Sortino oranıyla strateji performansını değerlendir

Sortino oranı, risksiz getiri üzerindeki aşırı getirinin aşağı yönlü sapmaya bölünmesiyle elde edilir ve böylece "kötü" oynaklığa göre aşırı getiriyi ölçer. Başka bir deyişle, pozitif aşırı getirinin oynaklığını cezalandırmaz.

Aynı stratejiyi önceki egzersizde olduğu gibi Sortino oranıyla değerlendirecek ve farklı bir tablo çizip çizmediğine bakacaksın. Hatırlatma olarak, strateji iki hareketli ortalama göstergesini kullanan sinyal tabanlı bir strateji. Google'ın 3 yıllık tarihsel hisse senedi fiyat verisiyle yapılan strateji geriye dönük test istatistiği resInfo içinde yüklendi. Sharpe oranları senin için yazdırıldı ve konsolda görünür.

Bu egzersiz

Python ile Finansal Alım Satım

kursunun bir parçasıdır

Kursu Görüntüle

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

# Print annual Sortino ratio
yearly_sortino = ____
print('Annual Sortino ratio: %.2f'% yearly_sortino)

# Print monthly Sortino ratio
monthly_sortino = ____
print('Monthly Sortino ratio %.2f'% monthly_sortino)

Kodu Düzenle ve Çalıştır

Bu egzersiz

Python ile Finansal Alım Satım

kursunun bir parçasıdır

IntermediárioNível de habilidade

4.8+

Kursa Ücretsiz Başlayın

What is financial trading, why do people trade, and what’s the difference between technical trading and value investing? This chapter answers all these questions and more. You’ll also learn useful tools to explore trading data, generate plots, and how to implement and backtest a simple trading strategy in Python.

Exercise 1: What is financial trading Exercise 2: The concept of trading Exercise 3: Plot a time series line chart Exercise 4: Plot a candlestick chart Exercise 5: Getting familiar with your trading data Exercise 6: Resample the data Exercise 7: Plot a return histogram Exercise 8: Calculate and plot SMAs Exercise 9: Financial trading with bt Exercise 10: The bt process Exercise 11: Define and backtest a simple strategy

Let's dive into the world of technical indicators—a useful tool for constructing trading signals and building strategies. You’ll get familiar with the three main indicator groups, including moving averages, ADX, RSI, and Bollinger Bands. By the end of this chapter, you’ll be able to calculate, plot, and understand the implications of indicators in Python.

Exercise 1: Trend indicator MAs Exercise 2: Calculate and plot two EMAs Exercise 3: SMA vs. EMA Exercise 4: Strength indicator: ADX Exercise 5: Understand the ADX Exercise 6: Calculate the ADX Exercise 7: Visualize the ADX Exercise 8: Momentum indicator: RSI Exercise 9: Understand the RSI Exercise 10: Calculate the RSI Exercise 11: Visualize the RSI Exercise 12: Volatility indicator: Bollinger Bands Exercise 13: Understand Bollinger Bands Exercise 14: Implement Bollinger Bands

You’re now ready to construct signals and use them to build trading strategies. You’ll get to know the two main styles of trading strategies: trend following and mean reversion. Working with real-life stock data, you’ll gain hands-on experience in implementing and backtesting these strategies and become more familiar with the concepts of strategy optimization and benchmarking.

Exercise 1: Trading signals Exercise 2: Understand trading signals Exercise 3: Build an SMA-based signal strategy Exercise 4: Build an EMA-based signal strategy Exercise 5: Trend-following strategies Exercise 6: Construct an EMA crossover signal Exercise 7: Build and backtest a trend-following strategy Exercise 8: Mean reversion strategy Exercise 9: Match the signals with the strategies Exercise 10: Construct an RSI based signal Exercise 11: Build and backtest a mean reversion strategy Exercise 12: Strategy optimization and benchmarking Exercise 13: Conduct a strategy optimization Exercise 14: Perform a strategy benchmarking

How is your trading strategy performing? Now it’s time to take a look at the detailed statistics of the strategy backtest result. You’ll gain knowledge of useful performance metrics, such as returns, drawdowns, Calmar ratio, Sharpe ratio, and Sortino ratio. You’ll then tie it all together by learning how to obtain these ratios from the backtest results and evaluate the strategy performance on a risk-adjusted basis.

Exercise 1: Strateji getirisi analizi Exercise 2: Bir backtest'in getiri sonuçlarını gözden geçir Exercise 3: Bir backtest'in getiri histogramlarını çiz Exercise 4: Birden fazla stratejinin getiri sonuçlarını karşılaştır Exercise 5: Gerileme (Drawdown)Exercise 6: Düşüşlerle performansı gözden geçir Exercise 7: Calmar oranını hesapla ve gözden geçir Exercise 8: Sharpe oranı ve Sortino oranı Exercise 9: Sharpe oranıyla strateji performansını değerlendir Exercise 10: Sortino oranıyla strateji performansını değerlendir

Geçerli Egzersiz

Exercise 11: Tebrikler!