Being Front-Run On DEXes
Introduction
I’ve been thinking about executing large portfolios on decentralized exchanges like Hyperliquid.
In theory, when:
You have alpha.
Your positions and orders are open and public, as in the case of DEXes like Hyperliquid.
Then:
You should expect a class of traders that will attempt to front-run you to capture your alpha before you do.
They will do this by producing orders that attempt to trade into your desired positions before you can.
The net result is that you should experience greater costs (slippage) as a result of being front-run.
Imagine you wanted to buy $1,000,000 of BTC at $100,000. There happens to be someone offering exactly $1,000,000 of BTC at $100,000. A front-runner sees your intent, steps in ahead of you, takes that offer, and then sells $1,000,000 of BTC to you at $100,100. That extra $100 is slippage you could have avoided had your intentions been hidden.
The Extreme Ends of Front-Running
In theory, if you extrapolate this to its “natural conclusion,” it should discourage almost any kind of “serious trading” on DEXes at all.
However, we know that not to be true. Plenty of very serious players trade professionally on Hyperliquid with alpha. So it seems clear that it’s not so clear-cut that “players with alpha should not trade on DEXes.”
Can we reason about intuitive bounds for the limits of being front-run? I think so, if we work from first principles and look at the evidence that is available.
It is quite clear that if you are very small and are trading in a highly opaque venue like Binance, the probability of being front-run is effectively zero. Being small means your footprint (trading volume) relative to the market is so small that you are practically invisible, AND, even if you had absolute predictability, no one would be able to attribute your trading activities (orders and trades) to you.
On the other hand, the canonical example of a very large, very transparent wallet on Hyperliquid is the HLP vault itself — the public market maker vault that provides liquidity to other traders on Hyperliquid. I am fairly certain that there are dedicated strategies front-running HLP, and that constant pressure has effectively compressed market-making alpha to ~0.
HLP represents a fairly extreme example. Firstly, it is simultaneously “exceedingly large” and “exceedingly transparent.” It is “exceedingly large” because its footprint in the long tail of illiquid assets is enormous (e.g. its trading size is a large percentage of the average daily traded volume).
Further, it is “exceedingly transparent” because it is primarily a market maker, trying to provide liquidity with the explicit goal of unwinding existing inventory at a premium. This means that given a “large” position on HLP, you know it is eventually going to need to unwind the position. To make matters worse, you can see every position AND every order that HLP makes. This allows you to position your portfolio to buying cheaper and selling richer to HLP whenever you see that it needs to buy to unload its shorts, and vice versa.
All of these attributes make HLP a particularly attractive target for front-running, no different from ETFs being front-run due to their rigid adherence to index rebalances. In the hedge fund world, obviously, you would be flagged by compliance in every possible dimension if you actually used the word “front-running”; instead, the lingo is that index rebal teams are extremely good at providing a service of “anticipating and earning a premium from providing liquidity” to these ETFs.
How Does Front-Running Happen?
In the canonical sense of front-running, a market participant knows in advance what another market participant will do, and then takes a series of actions that profit from that knowledge.
One (very illegal) example: if I were an insurance agent, and I knew my very wealthy client was going to buy $1 billion worth of an illiquid stock through today’s trading session, then, at the open of the session, I send in a market buy order of $1 million, with a market sell order of the same number of shares at the close.
By knowing my client’s intentions and actions, I was able to profit by getting filled ahead of him, having his buying activity push prices up, and pocketing the difference. This is highly illegal because I would have: 1) acted on insider information, 2) violated my fiduciary duty, and 3) benefited at the expense of my client.
However, this is a good example because it shows clearly that I am able to profit only because I know another market participant’s intentions and actions and can estimate the result of those actions, and therefore position myself to take advantage of them.
Every day, front-running happens in smaller ways with less illegality. Trading algorithms approximate intent without being told, using public information available to everyone (orders, trades, positions). They then estimate the market result of the actions that follow from such approximate intent, and decide whether or not to act based on the expected value of “front-running.”
From here we can reason that the transparency and leakage of your “intention” is really the primary determinant of whether or not you are going to get trivially front-run.
The Gradient of Front-Running
Okay, so we know that if you are small and trading on an opaque exchange, you should have no concerns about being front-run, because no one can determine your intentions. Similarly, if you are large, are trading on a transparent exchange, and have very transparent intentions (e.g. HLP), you are going to be hopelessly front-run.
These bounds are not that useful for the vast majority of traders. We are far more interested in the “in-between” scenarios. As mentioned above, what ultimately determines your propensity to be front-run is how transparent your intentions are.
Even if you are large and are trading on an opaque exchange, it is not easy to front-run you. Your orders will show as “large footprints” as part of the average daily traded volume, but it is not trivial to attribute all orders to a “single party” unless you are trading extremely transparently — e.g. you have no randomization, you trade in child orders of a fixed number of lots or notional, or you send child orders in very predetermined patterns (every 30 seconds).
If you are able to bury your intention — e.g. you trade random sizes, with randomly sent child orders, at random intervals, and avoid placing a large bid relative to the average daily volume or relative to the available size on the order book — it is much harder to attribute your orders to a single person. The market may be able to tell that there is large buying interest in aggregate, but may not be able to attribute that buying interest to an informed party with alpha, and therefore will not price liquidity as such.
Thankfully, we can actually extrapolate this to transparent exchanges. The reason plenty of vaults exist on Hyperliquid and Lighter despite their relative transparency is that it is not actually trivial to front-run these vaults.
Without burying the lede, unless you are of relatively large size (e.g. an institutional vault with hundreds of millions of dollars), you have almost no need to worry about being front-run, because there are...
Limits to Front-Running
Trying to capture alpha from front-running without doing it illegally is itself an exercise in alpha generation. You are MODELING intention from public information (orders, trades, positions) and are subject to model risks.
Orders, trades, and positions may be visible, but intent isn’t. A resting limit could be alpha, inventory management, or a hedge. Models that assume alpha on every order will die from a thousand cuts of false positives.
Further, let’s presume that you can actually distill intent somewhat correctly. Even then, the alpha itself is not “omnipotent.” All alphas carry some statistical noise, and you expose your portfolio to the statistical noise of the alpha plus the model risk of misinterpreting certain actions as alpha.
You might argue that if you blindly copy your target’s actions 1:1, then you definitely capture all the alpha — but the problem is that you actually expose yourself to being exploited. If you send a buy order every time your target does, then if your target wants to sell, it can send a buy limit order, watch you send the same, cancel immediately, and sell into you. So you can see, front-running thoughtlessly opens up vulnerabilities of its own.
One should also remember and recognize that alpha has a time horizon. There are alphas that are so short-lived that your attackers themselves may not be able to exploit them (e.g. HFT taker alphas), or alphas that are so long-duration that your attackers may be discouraged from having to carry risk with you (e.g. multi-day or weekly rebalances).
Lastly, even if you have an extremely sophisticated front-runner on your tail, the truth is that it will show up as only a few bps of impact. If you really do have persistent alpha, plenty of strategies clear a few extra bps of impact.
How Not to Be an Easy Target
Even knowing that it’s not going to be trivial, your job as a smart, alpha-generating market participant IS to hide your intent to make it AS DIFFICULT AS POSSIBLE for an attacker to front-run you.
There are many things you can do, with varying complexity and effectiveness. The very first thing you should do is to be obsessed about collecting telemetry and logs so that you can quantify the exact “magnitude” to which you are being front-run, if at all. You do this by looking at markouts, slippage, and impact across a large sample of orders and trades.
Then, once you have the data, you can take a series of defensive actions. A common thread tying them together is that you should make it “non-obvious” whether you are trying to buy or sell, how much you actually want to buy or sell, at what urgency you are trying to buy or sell, and whether you are trying to trade into an alpha-generating position or a hedging position.
Some simple ways in which you can obfuscate your intent are to quote both sides at once, in random sizes, at intervals that are not always deterministic.
One (high-level, complex) way in which you can effectively obfuscate your positions is to split your portfolio up into multiple wallets, each with long/short neutrality and individually “margin-efficient.” Within each wallet you have a mix of alpha-generating positions and hedging positions. Some wallets are 80% alpha-generating and 20% hedging; others are 80% hedging and 20% alpha-generating. You rotate the “type” of each wallet over time, and you introduce new wallets and decommission old ones randomly over time.
This means that if they are only following one wallet, they may end up following the hedging wallet and into loss-generating positions meant for hedging purposes. If they are following all wallets, you can then employ sequences of contradictory actions that obscure your intent. I’ll leave it up to the reader’s imagination as to what this might look like!
Lastly, there are some (external) solutions for this that already exist. I have not personally used them, but at their core, they solve for privacy with one of two approaches:
Pooling orders together, executing them internally, and then exhausting the residual on the DEXes, finally attributing the positions back to you — no different from a Central Liquidity Book (CLB) in a hedge fund netting orders from pods and attributing positions back.
Splitting your orders, along with those of other users of the solution, into multiple wallets, executing them on DEXes, and then attributing the positions back to you.
Conclusion
If you are a retail trader doing small sizes, you probably have nothing to worry about even if you are trading on transparent DEXes. There are limits to front-running that make it non-trivial for others to profit from your activities at your expense.
That being said, as you gradually increase in size and the quality of your alpha improves, it creates a natural incentive for front-runners to pick you off. At that point, you should dedicate more resources to obscuring your intent and making their lives as hard as possible.
This is not a “solved problem” by any means, and will be an ongoing “cat and mouse” game for any institution or trader moving size on open, decentralized, transparent liquidity venues.
Happy to add any good thoughts to the discussion in follow-up articles!