I'm reading the environment. Is this still active?

Hi Yvictor

Thanks for your TradingGym project which is really interesting and helpful.

I’m a bit unclear with two things in trading_env.py.

(1)Will code line [next_index = self.step_st+self.obs_len+1] in self.step function result in a blank trading day?

Suppose obs_len = 10 and step_len =5, the initial self.obs_res = self.obs_features[0:10], next_index = self.step_st+self.obs_len+1 =11, where is the 10th day info? Considering python list design exclude the last element. Is this a bug or I miss something?

(2)Would it be nicer if reward_ret value is a percent return rather than a absolute value?
Something like
self.reward_fluctuant = (self.price_current*self.position_share - self.transaction_details.iloc[-1]['price_mean']self.position_share - self.feeabs_pos) / self.transaction_details.iloc[-1]['price_mean']

By the way, I notice that, every step return a reward which is actually a stock value (cumulative return) rather than a flow value (the interval return). I doubt which is reasonable. Would you mind explaining something about this, it would be really appreciated. Thanks for your code and time.

Have a good day.

Maybe line 207 should be changed from

 if self.step_st+self.obs_len+self.step_len >= len(self.price):

to

 if self.step_st+self.obs_len >= len(self.price):

Hey brother i am new to git hub and i saw you that you are discussing about trading algo software bro can you make me a algo for gold trading fir trading view

Hey! Great project, really excited about it but having a small problem.

Can't run the agent, env.backtest is causing a problem, so in the trading_env.make function I added the parameter backtest=1, and now the backtest_done is popping up as having to attribute.

This seems to be a problem with threading, from what I can read online.

Has anyone had success beyond the point of this error? Is it a package version I can downgrade?

Attached my notebook.
trading-gym-andy.zip

no matter what I add to trading_env.make, including backtest_done=0 or 1, it fails to see it as an attribute... wtf!

Thank you for this I was looking for something like this. when I am trying out this I am getting a assertion error like this

self.ax.lines.remove(self.price_plot[0])
AttributeError: 'trading_env' object has no attribute 'ax'

data frame sample

>>> df.head()
   serial_number        Date   Open   High    Low  Close      Volume
0              0  1998-01-02  13.63  16.25  13.50  16.25   6411700.0
1              1  1998-01-05  16.50  16.56  15.19  15.88   5820300.0
2              2  1998-01-06  15.94  20.00  14.75  18.94  16182800.0
3              3  1998-01-07  18.81  19.00  17.31  17.50   9300200.0
4              4  1998-01-08  17.44  18.62  16.94  18.19   6910900.0

I want to use Volume column alone as the my observation state. This is the whole code

import random
import numpy as np
import pandas as pd
import trading_env

df = pd.read_csv('./dataset/AAPL.csv')

df.rename(columns={'Unnamed: 0':'serial_number'},inplace=True)

env = trading_env.make(env_id='training_v1', obs_data_len=50, step_len=14,
                       df=df, fee=0.1, max_position=5, deal_col_name='Close', 
                       feature_names=['Volume'])


env.reset()
env.render()

state, reward, done, info = env.step(random.randrange(3))

### randow choice action and show the transaction detail
for i in range(500):
    print(i)
    state, reward, done, info = env.step(random.randrange(3))
    print(state, reward)
    env.render()
    if done:
        break

env.transaction_details

IMPORTANT: Can you please tell me what is the action space index for buy, sell and hold. I can see action space consists of three integers but can't find where its mapped to.

sorry

What's can I do?
please help!

May I know if there is any description about the environment such as what is the obs, reward, action?

Also, may I know what is the difference between backtest and training environments?

thanks!

Backtesting
loading env just like training
env = trading_env.make(env_id='backtest_v1', obs_data_len=1024, step_len=512,
df=df, fee=0.1, max_position=5, deal_col_name='Price',
feature_names=['Price', 'Volume',
'Ask_price','Bid_price',
'Ask_deal_vol','Bid_deal_vol',
'Bid/Ask_deal', 'Updown'])

start to backtest
agent = YourAgent()

transactions = []
while not env.backtest_done:
state = env.backtest()
done = False
while not done:
state, reward, done, info = env.step(agent.choice_action(state))
#print(state, reward)
#env.render()
if done:
transactions.append(info)
break
transaction = pd.concate(transactions)
transaction

Making new env: backtest_v1
Traceback (most recent call last):
File "\TradingGym-master\BackTest.py", line 32, in
state = env.backtest()
AttributeError: 'trading_env' object has no attribute 'backtest'

how could I fix this.

Hi, thanks for another new great gym environment!

Its not actual issue, more like question:
I am curious about actual RL trained strategies examples (not necessary profitable), because I didn't find one and OpenAI didn't pay much attention to financial gyms. It will be much easier to learn on existed examples, how tune architecture or parameters. I would be very grateful if you point me out useful links if you know some. Thanks