Expected Value and Kelly Criterion
High-frequency trading (HFT) firms
The best for beginners is alternative data strategy
if the economy/market is up or down you make money regardless
if the economy/market is down, you lose money, if it’s up you make money. Most trading firms are beta-based
Languages used for machine learning:
Examples of Popular ML Training Techniques/Algorithms
Naïve Bayes Classifier Algorithm K Means Clustering Algorithm Support Vector Machine Algorithm Apriori Algorithm Linear Regression Logistic Regression Artificial Neural Networks Random Forests Decision Trees K Nearest Neighbors Convolution Neural Network Recurrent Neural Network
Python Interactive Brokers Installation and Walkthrough
Commissions – The costs of commissions and data subscriptions add up, especially for those executing a lot of trades. While IB is known to offer low commissions, this is not the case across all markets. They also charge for data and don’t pay out interest under a certain threshold. It’s worth comparing the cost-effectiveness of trading with IB versus some of the other brokers out there before investing your time into learning the API.
From the article:
Liew stresses that the most important part of algorithmic trading is “understanding under which types of market conditions your robot will work and when it will break down” and “understanding when to intervene.” Algorithmic trading can be rewarding, but the key to success is understanding. Any course or teacher promising high rewards without sufficient understanding should be a major warning sign to stay away.