In-house market making means your own team runs the bots, funds the inventory and manages the risk of quoting your token on exchanges. Hiring a market maker means a specialist firm does that work under a contract, using its own systems and, depending on the model, its own capital or tokens you lend it. For most token projects, hiring is the better choice at launch: the fixed costs of a competent desk are the same whether it supports one asset or fifty, and the failure modes of a first-time in-house desk are expensive and public. In-house makes sense in a narrower set of cases, mostly for teams with existing trading talent, a single venue to cover, or a specific need for control. This comparison walks through the trade-offs and ends with a decision framework.
What Each Option Actually Involves
Running market making in-house
An in-house setup is more than a bot. To quote continuously and safely you need:
- Trading infrastructure: exchange connectivity, order management, real-time inventory tracking, kill switches and monitoring.
- Strategy and parameters: spread targets, depth per level, inventory limits, how quotes react to volatility and to moves on other venues.
- Capital: both your token and the quote asset (usually stablecoins) on every venue you cover, sized to absorb flow without running out.
- People: someone accountable for the desk at all hours, because markets do not close and exchange incidents rarely happen during office time.
- Controls: who can move funds, how API keys are scoped, how losses are reported and when quoting stops.
Hiring a market maker
A hired market maker brings its own infrastructure, strategy team and exchange relationships. The project usually provides one of two things:
- A token loan with call options (the loan/option model), where the firm borrows tokens, quotes with them and may buy them at agreed strike prices later.
- A retainer, where the project pays a fee and often provides both tokens and quote capital, and the firm operates them under agreed KPIs.
The models and their trade-offs are covered in detail in crypto market making fee models. What matters here is that in both cases you are buying operational capability, not just a bot.
Side-by-Side Comparison
| Factor | In-house | Hired market maker |
|---|---|---|
| Upfront cost | Engineering build or software licences, plus hiring | Contract setup; retainer or token loan terms |
| Ongoing cost | Salaries, infrastructure, exchange fees, trading losses | Retainer, option dilution, or both |
| Capital required | All token and quote inventory, on every venue | Varies by model; loan model can reduce quote capital needs |
| Time to go live | Typically months for a robust setup | Typically weeks once terms are agreed |
| Exchange access | Standard API tiers unless you negotiate otherwise | Firms often have existing relationships and fee tiers |
| Cross-venue coverage | Hard to do well across many venues | Usually part of the service |
| Control and transparency | Full | Depends on reporting terms in the contract |
| Conflict of interest | None with an external party; internal conflicts remain | Possible if option terms reward the firm for a falling price |
| Key-person risk | High; a small team is a single point of failure | Spread across the firm's desk |
| Regulatory exposure | The project itself is trading its own token | The firm trades; the project still owns the arrangement |
None of these rows is decisive on its own. The weighting depends on your situation, which is where the framework below helps.
Where In-House Looks Better Than It Is
"We will save the fee"
The fee is visible; the cost of running a desk is not. Engineering time, monitoring, inventory that sits idle, and the trading losses of an inexperienced desk are real costs that rarely make it into the comparison spreadsheet. A single stale order left on the book during a fast move can cost more than months of a retainer.
"We know our token better than anyone"
Knowing the token is not the same as knowing order flow. A market maker's edge comes from managing inventory risk, reacting to cross-venue price moves and detecting toxic flow from arbitrage bots. Those skills transfer across tokens, which is exactly why specialists exist.
"We will have full control"
You will, and that includes full responsibility. If your desk accidentally creates trades between your own accounts, or quotes in a way that looks like price support, the project's name is on it. Make sure any in-house setup has controls that prevent self-matching.
Where Hiring Has Real Downsides
Outsourcing is not automatically safe. The common problems:
- Misaligned incentives. Under loan/option deals, a firm can profit if the token falls and it returns borrowed tokens bought back cheaply. Strike structure and reporting terms matter.
- Opaque reporting. If you only see a monthly summary, you cannot tell whether KPIs were met. Insist on venue-level data.
- Weak KPIs. Volume targets alone are easy to hit and say little about liquidity quality. Spread, depth within a band and uptime are better measures; see how to evaluate market maker performance.
- Lock-in. Long notice periods and unclear token return terms make it hard to leave a provider that underperforms.
All of these are contract problems, which means they are negotiable before signing. A market maker agreement checklist is the right place to start.
Hybrid Models
The choice is not always binary. Common hybrids include:
- Hired CEX coverage, in-house DEX management. The project manages its own liquidity pool positions on-chain (often protocol-owned liquidity) while a firm covers centralized exchange order books. This works well when your DEX setup is simple; if you are still choosing a venue, our list of the best DEXs to launch a token covers the trade-offs.
- Software licence plus advisory. The team runs licensed market making software with external guidance on parameters. This gives control but keeps most of the operational risk in-house.
- Start outsourced, build later. Use a market maker through launch and the first unlock cycles, then reassess once the token has stable volume and the team has trading talent.
- Two providers. Some projects split venues between two firms to compare performance and avoid single-provider dependence. This needs clear venue allocation to avoid the firms trading against each other.
Decision Framework: Which Should You Pick?
Work through these questions in order. If you answer "no" to any of the first three, hire.
- Do you already employ people who have run a trading desk? Not traders in general, but people who have managed inventory risk and exchange connectivity in production.
- Can you fund full inventory on every venue you need to cover, and absorb trading losses while you learn?
- Can you staff monitoring around the clock, including weekends and exchange incidents?
- How many venues do you need? One DEX pool is manageable in-house. Several centralized exchanges with cross-venue arbitrage is a different problem.
- How close is your launch? If listing is weeks away, building a desk is not realistic. Launch with a provider.
- What do your exchanges expect? Some exchanges ask for a named market maker as part of the listing process.
- How sensitive are you to the regulatory view of a project trading its own token? Get legal advice either way; the answer influences structure, not just cost.
Quick verdicts
| Your situation | Likely best fit |
|---|---|
| Pre-launch, first CEX listings, no trading team | Hire a market maker |
| Single DEX pool, small treasury, simple token | In-house pool management can work |
| Several CEXs plus DEX, launch in under three months | Hire, possibly with in-house DEX management |
| Mature token, stable volume, experienced in-house traders | In-house or hybrid becomes viable |
| Unhappy with a current provider | Renegotiate KPIs and reporting, or switch providers before going in-house |
Checklist Before You Decide
- Total cost of in-house estimated, including salaries, infrastructure and expected trading losses
- Venue list finalized, with depth and spread targets per venue
- Inventory available for each venue, in both token and quote asset
- Monitoring and incident ownership assigned around the clock
- Legal view obtained on the project trading its own token
- If hiring: at least two proposals compared on KPIs, reporting and token return terms
- Exit plan defined for either path
The Bottom Line
In-house market making is a business in its own right, and most token teams are building a different business. Hiring a specialist usually gets you better liquidity sooner, at a cost that is easier to predict, as long as the contract aligns incentives and gives you the data to check the work. In-house becomes realistic later, when volume is stable and you have people who have done it before. Fibonacci Capital works with token teams on both the hired and hybrid models, and the first conversation is usually about which venues and KPIs actually matter for your token.
If you want to compare the options for your own launch, get in touch with Fibonacci Capital.