiveBrokersExchange.md

@@ -35,7 +35,7 @@ An exchange for trading using the Interactive Brokers API.
   - The performance of the active account on the exchange since the last reset.
 - `generated_space`
   - The initial shape of the observations generated by the exchange, before feature transformations.
-- `generated_columns`
+- `observation_columns`
   - The list of column names of the observation data frame generated by the exchange, before feature transformations.
 - `observation_space`
   - The final shape of the observations generated by the exchange, after feature transformations.

docs/source/components/exchanges/simulated/FBMExchange.md

@@ -47,7 +47,7 @@ We generate prices, and train on that. Simple.
   - The performance of the active account on the exchange since the last reset.
 - `generated_space`
   - The initial shape of the observations generated by the exchange, before feature transformations.
-- `generated_columns`
+- `observation_columns`
   - The list of column names of the observation data frame generated by the exchange, before feature transformations.
 - `observation_space`
   - The final shape of the observations generated by the exchange, after feature transformations.

docs/source/components/exchanges/simulated/SimulatedExchange.md

@@ -39,7 +39,7 @@ The reason we create simulated exchanges is so we create more robust models quic
   - The performance of the active account on the exchange since the last reset.
 - `generated_space`
   - The initial shape of the observations generated by the exchange, before feature transformations.
-- `generated_columns`
+- `observation_columns`
   - The list of column names of the observation data frame generated by the exchange, before feature transformations.
 - `observation_space`
   - The final shape of the observations generated by the exchange, after feature transformations.

docs/source/components/rewards/SimpleProfit.md

@@ -37,7 +37,7 @@ When the bot says buy, it sets the variable `_is_holding_instrument` to `True`,
 We see that inside of this line of code here. This allows us to check to see if we've made a profit later.
 
 ```py
-elif trade.is_buy and trade.amount > 0:
+elif trade.is_buy and trade.size > 0:
     self._purchase_price = trade.price
     self._is_holding_instrument = True
 
@@ -48,10 +48,10 @@ elif trade.is_buy and trade.amount > 0:
 We then sell afterward using the original trade price as a reference. Which is suggested in the lines below:
 
 ```py
-if trade.is_sell and trade.amount > 0:
+if trade.is_sell and trade.size > 0:
     self._is_holding_instrument = False
     profit_per_instrument = trade.price - self._purchase_price
-    profit = trade.amount * profit_per_instrument
+    profit = trade.size * profit_per_instrument
     profit_sign = np.sign(profit)
 
     return profit_sign * (1 + (5 ** np.log10(abs(profit))))

docs/source/examples/overview.md

@@ -15,7 +15,7 @@ The beginning of the code in [Exchange](https://github.com/notadamking/tensortra
 class Exchange(object, metaclass=ABCMeta):
     """An abstract exchange for use within a trading environment."""
 
-    def __init__(self, base_instrument: str = 'USD', dtype: TypeString = np.float32, feature_pipeline: FeaturePipeline = None):
+    def __init__(self, base_instrument: str = 'USD', dtype: Union[type, str] = np.float32, feature_pipeline: FeaturePipeline = None):
         """
         Arguments:
             base_instrument: The exchange symbol of the instrument to store/measure value in.
@@ -50,8 +50,8 @@ class SimulatedExchange(Exchange):
         self._commission_percent = self.default('commission_percent', 0.3, kwargs)
         self._base_precision = self.default('base_precision', 2, kwargs)
         self._instrument_precision = self.default('instrument_precision', 8, kwargs)
-        self._min_trade_amount = self.default('min_trade_amount', 1e-6, kwargs)
-        self._max_trade_amount = self.default('max_trade_amount', 1e6, kwargs)
+        self._min_trade_size = self.default('min_trade_size', 1e-6, kwargs)
+        self._max_trade_size = self.default('max_trade_size', 1e6, kwargs)
 
         self._initial_balance = self.default('initial_balance', 1e4, kwargs)
         self._observation_columns = self.default(

docs/source/examples/trading_context.json

@@ -178,8 +178,8 @@
         "    api_secret_key: \"do8u43hgiurwfnlveio\"\n",
         "    min_trade_price: 1e-7\n",
         "    max_trade_price: 1e7\n",
-        "    min_trade_amount: 1e-4\n",
-        "    max_trade_amount: 1e4\n",
+        "    min_trade_size: 1e-4\n",
+        "    max_trade_size: 1e4\n",
         "```\n",
         "\n",
         "\n",
@@ -195,8 +195,8 @@
         "      \"instrument_precision\": 10,\n",
         "      \"min_trade_price\": 1e-7,\n",
         "      \"max_trade_price\": 1e7,\n",
-        "      \"min_trade_amount\": 1e-4,\n",
-        "      \"max_trade_amount\": 1e4,\n",
+        "      \"min_trade_size\": 1e-4,\n",
+        "      \"max_trade_size\": 1e4,\n",
         "      \"initial_balance\": 1e5,\n",
         "      \"window_size\": 5,\n",
         "      \"should_pretransform_obs\": true,\n",