The short of it
- A relative strength reading measures a price's own recent gains against its own recent losses, not one stock against another
- Trend 200, the closest strategy in Traderbot's lineup to this logic, returned 7.9% a year over nine years against a 13.7% benchmark
- Only two of six signal-based strategies beat the benchmark, and the strongest performer also carried the deepest drawdown
- Institutional Consensus, built on public 13F filings rather than price, outperformed most of the price-based signals in the comparison
What stocks relative strength index actually measures
A stocks relative strength index measures how fast a price has been rising or falling relative to its own recent history, rather than comparing one stock against another. It moves within a fixed range, climbing when recent gains dominate and falling when recent losses do, and a trader reads it to judge whether a move looks stretched rather than to price the stock outright.
Traderbot does not build a strategy directly on this specific indicator. Four of its own rules apply a related idea, though: judging a price by its own recent path rather than by a story about the company behind it. That price history reaches back to 2014-01-01 and totals 465,335 daily closes, long enough to judge a signal across more than one market cycle rather than one lucky quarter.
Where a relative strength rule fits among Traderbot's signals
The closest strategy in Traderbot's lineup is Trend 200, which holds a position only while price sits above a long moving average and exits once price falls below it. A relative strength reading works on a similar principle, just measured differently: instead of comparing today's price to a single moving average, it weighs the size of recent gains against the size of recent losses.
Both approaches share one trait: neither one asks what a company does or what it is worth, only how its price has been behaving lately. Neither approach reads a filing, either, which sets both apart from the institutional strategies covered later.
Nine years of signal-based strategies against the benchmark
Traderbot ran six of these signal-driven strategies from $10,000.00 starting 2017-01-03, and measured each against a plain S&P 500 fund, which returned 13.7% a year across the same window.
| Strategy | Annual return | Deepest fall | Ending value |
|---|---|---|---|
| Crypto Trend | 48.0% | 80.4% | $433,052.62 |
| Ladder 36 Plus | 15.4% | 43.7% | $39,797.75 |
| Volatility Target | 9.6% | 25.2% | $24,073.85 |
| Dual Momentum | 8.7% | 43.7% | $22,239.50 |
| Trend 200 | 7.9% | 25.1% | $20,744.96 |
| Sector Rotation | -0.5% | 36.6% | $9,508.82 |
Only two of the six beat the benchmark, and the strongest signal-based result, Crypto Trend, carried the deepest fall of the entire group. A rule built purely on recent price strength does not avoid losing stretches; it simply reacts to them differently than a plain index holding would.
Volatility Target sat closest to the benchmark without reaching it, holding less of the index while it moved sharply and more of it while things stayed calm, ending at 9.6% a year with a 25.2% deepest fall.
The arithmetic of a signal that trades rarely
Trend 200 filled only 79 times across the tested window, reacting only when price crossed its long moving average rather than adjusting continuously the way a bounded indicator might. Nine years and roughly seven months separate 2017-01-03 from 2026-08-14, and compounding $10,000.00 at Trend 200's 7.9% a year across that stretch, by hand, comes out close to $20,600, within a few hundred dollars of the strategy's actual $20,744.96 result.
That small gap between the hand-calculated estimate and the real backtest is the kind of check worth running on any rule before trusting its published rate. The same arithmetic applied to the benchmark's 13.7% a year lands close to $34,300, well ahead of the signal-based result.
When a strength signal turns into a losing rule
Sector Rotation, which moves into the three strongest sectors of the last six months, lost money outright over the same nine years, returning -0.5% a year with a 36.6% deepest fall. Chasing whatever has been strongest recently can mean buying in just as that strength runs out, which is the risk built into any rule that reads price momentum without a second check.
Risk Parity, by contrast, gave the quieter asset the larger share rather than chasing strength at all, and finished ahead of Sector Rotation at 7.4% a year with a smaller 23.7% deepest fall. Ladder 36, the plain savings-plan strategy without a momentum core, sat close by at 7.0% a year, neither chasing strength nor avoiding it outright.
Reading a signal against public filings instead of price
Not every Traderbot strategy reads price at all. Institutional Consensus buys whatever the largest managers reported buying last quarter, based on public form 13F filings rather than on any price-based signal, and it returned 13.0% a year over the identical window, ahead of every signal-based strategy in the table above except Crypto Trend and Ladder 36 Plus.
That comparison is a reminder that a relative-strength-style signal is only one way to decide what to hold; a filing-based rule can outperform it without looking at price momentum at all. Fund Mirror, which copies one manager's reported weights instead of a consensus, returned only 6.2% a year over the same window, showing that not every filing-based rule fares as well.
Testing a signal before trusting it
Traderbot backtests every one of these approaches, price-based and filing-based alike, on the algorithms page. The money there is simulated rather than live, and each operation that moves it, a deposit, a withdrawal, a buy, a sell or a plan payment, costs one percent. The filings behind the institutional strategies can be checked directly through SEC EDGAR company search.