Fungsi risiko PyPortfolioOpt

Tujuan dari masalah optimisasi portofolio Markowitz adalah meminimalkan varian portofolio, dengan sejumlah kendala. Apakah Anda ingat cara menghitungnya dari bab 2? Varian portofolio = bobot ditranspos * matriks kovarians * bobot. Dengan PyPortfolioOpt kita menyebut matriks kovarians sebagai sigma, untuk menandakan bahwa ini adalah kovarians sampel \(\Sigma\).

Dalam latihan ini Anda akan melihat bahwa fungsi PyPortfolioOpt untuk menghitung sigma memberikan hasil yang persis sama seperti jika Anda menghitung kovarians secara manual. Hal yang sama berlaku untuk perhitungan imbal hasil ekspektasian; Anda juga dapat memverifikasi bahwa PyPortfolioOpt memberikan keluaran yang sama seperti menghitung imbal hasil harian terannualisasi secara manual. Disediakan stock_prices. Mari kita jelajahi lebih lanjut…

Latihan ini adalah bagian dari kursus

Pengantar Analisis Portofolio dengan Python

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# Get the returns from the stock price data
returns=____.____()

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Latihan ini adalah bagian dari kursus

Pengantar Analisis Portofolio dengan Python

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4.9+

Mulai Kursus Gratis

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.

Exercise 1: Welcome to Portfolio Analysis!Exercise 2: Why invest in portfolios Exercise 3: The effect of diversification Exercise 4: Portfolio returns Exercise 5: Portfolio losses and gaining it back Exercise 6: Calculate mean returns Exercise 7: Portfolio cumulative returns Exercise 8: Measuring risk of a portfolio Exercise 9: Portfolio variance Exercise 10: Standard deviation versus variance

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.

Exercise 1: Annualized returns Exercise 2: Annualizing portfolio returns Exercise 3: Comparing annualized rates of return Exercise 4: Risk adjusted returns Exercise 5: Interpreting the Sharpe ratio Exercise 6: S&P500 Sharpe ratio Exercise 7: Portfolio Sharpe ratio Exercise 8: Non-normal distribution of returns Exercise 9: Skewness of the S&P500 Exercise 10: Calculating skewness and kurtosis Exercise 11: Comparing distributions of stock returns Exercise 12: Alternative measures of risk Exercise 13: Sortino ratio Exercise 14: Maximum draw-down portfolio

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.

Exercise 1: Comparing against a benchmark Exercise 2: Active return Exercise 3: Industry attribution Exercise 4: Risk factors Exercise 5: Size factor Exercise 6: Momentum factor Exercise 7: Value factor Exercise 8: Factor models Exercise 9: Fama French factor correlations Exercise 10: Linear regression model Exercise 11: Fama French Factor model Exercise 12: Portfolio analysis tools Exercise 13: Performance tear sheet Exercise 14: Industry exposures with Pyfolio

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.

Exercise 1: Teori portofolio modern Exercise 2: Memahami efficient frontier Exercise 3: Menghitung risiko dan imbal hasil yang diharapkan Exercise 4: Fungsi risiko PyPortfolioOpt

Latihan Saat Ini

Exercise 5: Kinerja portofolio optimal Exercise 6: Sharpe maksimum vs. volatilitas minimum Exercise 7: Optimisasi portofolio: Sharpe Maksimum Exercise 8: Optimisasi volatilitas minimum Exercise 9: Membandingkan Sharpe maksimum dengan volatilitas minimum Exercise 10: Optimisasi portofolio alternatif Exercise 11: Imbal hasil dan risiko berbobot eksponensial Exercise 12: Membandingkan pendekatan Exercise 13: Mengubah span Exercise 14: Rekap