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Questions tagged [algorithmic-trading]

For questions about algorithmic trading (stocks, commodities bonds, etc.) and predictive financial algorithms in general.

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How to clip actions based on state in RL environment for trading (and other tips to approach optimal trade execution)?

I’m currently trying to use RL to analyze price impact in financial markets for optimal trade execution and have coded up a custom gymnasium environment to do so. Now, I'm deciding on which RL ...
walrus's user avatar
  • 1
0 votes
1 answer

Trading bot with RL, automated actions, nonconvergence

I am playing around with RL to develop a trading bot (using DQN). (Disclaimer: I know, that short term stock movements are near-random and having a bot that is actually useful not likely to happen. ...
Andy's user avatar
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2 votes
3 answers

Do I need to normalize all state-space variables? If so, how?

I am playing around with a DRL agent in a stock-trading environment. I have normalized all the external input data (the features that my agent will use). However, what about characteristics that don't ...
Vladimir Belik's user avatar
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1 answer

Does $S_{t+1}$ denote the future information in Q-learning?

In Q-learning, $Q(S_t,a)$ is updated by the Bellman equation. $Q(S_t,a) = r + \max_{a'}(Q(S_{t+1},a'))$ where $S_{t+1}$ is the future state. Let's say $S$ denotes the stock price, does it mean we are ...
L.Chau's user avatar
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1 vote
1 answer

How should I define the reward function for a stock trading-like game?

Problem setting Consider a game like trading a stock At each step, the agent can buy / sell a stock. Trade is a pair of ...
em1971's user avatar
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1 vote
1 answer

Is there a way to parallelise the RL training on multiple stocks to avoid the memory issue?

I have some plans in working with Reinforcement Learning in order to predict the stock price movement. For a stock like TSLA some training features might be the pivot price values and the set of the ...
Alex's user avatar
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1 vote
1 answer

Selecting features for a neural network: is it redundant to have a feature that is an average (or max, or min) of some other features

I'm trying to create a neural network that would able to look at the current price of a crypto asset and classify between a "BUY", "SELL" or "HOLD". So far for my input ...
Arthur Song's user avatar
1 vote
0 answers

Given the daily stock prices of the last 3 years, how should I sample the training data for episodic RL?

I am playing around with a stock trading agent trained via (deep) reinforcement learning, including memory replay. The agent is trained for 1000 episodes, where each episode consists of 180 timesteps (...
Scarysize's user avatar
  • 111
0 votes
1 answer

Looping over Sarsa algorithm for better Q values

Let's say an RL trading system places trades based on pricing data. Each episode represents 1 hour of trading, and there are 24 hours of data available. The Q table represents for a given state, what ...
blue-sky's user avatar
  • 335
1 vote
4 answers

What are the most popular and effective approaches to leveraging AI for stock price prediction?

Currently, what are the most popular and effective approaches to leveraging AI for stock price prediction? It seems like there could be several approaches and problem formulations: Supervised ...
information_interchange's user avatar
1 vote
0 answers

What are the pros and cons of deep learning and machine learning to develop a trading system?

As I want to start coding a new Trading AI this year (first based on Python and later maybe in C++) I stumbled over the following question: Today, I would like to make a pro/contra list with you in ...
Nils Schulz's user avatar
1 vote
0 answers

How can we make sure how well the reinforcement learning agent works on a stock dataset?

I read a paper, which is about Deep Reinforcement Learning and it tries to use this method on stock data set. It has been shown that it reaches the maximum return (profit). It has been implemented in ...
Mahdi Amrollahi's user avatar
1 vote
1 answer

How do you game an automatic trading system by messing with data, as opposed to hacking the algorithm itself?

There was a recent question on adversarial AI applications, which led me to start digging around. Here my interest is not general, but specific: How do you game an automatic trading system by messing ...
DukeZhou's user avatar
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1 vote
2 answers

Are there profitable hedge funds using AI? [closed]

Is there any research in this area?
bobbyor's user avatar
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8 votes
1 answer

Suitable reward function for trading buy and sell orders

I am working to build a deep reinforcement learning agent which can place orders (i.e. limit buy and limit sell orders). The actions are ...
fgauth's user avatar
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