From Paper Trading to Real Money: One Month of Consistent Profits and the Big Question
TL;DR
A Reddit trader shared their journey of testing a self-coded trading bot on Interactive Brokers’ paper trading platform for one month, achieving consistent profits. The post sparked a heated debate in r/algotrading with 119 comments discussing whether paper trading success translates to live trading, the psychological barriers of going live, and the technical differences between simulated and real market conditions. The consensus? Paper trading is a necessary first step, but it’s far from the whole story. Real trading introduces slippage, liquidity issues, and emotional challenges that no simulation can replicate.
What the Sources Say
The discussion on Reddit revealed several key themes that experienced algo traders agree on:
Paper Trading Is Just the Beginning
The community consensus is clear: one month of paper trading profits doesn’t guarantee live success. According to multiple commenters, paper trading serves as a basic sanity check for your code and strategy, but it’s not a reliable predictor of real-world performance. One user put it bluntly: “Paper trading is good for testing if your code works, not if your strategy works.”
The main reason? Paper trading doesn’t account for real market microstructure. When you place a market order in paper trading, you typically get filled at the displayed bid or ask price instantly. In live trading, you’re competing with high-frequency trading firms, dealing with partial fills, and experiencing slippage—the difference between your expected price and actual execution price.
The Slippage Reality Check
Several experienced traders in the thread emphasized that slippage can make or break a profitable strategy. One commenter shared: “What looks like a 2% monthly return in paper trading might become break-even or even negative once you factor in real slippage and commissions.”
This is particularly true for strategies that:
- Trade frequently (hundreds or thousands of trades per month)
- Trade less liquid instruments
- Use market orders instead of limit orders
- Rely on tight profit margins per trade
The community strongly recommended that before going live, the trader should analyze their strategy’s sensitivity to slippage and model realistic execution assumptions based on actual market depth data.
Start Small, Scale Gradually
There’s overwhelming agreement on one point: don’t go “full live” immediately. The recommended approach is to start with the smallest position sizes possible—what one trader called “embarrassingly small”—and gradually scale up as you gain confidence and validate that your paper trading results translate to real markets.
One experienced trader shared their approach: “I ran paper trading for three months with good results, then went live with 1% of my intended capital. After another three months of live trading matching my paper results, I increased to 10%. Only after six months of live verification did I go to full size.”
The Psychological Factor Nobody Talks About
Multiple commenters highlighted something that surprised the original poster: the emotional difference between paper and live trading is massive, even when running automated strategies. When it’s your real money on the line, you’ll second-guess your code, panic during drawdowns, and be tempted to manually intervene—all things that can destroy an otherwise sound strategy.
One trader noted: “I’ve seen people with profitable strategies blow up their accounts not because the strategy failed, but because they couldn’t emotionally handle a normal 15% drawdown and shut everything down at the worst possible moment.”
Interactive Brokers Specific Considerations
Several IBKR users chimed in with platform-specific advice. IBKR’s paper trading is generally considered one of the better simulations available, but it still has limitations:
- Paper trading fills are often more optimistic than live fills
- Market data might have slight delays compared to live feeds
- Order queue priority isn’t accurately simulated
- The paper trading environment doesn’t account for account-level risks like margin calls under real market stress
One IBKR user recommended: “Before going live, backtest your strategy with conservative slippage assumptions (0.02-0.05% per trade depending on the instrument), then compare that to your paper trading results. If the backtested version is still profitable, you’re in better shape.”
Warning Signs and Red Flags
The community identified several red flags that suggest a strategy might not be ready for live trading:
- Unrealistic returns: If you’re showing 10%+ monthly returns consistently, something’s probably wrong with your simulation
- High win rate with tiny losses: This often indicates you’re not accounting for slippage or you’re using market orders that won’t fill at expected prices
- Strategy works on paper but not in backtest: Major warning sign of look-ahead bias or data issues
- Can’t explain why it works: If you don’t understand the market inefficiency you’re exploiting, you won’t know when it stops working
The Contradictions
While most commenters urged caution, there were dissenting voices. A few traders argued that overthinking and endless testing can be its own form of failure. “At some point, you just have to take the leap with small size,” one commenter wrote. “I’ve seen people paper trade for years and never go live because they’re always finding one more thing to test.”
Another trader countered the slippage concerns: “If you’re using limit orders and trading liquid instruments, slippage isn’t the boogeyman everyone makes it out to be. I went live after two weeks of paper trading and my results were within 5% of paper.”
However, these minority opinions were generally from traders using longer timeframes and more liquid markets—not high-frequency strategies or illiquid instruments.
Pricing & Alternatives
Since this discussion centered on Interactive Brokers’ paper trading, here’s how IBKR compares to alternatives for testing algorithmic strategies:
| Platform | Paper Trading | Live Trading Costs | API Quality | Best For |
|---|---|---|---|---|
| Interactive Brokers | Free, unlimited | $0 commissions for US stocks (IBKR Lite); ~$0.005/share for Pro | Excellent (TWS API, REST) | Serious algo traders, multi-asset |
| Alpaca | Free paper trading | $0 commissions (US stocks/crypto) | Good (REST, WebSocket) | Beginners, US markets only |
| TradeStation | Free simulation | $0 commissions stocks; futures vary | Good (EasyLanguage, API) | Futures traders, strategy testing |
| ThinkorSwim (Schwab) | Free paperMoney | $0 commissions stocks | Limited (lacking robust algo API) | Manual backtesting, retail traders |
| QuantConnect | Free cloud backtesting | Connect to IBKR/Alpaca for live | Excellent (C#, Python) | Strategy development, backtesting |
Note: Pricing information is based on the general market as of early 2026. Always verify current pricing directly with providers, as commission structures can change.
The Bottom Line: Who Should Care?
You should care about this discussion if you’re:
Testing your first algorithmic trading strategy: This thread is a masterclass in what experienced traders wish they’d known before going live. The advice to start small and scale gradually could save you thousands in tuition fees to the market.
Overestimating paper trading results: If you’re seeing fantastic returns in simulation, this reality check is essential reading. Understanding the gap between paper and live trading will help you set realistic expectations.
Building trading bots or automation: Whether you’re using Python with IBKR’s API, QuantConnect, or any other platform, the principles discussed here apply universally. Real market microstructure doesn’t care what programming language you use.
Evaluating when to go live: The community’s framework—paper trade to verify code works, backtest with realistic slippage assumptions, start live with tiny size, scale gradually—is a blueprint worth following.
You can probably skip this if you’re:
- A long-term investor not using automation (none of this applies to buy-and-hold strategies)
- Only interested in manual discretionary trading (though the psychological insights still apply)
- Already running live algo strategies successfully (though the comments section might still offer validation)
The real value of this discussion isn’t in the original poster’s one-month paper trading results—it’s in the collective wisdom of the 119 comments. The r/algotrading community has seen countless traders blow up their accounts by going live too quickly, and their hard-earned lessons are distilled into this thread.
If there’s one takeaway, it’s this: paper trading is where you test your code, not your strategy. Real validation only comes from live trading with small enough size that the inevitable losses won’t hurt. As one seasoned trader put it: “If losing your entire test account wouldn’t bother you, your position size is right. If it would sting, you’re already too big.”
Sources
- Am I ready to go full live? 1 month of constant profits with a self-made code on live paper trading IBKR - Reddit discussion with 119 comments in r/algotrading