In a previous post, we demonstrated the mean-reverting and trending properties of SP500. We subsequently developed a trading system based on the mean-reverting behavior of the index. In this installment, we will develop a trend-following trading strategy.
http://tech.harbourfronts.com/trend-following-trading-system-quantitative-trading-in-python/
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In a previous post, we demonstrated the mean-reverting and trending properties of SP500. We subsequently developed a trading system based on the mean-reverting behavior of the index. In this installment, we will develop a trend-following trading strategy.
http://tech.harbourfronts.com/trend-following-trading-system-quantitative-trading-in-python/
Garman-Klass-Yang-Zhang Historical Volatility Calculation – Volatility Analysis in Python
Harbourfront Technologies
1 minute 41 seconds
5 years ago
Garman-Klass-Yang-Zhang Historical Volatility Calculation – Volatility Analysis in Python
We present an extension of the Garman-Klass volatility estimator that also takes into consideration overnight jumps. Garman-Klass-Yang-Zhang (GKYZ) volatility estimator consists of using the returns of open, high, low, and closing prices in its calculation. It also uses the previous day’s closing price.
http://tech.harbourfronts.com/trading/garman-klass-yang-zhang-historical-volatility-calculation-volatility-analysis-python/
Harbourfront Technologies
In a previous post, we demonstrated the mean-reverting and trending properties of SP500. We subsequently developed a trading system based on the mean-reverting behavior of the index. In this installment, we will develop a trend-following trading strategy.
http://tech.harbourfronts.com/trend-following-trading-system-quantitative-trading-in-python/
