System Trader – Articles

Introduction to Trend-Following (revised) – Assumptions, Expectations, Indicators, Backtests and Conclusions – with video (Premium)

This article will dive into trend following. We will start by going over some key assumptions and expectations to consider when implementing a trend-following strategy. What are realistic Win Rates and Profit/Loss ratios? Attention then turns to selecting a timeframe suitable to trend-following. I will then explain 10 trend-following indicators

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Sector Breadth Models versus a Simple Trend Following Technique (Premium)

Sometimes what seems logical and helpful, is not and needs to be reconsidered. This is my conclusion with the sector breadth models. They are logical, and perhaps helpful at times, but they do not add value when it comes to timing trends in the sector SPDRs. A simple StochClose strategy performed better overall. This article will quantify signals for three breadth models using the sector SPDRs.

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Turn of the Month Strategy – Strong Long-term Performance, Beats Buy-Hold, Some Weak Months

The turn of the month shows a strong bullish bias with an extremely stable equity curve that really took off the last few years. This strategy, which is only invested 38% of the time, outperformed buy and hold with a higher Compound Annual Return. Overall, the eight day percentage change at the turn of the month is positive 68% of the time for SPY. Despite strong numbers overall, February is weakest month when testing over the last twenty years, and we just happen to be in February.

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Picking Moving Average Combos that Adapt to Changing Environments – Comparing Daily, Weekly and Monthly Signals

This article will explore and backtest different moving average combinations on the S&P 500 SPDR over the last twenty years. Most moving average strategies work great when SPY trends, regardless of the period settings. However, SPY (aka, the market) does not always trend and trends are not uniform. Some are short and fast, while others are long and steady. This means we need moving averages that can best adapt to different environments.

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