7 Questions to Ask Before Buying Any Trading Bot

The market for automated trading bots has exploded over the past few years. A quick search returns hundreds of options -- desktop software, cloud platforms, Python scripts, mobile apps -- all claiming some version of "let our algorithm make money while you sleep." Some of these tools are legitimate. Many are not.

The problem is that most buyers do not know how to tell the difference. Marketing pages are full of equity curves that only go up, vague references to "proprietary AI," and testimonials from accounts that may or may not be real. By the time you realize a product does not work, your money is gone and your brokerage account may be lighter too.

These seven questions are a framework for evaluating any trading bot before you spend money on it. They are not specific to any product, platform, or price point. A $29 script from GitHub and a $5,000 institutional platform should both be able to answer them. If a vendor cannot or will not provide clear answers, that tells you everything you need to know.

1. Can I See How It Makes Decisions?

This is the most important question on the list. If you cannot understand how a bot decides to buy or sell, you cannot evaluate whether those decisions are sound. You are effectively handing your money to a stranger and hoping for the best.

Why it matters. Transparency is the foundation of trust in any trading system. Professional institutional traders would never deploy an algorithm they could not explain to a risk manager. Retail traders deserve the same standard. If you cannot trace a trade from data input to signal generation to order execution, you have no way to diagnose problems when they occur -- and they will occur.

What a good answer looks like. The vendor explains the signal logic in plain language. You can see which indicators or data sources drive each decision. There is a trade journal or log that records why every trade was taken, including the confidence score, the data inputs that triggered the signal, and the risk parameters that shaped the position size. Configurable parameters are documented and adjustable.

Red flags. "Our proprietary algorithm uses advanced AI that is too complex to explain." Any product that hides behind complexity is either doing something trivially simple that would not justify the price, or doing something they do not want you to scrutinize. Both are bad. Also watch for products that show you a dashboard of trades but never explain the reasoning behind them.

How slmaj handles this. Every signal source is visible and documented. The trade journal logs the specific data sources that contributed to each signal, the confidence score, and the risk calculations that determined position size. You can open the config file and see exactly which indicators are enabled, what thresholds trigger trades, and how risk parameters constrain every decision. Nothing is hidden behind a "proprietary" label.

2. Does It Start in Paper Trading Mode?

Paper trading uses real market data with simulated execution -- no actual money at risk. It is the only responsible way to test a new trading system. Any bot that expects you to connect a funded brokerage account on day one is prioritizing its conversion rate over your financial safety.

Why it matters. Even if a bot's strategy is sound, you need to verify that it works in your specific environment: your broker, your account size, your internet connection, your risk tolerance. Paper trading lets you do this without financial consequences. It also gives you time to learn the software, understand the signals, and build confidence in the system before real money is involved.

What a good answer looks like. Paper trading is the default mode. The bot ships configured for simulation. Switching to live trading requires a deliberate change -- editing a config file, toggling a setting, or completing a setup wizard that makes the transition explicit. The documentation recommends a minimum paper trading period (typically 2-4 weeks) before going live.

Red flags. "Connect your broker and start earning today." Any product that pushes you toward live trading immediately is optimizing for engagement, not for your outcomes. Also be cautious of products that offer paper mode but make it difficult to find or configure -- if live trading is the path of least resistance, many users will skip paper mode entirely.

How slmaj handles this. Every installation starts in paper mode by default. The setup wizard writes mode: paper and port: 7497 (IBKR's paper trading port) into your config file automatically. Switching to live trading requires changing a single config value and restarting the bot. The documentation recommends a minimum of 2-4 weeks of paper trading with at least 50 completed trades before considering live execution. See the paper trading guide for full details.

3. What Risk Controls Are Built In?

A trading bot without robust risk controls is a liability. Markets are unpredictable, and even the best strategy will experience drawdowns. The question is not whether losses will happen, but whether the bot has mechanisms to limit them before they become catastrophic.

Why it matters. Risk management is what separates a tool from a gamble. Without built-in safeguards, a single bad day -- a flash crash, a gap down on earnings, a black swan event -- can wipe out weeks or months of gains. Multiple independent risk layers are essential because any single control can fail or be insufficient for an extreme scenario.

What a good answer looks like. The bot implements multiple layers of risk management that operate independently. At minimum, you should see: position size limits (maximum dollars per trade), stop losses (automatic exits when a position moves against you), daily loss caps (the bot stops trading if cumulative losses hit a threshold), and portfolio-level exposure limits. Every risk parameter should be configurable, documented, and enforced automatically -- not dependent on you watching the screen.

Red flags. "Risk management is your responsibility" with no built-in tools to help you manage it. Also watch for bots that claim to have risk controls but do not let you configure them, or ones where the default settings are absurdly aggressive (e.g., no stop losses, no daily loss limits). If the vendor's marketing focuses entirely on returns and never mentions drawdowns or risk, that is a problem.

How slmaj handles this. Five independent risk layers are built in and active by default. Position size limits cap the maximum dollar amount per trade. Stop losses automatically exit positions that move against you beyond a configurable threshold (default: 2%). Daily loss caps halt all new trades if cumulative losses exceed your limit. Kelly Criterion-based position sizing adjusts exposure based on recent performance. A circuit breaker and manual kill switch let you shut everything down instantly. Every parameter is in the config file, documented in the risk controls reference, and adjustable without writing code.

4. Is It a One-Time Purchase or a Subscription?

The pricing model tells you a lot about the vendor's incentives and the long-term cost of ownership. Neither model is inherently better, but you should understand what you are committing to.

Why it matters. A $50/month subscription costs $600 per year and $3,000 over five years. For a small account, that subscription cost can eat into returns significantly. A $99/month "premium" tier costs $1,188 annually -- more than many traders earn from their bot in the first year. Subscription models also create a dependency: if you stop paying, you lose access, even if the software was working well.

One-time purchases have a different trade-off. You pay more upfront but own the software indefinitely. Updates may or may not be included. The vendor's incentive shifts from retaining subscribers to selling new copies, which can mean less ongoing development but also less pressure to lock you in.

What a good answer looks like. Transparent pricing with no hidden costs. If it is a subscription, the vendor clearly states what happens if you cancel (do you lose access immediately or at the end of the billing period?). If it is a one-time purchase, the vendor explains what is included -- lifetime updates, a fixed update period, or a separate maintenance fee. No "premium signal" upsells that gate essential functionality behind additional payments.

Red flags. A low entry price followed by aggressive upsells: "Unlock our Premium Signals for just $79/month." Mandatory add-ons that make the base product useless without additional purchases. Subscription tiers where the cheapest plan is deliberately crippled. Opaque "enterprise" pricing that requires a sales call.

How slmaj handles this. One-time purchase at two tiers: Standard at EUR 149 and Pro at EUR 299. No monthly fees, no subscription, no recurring charges. Both tiers include the full bot, all signal sources, all risk controls, and all documentation. The Pro tier adds priority support and early access to new features. You buy it once and run it for as long as you want.

5. Where Do the Signals Come From?

A trading signal is only as good as the data behind it. A bot that relies on a single indicator -- say, RSI crossing above 30 -- is fragile. Markets are complex, and single-indicator strategies tend to work in certain conditions and fail catastrophically in others.

Why it matters. Professional quantitative traders use multiple independent data sources precisely because no single source is reliable on its own. When technical indicators, fundamental data, sentiment analysis, and macroeconomic signals all agree, the probability of a good trade increases. When they disagree, the bot should reduce confidence or sit out entirely. Diversified data sources also provide resilience -- if one feed goes down or returns bad data, others can compensate.

What a good answer looks like. The vendor names specific data sources. You can see which ones are active, how they are weighted, and how they combine into a final signal. The documentation explains what each source provides and why it was included. Ideally, the bot uses a mix of data types: price and volume (technical), financial statements and filings (fundamental), news and social media (sentiment), and economic indicators (macro).

Red flags. "Uses advanced AI" with no explanation of what data the AI was trained on or what inputs it receives. A bot that claims to predict the market but cannot tell you where its predictions come from. Products that rely on a single data source or a single indicator dressed up with complex-sounding names. "Proprietary signals" with no transparency into how they are generated.

How slmaj handles this. Signals are generated from 25+ named data sources across four categories. Technical data comes from Yahoo Finance and Alpha Vantage (price, volume, moving averages, momentum indicators). Fundamental data includes SEC filings, earnings reports, and financial ratios. Sentiment data is sourced from Reddit, StockTwits, and news APIs. Macroeconomic data comes from FRED (Federal Reserve Economic Data). Every source is listed in the data sources documentation with details on what it provides, how it is weighted, and how to configure it.

6. What's the Track Record -- and How Is It Measured?

Performance claims are where most trading bot marketing crosses the line from optimistic to dishonest. The difference between a legitimate track record and a fabricated one comes down to methodology, transparency, and what is left out.

Why it matters. Backtested returns are trivially easy to manipulate. With enough parameter tuning, you can make any strategy look profitable on historical data -- this is called overfitting, and it tells you nothing about future performance. Even honest backtests systematically overestimate returns because they assume perfect fills, zero slippage, and no market impact. Forward-tested results (paper or live) are more meaningful but still imperfect.

What a good answer looks like. The vendor is honest about the limitations of backtesting. Performance data includes both wins and losses, not just a cherry-picked equity curve. Drawdowns are reported alongside returns. The methodology is explained: what period was tested, what instruments were included, what assumptions were made about fills and commissions. The vendor recommends paper trading to verify performance in your own environment rather than asking you to trust their numbers.

Red flags. Screenshots of a brokerage account showing massive returns with no context. "1,000% returns in 6 months" without mentioning the drawdowns, the risk taken, or whether the results are backtested or live. Cherry-picked timeframes that coincidentally align with a strong bull market. Testimonials from unverifiable accounts. Any vendor that guarantees returns -- in any market, under any conditions -- is either lying or does not understand how markets work.

How slmaj handles this. We do not publish hypothetical return figures because they would be misleading. Backtested performance depends heavily on the time period, instruments, and assumptions used -- presenting a single number as representative would be dishonest. Instead, the recommendation is straightforward: run the bot in paper mode for 2-4 weeks with your own account and evaluate the results yourself. The built-in dashboard tracks win rate, Sharpe ratio, maximum drawdown, profit factor, and average P&L per trade so you can make an informed decision based on data you generated, not data we selected. See our paper trading vs live trading guide for how to evaluate your results.

7. What Happens When Something Goes Wrong?

Every piece of software fails eventually. Internet connections drop. Brokers restart their servers. APIs return errors. The relevant question is not whether failures will happen, but what the bot does when they do -- and what support is available to help you recover.

Why it matters. A trading bot that crashes while you have open positions is not just an inconvenience -- it is a financial risk. If stop losses exist only in the bot's memory and not as orders at the broker, a crash could leave you exposed to unlimited losses. Similarly, if the bot has no error handling for a broker disconnection, it might fail to execute a critical exit order. The failure modes of a trading bot are at least as important as its normal operation.

What a good answer looks like. Stop losses are placed as actual orders at the broker level, not just tracked internally. This means they persist even if the bot crashes, your computer loses power, or your internet goes down. The bot has documented error handling for common failure scenarios: broker disconnection, data feed interruption, partial fills, and API rate limits. There is clear documentation for setup, configuration, and troubleshooting. Support is available through a defined channel with reasonable response times.

Red flags. No documentation beyond a README file. "Community Discord" as the only support channel, especially if the community is small or inactive. Stop losses that are tracked internally but never submitted as broker orders -- this means a bot crash leaves your positions unprotected. No mention of error handling or failure modes anywhere in the documentation. A vendor that has never thought about what happens when things go wrong probably has not built a product that handles those situations gracefully.

How slmaj handles this. Stop losses are submitted as bracket orders directly to Interactive Brokers. They exist as real orders on IBKR's servers, which means they execute even if slmaj crashes, your machine loses power, or your internet connection drops. The bot includes automatic reconnection logic for broker disconnections and graceful degradation when individual data feeds fail. Documentation covers setup, configuration, risk controls, data sources, and common troubleshooting scenarios. Support is available via email for Standard tier and priority email for Pro tier. The IBKR setup guide walks through every step of the connection process.

Putting It All Together

Here is a summary of all seven questions with the red flags and green flags for each. Use this as a quick-reference checklist when evaluating any trading bot.

Question	Red Flag	Green Flag
Can I see how it makes decisions?	"Proprietary AI, too complex to explain"	Visible signal logic, trade journal with reasoning
Does it start in paper trading mode?	"Connect your broker and start earning today"	Paper mode is the default, must opt into live
What risk controls are built in?	"Risk management is your responsibility"	Multiple independent layers, all configurable
One-time purchase or subscription?	Aggressive upsells, premium signal add-ons	Transparent pricing, no hidden costs
Where do the signals come from?	"Uses advanced AI" with no specifics	Named data sources, documented signal logic
What is the track record?	"1,000% returns" with no methodology	Honest about limitations, recommends paper testing
What happens when something goes wrong?	No docs, Discord-only support	Broker-side stop losses, clear documentation, email support

If a trading bot cannot answer all seven of these questions clearly and honestly, move on. There are enough options in the market that you do not need to settle for opacity, missing safety features, or evasive answers about performance.

The best indicator of a legitimate product is not its marketing -- it is the vendor's willingness to tell you exactly how the product works, where its limitations are, and how to verify its performance for yourself before risking real money.

Frequently Asked Questions