FX Market Making with Internal Liquidity
Abstract: As the FX markets continue to evolve, many institutions have started offering passive access to their internal liquidity pools. Market makers act as principal and have the opportunity to fill those orders as part of their risk management, or they may choose to adjust pricing to their external OTC franchise to facilitate the matching flow. It is, a priori, unclear how the strategies managing internal liquidity should depend on market condions, the market maker's risk appetite, and the placement algorithms deployed by participating clients. The market maker's actions in the presence of passive orders are relevant not only for their own objectives, but also for those liquidity providers who have certain expectations of the execution speed. In this work, we investigate the optimal multi-objective strategy of a market maker with an option to take liquidity on an internal exchange, and draw important qualitative insights for real-world trading.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Explain it Like I'm 14
Plain‑English Summary of “FX Market Making with Internal Liquidity”
1. What is this paper about?
This paper looks at how foreign exchange (FX) market makers—people or systems that constantly quote buy and sell prices for currencies—should use a special kind of “inside” liquidity. This inside liquidity is a private pool of orders from their own clients that the market maker can trade against. The goal is to figure out the best way to set prices for outside customers while deciding when to use the inside pool to manage risk and make money.
2. What questions are the researchers trying to answer?
The paper asks, in simple terms:
- How should a market maker change their prices for outside customers when there are passive (waiting) orders available inside their private exchange?
- When is the right time to take those inside orders?
- How do different types of client orders (like steady trickles or big chunks) change the best strategy?
- Can a smart strategy beat a common, simple approach that many people might assume is fine?
3. How did they study it? (Methods explained simply)
Think of the market maker as a shop owner:
- They set price tags for buying from customers (bid) and selling to customers (ask).
- They keep an inventory of the product (a currency position), which can be risky if it gets too big.
- They also have a private, in‑store stash of supply (inside or “internal” liquidity) that they can buy from when needed.
The researchers built a mathematical model of this situation:
- The market price wiggles randomly over time (like a coin drifting up and down).
- Outside customer trades arrive more often when the shop’s price tags are more attractive (smaller spread).
- Inside client orders may appear, disappear, or get refilled depending on the client’s strategy. They model three common styles:
- Iceberg: only a small part of a big order is visible; when you take it, more usually pops up immediately.
- TWAP (Time‑Weighted Average Price): orders arrive steadily over time, but not constantly—there are gaps.
- Full Amount: one big order placed all at once and that’s it.
- The market maker chooses two things:
- How to set buy/sell prices for different order sizes.
- When to use the inside order (i.e., when to trade with the internal exchange).
They then define a score the market maker wants to maximize:
- Profit and loss (P&L): make more money overall.
- Don’t hold too large a position (inventory), because that’s risky.
- Don’t leave inside client orders waiting too long (this is penalized to reflect service quality).
Solving this carefully leads to a “big equation” that balances all those goals at every moment. Mathematicians call this kind of problem an HJBQVI (a mouthful meaning: a decision‑making equation with both continuous choices—pricing—and occasional actions—taking the order). The authors solve it on a computer using real trading data (GBP/USD) to calibrate how often trades happen and how sensitive they are to price.
4. What did they find, and why does it matter?
Here are the main practical takeaways:
- There is an execution threshold: a level of inventory where the market maker will immediately take the inside order. If they are not past that threshold, they won’t take it yet; instead, they will skew outside prices to attract trades that move their inventory toward that threshold.
- Pricing skew depends on risk and liquidity: how much the market maker tilts prices (to encourage helpful outside flow) depends on their risk appetite, how much inside liquidity is available, and the client’s posting style and price level.
- Type of client order matters:
- Iceberg orders (often replenished) encourage more price adjustments because the market maker can rely on that inside supply being there.
- TWAP orders (arriving intermittently) lead to different timing—fills are more sensitive to the client’s posted price.
- Full amount orders (a big one‑off) can push the execution threshold higher, encouraging immediate use even from a neutral position.
- The optimal strategy beats a naïve one: a simple approach many might assume—just adding the internal order to the public “price ladder” with a small margin and taking it whenever inventory is negative—fills faster but makes less money. The smart strategy fills more thoughtfully and earns more P&L.
- Fees vs. margins: charging a small fee per unit (paid by clients who use the internal pool) tends to help both profits and execution volume for the optimal strategy. Adding a margin (mark‑up) helps profits but often reduces how much gets filled, making it less effective overall.
Why this matters:
- For market makers: using the internal pool thoughtfully increases profits and controls risk.
- For clients: how they place orders (iceberg, TWAP, full amount) and at what price affects how quickly they get filled. TWAP fill times are more sensitive to how “aggressive” the client’s price is.
- For the market: passive internal orders can cause “passive impact” if the market maker tilts outside prices to manage risk, which outside traders may detect and react to.
5. What’s the bigger impact?
This research shows a clear, practical way for FX dealers to manage internal liquidity while serving outside customers. It makes internalization more transparent: rather than simply dumping inside orders into public pricing, dealers should use an execution threshold and controlled price skew to balance profit, risk, and client service.
It also explains a real market effect: passive orders placed inside can push the market indirectly because the dealer changes outside prices to manage their inventory and service those orders. Understanding this helps clients set expectations (like how long fills might take) and helps dealers design fair, efficient systems. In short, smarter internalization benefits both sides when done with the right strategy and incentives.
Collections
Sign up for free to add this paper to one or more collections.
