Learning Track: Algorithmic Trading in Cryptocurrency and Forex
9 Hours
A 4-course specialisation for new-age traders, programmers and analysts, who wish to ride the forex and cryptocurrency markets. Learn to use quantitative techniques taught by market practitioners, identify rare trading opportunities and automate your trading. Leverage the power of backtesting to analyse past performance and enhance your trading skills. Get over 8 new strategy ideas, tested over historical data that may give you an edge in competitive markets.
Level
BEGINNER to ADVANCED
Authors
FXCM
QuantInsti®
Price Lifetime Access Limited Time Offer
₹9100 /-
Original Price: ₹40696
78% OFF
- Live Trading
- Learning Track
- Prerequisites
- Syllabus
- About author
- Testimonials
- Faqs
Live Trading
Create a momentum trading strategy in the Forex market.
Create and backtest a forex value strategy based on REER.
Explain macroeconomic factors affecting the forex market and analyze various forex valuation methods.
Create and backtest three different types of strategies: Ichimoku Cloud Strategy, Calendar Anomalies and Divergence Strategy on Cryptocurrencies.
Backtest and implement long-only momentum strategy, pairs trading and K-means clustering trading strategy on cryptocurrencies.
Paper trade and live trade your strategies without any installations or downloads.
Skills Covered
Strategy Paradigms
- Pairs trading strategy
- Momentum strategy
- Hurst Exponent strategy
- REER trading strategy
- Calendar Anomalies
Technical Indicators & Core Concepts
- Ichimoku cloud
- Aroon up and down
- Unsupervised learning
- K-means Clustering
- FX Valuation
Python Libraries
- TA-Lib
- Matplotlib
- Pandas
- Numpy
- Sklearn's K-Means
learning track 6
Algorithmic Trading in Cryptocurrency and Forex
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INTERMEDIATE
ADVANCED
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learning track
Algorithmic Trading in Cryptocurrency and Forex
Full Learning Track
These courses are specially curated to help you with end-to-end learning of the subject.
Need help? Write to us at quantra@quantinsti.com or call us at +91 8450963428.
Course Features
CommunityFaculty Support on Community
- Interactive Coding Exercises
Interactive Coding Practice
- Capstone Project
Capstone Project using Real Market Data
- Trade & Learn Together
Trade and Learn Together
- Get Certified
Get Certified
Prerequisites
You should understand the basic terminology around financial markets such as sell, buy, margin, entry positions, exit positions, etc. But if you want to be able to code and implement the strategies in Python, the ability to work with numpy and pandas dataframe in Python is required. These skills are covered in the course ‘Python for Trading: Basic’.
Syllabus
Forex Trading using Python: Basics
- Introduction to Forex TradingThis section covers the basics of Forex trading and explains how macroeconomic factors affect the Forex market.
Introduction to Forex Trading5m 11s
Quantra Features and Guidance3m 48s
What is PIP?2m
What is Spread?2m
What is Spread Value?2m
Factors Affecting Forex Trading4m 28s
Interest Rate2m
Inflation2m
Participants in the Forex Market2m
- Momentum Trading StrategyThis section focuses on explaining the details of the momentum trading strategy, and coding and backtesting it in Quantra Blueshift.
Momentum Trading Strategy Overview2m 42s
What is Momentum Strategy?2m
Momentum Strategy Rationale2m
Momentum Strategy Logic2m
Ranking Criteria for Currency Pairs2m
Approach to Capital Allocation2m
Rebalance Frequency2m
Quantra Blueshift Functions10m
Code the Momentum Trading Strategy3m 20s
Quantra Blueshift Features2m
Initialize Function2m
Define Currency List5m
Syntax for Schedule Function2m
Fetch the Historical Data5m
Calculate Returns5m
Method to Place Order2m
Assessment Test On Forex Markets and Momentum Strategy12m
- Live Trading on BlueshiftThis section will walk you through the steps involved in taking your trading strategy live. You will learn about backtesting and the live trading platform, Blueshift. You will learn about code structure, various functions used to create a strategy and finally, paper or live trade on Blueshift.Uninterrupted Learning Journey with Quantra2m
Section Overview2m 19s
Live Trading Overview2m 41s
Vectorised vs Event Driven2m
Process in Live Trading2m
Real-Time Data Source2m
Blueshift Code Structure2m 57s
Important API Methods10m
Schedule Strategy Logic2m
Fetch Historical Data2m
Place Orders2m
Backtest and Live Trade on Blueshift4m 5s
Additional Reading10m
Blueshift Data FAQs10m
- Live Trading TemplateBlueshift Live Trading TemplatePaper/Live Trading Long Short FX Strategy10m
FAQs for Live Trading on Blueshift10m
- Risk ManagementThis section demonstrates how to manage the intraday risk while trading in the Forex market.
Risk Management in Forex2m 49s
Downside of Leverage2m
Stop Loss2m
How to Allocate Capital?2m
Course Summary1m 55s
Assessment Test - II6m
Value Strategy in Forex
- Introduction to the CourseThis section discusses how different macroeconomic factors such as inflation, balance of trade, etc. affect the forex market.
Introduction to the Course1m 51s
Quantra Features and Guidance3m 48s
Macroeconomic Factors Affecting Forex Market5m 26s
Balance of Trade2m
Effect of Interest Rates2m
Carry Trade2m
Effect of Inflation2m
- Valuation of ForexThis section helps you understand different Forex valuation methods such as Purchasing Power Parity (PPP), Nominal Effective Exchange Rate (NEER) and Real Effective Exchange Rate (REER).
Purchasing Power Parity (PPP)3m 52s
Exchange Rate Using PPP2m
Valuation Using PPP2m
Relative PPP2m
Compute Exchange Rate2m
Real Effective Exchange Rate (REER)3m 14s
Nominal Exchange Rate2m
Real Exchange Rate2m
Nominal and Real Effective Exchange Rate2m
Calculation of REER10m
REER Formula2m
Test on Forex and Valuation of Forex14m
- Forex Value Strategy: LogicThis section explains the working of the strategy and provides the logic behind it.Forex Value Strategy2m 10s
REER Data Source2m
Strategy Logic2m
Valuation Methods2m
Trading Signal Based on REER2m
- Forex Value Strategy: ImplementationAfter learning about the strategy logic, this section moves on to explain the Python code for implementing it and demonstrates the returns from it. It also provides the downloadable Python code for the strategy.Code the Forex Value Strategy2m 6s
Download REER Data5m
How to Use Jupyter Notebook?2m 5s
FX Value Strategy in Python10m
Frequently Asked Questions10m
Read the Data5m
Generate Trading Signal5m
Fill NaN Values2m
Compute Strategy Returns5m
Plot the Strategy Returns5m
Course Summary1m 2s
Test on Forex Value Strategy10m
- Run Codes Locally on Your MachineLearn to install the Python environment in your local machine.Uninterrupted Learning Journey with Quantra2m
Python Installation Overview1m 59s
Flow Diagram10m
Install Anaconda on Windows10m
Install Anaconda on Mac10m
Know your Current Environment2m
Troubleshooting Anaconda Installation Problems10m
Creating a Python Environment10m
Changing Environments2m
Quantra Environment2m
Troubleshooting Tips For Setting Up Environment10m
How to Run Files in Downloadable Section?10m
Troubleshooting For Running Files in Downloadable Section10m
- Live Trading on IBridgePySection Overview2m 2s
Live Trading Overview2m 41s
Vectorised vs Event Driven2m
Process in Live Trading2m
Real-Time Data Source2m
Code Structure2m 15s
API Methods10m
Schedule Strategy Logic2m
Fetch Historical Data2m
Place Orders2m
IBridgePy Course Link10m
Additional Reading10m
Frequently Asked Questions10m
- Paper and Live TradingIn this section, a live trading strategy template will be provided to you. You can tweak the strategy template to deploy your strategies in the live market!Template Documentation10m
Template Code File2m
- Downloadable ResourcesYou can download the Python strategy codes at the end of the course.Python Codes and Data2m
Crypto Trading Strategies: Intermediate
- Introduction to CryptocurrenciesBefore moving on to cryptocurrency trading, it is important to understand the basic concepts of cryptocurrencies. This includes topics like crypto wallets, exchanges, transactions, trading bots etc.
Prologue2m 29s
Course Structure2m
Frequently Asked Questions2m
Quantra Features and Guidance3m 48s
What Are Cryptocurrencies?2m 10s
Transactions2m
Crypto Wallets4m 27s
Confirmation2m
E-Wallets Have..2m
Transaction Fee2m
Wallet Risk2m
What Are Trading Bots?2m
Bots2m
Exchange2m
Additional Reading on Cryptocurrencies2m
Additional Reading on Blockchain2m
Test on Basic Concepts of Cryptocurrencies10m
- Getting Cryptocurrency DataCryptocurrency Data5m
Additional Reading for Crypto Assets2m
- Trading Using Calendar AnomaliesIn this section, learn how to perform cryptocurrency trading using the calendar anomalies strategy, along with its Python code and strategy returns.
Calendar Anomalies Strategy Overview1m 45s
Calendar Anomalies2m
Calendar Anomalies in Cryptocurrency2m
Day of the Week Anomaly2m
The Best Day to Buy the Bitcoin2m
The Best Day to Sell the Bitcoin2m
Strategy Code Overview1m 17s
How to Use Jupyter Notebook?2m 5s
The Day of the Week Strategy10m
Frequently Asked Questions10m
Load Data From Csv File2m
Daily Percent Change2m
The Highest Sharpe Ratio Day5m
Strategy Returns5m
Test on Calendar Anomalies Strategy10m
- Ichimoku CloudIn this section, you will learn how to code and backtest Ichimoku Cloud cryptocurrency trading strategy using Python and determine the strategy returns.Ichimoku Cloud2m
Ichimoku Cloud2m
Conversion Line2m
Leading Span A2m
Cloud2m
Trend2m
Moving Average Crossover2m
Calculate and Plot the Ichimoku Cloud10m
Rolling High Value5m
Ichimoku Cloud Based Strategy5m
Generating Buy Signals5m
Strategy Returns5m
Test on Ichimoku Cloud Trading Strategy10m
- Transaction Cost and SlippageThe journey towards building a good backtest for a strategy idea is incomplete without considering the transaction costs and slippages. In simple words, transaction costs encompass brokerage, commission, etc. Slippage is the difference between the expected and executed price. Learn these concepts and understand how to incorporate them into your backtesting code.Transaction Cost and Slippage2m
Calculation of Transaction Cost5m
Calculation of Slippage5m
Transaction Costs and Slippage5m
Additional Reading2m
- Performance AnalysisTo understand whether your strategy is working, you need to analyse certain metrics. In this section, you will learn how to evaluate the trade level metrics to depict how well the strategy has performed over a certain period of time, as well as evaluate the performance of your strategy based on returns, risk and both.Trade Level Analytics5m
Average PnL Per Trade5m
Win Percentage5m
Average Trade Duration5m
Additional Reading on Trade Level Analytics2m
Performance Metrics5m
Maximum Drawdown5m
Additional Reading on Performance Metrics10m
- Divergence StrategyIn this section, you will learn how to trade the divergence between RSI and price series and the risks associated with intraday trading using AROON indicator and determine the strategy returns. At the end of the course, you will be provided with the downloadable strategy codes.Divergence Strategy2m
The Spread2m
Aroon Up Value2m
Divergence Strategy10m
Upspread2m
Calculate the RSI5m
Calculate the Aroon Values5m
Aroon of RSI2m
Calculate the Spread5m
The Threshold of Spread2m
Generate Buy Signals5m
Plot the Strategy Returns5m
Test on Divergence Strategy10m
Additional Reading2m
Look-Ahead Bias in Backtesting2m
- Risk ManagementIn this section, you will learn the importance of managing risk while trading. You will also discover a few risk management techniques.Risk Management2m
- Run Codes Locally on Your MachineLearn to install the Python environment in your local machine.Uninterrupted Learning Journey with Quantra2m
Python Installation Overview1m 59s
Flow Diagram10m
Install Anaconda on Windows10m
Install Anaconda on Mac10m
Know your Current Environment2m
Troubleshooting Anaconda Installation Problems10m
Creating a Python Environment10m
Changing Environments2m
Quantra Environment2m
Troubleshooting Tips For Setting Up Environment10m
How to Run Files in Downloadable Section?10m
Troubleshooting For Running Files in Downloadable Section10m
- Live Trading on IBridgePySection Overview2m 2s
Live Trading Overview2m 41s
Vectorised vs Event Driven2m
Process in Live Trading2m
Real-Time Data Source2m
Code Structure2m 15s
API Methods10m
Schedule Strategy Logic2m
Fetch Historical Data2m
Place Orders2m
IBridgePy Course Link10m
Additional Reading10m
Frequently Asked Questions10m
- Paper and Live TradingIn this section, a live trading strategy template will be provided to you. You can tweak the strategy template to deploy your strategies in the live market!Template Documentation10m
Template Codes2m
- Capstone ProjectIn this section, you will apply the knowledge you have gained in the course so far. You will generate buy or sell signals based on the technical indicators covered in this course.Getting Started2m
Problem Statement2m
- Downloadable ResourcesYou can download the Python strategy codes at the end of the course.Summary2m
Next Steps2m
Python Codes and Data2m
Crypto Trading Strategies: Advanced
- Machine Learning in Cryptocurrency TradingThis section explains the working and implementation of an unsupervised machine learning algorithm called K-Means and how it can be used in cryptocurrency trading to capture market trends.
Introduction to the Course1m 56s
Quantra Features and Guidance3m 48s
Understanding K-Means Algorithm3m 44s
Unsupervised Learning2m
Locating the Cluster Center2m
Applying K-Means in Python3m 32s
K-Means: Indicators2m
How to Use Jupyter Notebook?2m 5s
Clustering Strategy for Cryptocurrencies10m
Frequently Asked Questions10m
Cryptocurrency: Strategy Signal2m
- Code the K-Means StrategyIn this section, learn to code the strategy in Python and to use it to predict clusters and generate trading signals.
Calculating the SMA5m
Function for Calculating the Movement2m
Instantiating the K-Means5m
Unsupervised Learning Algorithms2m
Training the K-Means5m
Convert the Input Data2m
Predicting the Clusters5m
Using the Sklearn Prediction2m
Trading Signal5m
- Pairs Trading StrategyIn this section, you will learn about the pairs trading strategy and concepts like stationarity, hedge ratio, and co-integration.Pairs Trading2m 1s
Stationarity2m
Cointegration2m
Spread2m
Hedge Ratio2m
- Code the Pairs Trading StrategyThis section demonstrates the implementation of the pairs trading strategy using Python and how it can be applied in cryptocurrency trading. It also provides the strategy returns to determine the performance.Strategy2m 22s
ADF Test10m
Bollinger Band2m
Bollinger Band - Spread2m
Pairs Trading Strategy10m
Hedge Ratio5m
Cointegration5m
Moving Standard Deviations5m
Buy Signal5m
Plot Strategy Returns5m
Test on K-Means and Pairs Trading14m
- Hurst ExponentThis section focuses on developing an understanding of a statistical technique called Hurst Exponent, analyzing and calculating it. It also demonstrates how it can be used for cryptocurrency trading.Hurst Exponent2m 59s
Understanding Market Nature2m
Understanding the Hurst Exponent2m
Hurst Exponent Calculation10m
Analyzing the Hurst Exponent2m
Strategy Using Hurst Exponent2m 27s
RSI With Hurst2m
Crypto Trading Using Hurst Exponent10m
- Code the Hurst StrategyThis section explains the working and implementation of the Hurst Strategy using Python and determines the strategy returns.Effect on Net Profit2m
Converting to Datetime5m
Convert Timestamp2m
Calculate the Hurst Exponent5m
Understanding the Hurst Function2m
Generate the Persistence Signal5m
Calculate the RSI5m
Understanding the Input2m
Calculating the Strategy Returns5m
Understanding the Strategy2m
- Quant Strategy FrameworkThis section covers the quant strategy framework, its components, and its advantages. It also covers topics like Universal Selection Criteria and Capital Allocation.Framework Overview2m 47s
Advantages of the Framework2m
Components of the Framework2m
Universe Selection Criteria2m
Capital Allocation2m
Additional Reading10m
- Code the Long-Only Momentum StrategyUsing the framework explained in the earlier section, a long-only momentum strategy is developed and coded in Python in this section. You can find the downloadable strategy codes in this section.Long-Only Momentum Strategy10s
Pandas Datetime Function2m
Percent Change2m
Rank 2-Day Returns5m
Combined Alpha Score5m
Strategy Returns5m
Summary1m 22s
Test on Hurst Exponent, Long-Only Momentum Strategy and Quant Strategy Framework14m
- Run Codes Locally on Your MachineLearn to install the Python environment in your local machine.Uninterrupted Learning Journey with Quantra2m
Python Installation Overview1m 59s
Flow Diagram10m
Install Anaconda on Windows10m
Install Anaconda on Mac10m
Know your Current Environment2m
Troubleshooting Anaconda Installation Problems10m
Creating a Python Environment10m
Changing Environments2m
Quantra Environment2m
Troubleshooting Tips For Setting Up Environment10m
How to Run Files in Downloadable Section?10m
Troubleshooting For Running Files in Downloadable Section10m
- Live Trading on IBridgePySection Overview2m 2s
Live Trading Overview2m 41s
Vectorised vs Event Driven2m
Process in Live Trading2m
Real-Time Data Source2m
Code Structure2m 15s
API Methods10m
Schedule Strategy Logic2m
Fetch Historical Data2m
Place Orders2m
IBridgePy Course Link10m
Additional Reading10m
Frequently Asked Questions10m
- Paper and Live TradingIn this section, a live trading strategy template will be provided to you. You can tweak the strategy template to deploy your strategies in the live market!Template Documentation10m
Template Code Files2m
- Downloadable ResourcesYou can download the Python strategy codes at the end of the course.Python Codes and Data2m
about author
FXCM
FXCM or Forex Capital Markets, acts as a retail broker for foreign exchange market, which was founded in 1999. It offers access to the global forex trading market, with intuitive platform options, including award-winning Trading Station. Their customer service team, one of the best in the industry, is available 24/5, wherever you are in the world.
QuantInsti®
QuantInsti is the world's leading algorithmic and quantitative trading research & training institute with registered users in 190+ countries and territories. An initiative by founders of iRage, one of India’s top HFT firms, QuantInsti has been helping its users grow in this domain through its learning & financial applications based ecosystem for 10+ years.
Why quantra®?
- More in Less Time
Gain more in less time
- Expert Faculty
Get taught by practitioners
- Self-paced
Learn at your own pace
- Data & Strategy Models
Get data & strategy models to practice on your own
User Testimonials
Software Developer, Nigeria
The course is quite informative for algorithm trading newbies though it was a short course.
Credit Analyst, Malaysia
Very informative! glad to join in the discount period. The content is delivered in a direct and practical manner. What I also liked is that Quantra provides lifetime access to all these courses, allowing me to revisit the parts that I later need to brush up on.
Software Developer, Argentina
It's practical and with the exercises you really understand all the strategies.
Lead Data Science at Covr Financial Technologies, United States
A good intro to crypto strategy.
RU
Netherlands
I really enjoyed studying at Quantra. I learned a lot of useful and good things for myself, and most importantly, I learned how to describe these strategies in the code. I also liked the fact that not only my knowledge about the exchange market is increasing, but now, I am also exposed to statistics, machine learning, and development. I found the crypto courses to be very interesting as well. These courses will definitely prove to be very helpful for me to find a job in the Quantitative Finance domain.
VR
United Kingdom
The course covers several popular ML trading techniques and shows how to design and start trading profitable crypto strategies.
TH
Vietnam
The course is practical and easy to follow
VR
United Kingdom
Not a huge fan of Crypto, this course simplified my understanding on Crypto trading!
CV
India
I thoroughly enjoyed the “Crypto Trading Strategies: Intermediate” course! It was an excellent, highly informative experience. The course material was well-structured, clear. It significantly enhanced my understanding of intermediate crypto strategies, providing valuable insights and actionable techniques. Highly recommended for anyone looking to deepen their crypto trading knowledge and skills!
PC
Serbia
Good starting point for the advanced part of the subject!
CL
Heavy haul truck driver, United States
I found the ‘Crypto Trading Strategies: Intermediate’ course at Quantra to be excellent. I am a part-time trader with a deep interest in statistics and programming. I would like to apply these skills in trading and investing.
MP
United Kingdom
Lot of new information for me
GG
Canada
New info, really good
TP
Australia
Very well structured and easy to follow.
MS
United Kingdom
Decent course. Learned some interesting stuff.
No
Czechia
Well presented macro-valuation of world currencies.
JP
India
The knowledge gained from the lectures so far has really helped me with understanding with regards to investing in the Forex market. I enjoyed going through the course. I did it all without taking a break. I'm very excited about the information and confidence I got out of it.
AB
Support Executive, India
I really liked and enjoyed doing the interactive exercises in this course, as this a very new concept for me, it really helped me learn and get comfortable with Python. The Interactive exercises have proper instructions, it also prompts you whenever you make an error while coding, so that you are aware of where you went wrong and can rectify the error. I also liked the step-by-step explanation of the Momentum based strategy while being implemented using Blueshift. This gave me great clarity on how python is practically used in the trading domain.
VG
Spain
This course provides a very clear explanation of Forex basics and a useful example of how to implement strategies with backtesting capabilities in Python.
AP
Italy
A brief, but very decent overview of the subject. A great introduction in that respect.
IE
Head of ICT Deparment at Ibom Specialsit Hospital, Nigeria
The videos were well-explained. I loved, most especially, the coding aspect of the tutorial.
Faqs
- Are there any webinars, live or classroom sessions available in the course?
No, there are no live or classroom sessions in the course. You can ask your queries on community and get responses from fellow learners and faculty members
- Is there any support available after I purchase the course?
Yes, you can ask your queries related to the course on the community: https://quantra.quantinsti.com/community
- What are the system requirements to do this course?
Fast-speed internet connection and a browser application is required for this course. For the best experience, use Chrome.
- What is the admission criteria?
There is no admission criterion. You are recommended to go through the prerequisites section, be aware of skill sets gained and to learn the most from the course.
- Is there a refund available?
We respect your time, and hence, we offer concise but effective short-term courses created under professional guidance. We try to offer the most value within the shortest time. There are a few courses on Quantra which are free of cost. Please check the price of the course before enrolling in it. Once a purchase is made, we offer complete course content. For paid courses, we follow a 'no refund' policy.
- Is the course downloadable?
Some of the course material is downloadable such as Python notebooks with strategy codes. We also guide you to use these codes on your own system for you to practice further.
- Can the Python strategies provided in the course be used immediately for trading?
We focus on teaching about quantitative and machine learning techniques and how learners can use them for developing their own strategies. You may or may not be able to directly use them in your own system. Please do note that we are not advising or offering any trading/investment services. The strategies are used for learning & understanding purposes and we do not take any responsibility for the performance or any profit or losses that using these techniques results in.
- Are you using real time Stock market data in the course?
No. We do not take examples from 'real time data', but you shall be learning to code through historical data. Please do note that there is a section at the end that will guide you on how to automate for real time live trading. You can get more detailed learning on how to automate trading strategies through our free course, 'Automated trading with IBridgePy using Interactive Brokers Platform'.
- Will I be getting a certificate post the completion of the programme?
Yes, you will get a certificate for each course separately within a few hours of completion of the course. The certificates are downloadable from your account tab "My Certificates".
- What does "lifetime access" mean?
Lifetime access means that once you enroll in the course, you will have unlimited access to all course materials, including videos, resources, readings, and other learning materials for as long as the course remains available online. There are no time limits or expiration dates on your access, allowing you to learn at your own pace and revisit the content whenever you need it, even after you've completed the course. It's important to note that "lifetime" refers to the lifetime of the course itself—if the platform or course is discontinued for any reason, we will inform you in advance. This will allow you enough time to download or access any course materials you need for future use.
- Is Python an essential skill for automated trading for beginners?
Python is not strictly essential for beginners in automated trading, but it is highly recommended. Here’s why:
Ease of Learning: Python has a beginner-friendly syntax, making it accessible even for those new to programming.
Versatility: Python is widely used in the finance industry for tasks like backtesting, data analysis, and building trading algorithms. Libraries like Pandas, NumPy, and TA-Lib make it easy to analyse financial data
Extensive Community Support: Python's popularity means a vast amount of tutorials, forums, and resources are available for troubleshooting and learning.
Integration with Broker APIs: Many brokers and trading platforms offer APIs with Python support, enabling seamless integration for order execution and real-time data analysis.
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