RealTest Short Term Mean Reversion Strategy
A RealTest strategy that buys short-term pullbacks in S&P 500 stocks that are still in a confirmed uptrend, following the Connors and Alvarez methodology. By only buying dips inside a rising trend, it stays with strong stocks going through temporary weakness rather than ones that are breaking down. Tested on survivorship-free Norgate data with commissions modeled, and trading live since October 2024.
Live traded since Oct 2024Trading costs included
Survivorship-bias-free data
Strategy
SPY buy & hold
Sharpe ratio?
0.97
+102%vs SPY 0.48
Best year?
+120.2%
4.5×SPY best: 27.0% in 2003
Max drawdown?
-19.0%
62% smallervs SPY -49.9%
Validated four ways
Live market performance
Performs in real market conditions since 2024-10-09
VerifiedStatistical validation
Validated across in-sample & out-of-sample data
Walk forward analysis
Tests robustness across unseen data
Monte Carlo stress test
Resilient against 1,000+ sequence risk simulations
What happened in every crash
| Crisis | Dates | Strategy | SPY | Same $100k in |
|---|---|---|---|---|
| Dotcom crash | Mar 2000 – Oct 2002 | 136.2% | -41.8% | |
| 2008 financial crisis | Oct 2007 – Mar 2009 | -5.1% | -49.9% | |
| COVID-19 crash | Feb 2020 – Mar 2020 | -1.6% | -28.7% | |
| 2022 bear market | Jan 2022 – Oct 2022 | 12.9% | -21.3% |
Strategy monthly returns
| Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | Year | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2000 | 10.6 | 2.3 | 16.8 | 13.0 | 15.3 | 3.8 | 4.5 | 2.2 | -0.5 | 12.9 | -6.9 | 10.2 | 120.2% |
| 2001 | 0.5 | 0.8 | 4.4 | 2.4 | -0.5 | 0.7 | 4.0 | 0.6 | -9.1 | 2.8 | 3.2 | 4.9 | 14.9% |
| 2002 | 1.8 | -3.8 | 1.0 | 3.9 | 1.5 | 1.3 | -0.5 | 0.0 | -1.4 | -0.1 | 0.6 | 1.8 | 6.1% |
| 2003 | -0.7 | 2.3 | 4.6 | 2.1 | 0.4 | 5.5 | 3.5 | 3.1 | -1.6 | 5.6 | 1.5 | 2.4 | 32.5% |
| 2004 | 0.1 | 0.7 | 3.3 | -5.3 | 1.9 | 2.0 | -1.5 | -1.7 | -0.5 | -0.7 | -0.0 | 2.2 | 0.3% |
| 2005 | 0.6 | 2.2 | -0.7 | 3.4 | 5.0 | 0.0 | 1.5 | -0.7 | 0.0 | 0.2 | -0.7 | 0.7 | 11.9% |
| 2006 | 1.5 | 1.4 | 1.7 | 2.0 | -3.5 | 3.3 | 0.1 | 0.0 | 0.8 | -1.0 | -0.5 | 1.0 | 6.9% |
| 2007 | 0.9 | -0.3 | -0.1 | -0.1 | 0.4 | 0.0 | -1.9 | 14.3 | 0.0 | 2.1 | 2.5 | 0.4 | 18.9% |
| 2008 | -9.4 | -0.3 | 6.9 | -2.0 | 1.3 | -0.1 | -4.0 | 2.2 | 4.2 | -7.9 | 0.0 | -0.1 | -9.9% |
| 2009 | 2.1 | -0.3 | -1.1 | 5.2 | 2.2 | 3.1 | 0.2 | 0.4 | 2.0 | -1.6 | 8.1 | 0.6 | 22.7% |
| 2010 | -3.0 | 10.1 | 0.2 | -1.4 | -0.2 | -1.5 | 1.8 | -0.7 | 1.0 | 0.7 | 0.5 | 0.9 | 8.2% |
| 2011 | -0.2 | 4.1 | 1.6 | 0.0 | 1.6 | 0.6 | -1.5 | -3.3 | -0.4 | 8.0 | 0.2 | 1.4 | 12.4% |
| 2012 | 1.0 | 0.9 | 1.4 | -0.4 | 1.2 | 6.6 | 1.3 | 0.5 | 0.0 | -0.8 | 0.3 | 0.0 | 12.5% |
| 2013 | -0.0 | 0.5 | 0.3 | 2.7 | 0.8 | 1.7 | 0.6 | -1.1 | 0.8 | 1.6 | -0.7 | -0.6 | 6.6% |
| 2014 | -1.2 | 1.6 | -1.5 | 1.6 | 0.9 | 0.2 | 0.6 | 0.7 | -0.4 | 2.4 | -0.3 | 0.6 | 5.3% |
| 2015 | 1.2 | -0.1 | -0.1 | -0.6 | 0.2 | 0.0 | 0.5 | 8.7 | 0.8 | 3.5 | 0.6 | 0.8 | 16.2% |
| 2016 | 0.1 | 6.8 | 0.0 | 0.0 | 0.0 | 0.4 | 0.8 | 1.5 | 0.1 | -2.8 | 0.7 | -1.5 | 6.0% |
| 2017 | -1.4 | -0.6 | 1.1 | 0.3 | 0.5 | -0.0 | 0.6 | 1.1 | 0.3 | 2.5 | 0.7 | 1.4 | 6.6% |
| 2018 | 0.6 | 2.4 | -0.1 | 0.0 | -0.2 | 0.6 | 0.6 | 1.1 | 1.0 | 1.6 | 3.8 | -0.0 | 11.9% |
| 2019 | -0.1 | 0.5 | -0.1 | 0.8 | -1.6 | 0.8 | -0.6 | -0.8 | 0.4 | -0.3 | 0.4 | 0.0 | -0.6% |
| 2020 | -0.3 | -1.1 | 5.2 | 0.0 | 0.8 | 0.3 | 0.1 | -0.1 | 2.8 | -2.2 | 5.1 | 0.0 | 10.9% |
| 2021 | 2.4 | 10.8 | -2.5 | -0.9 | 0.2 | 0.0 | 9.9 | 5.2 | 2.3 | 0.9 | 0.5 | 1.6 | 33.8% |
| 2022 | -1.4 | 3.5 | 6.6 | 2.4 | 5.4 | -5.6 | 0.2 | 0.0 | 0.1 | 3.0 | 1.8 | -0.6 | 15.9% |
| 2023 | 0.5 | 1.5 | -1.2 | 0.4 | -0.3 | 0.0 | 0.5 | -1.7 | -0.0 | -0.7 | 1.9 | 0.0 | 0.9% |
| 2024 | 0.8 | 0.6 | 2.6 | 5.5 | 0.7 | 0.6 | -1.3 | 0.4 | 0.6 | -1.8 | 2.4 | 1.8 | 13.5% |
| 2025 | 2.8 | 0.1 | -5.0 | 8.8 | -2.6 | 0.0 | 0.1 | 0.7 | 0.1 | 0.4 | 4.6 | 0.5 | 10.4% |
| 2026 | 0.9 | 2.7 | 5.0 | 1.5 | 0.9 | 1.7 | 14.8 | 0.5 | 30.9% |
Strategy overview
Strategy details & model assumptions
Details
StyleMean reversionUniverseS&P 500 current & past stocksTimeframeDailySideLongEntry executionLimit orderExit executionLimit order
Costs included in results
Commission$0.005 / shareLimit price buffer0.1% past limitSPY benchmarkNo fees applied (favors SPY)
What you get
RealTest strategy code (.rts)
Complete RealTest (.rts) strategy code. Import, backtest, and modify.
Plain text rules
Trade it on any platform without reading the code.
What you need
Market dataNorgate Data US Stocks. Platinum Plan to reproduce the backtest, because it carries delisted stocks. Silver Plan is enough to trade it live.SoftwareRealTest (since 2024 or later).Without RealTest or NorgateThe rules come as plain English, not only as code. You can use the strategy rules in TradingView, Python, AmiBroker or your own tools.
Quick start & live trading
Quick start guide
From download to first backtest in 1 minute
1
You download the .rts file
Click download
2
You open it in RealTest
File → Open → Select file
3
You import symbols
Click import
4
You run the backtest
Click test
Daily live trading
For RealTest automated execution
1
Open OrderClerk
Click 'Connect to IB'
2
Import signals
Click 'Import' in RealTest
3
Generate orders
Click 'Orders' in RealTest
4
Execute trades
Click 'Place Orders'
What traders say
❝
Buying a SetupAlpha strategy didn't save me money, it saved me research time. I estimate it replaced 70–90 hours of development, debugging, and validation. Even if I never trade the strategy exactly as delivered, the research process was worth the investment.
Roman Blackwood
Founder of AI in Trading (+13K subscribers)
❝
I've been using a strategy from SetupAlpha and I'm really impressed with its elegance and stability. The unique approach gives me a fresh perspective and ideas I can apply to other strategies I'm developing. I'm currently working on integrating it into my suite of trading strategies.
TradeQuantiX
Multi-country systematic trader (+4.7K subscribers)
❝
I traded discretionary for over a decade and kept putting off going systematic because I did not know where to start. Having a finished, tested system to take apart was what finally got me moving.
Daniel
Crypto trader
❝
I have run it live since 2024 and it is still in my portfolio. It also changed how I test the systems I build myself.
Systematic Traders
Algo trader & Substack writer (+6.4K subscribers)
FAQ
What is RealTest Short Term Mean Reversion Strategy?
A RealTest strategy that buys short-term pullbacks in S&P 500 stocks that are still in a confirmed uptrend, following the Connors and Alvarez methodology. By only buying dips inside a rising trend, it stays with strong stocks going through temporary weakness rather than ones that are breaking down. Tested on survivorship-free Norgate data with commissions modeled, and trading live since October 2024.
Why should this edge keep working?
A stock in a steady uptrend that dips for a few days is usually seeing normal profit-taking, not the end of its trend. Once that short-term selling clears, the stock tends to resume its uptrend. The strategy only buys these dips in stocks that are already trending higher, so it is buying temporary weakness in a strong name rather than one that is genuinely falling apart. Buying pullbacks within an uptrend is one of the most tested ideas in short-term mean reversion.
What is RealTest and what software do I need?
RealTest is a backtesting and trade automation platform for systematic traders, built by Martin Parker at MHP Trading. Each strategy comes as an .rts file you import directly. To trade it live you add OrderClerk and an Interactive Brokers account.
How was this backtested?
Survivorship-free Norgate data from January 2000 to the present, with out-of-sample walk-forward analysis and over 1000 Monte Carlo simulations to test stability.
Are transaction costs included?
Yes. The results include Interactive Brokers commissions, and a limit-order buffer of 0.1% past limit, so the equity curve is after costs.
When did live trading start?
Live trading started in October 2024. The equity curve shows the backtest from 2000 and real performance from that point on.
What's included in the download?
RealTest .rts file (complete source). Plain-text trading rules. Full documentation with parameter explanations.
How does it compare to SPY?
The chart at the top plots this strategy against SPY, the S&P 500 ETF, from 2000 with both starting at $100,000. The Full metrics panel lists the exact numbers side by side, including CAGR, maximum drawdown, Sharpe and Sortino for the strategy and for SPY over the same period.
Can I modify the code?
Yes. You get the complete source code with a perpetual license, so you can adjust parameters, change position sizing, combine it with other systems, or use it as a starting point for your own research.
What market data do I need?
Norgate Data (recommended) for survivorship-free US equities. Yahoo Finance works for basic testing but lacks delisted stocks. The backtest results shown here use Norgate Platinum.
Can I automate execution?
RealTest to OrderClerk to Interactive Brokers. Generate signals daily in RealTest, execute automatically via OrderClerk to IBKR. Setup course available.
Can I ask questions about the code or the strategy?
Yes. Email setupalpha.capital@gmail.com and you will get an answer, before or after you buy.
Portfolio growth since 2000
3,473.6%
SPY same period: 491.9%
$790one-time
Instant download
| Metric | Strategy | SPY |
| Sharpe | 0.97 | 0.48 |
| ROR | 14.31% | – |
| Sortino | 0.79 | 0.45 |
| MAR | 0.75 | – |
| Net profit | $3.5M | $492k |
| Expectancy | 2.31% | – |
| Max exposure | 151.78% | 100% |
| Worst year | -9.9% | -33.2% |
Download the complete strategy now
Active Script - C:\REALTEST\Strategies\short_term_mean_reversion.rts
Plain text rules
Trade it on any platform without reading the code.
RealTest Short Term Mean Reversion Strategy
$790one-time
Instant download