In the TASC September issue, Alfred Tagher presented a new indicator based on the Commitment Of Traders (COT) report. This report is available on the NASDAQ website. It is released weekly by the Commodities Futures Trading Commission and reflects the activities of various groups of commercial and noncommercial traders. Evaluating this report allows trading systems to automatically follow the “smart money”.
Continue reading “High-Conviction Trading”
All the popular ‘smoothing’ indicators, like SMA or lowpass filters, exchange more lag for more smoothing. In TASC 4/2023, John Ehlers suggested the undersampling of price curves for achieving a better compromise between smoothness and lag. We will check that by applying a Hann filter to the original price curve and to a 5-fold undersampled curve. Continue reading “Undersampling”
In his TASC February 2023 article, John Ehlers proposed to use the average of open and close, rather than the close price, for technical indicators. The advantage is a certain amount of noise reduction. On intraday bars the open-close average is similar to an SMA(2). It makes the data a bit smoother, but at cost of additional lag by half a bar. Continue reading “Open or Close? Why Not Both?”
There are already uncounted variants of moving averages. Vitali Apirine invented another one in his article in the Stocks&Commodities September issue. The LREMA is an EMA with a variable period derived from the distance of the current price and a linear regression line. This ensures an optimal EMA period at any point – at least in theory. Will this complex EMA variant beat the standard EMA for detecting trend changes?
Continue reading “The Linear Regression-Adjusted Exponential Moving Average”
Price charts normally display price over time. Or in some special cases price over ranges or momentum. In his TASC articles in June and July 2022, John Ehlers proposed a different way of charting. The relation of two parameters, like price over momentum, or price A over price B, is displayed as a 2D curve in a scatter plot. The resulting closed or open loop is supposed to predict the future price development. Of course only if interpreted in the right way.
Continue reading “Ehlers Loops”
“Sell in May and go away” is an old stock trader’s wisdom. But in his TASC May 2022 article, Markos Katsanos examined that rule in detail and found that it should rather be “Sell in August and buy back in October”. Can trading be really this easy? Let’s have a look at the simple seasonal trading rule and a far more complex application of it.
Continue reading “Never Sell in May!”
The exponential moving average (EMA) and the Relative Strength Indicator (RSI) are both very popular and useful indicators for algorithmic trading. So why no glue both together to get an even better indicator? That was the basic idea of Vitali Apirine’s TASC 3/2022 article. We’re measuring the relative strength of a volatility index (VIX), and use the result as an EMA time period. Do we now have the ultimate indicator to beat them all?
Continue reading “The Relative Vix Strength Exponential Moving Average”
The Fisher Transform converts data to or from a Gaussian distribution. It was first used in algorithmic trading by John Ehlers (1) , and became a common part of indicators since then. In a TASC February 2022 article, Ehlers described a new indicator, the Elegant Oscillator, based on the Inverse Fisher Transform. Let’s have a look at this indicator and how it’s used in a trading system.
Continue reading “The Inverse Fisher Transform”
John Ehlers strikes again. The TASC January 2022 issue features another indicator supposedly improved with Hann windowing – the RSIH, a RSI with Hann flavour. Can it beat the standard RSI?
Continue reading “Yet Another Improved RSI”
As an application to the windowing technique described the the previous article, John Ehlers proposed a new trend indicator that he claimed is robust and yet simple. The latter is certainly true, as the MAD (Moving Average Difference) oscillator is, as the name says, just the difference of two moving averages normalized to +/-100. Continue reading “The MAD indicator”