Quant Investing for Portfolio Managers
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- Live Trading
- Learning Track
- Prerequisites
- Syllabus
- About author
- Testimonials
- Faqs
Learn Advanced Factor Investing
- Optimise portfolios using quant techniques
- Backtest unconventional factors such as skewness for generating alphas
- Implement different factor timing approaches
- Apply factor tilting to adjust weights to different factors
- Evaluate portfolio performance and assess risk through metrics such as returns, Sharpe ratio, drawdowns and factor Beta
- Limitations of factor investing such as data mining, specification error, crowding

Skills for Quant Investing
Python
- Pandas
- NumPy
- TA-Lib
- Matplotlib
Concepts & Trading
- Non-Traditional Factors
- Factor Timing and Tilting
- Winsorization and Z-Score
- Factor Portfolio Risk
Strategies
- Skewness Factor Strategy
- Factor Timing Strategy
- Scoring-Based Factor Portfolio
- Rank-Based Factor Portfolio

learning track 7
This course is a part of the Learning Track: Portfolio Management and Position Sizing using Quantitative Methods
Course Fees
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 for Quant Investing
To start with the course, you need to have a basic understanding of financial markets. You should also be familiar with some basic investment principles, including risk and return, portfolio, and asset allocation. A basic knowledge of Python, including pandas dataframe, matplotlib, and loops for strategy implementations.
Quantitative Investing Course
- Introduction to the CourseThis section serves as a preview of the course and introduces the course contents. The interactive methods used in this course will assist you in not only understanding the concepts but also answering all questions regarding the use of machine learning algorithms for momentum trading. This section explains the course structure as well as the various teaching tools used in the course, such as videos, quizzes, coding exercises, and the capstone project. It also covers a few course-related frequently asked questions.
Fundamentals of Factor Investing
This section tackles the first question which arises in every portfolio manager's mind, "Why should I create a portfolio using factors?" You will also explore the journey of factor investing, right from the CAPM to the newer models introduced in the 21st century.Why Factor Investing?2mDefine Factor Investing5mFactor Investing vs Actively Managed Funds5mMulti-Factor Portfolio5mPerformance of Factor Based Portfolios5mJourney of Factor Investing2mCAPM and Influence on Returns5mThree-Factor Model5mFive-Factor Model5mDefine Factor Premium5mTraditional Factor5mPurpose of Identifying Factors5mTypes of Factors2mCore Building Blocks of Factor Investing5mIdentify Non-Traditional Factor5mCharacteristics of Non-Traditional Factors5mAdditional Reading on Fundamentals of Factor Investing2mTest on Fundamentals of Factors12m- Why Traditional Factors Work?Traditional Factors have been around since decades, and yet they are still in practice among leading fund houses. Take a deep dive into the world of traditional factors and understand how they work. You will also get a brief overview on how you can create a traditional factor portfolio.Why Traditional Factors Work?2mIdentification of Style Factors5mStock Classification According to Quality5mReason of Momentum Factor5mFocus of Value Factor5mSize Factor Interpretation5mInstitutional Investors and Small-Cap Stocks5mBelief in Value Investing5mAnalysis Based on Quality Factor5mAnalysis Based on Value Factor5mAnalysis Based on Size Factor5m
- Traditional Factor Investing and PerformanceThe popularity of traditional factors has made portfolio managers around the world to sit up and take notice. There are a number of thematic ETFs which are developed by institutions to cater to the retail trader. You can explore their performance in this section.Investing in Factors and Factor Based Fund Performance2mApproaches to Factor Investing5mCreation of Portfolio Using Value Factor5mLimitation of P/E Ratio Based Value Investing5mFlexibility of Factor Investing5mInvesting in Multiple Factors5mFAQs on Traditional Factors2mSummary of Traditional Factors2mAdditional Reading of Traditional Factors2mTest on Traditional Factors12m
Existence of Non-Traditional Factors
Traditional Factors are not the only factors in existence. Both academicians and professional traders are exploring the world of finance to uncover hidden sources of alphas, which are being called non-traditional factors. In this section, you will also understand how non-traditional factors can be discovered.Why Do Non-Traditional Factors Exist?2mReason for Popularity of Non-Traditional Factors5mTraditional Factors and Alpha5mExample of Non-Traditional Factor5mNon-Traditional Factors and Portfolio Performance5mDifference Between Non-Traditional and Traditional Factors5mHow to Find Non-Traditional Factors?2mIdentification of Non-Traditional Factors5mExample of Alternative Data for Identification of Factors5mSkewness as Non-Traditional Factor5mAction After Identification of Non-Traditional Factor5mResearch Papers and Non-Traditional Factors5mFAQs on Non-Traditional Factors2mSummary of Non-Traditional Factors2mAdditional Reading of Non-Traditional Factors2m- Getting Data: Multiple AssetsIn this optional section, you will explore how to retrieve price data of multiple assets which can be used to create a factor portfolio.Uninterrupted Learning Journey with Quantra2mGetting Data: Multiple Assets5m
- How to Calculate Skewness?In this optional section, you will recall the meaning of skewness and how it can be calculated from a dataset.How to Calculate Skewness?1m 39sSkewness Measure5mIndication of Positive Skew5mSkewness and Normal Distribution5m
Creation of Non-Traditional Factors Portfolio
In this section, you will focus on the skewness factor which can be used to create and rebalance a non-traditional factor based portfolio.Creation of Skewness Factor Based Portfolio2mRelation Between Past Skewness and Future Returns5mData Frequency to Calculate Skewness5mType of Stocks Excluded in Portfolio Creation5mAverage Weekly Returns5mModification to Strategy in Research Paper5mRestriction of Potential Stock Universe5mStrategy Flow Diagram for Skewness Strategy2mCreation of Non-Traditional Factor Based Portfolio5mCalculate Skewness of Weekly Returns5mCalculate Absolute Value of Skewness5mSelect 10 Assets with Lowest Skewness5m- Challenges in Creation of Non-Traditional Factor PortfolioIn this section, you will list the reasons it is difficult to create a non-traditional factor portfolio.Challenges in Creation of Non-Traditional Factor Portfolio2mPrimary Challenge of Acquiring Data for Non-Traditional Factors5mSentiment Analysis and Bias5mMethod to Compare Non-Traditional Factor Data Across Assets5mTraditional and Non-Traditional Factor Portfolio5mFAQs on Creation of Non-Traditional Factors Portfolio2mSummary of Creation of Non-Traditional Factors Portfolio2mAdditional Reading of Creation of Non-Traditional Factors Portfolio2mTest on Creation of Non-Traditional Factors Portfolio10m
- Capstone Project on Non-Traditional Factor PortfolioIn this capstone project section, you will create a portfolio based on the kurtosis factor.Getting Started2mProblem Statement2mCapstone Project Model Solution2m
Factor Timing
Explore how market dynamics influence factor performance, the concept of factor timing, and practical approaches like economic cycle forecasting and price-based momentum for better portfolio management.Factor Timing: Why and How?2mFactor Outperformance5mPurpose of Factor Timing5mTiming is Money5mEconomic Cycles for Factor Timing5mMomentum Approach5mFAQs on Factor Timing2mAdditional Reading on Factor Timing2m- Generalized Hurst ExponentUnderstand the Generalized Hurst Exponent as a tool to analyse market trends, identify momentum, and refine factor timing strategies.Generalized Hurst Exponent2mGHE - Time Series5mTime Series Behaviour5mInterpretation of GHE5mVariation with q5mEstimating GHE5mGeneralized Hurst Exponent Calculation5mCalculate the Logarithm of Lag Values5mPerform a Linear Regression to Fit Log-Lags to Log-Moments5mCalculate the Generalized Hurst Exponent5mFAQs on Generalized Hurst Exponent2mAdditional Reading on Generalized Hurst Exponent2m
- Getting ETF DataDesigning and creating custom factors from data demands expertise, time, and resources. An alternative approach is to invest in ETFs that provide targeted exposure to specific factors. In this section, you will learn how to identify relevant ETF tickers, filter them according to your investment strategy, and retrieve their price data.How to Find ETF Data?2mSelecting ETFs and Fetching Data15m
Factor Timing Strategy
Learn to develop factor timing strategy by combining the Generalized Hurst Exponent to detect trends and technical indicators like Momentum (MOM) for confirming positive momentum signals.Factor Timing Strategy2mPurpose of Hurst Exponent5mTrending Market5mMOM Threshold5mLong-Only Strategy5mLower MOM Threshold5mFactor Timing Strategy Flow Diagram2mFactor Timing Single ETF5mCalculate the Momentum (MOM) Indicator5mTrading Signal5mFactor Timing Portfolio ETFs5mCalculate the Benchmark Returns5mCalculate the Portfolio Returns5mFAQs on Factor Timing Strategy2mAdditional Reading on Factor Timing Strategy2m- Effectiveness of Factor TimingExamine the strengths and limitations of factor timing strategies, including insights from recent research, and explore how timing can reduce drawdowns, align with economic conditions, and improve portfolio resilience.Effectiveness of Factor Timing2mAnother Look at Timing the Equity Premiums5mMacroeconomic Data5mDesigning a Factor Timing Strategy5mEffectiveness of Factor Timing Strategies5mRising Interest Rates5mFAQs on Effectiveness of Factor Timing2mAdditional Reading on Effectiveness of Factor Timing2mTest on Factor Timing14m
- Live Trading on BlueshiftLearn how you can take your backtested strategy live with some important steps. Learn about the code structure, the various functions used to create a strategy, and finally, paper or live trade on Blueshift.Section Overview2m 19sLive Trading Overview2m 40sVectorised 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 TemplateThis section includes a live trading strategy template. You can tweak the code by changing securities or the strategy parameters. You can also analyse the strategy's performance in more detail.FAQs for Live Trading on Blueshift5mPaper/Live Trading Factor Timing Strategy2m
- Factor TiltingPortfolio managers utilise techniques like factor tilting to generate alpha by strategically allocating weights to key factors. In this section, you’ll learn what factor tilting is and the basic approach to implement it.Why Factor Tilting is Required2mStrategy Enquiry5mWeighting Approach Used5mWhat is Factor Tilting?5mScoring Methodology2mPurpose of Scoring5mProcess of Selecting Top Three Assets5mProcess for Creating Scores5mScoring Methodology5mFAQs on Factor Tilting2mAdditional Reading on Factor Tilting2mSummary of Factor Tilting2m
- Creation of Portfolio EngineIn this section, we will create a portfolio engine which will serve as the framework for backtesting a factor-based portfolio.Portfolio Engine: Backtesting Framework5mPurpose of Portfolio Engine5mKey Benefits of the Portfolio Engine5mFirst Notebook5mSecond Notebook5mThird Notebook5mFourth Notebook5mPortfolio Engine - Importing Data & Finding Rebalance Dates.5mPortfolio Engine - Portfolio Strategy5mPortfolio Engine - Portfolio Returns5mPortfolio Engine - Portfolio Performance5m
- Impact of Outliers on Scoring MethodologyThe scoring approach for tilting factors is intuitive, but it can lead to overly concentrated portfolios. In this section, you'll discover how outliers can have a significant impact on portfolio weights and overall performance.Impact of Outliers on Scoring Methodology2mPrimary Risk of Overexposure5mDiversification Importance5mPortfolio Returns Calculation5mFAQs on Impact of Outliers on Scoring Methodology2mTest on Factor Tilting12m
- Rank Based Weight AllocationRank based weight allocation is popular approach used for tilting weights.Rank Based Weight Allocation2mRanks Order5mRanks Weight Diversification5mDifferences Between Consecutive Rank Weights5mImplementing Rank Based Weight Allocation5mCalculate Ranks5mRank Based Weight Allocation5mBacktesting Rank Based Weight Allocation5mAdditional Reading on Rank Based Weight Allocation2m
- Limitations of Rank Based Weight AllocationRank based weight allocation is popular approach but comes with drawbacks.Limitations of Rank Based-Weight Allocation2mLimitation of Rank-Based Weight Allocation5mWhen to prefer score-based weight allocation?5mDrawback of Score-Based Weight Allocation5mFAQs on Rank Based Weight Allocation2mTest of Rank Based Weight Allocation14m
Process of Winsorization
Both the scoring and ranking methods have certain limitations. Wouldn't it be great if we could somehow the best parts of both methods? In this section, we will explore the process of winsorization and check how it will help us allocate weights efficiently.Process of Winsorization2mIdentification of Outliers5mPercentiles in Winsorization5mValue Below 10th Percentile5mAdvantage of Using Percentiles5mReason for Choosing Winsorization5mApplication of Winsorization in ETF5mReducing Impact of Outliers Using Winzorization5mPivot the ETFs Dataframe5mApply Winsorization on 60-Day Returns5mPlot the KDE of Winsorized Returns5mBacktesting with Winsorization5mFAQs on Process of Winsorization2mSummary of Process of Winsorization2mAdditional Reading of Process of Winsorization2mTest on Winsorization10m- Capstone Project on Factor CombinationIn this capstone project you will construct a factor portfolio by assigning weights to factors based on the Sortino ratio as the performance metric.Problem Statement on Factor Combination2m
- Calculation of Multiple MetricsYou have been able to create and backtest a portfolio using a single metric. Now, you will try to calculate multiple metrics which can be used later for portfolio allocation.Calculation of Multiple Metrics2mImportance of Multiple Metrics5mCombining Metrics for Better Decision-Making5mTypes of Metrics for Weight Allocation5mAvoiding Redundant Metrics5mChoosing the Right Number of Metrics5mPractical Application of Multiple Metrics5mCalculation of Multiple Metrics5mFAQs on Calculation of Multiple Metrics2mSummary of Calculation of Multiple Metrics2m
- Z-Score StandardisationIn this section, you will be able to standardise the scoring metrics using z-score.Z-Score Standardisation2mNeed for Standardisation5mZ-Score5mTransformed Dataset5mZ-Score Formula5mCalculate Z-Score5mZ-Score Standardisation of Scoring Metrics5mImplement Z-Score Standardisation5mFAQs on Z-Score Standardisation2mAdditional Reading on Z-Score Standardisation2m
- Use of Z-Score Values for Weight AllocationAfter combining the z-scores of multiple metrics we have to allocate weights in proportion of their z-score values. In this section, you will see how this can be achieved.Using Z-Score Values for Weight Allocation2mAdjustment of Z-Score Value5mCalculation of ETF Weights5mUse of Z-Score5mEffect of Shifted Z-Score on Weights5mOverall Weight Allocation Process Using Z-Scores5mCombined Z-Score Calculation5mUsing Z-Score Values for Weight Allocation5mFind Minimum Z-Score Value of Day5mCalculate Shift Value5mShift the Z-Score Values By Calculated Shift Value5mCalculate Sum of Z-Score Values5mCalculate Weight of Individual Assets5mBacktesting Using Multiple Metrics Scoring Method5mFAQs on Using Z-Score Values for Weight Allocation2mSummary of Using Z-Score Values for Weight Allocation2mAdditional Reading on Using Z-Score Values for Weight Allocation2mTest on Multiple Metric Based Scoring Methodology for Factor Portfolio Creation18m
Analyse the Performance of Multi-Factor Portfolio
This section highlights the need for a deeper analysis of portfolio performance, focusing on return consistency, concentration risks, and distribution. It emphasises diversification and introduces drawdown and stress event analysis for better risk understanding.Part Overview: Risk Assessment of Multi-Factor Portfolio2mPerformance of a Multi-Factor Portfolio2mNeed to Analyse Portfolio Returns5mUnderstanding Concentration Risk5mMitigating Concentration Risk5mInterpreting Skewness in Returns5mImportance of Kurtosis in Risk Analysis5mTakeaway from Multi-Factor Portfolio Performance5mRisks of Over-Allocation5mPerformance Analysis of Factor Portfolio5mCalculate the Cumulative Metrics5mCalculate Daily Volatility5mCalculate the Returns Metrics5mPlot the Returns Histogram5mFAQs on the Performance of a Multi-Factor Portfolio2mAdditional Reading on Performance of a Multi-Factor Portfolio2mSummary of Performance of a Multi-Factor Portfolio2mTest on Performance of a Multi-Factor Portfolio16mAnalyse the Drawdowns of Multi-Factor Portfolio
This section discusses in-depth risk analysis, focusing on drawdowns, recovery times, and the impact of market events. It concludes with an introduction to analysing portfolio sensitivity to factors.Drawdown Analysis of a Multi-Factor Portfolio2mImportance of Drawdown Analysis5mEvaluating Top 5 Drawdowns5mUnderstanding Recovery Times5mAnalysing Recovery of the October 2022 Drawdown5mIdentifying Market Stress Events5mSensitivity to Factors5mDrawdown Analysis of Factor Portfolio5mCalculate the Drawdown5mCalculate the Max Drawdown Date5mCalculating Recovery Date5mCalculating Recovery Duration5mFAQs on the Drawdown Analysis of a Multi-Factor Portfolio2mAdditional Reading on Drawdown Analysis of a Multi-Factor Portfolio2mSummary of Drawdown Analysis of a Multi-Factor Portfolio2mTest on Drawdown Analysis of a Multi-Factor Portfolio14m- Analyse the Sensitivity of Portfolio to its FactorsThis section explains how to measure portfolio sensitivity using factor beta, which shows how returns change with factor shifts. It uses linear regression for calculation and highlights that growth and momentum factors are key drivers of portfolio returns.Sensitivity of Portfolio to its Factors2mImportance of Factor Beta5mInterpreting Factor Beta Value5mMethod for Measuring Factor Beta5mLinear Regression Equation5mFactor Beta for a Multi-Factor Portfolio5mInterpreting Factor Beta Plot5mCalculate and Interpret Factor Beta5mCheck Index Alignment5mCalculate the Factor Beta5mFAQs on the Sensitivity of Portfolio to its Factors2mAdditional Reading on Sensitivity of Portfolio to its Factors2mSummary of Sensitivity of Portfolio to its Factors2mTest on Sensitivity of Portfolio to its Factors14m
- Core and Satellite InvestingCore and Satellite investing blends stability and growth by combining a diversified core for steady returns with satellite investments for higher growth potential.Core and Satellite Investing2mApproaches in Core and Satellite Investing5mFast-moving vs Slow-moving satellite5mBest Composition5mFAQs on Core and Satellite Investing2mAdditional Reading on Core and Satellite Investing2m
- Factor Investing in Emerging MarketsIn this section, we will examine how factors in developing markets behave differently compared to the developed markets. We will discuss the unique challenges and opportunities, including market inefficiencies, liquidity constraints, and macroeconomic influences.Factor Investing in Emerging Markets2mKey Reason for Factor Investing5mRapid Growth of Emerging Markets5mMajor Challenge5mEffectiveness of Factor Investing5mUnique Growth Theme5mFAQs on Factor Investing in Emerging Markets2mAdditional Reading on Factor Investing in Emerging Markets2m
- Limitations of Factor InvestingUnderstand the key challenges of factor investing, including data mining, specification errors, crowding, regime shifts, and overfitting. Learn strategies to mitigate these issues.Limitations of Factor Investing2mHistorical Data5mMitigate the Risk of Data Mining5mSpecification Error5mPrice-To-Earnings Ratio5mLow-Volatility Factor Strategy5mFAQs on Limitations of Factor Investing2mAdditional Reading on Limitations of Factor Investing2m
- 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
- Summary of the CourseIn this section, you will go through the summary of the course and access the data files and notebooks which were used in the course.Summary of the Course2mSummary of the Course and Next Steps2mPython Codes and Data2m
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Faqs
- When will I have access to the course content, including videos and strategies?
You will gain access to the entire course content including videos and strategies, as soon as you complete the payment and successfully enroll in the course.
- Will I get a certificate at the completion of the course?
Yes, you will be awarded with a certification from QuantInsti after successfully completing the online learning units.
- 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 are required for this course. For best experience, use Chrome.
- What is the admission criteria?
There is no admission criterion. You are recommended to go through the prerequisites section and be aware of skill sets gained and required to learn 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 how to use these codes on your own system to practice further.
- Can the python strategies provided in the course be immediately used for trading?
We focus on teaching these 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 don't take any responsibility for the performance or any profit or losses that using these techniques results in.
- I want to develop my own algorithmic trading strategy. Can I use a Quantra course notebook for the same?
Quantra environment is a zero-installation solution to get beginners to start off with coding in Python. While learning you won't have to download or install anything! However, if you wish to later implement the learning on your system, you can definitely do that. All the notebooks in the Quantra portal are available for download at the end of each course and they can be run in the local system just the same as they run in the portal. The user can modify/tweak/rework all such code files as per his need. We encourage you to implement different concepts learnt from different learning tracks into your trading strategy to make it more suited to the real-world scenario.
- If I plug in the Quantra code to my trading system, am I sure to make money?
No. We provide you guidance on how to create strategy using different techniques and indicators, but no strategy is plug and play. A lot of effort is required to backtest any strategy, after which we fine-tune the strategy parameters and see the performance on paper trading before we finally implement the live execution of trades.
- 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.