## Investment Analysis Portfolio Management with Python

### What you’ll learn

Calculate stock returns manually as well as on Python, using real world data obtained from free sources.

Extensively work with a variety of Python libraries including Pandas, NumPy, SciPy, Matplotlib, to name a few.

Understand why the math works, and what the equations mean – even if your math is weak and if math freaks you out.

Witness the power of diversification and how the risk of your portfolio can be lower than the individual assets that make up the portfolio!

Estimate the Expected Returns of Stocks using the Mean Method, State Contingent Weighted Probabilities, as well as Asset Pricing Models.

Calculate the total risk, market risk, and firm specific risk of stocks from scratch, and explore how the different risks interact.

Measure your investment portfolio’s performance by calculating portfolio returns and risks.

Optimise your portfolios by maximising your returns while minimising your risk.

Create custom functions to automate your Investment Analysis & Portfolio Management techniques, leveraging the power of Python.

Explore computations from scratch, so you understand how Python works behind the scenes.

### Requirements

Coding knowledge is REQUIRED. You don’t need to be an ‘expert’ in Python, but you DO need to know how to code.

At a minimum, we assume you know what lists, dictionaries, and tuples are; and you know the difference between strings, integers, and floats.

This is a Finance course which uses Python. It is NOT a Python course about Finance.

No prior knowledge of Finance is required nor assumed.

It’s okay if math freaks you out. Seriously. Every single equation is explained one variable at a time. We rip it apart to its core, and show you how simple it really is.

Knowledge of basic statistical analysis is useful but NOT essential.

You’ll need a calculator, pen and paper (seriously), and your development environment (e.g. Jupyter Notebooks, Text Editors)

We work with Jupyter Notebooks in the course, but .py versions of all Python code is available for download.

### Description

Say hello to Financial Analysis done right. Become a PRO at Investment Analysis & Portfolio Management with Python. Apply robust techniques that are rigorously grounded in academic and practitioner literature using Python for Finance.Explore Python’s robust modules including Pandas, NumPy, Matplotlib, Seaborn, and a whole lot more, working extensively with real world Finance data.Discover the simplicity and power of Python for Finance. Take command by creating your own functions, cleaning and wrangling real world data.Remove the guesswork by conquering the mathematics behind your own Investment Analysis & Portfolio Management process.Explore and master powerful relationships between stock prices, returns, and risk. Quantify and measure your investment risk, from scratch.Discover what your financial advisor should be doing to manage your portfolio – to manage your investments.While you do need to know how to code, there’s no prior Finance knowledge required. We’ll start you from the very basics, and build you to a financial analysis PRO, leveraging Python for Finance, thanks to:6 SECTIONS TO MASTERY (plus, all future updates included).Introduction: Understanding Investment Security Relationships & Estimating ReturnsExplore powerful relationships between risk, return, and price.Gain a solid command of the baseline fundamental law of Financial Analysis – The Law of One Price.Calculate stock returns for dividend and non-dividend paying stocks, manually.Download and work with real world data, and estimate stock returns on Python from scratch.Estimating Expected ReturnsEstimate expected returns using the average (mean) method.Create your own function on Python to automate the estimation of Expected Returns using the mean method.Estimate expected returns using ‘state contingent weighted probabilities’.Take the analysis further by learning how to estimate expected returns using Asset Pricing Models including the Capital Asset Pricing Model (CAPM).You’ll learn each approach theoretically AND practically, ensuring you fully understand why the formulas work the way they do.Understanding and Measuring Risk and RelationshipsEstimate the total risk of a stock manually and on Python.Estimate the market risk of a stock; again, manually and on Python!As a by-product of learning to measure the market risk, you’ll also learn how to quantity the relationships between securities – something that will be a focal theme of portfolio management and investment / financial analysis.As with the expected returns, you’ll learn to measure risk manually as on Python. Thanks to a solid understanding of why the equations work the way they do, you’ll see how some defaults in Python’s NumPy module can lead to inaccurate estimates.Measuring Portfolio Risk and ReturnEstimate the return of a 2 asset and multi-asset portfolio.Measure the risk of a 2 asset and multi-asset portfolio.Discover the 3 factors that influence / impact portfolio risk – 1 of which is more important than the other two combined!Explore how to calculate portfolio risk and returns on Python, from scratch.Exploring Diversification & OptimisationRisk reduction by diversification.Explore Optimal Diversification – identify the ‘optimal’ number of securities to hold.Optimise your portfolio weights to achieve a target expected return.Minimise your portfolio risk (mathematically) using robust financial analysis techniques, leveraging Python for Finance.Explore the power of Python’s SciPy library to quickly and efficiently optimise your portfolios.Decomposing DiversificationInvestigate and explore why, fundamentally, diversification works for financial analysis / investment analysis.Rethink the way you measure the relationships between securities for financial analysis by extending the current measure.Explore precisely how and why the most important factor of risk influences / impacts portfolio risk.DESIGNED FOR DISTINCTIONWe’ve used the same tried and tested, proven to work teaching techniques that’ve helped our clients ace their exams and become chartered certified accountants, get hired by the most renowned investment banks in the world, and indeed, manage their own portfolios. Here’s how we’ll help you master financial analysis, take command of one of the most important concepts in Finance, and turn you into an Investment Analysis & Portfolio Management PRO:A Solid FoundationYou’ll gain a solid foundation of the core fundamentals that drive the entire investment analysis and portfolio management process. These fundamentals are the essence of financial analysis done right. And form an integral part of Finance as a whole.Example WalkthroughsEvery major concept is taught with example question walkthroughs, so you can literally see how we analyse investments and conduct rigorous financial analysis, one step at a time.Loads of Practice QuestionsApply what you learn immediately with 150+ practice questions, all with impeccably detailed solutions.Cheat Sheets & ResourcesMathematical proofs, one page cheat sheets, workable .ipynb and .py Python code – all included.Say goodbye to information overload.Engage with carefully thought out, clutter-free, and engaging study materials that focus on the 20% finance fundamentals that drive 80% of the results.Easily follow through complex financial analysis concepts with great visuals that don’t overdo it.Explore byte-sized lectures that don’t cut corners – so you receive the right amount of information which will hold you in good stead wherever you go, whatever you move on to do.Finally understand why the math works.Learn why we divide some variables by something, and multiply other variables by something else. Get past the painful approach of memorising countless equations. Not only will we rip apart each equation one variable at a time, we’ll also give you mathematical proofs that show the equation’s logic one step at a time. Save yourself time and effort by understanding why the equation works the way it does. Then go out and create your own equations, and redefine the way you conduct your own financial analysis.Watch your confidence grow.Apply what you learn immediately in example question walkthroughs and progressively challenging quizzes with impeccably detailed solutions.Engage with over 150 questions ranging from simple true and false ones to more complex problems that take you outside your comfort zone.Questions are relevant for Ivy League / Russell Group University students studying any core Finance / Financial Analysis course, as well as professionals studying for the ICAEW CFAB, ACA, ACCA, and CFA qualifications.All questions designed in-house, by Russell Group Distinction Tutors.

### Overview

Section 1: Before You Start…

Lecture 1 Welcome to the Course. Here’s What You’re Going To Master.

Lecture 2 Disclaimer

Lecture 3 IMPORTANT: Pre-Requisites | Please read before enrolling.

Lecture 4 Course FAQs

Lecture 5 Important: Course Pointers

Lecture 6 Accessing Financial Data

Section 2: Understanding Price, Risk, and Return Relationships & Calculating Returns

Lecture 7 Price, Risk, and Return – Definitions & Relationships

Lecture 8 What is Shorting?

Lecture 9 Calculating Stock Returns

Lecture 10 Calculating Stock Returns II (Applied)

Lecture 11 Variable Notations & Descriptions Cheat Sheet

Lecture 12 Additional Resources

Section 3: Estimating Expected Returns

Lecture 13 Expected Returns using Average (Mean) Method

Lecture 14 Expected Returns using Average (Mean) Method II – Creating a Function on Python

Lecture 15 Expected Returns using State Contingent Weighted Probabilities

Lecture 16 Expected Returns using Asset Pricing Models I

Lecture 17 Expected Returns using Asset Pricing Models I (Applied)

Lecture 18 Expected Returns using Asset Pricing Models II

Lecture 19 Additional Resources

Section 4: Understanding and Measuring Risk & Relationships

Lecture 20 Estimating The Total Risk of a Stock I

Lecture 21 Estimating The Total Risk of a Stock II – Applied

Lecture 22 Estimating The Market Risk of a Stock I

Lecture 23 Estimating The Market Risk of a Stock II – Applied

Lecture 24 Estimating Firm Specific Risk

Section 5: Measuring Portfolio Returns and Risk

Lecture 25 Estimating Portfolio Returns

Lecture 26 Estimating Portfolio Risk I (2 Assets)

Lecture 27 Estimating Portfolio Risk II (Multiple Assets)

Lecture 28 Estimating Portfolio Risk II (Multiple Assets) – Applied

Lecture 29 Additional Resources

Section 6: Mastery Check

Lecture 30 Take a breather!

Lecture 31 Test Guidelines [READ BEFORE YOU START THE TEST]

Lecture 32 Additional Resources

Section 7: Exploring The Effects of Diversification & Optimisation

Lecture 33 Reducing Portfolio Risk by Diversification

Lecture 34 Optimal Diversification – Number of Securities to Hold

Lecture 35 Optimising Weights To Achieve A Target Return I

Lecture 36 Optimising Weights To Achieve A Target Return II – Applied

Lecture 37 Minimising Portfolio Risk – 2 Assets

Lecture 38 Minimising Portfolio Risk – Multiple Assets, Applied

Lecture 39 Additional Resources

Section 8: Decomposing Diversification – Investigating Why It Works

Lecture 40 A Bit Puzzling?

Lecture 41 Correlation of Securities

Lecture 42 Estimating Correlation – Applied

Lecture 43 Correlation and Risk

Lecture 44 Correlation, Risk, and Returns

Lecture 45 Solving the “Puzzles”

Section 9: BONUS: Continue Your Journey On Mastering Finance

Lecture 46 What would you like to learn next?

Lecture 47 Bonus: Explore Our Other Courses

Ivy League / Russell Group University students looking to increase their competitive advantage and enhance their skills.,Finance Managers keen on applying conceptual techniques including portfolio design using Python.,Investors wanting to work with techniques that are rigorously grounded in academic and practitioner literature.,Analysts, and aspiring Investment Bankers wanting to gain a solid foundation in investment analysis.,Anyone who wants to learn investment analysis and portfolio management with Python!

#### Course Information:

Udemy | English | 9h 6m | 3.58 GB

Created by: Fervent #LearnWithDistinction

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