Why quotes for the same bot range from $500 to $50,000
Ask five developers to quote "a trading bot" and you'll get numbers from $500 to $50,000. All five read the same message. None of them is lying.
The phrase covers a weekend script that forwards TradingView alerts to an exchange, and it covers a multi-strategy execution system running a prop desk. Those are different products the way a shed and a warehouse are different buildings. Until the scope is pinned down, every quote is a guess about which one you meant.
The second reason the numbers spread is the one buyers actually control: how well the strategy is written down. A strategy that exists as objective rules can be quoted accurately. "Enter long when the 1h close breaks the range high, risk 0.5% per trade, exit at 2R or on the opposite signal" is a spec. "I buy strength when the market feels ready" is a research project. Discretionary rules have to be extracted and turned into conditions a machine can evaluate, and every "it depends" in that conversation is billable hours. In our experience, vague strategy rules multiply cost more than any technology choice. More than the platform, more than the market, more than the language it's written in.
One caveat before any numbers. Automation does not create an edge. It only executes one you already have, faster and more consistently than you can. If the strategy loses money, the bot loses it on schedule. Everything below assumes you have something worth automating, and the last section covers what to do if you're not sure.
What actually drives the price
Six things move a quote, in roughly this order.
1. Strategy ambiguity. Covered above, and worth repeating because it dominates. Turning discretionary judgment into objective conditions is the most expensive line item on most projects, and it's the one you can shrink before contacting anyone. Write the rules down. If you can't, that's information too.
2. Platform and connectivity. A TradingView webhook bridge is the cheapest path, because TradingView does the signal work and the bot only executes. NinjaTrader automation means working inside its strategy framework and handling sim-versus-live quirks. MetaTrader automation means MQL5 EAs and broker-specific behavior. A raw exchange API integration costs the most, because everything from the data feed to order state tracking gets built from scratch.
3. The risk layer. Daily loss limits, a kill switch, position reconciliation after restarts. This is the part cheap quotes silently skip, because the bot demos fine without it. It's also the part that decides whether a bug costs you $80 or your account.
4. Testing and parity. Verifying the live system behaves like the backtest: same signals, same sizes, fills within modeled slippage. Skipping this step doesn't remove the work. It moves the testing into your live account.
5. Monitoring and alerting. A bot that needs constant watching defeats the point of automating. Real-time PnL, fill quality tracking, and an alert when something deviates cost money to build, and they pay for themselves the first time something breaks at 3am.
6. Ongoing maintenance. Exchanges change APIs, brokers migrate servers, libraries deprecate. More on this below, because it's the cost almost every buyer forgets to budget.
What the market actually charges
These are ranges we see across the market, from our own quotes and from projects that arrive at our door after going wrong elsewhere. Every project differs, and a serious developer will give you a specific number only after seeing your strategy rules.
| Tier | Typical cost | What you actually get | |---|---|---| | DIY with AI help | ~$0 cash | A working prototype, hundreds of your hours, edge cases discovered live | | Marketplace freelancer | $500-$3,000 | The happy path. Reconnection logic, risk layer, and testing usually missing | | Alert-to-execution bridge, built professionally | $1,500-$5,000 | Signal to order with a real risk layer, state persistence, basic monitoring | | Full custom strategy automation | $5,000-$15,000 | Strategy coded from your rules, backtesting, walk-forward validation, parity checks, monitoring, deployment | | Desk-grade infrastructure | $15,000-$50,000+ | Multi-account, multi-strategy execution with audit trail, for prop firms and small funds |
The DIY tier is real, and we recommend it for learning. ChatGPT or Claude will write you a functioning prototype in an afternoon, and building it teaches you where the hard parts are. The cash cost is near zero. The real price is hundreds of hours plus the tuition you pay in live losses when the first unhandled edge case hits: a duplicate alert, a partial fill, a disconnect during an open position. We covered where AI genuinely helps in how to actually use AI for trading, and code generation for prototypes is high on that list. Production is a different product.
The marketplace tier is where most first-time buyers land and where most horror stories start. $500 to $3,000 buys a developer who makes the bot place orders when signals arrive. That's maybe 30% of a production system. What's usually missing is invisible in a demo: what happens on disconnect, what happens on restart, what stops the bot when it misbehaves. You find out live.
The professional tiers price in the invisible parts. Around $1,500 to $5,000 gets a simple alert-to-execution bridge done properly, with state that survives restarts and a risk layer that halts trading when limits are hit. Full custom automation of a strategy, with backtesting, walk-forward validation, sim-to-live parity verification, and monitoring, runs $5,000 to $15,000. Multi-account infrastructure for prop firms and small funds, with the audit trail and controls a desk needs, starts around $15,000 and goes past $50,000 depending on scope. If that last tier sounds like you, we have a dedicated service for prop firms.
On hourly rates: developers who know both trading and production engineering charge roughly $50 to $150 per hour. Cheaper exists, but a developer who has never held a position doesn't know what a partial fill does to a stop order, and you'll pay for that education either way. D&T Systems works at $50+/h or fixed-scope milestones. We prefer fixed scope, because it forces the ambiguity conversation before the invoice instead of after.
The costs that show up after launch
The build quote is not the total cost. Budget for four things after go-live.
A VPS or small cloud server runs $20 to $100 per month depending on latency needs. Market data can be free through exchange feeds or a real line item for futures data subscriptions and historical tick data. Exchange and broker APIs change without your permission, and each change is a small maintenance event: Bybit revises an endpoint, your broker migrates servers, a library you depend on deprecates.
For that reason most professional builds come with a maintenance arrangement, commonly 10-20% of the build cost per year, or ad hoc hourly when something breaks. On a $10,000 build that's roughly $85 to $165 per month. It's the difference between "the API changed and the bot was patched the same week" and "the bot silently stopped trading in March and nobody noticed until May."
Why the cheap bot is the expensive one
The pattern we see most often: a trader pays $800 on a freelance marketplace, the bot runs fine for six weeks, then one night the exchange WebSocket drops during an open position. The bot reconnects, decides it's flat, and opens a second position on the next signal. No kill switch fires, because there isn't one. The damage from that single night exceeds what the professional build would have cost.
That story has variants: duplicate alerts that double size, restarts that orphan positions, slippage that quietly turns a marginal edge negative. The shape is constant. The money saved on the build gets repaid to the market with interest. We wrote up the full failure catalog in why your strategy works but your bot doesn't, and every failure in that post is a line item the cheap quote left out.
None of this means everyone needs the top tier. A small account testing a simple strategy is well served by a properly built bridge. What matters is knowing which parts your quote includes, and the next section is the checklist for finding out.
Five questions to ask before you pay anyone
Use these on any developer, including us. The answers separate someone who has run bots live from someone who has only made them demo well.
- How does the bot handle disconnects and restarts? The right answer involves persisted state and position reconciliation against the exchange on startup. "It reconnects automatically" covers only the easy half.
- Where does the risk layer live, and what does it check? You want pre-trade checks on size and daily loss, plus a kill switch that halts all order submission. If risk lives only inside the strategy logic, a strategy bug disables your protection at the same moment it starts misfiring.
- How will we verify live matches the backtest? Look for a parity plan: a paper trading period, comparison of live fills against modeled slippage, alerts on divergence. "The backtest is accurate" is a red flag.
- What happens when the exchange API changes? A maintenance arrangement, a support window, or at minimum an honest "that's billed hourly." Silence means you own the problem.
- Who owns the code? You should get the source and the right to modify it. A bot you can't read or move is a subscription with extra steps.
A developer who answers all five without flinching is worth the professional rate. A developer who gets defensive at question one just saved you thousands of dollars.
When you shouldn't pay anyone yet
Some of our diagnostic calls end with advice against hiring us: don't automate this yet.
If the edge is unproven, automation just loses money faster. A strategy that has never been tested out of sample, or that was tuned until the backtest looked good, will do live what most tuned strategies do live: give the backtest profits back. Most retail strategies fail honest testing. That's the base rate, and it has nothing to do with intelligence. Paying $8,000 to automate a strategy in that category buys a machine for donating to the market with excellent uptime.
Before hiring anyone, including us, run the strategy through walk-forward validation or at minimum an out-of-sample split. Our free Strategy Overfitting Score gives a quick read on whether a backtest smells like curve fitting. If the strategy survives, automate it, because at that point manual execution is the weakest link. If it doesn't survive, you just saved the entire budget above.
The standard disclaimer, meant sincerely rather than legally: trading is hard, losses happen, backtests degrade live, and nothing here is investment advice. This post is the pricing conversation we have on calls, written down, because buyers make better decisions with the real numbers in front of them.
Frequently asked questions
How much does a simple trading bot cost?
A simple alert-to-execution bridge, built professionally with a real risk layer and state that survives restarts, typically costs $1,500 to $5,000. Marketplace freelancers quote $500 to $3,000 for the same ask, but those builds usually cover only the happy path. Reconnection logic, risk limits, and testing are missing, and the gap shows up in live trading. The strategy itself is the biggest variable: clear written rules keep a project at the low end, while discretionary rules that need to be extracted and formalized push it up.
Can I get ChatGPT or another AI to build my trading bot for free?
Yes, for a prototype. Current AI models will write a working bot that connects to an exchange and places orders, and building one is a genuinely good way to learn. Production is a different product: persistent state across restarts, reconnection handling, duplicate signal protection, a kill switch, and verification that live behavior matches the backtest. AI will not add those unless you know to ask for each one, and the edge cases it misses get discovered with real money. The cash cost is near zero. The real cost is hundreds of hours and the losses from edge cases found live.
What does a trading bot cost to run and maintain each month?
Plan on $20 to $100 per month for a VPS or small cloud server, plus market data if your strategy needs paid feeds. Maintenance arrangements commonly run 10-20% of the build cost per year, so a $10,000 build carries roughly $85 to $165 per month. That covers the recurring reality of automated trading: exchange APIs change, brokers migrate servers, and libraries deprecate. Without a maintenance plan, those events either stop the bot silently or get fixed at ad hoc hourly rates.
How long does it take to build a trading bot?
A simple alert-to-execution bridge with proper risk controls takes 2 to 4 weeks. Full custom strategy automation with backtesting, walk-forward validation, and monitoring takes 4 to 12 weeks depending on strategy complexity and platform. Desk-grade multi-account systems run longer. Anything quoted in days is quoting the happy path only, and the weeks that were skipped get spent debugging in a live account instead.
Want a real number for your strategy?
Book a free 30-minute diagnostic call. You describe the strategy, we tell you honestly what it takes to automate it, and you leave with a written scope and a specific price. The scope is yours to keep, whether you hire us or shop it around.