In the first chapter, you’ll learn how a portfolio is build up out of individual assets and corresponding weights. The chapter also covers how to calculate the main characteristics of a portfolio: returns and risk. 

Welcome to Portfolio Analysis!

Why invest in portfolios

The effect of diversification

Portfolio returns

Portfolio losses and gaining it back

Calculate mean returns

Portfolio cumulative returns

Measuring risk of a portfolio

Portfolio variance

Standard deviation versus variance

Introduction to Portfolio Analysis

Chapter 2 goes deeper into how to measure returns and risk accurately. The two most important measures of return, annualized returns, and risk-adjusted returns, are covered in the first part of the chapter. In the second part, you’ll learn how to look at risk from different perspectives. This part focuses on skewness and kurtosis of a distribution, as well as downside risk. 

Annualized returns

Annualizing portfolio returns

Comparing annualized rates of return

Risk adjusted returns

Interpreting the Sharpe ratio

S&P500 Sharpe ratio

Portfolio Sharpe ratio

Non-normal distribution of returns

Skewness of the S&P500

Calculating skewness and kurtosis

Comparing distributions of stock returns

Alternative measures of risk

Sortino ratio

Maximum draw-down portfolio

Risk and Return

In chapter 3, you’ll learn about investment factors and how they play a role in driving risk and return. You’ll learn about the Fama French factor model, and use that to break down portfolio returns into explainable, common factors. This chapter also covers how to use Pyfolio, a public portfolio analysis tool. 

Confronto con un benchmark

Rendimento attivo

Attribuzione per settore

Fattori di rischio

Fattore dimensione

Fattore momentum

Fattore value

Modelli fattoriali

Correlazioni dei fattori di Fama-French

Modello di regressione lineare

Modello a fattori di Fama-French

Strumenti per l’analisi del portafoglio

Scheda di performance

Esposizioni settoriali con Pyfolio

Performance Attribution

In this last chapter, you learn how to create optimal portfolio weights, using Markowitz’ portfolio optimization framework. You’ll learn how to find the optimal weights for the desired level of risk or return. Lastly, you’ll learn alternative ways to calculate expected risk and return, using the most recent data only. 

Modern portfolio theory

Understanding the efficient frontier

Calculating expected risk and returns

PyPortfolioOpt risk functions

Optimal portfolio performance

Maximum Sharpe vs. minimum volatility

Portfolio optimization: Max Sharpe

Minimum volatility optimization

Comparing max Sharpe to min vol

Alternative portfolio optimization

Exponentially weighted returns and risk

Comparing approaches

Changing the span

Recap

Portfolio Optimization

Small portfolio

S&P500

Large portfolio

Factors for portfolio returns

Portfolio factors

Ti sei mai chiesto se un fondo d'investimento sia davvero una buona scelta? O hai confrontato due opzioni d'investimento chiedendoti cosa le distingua? Cosa significa davvero l'indicatore di rischio di questi fondi? Oppure lavori spesso con dati finanziari e vuoi ottenere un vantaggio? In questo corso entrerai nell'affascinante mondo degli investimenti: scoprirai cosa sono i portafogli, il rischio e il rendimento, e come analizzarli in modo critico. Lavorando su dati storici reali di titoli azionari, imparerai a calcolare misure significative di rischio, a scomporre la performance e a costruire un portafoglio ottimale in base al compromesso rischio-rendimento desiderato. Al termine, saprai prendere decisioni d'investimento guidate dai dati e comprenderai meglio i portafogli d'investimento.

Manipulating Time Series Data in Python

Intermediate Python for Finance

Impara a calcolare misure di rischio e rendimento e a creare un portafoglio ottimale per il trade-off.

Confronto con un benchmark

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