Deep Reinforcement Learning in Trading by Quantra presents instructions on how this model can accelerate the development of powerful trading strategies.
Deep Reinforcement Learning In Trading By Quantra
Deep Reinforcement Learning in Trading by Quantra provides you with a comprehensive walk-through on many skills that are useful for your trading. The coherent instructions on techniques and tutorials can help you understand the frameworks.
Through This Course, You Will Learn To Master:
- Finance and Math skills: Stochastic gradient descent, the Mean squared error, and so on.
- The application of Python: pandas, numpy, matplotlib, datetime, TA-lib, Tensorflow, Keras, SGD, and so on.
- Reinforcement Learning model: Double Q–Learning, Artificial Neural Networks, State, Rewards, Actions, Experience Replay, Exploration vs. Exploitation
The Content Of The Deep Reinforcement Learning In Trading By Quantran Covers:
- How the methods of deep reinforcement learning generate the advantages to trade more profitably.
- Instructions on input features for the buildup of a state, including candlesticks, technical indicators and time signatures.
- The whole process of creating and assembling state includes the development of input features in Python, how to increase the accuracy of the market move projection by the neutral network.
- Insights into the concepts of artificial neural networks for the variations of inputs.
- Guidelines on backtesting logic shed light on how to combine elements of the reinforcement learning model.
- The generation of RL model patterns and how to leverage the random data generator, etc. are openly shared for performance analysis and synthetic data.
- How to trade with the automated strategy to cut down on time and effort for the acceleration of profit momentum.
- Instructions on the installation of Python to your local machine.
- And so much more!
The course shows how reinforcement learning contributes to the process of creating, backtesting and paper trading, etc. The application of powerful strategies to real trading becomes much easier due to the framework.
There are many deep-dives into the trading methods and skills for your profitable trading. The Deep Reinforcement Learning in Trading by Quantra levels up your trading knowledge and skills. The more diverse your trading methods become, the more chances you have to gain the consistency of trading profitability.
About Thomas Starke
Thomas Starke is your instructor of Deep Reinforcement Learning in Trading. He leads a quant-trading team in AAAQuants, one of the top trading companies. His courses often mention various dimensions of topics and instruct illuminating methods for the consistency of trading profitability. Thomas has years of experience through working at the Vivienne Court, Memjet Australia, etc. He is the founder of a microchip design company. The project that Thomas Starke has worked on is research for Rolls-Royce PLC.
Quantra presents striking approaches and models to trading and investing. The courses and educational programs share with you the cutting-edge tools and techniques. Thus, you can develop the trading edges in such a volatile market.
The frameworks developed by the Quantra team are data-driven and robust models. The ultimate goal of the Quantra program is to help you maintain the consistency of high profitability.
The detailed instructions are combined with the illustrations of real case studies and examples. Quantra courses have the top-down approach for comprehensive walk-throughs.
For further information about Deep Reinforcement Learning in Trading by Quantra, in terms of price, samples, etc. or other courses/books sharing the same topic, you can reach out to our support team via Email, Skype or live chat on our website.