The test I ran
I took the 160-day illustrative close series from Foundations and applied three rules. Rule A is buy and hold. Rule B is long the series when yesterday’s close is above yesterday’s 50-day SMA, else cash. Rule C is a 20 / 50 crossover: long when SMA-20 is above SMA-50. Fills are the next day, as described in Architecture. Cash earns nothing. I am showing this as a methods check, not as a live track record.
The idea is the same one Faber (2007) used on monthly index data with a 10-month average, and the same family Brock et al. (1992) studied on the Dow. My window is much shorter and the path is constructed, so the numbers are for the graphs on this page only.
Numbers from this path
| Rule | Total return | Max drop | Flips |
|---|---|---|---|
| Buy and hold (illustrative) | −6.5% | −10.4% | 1 |
| SMA-50 long/cash | −3.3% | −4.3% | 12 |
| SMA-20 / SMA-50 cross | −1.1% | −2.9% | 4 |
Table 2. On this one path, buy and hold made more money and also fell more. The 50-day rule gave up some return and cut the worst peak-to-trough drop roughly in half. The 20 / 50 cross traded more often and did worse than the slower rule. That last part matches what I expected after reading that faster averages whip around in noisy stretches (StockCharts, n.d.).
What went wrong on purpose
Around the middle of the sample the price drops, bounces, drops again. The 50-day average is still high, so the rule sells late. Then price pokes above the average and the rule buys, then the second dip knocks it back to cash. That extra round trip is a whipsaw. It is the standard failure mode of trend rules in a range (Quantpedia, 2023). A student looking only at the “sold before the crash” part of Figure 8 would miss this.
RSI told a similar story. During the drop, RSI-14 spent time under 30. If I had bought those oversold prints I would have been catching a falling series, not fading a finished move. That is why I did not combine “RSI under 30 means buy” with a downtrend filter in this first pass. Mean-reversion and trend-following fight each other unless you say when each one is allowed to speak.
How this sits next to published work
Faber’s 10-month SMA overlay is famous because, in his long sample, it reduced drawdowns in equity indexes while keeping most of the upside (Faber, 2007). Siegel’s discussion of a 200-day rule on the Dow is in the same family (cited in Quantpedia, 2023). My table is not a replication of those papers. I do not have 1886–2006 of the Dow on this site. I only wanted to see the same shape — less pain, less return, some extra trades — show up in a tiny example I fully control.
Brock, Lakonishok, and LeBaron (1992) is the citation I keep coming back to for the crossover itself. They were asking whether simple rules had statistical content, not whether a computer-engineering student should trade them with rent money. I am asking the smaller question: can I implement the rule without cheating on time, and does the picture look like the story in those papers? On this path, yes for the slow rule, no for the impatient one.
Limits
- One constructed series. No other tickers, no other decades.
- No dividends, no T-bill rate when in cash, one small cost number.
- No walk-forward, no hold-out year, no statistical test of edge.
- Charts on this website are for teaching the pipeline.
None of this is investment advice. It is a write-up of a beginner study on how a trading program processes data and decides to act.