Learning Track: Algorithmic Trading in Cryptocurrency and Forex
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- Live Trading
- Learning Track
- Prerequisites
- Syllabus
- About author
- Testimonials
- Faqs
Live Trading

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
Full Learning Track
These courses are specially curated to help you with end-to-end learning of the subject.
Course Features
- Community
Faculty 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
- Introduction to Forex TradingThis section covers the basics of Forex trading and explains how macroeconomic factors affect the Forex market.Introduction to Forex Trading5m 11sQuantra Features and Guidance3m 48sWhat is PIP?2mWhat is Spread?2mWhat is Spread Value?2mFactors Affecting Forex Trading4m 28sInterest Rate2mInflation2mParticipants 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 42sWhat is Momentum Strategy?2mMomentum Strategy Rationale2mMomentum Strategy Logic2mRanking Criteria for Currency Pairs2mApproach to Capital Allocation2mRebalance Frequency2mQuantra Blueshift Functions10mCode the Momentum Trading Strategy3m 20sQuantra Blueshift Features2mInitialize Function2mDefine Currency List5mSyntax for Schedule Function2mFetch the Historical Data5mCalculate Returns5mMethod to Place Order2mAssessment 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 Quantra2mSection Overview2m 19sLive Trading Overview2m 41sVectorised vs Event Driven2mProcess in Live Trading2mReal-Time Data Source2mBlueshift Code Structure2m 57sImportant API Methods10mSchedule Strategy Logic2mFetch Historical Data2mPlace Orders2mBacktest and Live Trade on Blueshift4m 5sAdditional Reading10mBlueshift Data FAQs10m
- Live Trading TemplateBlueshift Live Trading TemplatePaper/Live Trading Long Short FX Strategy10mFAQs 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 49sDownside of Leverage2mStop Loss2mHow to Allocate Capital?2mCourse Summary1m 55sAssessment Test - II6m
- 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 51sQuantra Features and Guidance3m 48sMacroeconomic Factors Affecting Forex Market5m 26sBalance of Trade2mEffect of Interest Rates2mCarry Trade2mEffect of Inflation2m
Valuation of Forex
This 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 52sExchange Rate Using PPP2mValuation Using PPP2mRelative PPP2mCompute Exchange Rate2mReal Effective Exchange Rate (REER)3m 14sNominal Exchange Rate2mReal Exchange Rate2mNominal and Real Effective Exchange Rate2mCalculation of REER10mREER Formula2mTest 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 10sREER Data Source2mStrategy Logic2mValuation Methods2mTrading 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 6sDownload REER Data5mHow to Use Jupyter Notebook?2m 5sFX Value Strategy in Python10mFrequently Asked Questions10mRead the Data5mGenerate Trading Signal5mFill NaN Values2mCompute Strategy Returns5mPlot the Strategy Returns5mCourse Summary1m 2sTest on Forex Value Strategy10m
- Run Codes Locally on Your MachineLearn to install the Python environment in your local machine.Uninterrupted Learning Journey with Quantra2mPython Installation Overview1m 59sFlow Diagram10mInstall Anaconda on Windows10mInstall Anaconda on Mac10mKnow your Current Environment2mTroubleshooting Anaconda Installation Problems10mCreating a Python Environment10mChanging Environments2mQuantra Environment2mTroubleshooting Tips For Setting Up Environment10mHow to Run Files in Downloadable Section?10mTroubleshooting For Running Files in Downloadable Section10m
- Live Trading on IBridgePySection Overview2m 2sLive Trading Overview2m 41sVectorised vs Event Driven2mProcess in Live Trading2mReal-Time Data Source2mCode Structure2m 15sAPI Methods10mSchedule Strategy Logic2mFetch Historical Data2mPlace Orders2mIBridgePy Course Link10mAdditional Reading10mFrequently 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 Documentation10mTemplate Code File2m
- Downloadable ResourcesYou can download the Python strategy codes at the end of the course.Python Codes and Data2m
- 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 29sCourse Structure2mFrequently Asked Questions2mQuantra Features and Guidance3m 48sWhat Are Cryptocurrencies?2m 10sTransactions2mCrypto Wallets4m 27sConfirmation2mE-Wallets Have..2mTransaction Fee2mWallet Risk2mWhat Are Trading Bots?2mBots2mExchange2mAdditional Reading on Cryptocurrencies2mAdditional Reading on Blockchain2mTest on Basic Concepts of Cryptocurrencies10m
- Getting Cryptocurrency DataCryptocurrency Data5mAdditional Reading for Crypto Assets2m
Trading Using Calendar Anomalies
In 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 45sCalendar Anomalies2mCalendar Anomalies in Cryptocurrency2mDay of the Week Anomaly2mThe Best Day to Buy the Bitcoin2mThe Best Day to Sell the Bitcoin2mStrategy Code Overview1m 17sHow to Use Jupyter Notebook?2m 5sThe Day of the Week Strategy10mFrequently Asked Questions10mLoad Data From Csv File2mDaily Percent Change2mThe Highest Sharpe Ratio Day5mStrategy Returns5mTest 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 Cloud2mIchimoku Cloud2mConversion Line2mLeading Span A2mCloud2mTrend2mMoving Average Crossover2mCalculate and Plot the Ichimoku Cloud10mRolling High Value5mIchimoku Cloud Based Strategy5mGenerating Buy Signals5mStrategy Returns5mTest 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 Slippage2mCalculation of Transaction Cost5mCalculation of Slippage5mTransaction Costs and Slippage5mAdditional 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 Analytics5mAverage PnL Per Trade5mWin Percentage5mAverage Trade Duration5mAdditional Reading on Trade Level Analytics2mPerformance Metrics5mMaximum Drawdown5mAdditional 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 Strategy2mThe Spread2mAroon Up Value2mDivergence Strategy10mUpspread2mCalculate the RSI5mCalculate the Aroon Values5mAroon of RSI2mCalculate the Spread5mThe Threshold of Spread2mGenerate Buy Signals5mPlot the Strategy Returns5mTest on Divergence Strategy10mAdditional Reading2mLook-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 Quantra2mPython Installation Overview1m 59sFlow Diagram10mInstall Anaconda on Windows10mInstall Anaconda on Mac10mKnow your Current Environment2mTroubleshooting Anaconda Installation Problems10mCreating a Python Environment10mChanging Environments2mQuantra Environment2mTroubleshooting Tips For Setting Up Environment10mHow to Run Files in Downloadable Section?10mTroubleshooting For Running Files in Downloadable Section10m
- Live Trading on IBridgePySection Overview2m 2sLive Trading Overview2m 41sVectorised vs Event Driven2mProcess in Live Trading2mReal-Time Data Source2mCode Structure2m 15sAPI Methods10mSchedule Strategy Logic2mFetch Historical Data2mPlace Orders2mIBridgePy Course Link10mAdditional Reading10mFrequently 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 Documentation10mTemplate 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 Started2mProblem Statement2m
- Downloadable ResourcesYou can download the Python strategy codes at the end of the course.Summary2mNext Steps2mPython Codes and Data2m
- 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 56sQuantra Features and Guidance3m 48sUnderstanding K-Means Algorithm3m 44sUnsupervised Learning2mLocating the Cluster Center2mApplying K-Means in Python3m 32sK-Means: Indicators2mHow to Use Jupyter Notebook?2m 5sClustering Strategy for Cryptocurrencies10mFrequently Asked Questions10mCryptocurrency: Strategy Signal2m
Code the K-Means Strategy
In this section, learn to code the strategy in Python and to use it to predict clusters and generate trading signals.Calculating the SMA5mFunction for Calculating the Movement2mInstantiating the K-Means5mUnsupervised Learning Algorithms2mTraining the K-Means5mConvert the Input Data2mPredicting the Clusters5mUsing the Sklearn Prediction2mTrading 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 1sStationarity2mCointegration2mSpread2mHedge 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 22sADF Test10mBollinger Band2mBollinger Band - Spread2mPairs Trading Strategy10mHedge Ratio5mCointegration5mMoving Standard Deviations5mBuy Signal5mPlot Strategy Returns5mTest 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 59sUnderstanding Market Nature2mUnderstanding the Hurst Exponent2mHurst Exponent Calculation10mAnalyzing the Hurst Exponent2mStrategy Using Hurst Exponent2m 27sRSI With Hurst2mCrypto 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 Profit2mConverting to Datetime5mConvert Timestamp2mCalculate the Hurst Exponent5mUnderstanding the Hurst Function2mGenerate the Persistence Signal5mCalculate the RSI5mUnderstanding the Input2mCalculating the Strategy Returns5mUnderstanding 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 47sAdvantages of the Framework2mComponents of the Framework2mUniverse Selection Criteria2mCapital Allocation2mAdditional 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 Strategy10sPandas Datetime Function2mPercent Change2mRank 2-Day Returns5mCombined Alpha Score5mStrategy Returns5mSummary1m 22sTest 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 Quantra2mPython Installation Overview1m 59sFlow Diagram10mInstall Anaconda on Windows10mInstall Anaconda on Mac10mKnow your Current Environment2mTroubleshooting Anaconda Installation Problems10mCreating a Python Environment10mChanging Environments2mQuantra Environment2mTroubleshooting Tips For Setting Up Environment10mHow to Run Files in Downloadable Section?10mTroubleshooting For Running Files in Downloadable Section10m
- Live Trading on IBridgePySection Overview2m 2sLive Trading Overview2m 41sVectorised vs Event Driven2mProcess in Live Trading2mReal-Time Data Source2mCode Structure2m 15sAPI Methods10mSchedule Strategy Logic2mFetch Historical Data2mPlace Orders2mIBridgePy Course Link10mAdditional Reading10mFrequently 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 Documentation10mTemplate Code Files2m
- Downloadable ResourcesYou can download the Python strategy codes at the end of the course.Python Codes and Data2m
about author



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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.