“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.
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?
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.
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?
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”
If indicators didn’t help your trading so far, just pimp them by preprocessing their input data. John Ehlers proposed in his TASC September article the windowing technique: multiply the input data with an array of factors. Let’s see how triangle, Hamming, and Hann factor arrays can improve the SMA indicator.
Compared to plain indicators, bands have the advantage that they look more colorful on charts. And they offer more lines to trigger trade signals. In this way, bands beat any old single-line indicator hands down. This was also noticed by Vitali Apirine, who invented in the Stocks&Commodities August 2021 issue a new sort of bands.
There’s no doubt that buying and holding index ETFs is a long-term profitable strategy. But it has two problems. It does not reinvest profits, so the capital grows only linearly, not exponentially. And it exposes the capital to the full rollercoaster market risk. A sure way to go out of the market in a downtrend, and invest the profits back in an uptrend would be (almost) priceless. Markos Katsanos promises no less in his Stocks&Commodities July 2021 article. Does this really work? Continue reading “Buy&Hold? No, Buy&Sell!”
The previous article dealt with John Ehlers’ AM and FM demodulating technology for separating signal and noise in price curves. In the S&C June issue he described a practical example. Applying his FM demodulator makes a strategy noticeably more robust – at least with parameter optimization.
Price curves consist of much noise and little signal. For separating the latter from the former, John Ehlers proposed in the Stocks&Commodities May 2021 issue an unusual approach: Treat the price curve like a radio wave. Apply AM and FM demodulating technology for separating trade signals from the underlying noise. Continue reading “The Price Wave Radio”