How Larry Connors Trading Strategies Actually Work in Practice
Most people learn about the 5-day moving average strategy after reading something about Larry Connors. The concept itself is straightforward enough, but getting it to work in live markets involves some specifics that most introductions gloss over. The core setup looks at a stock or ETF pulling back toward its 5-day exponential moving average while staying above the 200-day simple moving average. You buy when price touches or dips below that 5-day line. You sell when price climbs back up to roughly 2% above your entry point. The whole thing takes maybe ten seconds to execute if you have alerts set up properly, though building a watchlist of candidates that meet the criteria can take longer depending on your tools.
Position Sizing and Risk Management
Connors recommended position sizing around 30% of your account per trade, with a hard stop at 7% below entry. If you're using leverage through margin, the math gets ugly fast because a 7% move against you plus borrowing costs compounds quickly. I ran into this personally with a small-cap biotech position in early 2023 where the 5-day bounce never came and the 200-day trend had already broken. The stop would have saved me from holding a losing position for weeks, but the timing made the trade feel wrong going in because the broader market was in chop. Here is the thing most beginners miss. The 5-day MA only works when you are catching the early part of a pullback within an established uptrend. If the 200-day MA is pointing down or flat, you are not doing Larry Connors Trading Strategies anymore. You are just buying cheap stocks hoping they bounce. The 200-day direction filter is what separates a trend-following mean reversion system from gambling.
Entry and Exit Mechanics
The entry signal triggers when a security trades at or below its 5-day EMA. You do not need it to break below. A touch is sufficient. Some traders wait for a full candle close below the 5-day to confirm, but that means you miss entries when the bounce happens quickly. In practice, I found that buying intraday when the price hits the 5-day gives better fills than waiting for the close, especially in ETFs and large-cap names where intraday volatility tends to be more predictable. Selling happens at 2% above cost basis, not when price reaches a certain level relative to the moving average. This fixed target approach removes emotion from the exit decision. The trade exits whether the stock keeps climbing or immediately reverses. You do not hold hoping for more because the rule already told you when to get out. I encountered a situation with a leveraged ETF where the 2% exit rule caused me to sell too early during a strong momentum phase. The position kept running another 8% before reversing. The workaround was adjusting the profit target to 3% for high-beta names in clear trend environments. This change improved my win rate on trend days without significantly affecting my overall returns. You have to decide whether you want more frequent small wins or fewer larger ones.
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Watchlist Construction and Screening
You need a universe of securities to scan. Connors typically used the S&P 500 or Russell 2000 constituents. The key filter is the 200-day SMA trending upward. Most screening tools let you set a slope requirement. I found that requiring the 200-day to be above its value from 20 days ago works well as a practical proxy for trend direction. Volume matters less than price action for entry timing. The strategy works on any liquid security. ETFs like SPY, QQQ, and sector funds are common choices. Individual stocks require more careful screening because earnings events and news flow can disrupt the pattern. A stock gapping down on bad earnings does not reliably bounce off the 5-day in the same way routine pullbacks do. Here is a counter-intuitive point. The best setups often come from names that are not the biggest movers. Watching the stocks that dropped 1-2% on low volume while the market stayed flat usually gives better entries than chasing the names that gapped down 5% on heavy selling. Those sharp drops often signal news-driven events that the strategy is not designed to handle.
Backtested Performance and Real-World Results
Connors published backtests showing annual returns in the 15-20% range for individual names and slightly lower for ETFs. The strategy produced positive returns in most years from 2000 through 2020. Drawdowns typically ranged from 10-15% during corrections. The strategy underperformed during extended bull markets where stocks did not pull back to the 5-day frequently. In my own testing, the strategy worked well during 2017 and 2019 when pullbacks were shallow and frequent. It struggled during 2020's March crash where stocks gapped below the 5-day and kept falling. The stop loss would have triggered repeatedly, and the 200-day filter did not protect against the speed of the decline. Switching to a shorter holding period of 2-3 days instead of the standard 5-day helped limit losses in those environments.
Pitfalls and Limitations
The strategy assumes mean reversion will occur within days, not weeks. If a stock stays below the 5-day for extended periods, you are either holding through a correction or picking up a falling knife. The 7% stop loss is designed to cut losers quickly, but it can also get hit by normal intraday volatility in high-beta names. Transaction costs eat into returns if you trade too frequently. Each round-trip trade costs approximately 0.1-0.2% in commissions and slippage for most retail accounts. At 30% position sizing, a single losing trade with the stop takes about 2% off your portfolio. You need roughly five winning trades to make up for one stopped-out position. The strategy does not work well in sideways markets where the 200-day MA flattens. Price oscillates around the moving average without clear trend direction. Whipsaws become frequent and the stop loss triggers repeatedly. I learned this the hard way during 2022's range-bound period for tech stocks. The solution was skipping trades when the 200-day slope fell below a threshold I set at 2% annualized growth. This reduced my trade frequency but improved my win rate significantly.
If you want an alternative, consider the 10-day RSI approach Connors developed separately. It has different entry conditions and works better in markets where pullbacks are deeper and less predictable. The trade-off is longer holding periods and fewer signals overall.
