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. 

Rendimenti annualizzati

Annualizzare i rendimenti del portafoglio

Confrontare i tassi di rendimento annualizzati

Rendimenti corretti per il rischio

Interpretare lo Sharpe ratio

Rapporto di Sharpe dell'S&P500

Sharpe ratio del portafoglio

Distribuzione non normale dei rendimenti

Asimmetria dell'S&P500

Calcolare asimmetria e curtosi

Confrontare le distribuzioni dei rendimenti azionari

Misure alternative del rischio

Rapporto di Sortino

Portafoglio con massimo drawdown

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. 

Comparing against a benchmark

Active return

Industry attribution

Risk factors

Size factor

Momentum factor

Value factor

Factor models

Fama French factor correlations

Linear regression model

Fama French Factor model

Portfolio analysis tools

Performance tear sheet

Industry exposures with 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.

Rendimenti corretti per il rischio

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