Leveraging artificial intelligence to build algorithmic trading strategies
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Transcript of Leveraging artificial intelligence to build algorithmic trading strategies
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Leveraging Artificial Intelligence to Build Algorithmic StrategiesBrought to you by:
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Welcome
Tad Slaff
CEO/Co-founderInovance
• Math background• 6+ years experience
applying AI and ML to algo trading
• Main expertise in forex
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Overview
1. Terminology2. Best Practices and Common Pitfalls3. Strategy Development Applications
1. Indicator Selection2. Pattern Recognition Algorithms3. Association Rule Learning
4. Building a live strategy with TRAIDE
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Terminology
• Artificial Intelligence• The study and design of intelligent
agents.• Intelligent agent: a system that
perceive its environment and takes action to maximize its chance of success [1].
• Machine Learning• Algorithms that can learn and
make predictions without being explicitly programmed [2].
• Pattern Recognition• Branch of machine learning
focused on uncovering patterns in data [3].
• Association Rule Learning• Discovering interesting
relationships, usually formatted as “if/then” statements [4].
• Big Data• The Four V’s: Volume, Velocity,
Variety, Veracity [5].
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Source: https://inovancetech.com/buzzwords.html
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Best Practices and Common Pitfalls
1 ) Defining Success• What are you trying to
achieve?
2 ) Simplicity• Do you really need to use AI
or machine-learning techniques?
3 ) Focus on Process• Where are the assumptions or
uncertainties in your workflow?
4 ) Skepticism• Are you confident in your
results?
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Indicator SelectionHow do I know which indicators to use when building my strategy?
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Indicator Selection: Machine-Learning AlgorithmsDecision Trees or Random Forests
• Splitting the data set using recursive partitioning.
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Indicator Selection: Machine Learning Techniques
Wrappers• Leveraging a machine-learning algorithm to select and
evaluate indicator subsets.
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Indicator Selection: Machine Learning Techniques
Ensemble Learning• Combining multiple,
uncorrelated classifiers to generate a singular, more robust signal.
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Pattern Recognition and Association Rule LearningHow do I find robust entry and exit signals based on the indicators I’ve selected?
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Pattern Recognition and Association Rule Learning
Pattern Recognition• Branch of machine learning focused on uncovering patterns
and regularities in data.
Association Rule Learning• Discovering interesting relationships, usually formatted as
“if/then” statements.
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Pattern Recognition and Association Rule Learning
1) Recognize Patterns
RSI(3) Open - SMA(50)
Long Between 50 and 70
Open over 20 pips above SMA(50)
Short Less than 25Open between 10 and 5 pips
below SMA(50)
2) Association Rules
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Pattern Recognition and Association Rule Learning
Advantages• Leverage machine-learning
algorithms• Transparent• Easily manually
implemented• Leverage human intuition
Disadvantages• Difficult with high
complexity• Large number of indicators• More complex algos or
ensembles• Not inherently easy to
automate• Requires human input
(subjective analyses)
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Let’s build a strategy!
Easily apply pattern recognition and association rule learning techniques to build your strategy.
Live Strategy:https://traide.inovancetech.com/#/simulation/56f183a8e4b0aa46bd79ae82
TRAIDE
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To Learn Automated Trading
Connect With Us:
SINGAPORE11 Collyer Quay, #10-10, The Arcade,Singapore - 049317Phone: +65-6221-3654
INDIAA-309, Boomerang,Chandivali Farm Road, Powai,Mumbai - 400 072Phone: +91-022-61691400