Smart Order Router

🎓 Crash Course
🚀 Building and running
🧠 Strategies
🛠️ Troubleshooting
⚖️ License

Overview

SORs are off-chain bots that execute a routing algorithm that scans the blockchain for open limit orders, matches them based on their trigger conditions, and submits new transactions back to the ledger to perform the swap state transitions. Each Smart Swap encodes trigger conditions that the SOR must fulfill to execute the swap. The SOR continuously scans and analyzes the current state of the limit orders and relies on the configured matching strategy to best execute a customer’s order based on price.

Specifically, the bot periodically builds a multi-asset order book consisting of one order book for each token pair listed in its configuration. Each order book contains only sell and buy orders for the same pair of tokens. The bot runs the selected strategy over the multi-asset order book to obtain a list of matches. The matches are then translated into transactions that will be signed and submitted by the bot.

Crash Course GeniusYield DEX Orders <> SOR

Let's start with a concrete and short overview of the GY DEX Orders, so the context of the SOR for using, modifying, and improving with new custom strategies is properly established. A complete description can be found in the GY whitepaper.

Given a pair of tokens, an order will contain the number of tokens it offers, the price of one unit of those offered, and the minimal amount we are forced to buy from the order. Besides that, the order will have some life timeline and, of course, a notion of ownership related to the one that created it. For example, we could create an order offering of 10 tokenA, with a unit price of 2 tokenB, that is, we expect to receive 2 tokenB per 1 tokenA. Also, we want the minimal amount to be bought be 5 tokenA. Clearly, the owners of this order will be us and it's important to mention that all this information is mandatory, but we can avoid setting the life timeline, meaning the order will always be available. Once we create an order, the offered tokens will be locked on the order.

Given an order, two interesting "actions" can be performed over it. The owner can cancel it and get back the locked tokens. Or anyone can fill it, filling an order is just paying the correct amount of tokens the owner of the order expects to receive related to the amount of tokens we want to buy from that order. Following the previous example, anyone could fill that order by buying from it 6 tokenA and paying the owner 12 tokenB. But, it isn't possible to buy, for instance, 3 tokenA from the order because the minimal amount was setup to 5, except the amount of offered tokens is less than that.

One important thing to mention that is transparent for any end user, is that there are two kinds of fills: complete and partial. A complete fill will buy all the offered tokens from the order, and for the partial fill, we need to specify the amount we want to buy from the order. For us, that will be running and probably improving this implementation is relevant because, as we will see in a moment, we can design different matching strategies using these two different fills.

Up to this point, we quickly covered the key actions that can be performed over the orders. There shouldn't be any surprise if we mention that each action is performed by a transaction.

Now, let's suppose, besides the previous order, we have another one offering of 20 tokenB, with a unit price of 0.4 tokenA. We could earn some tokens by “combining” the two orders and take advantage of the price difference. Following the example, given we bought 6 tokenA using 12 tokenB, we now can use these 6 tokenA to buy back 15 tokenB from this other order, earning 3 tokenB. These two fills can be combined into a single transaction, in fact, we could combine more than two orders.

The SOR has the ability to build these transactions matching orders programmatically, that is, combining orders into a single transaction. Which orders the SOR will match is determined by the strategy that must be configured in advance. To reason about any strategy, we need to classify orders into sell or buy. It's possible for an order to be a buy or sell, depending on the token used to earn the difference between the orders. In the previous example, we earned in tokenB, but we could have earned in tokenA. So, given a token pair, we will specify which token is the commodity and which is the currency, which will establish if a given order is a sell order or a buy order: If the order offers commodity, then it will be classified as a sell order. On the other hand, if the order involves buying the commodity with currency (that is offers currency), it will be considered a buy order.

Using the previous example we could have two cases:

Commodity A | Currency B Commodity B | Currency A

Amount	Price	Type
`10 tokenA`	`2 tokenB`	Sell
`8 tokenA`	`2.5 tokenB`	Buy

Amount	Price	Type
`20 tokenB`	`0.4 tokenA`	Sell
`20 tokenB`	`0.5 tokenA`	Buy

If we want our earnings to be in tokenB, then the commodity must be tokenA. We can buy from the sell order, 6 tokenA using 12 tokenB, then using these 6 tokenA we buy back 15 tokenB from the buy order, earning 3 tokenB. However, if we want our earnings to be in tokenA, then the commodity must be tokenB. So we can buy from the sell order, 18 tokenB using 7 tokenA, then using these 18 tokenB we buy back 9 tokenA from the buy order, earning 2 tokenA.

Building and running

Docker

🚧 Coming Soon 🚧

Local build

First, you need to setup the necessary tooling to work with haskell.nix. A complete guide and troubleshooting of how to install and configure nix can be found on one of the officials IOG repositories: plutus-apps. Once we completed the previous steps we can simply run nix develop, and it will drop you into a shell with all the necessary tools. Once inside the environment, you can build the order bot with cabal build all.

Orderbot Config

To run the order bot, it is necessary to setup the provider and specify the bot options. There is one option for a completely local provider and two remote ones.

Local Provider

Kupo can be used as a local provider. For this it is necessary to provide a path to a cardano node socket file and the Kupo url in the atlas-config-kupo.json file.

Remote Providers

There are two possible remote providers: Maestro or Blockfrost. In order to function properly, each provider requires a specific API-TOKEN or API-KEY (that should be created on each official site). These must be entered into the appropriate provider configuration file, either atlas-config-maestro.json or atlas-config-blockfrost.json.

You must also configure the networkId to specify which Blockchain to use. Inside any of those configuration files, we can also configure the logging mechanisms, we can specify the log severity level with Debug, Info, Warning, but also the sinking of the information by choosing between a console log or a file. Besides different levels of verbosity. We even can have multiple logs, for instance on the example below we are logging some Info level info into de console, and some Debug level info into the Debug.log file.

"logging": [ { "type": { "tag": "stderr" }, "severity": "Info", "verbosity": "V2" }
           , { "type": { "tag": "gySource", "source" : "Debug.logs" }, "severity": "Debug", "verbosity": "V2" }
           ]

In addition, to configure the bot, it is necessary to edit the bot-config.json file. The complete bot configuration looks like this:

{ "signingKeyFP": "bot.skey"
, "collateral": "5b4fd2daa591e971b24e338275cc3c0710acadb6544a95930164c2c5c68a3a6c#0"

, "nftMintingPolicyFP": "compiled-scripts/minting-policy"
, "orderValidatorFP": "compiled-scripts/partial-order"
, "validatorRefs":
  { "refAddr": "addr_test1wpgexmeunzsykesf42d4eqet5yvzeap6trjnflxqtkcf66g0kpnxt"
  , "refNftAC": "fae686ea8f21d567841d703dea4d4221c2af071a6f2b433ff07c0af2.e6a295bb83d06f53fcf91151f54acec0a63fbd6f0d924206d5d012e6da3b72af"
  , "refNftUtxoRef": "39f987a6beb9cc4c45bba149a21c28068f640f3593f15f8157f0b6022b431977#0"
  , "scriptRef": "39f987a6beb9cc4c45bba149a21c28068f640f3593f15f8157f0b6022b431977#1"
  , "nftPolicyRef": "39f987a6beb9cc4c45bba149a21c28068f640f3593f15f8157f0b6022b431977#0"
  }

, "strategy": "OneSellToManyBuy"
, "scanDelay": 40000000
, "maxOrderMatches": 5
, "maxTxsPerIteration" : 5
, "randomizeMatchesFound": true

, "scanTokens" :
  [
    { "commodityAsset" : "c6e65ba7878b2f8ea0ad39287d3e2fd256dc5c4160fc19bdf4c4d87e.7447454e53"
    , "currencyAsset" : "lovelace"
    }
  ]
}

signingKeyFP, we need to specify the bot signing key, that must be placed on a file.
collateral, an optional field to specify the collateral for the bot. If not present, Atlas will choose a suitable UTxO as collateral.
nftMintingPolicyFP and orderValidatorFP, the filepath where the minting policy and validator are stored.
"validatorsRefs", contains the information necessary for the validator. Contains 3 mandatory fields and 2 optional ones.
- "refAddr", address where the reference NFT is placed.
- "refNftAc", assetClass of the reference NFT is placed.
- "refNftUtxoRef", UTxO reference where the reference NFT is placed.
- "scriptRef", an optional parameter for the script reference. This UTxO has to have the partial order validator as a script ref.
- "nftPolicyRef", an optional parameter for the script reference of the partial orders NFT. This UTxO has to have the partial order NFT minting policy as a script ref.
strategy, currently the SOR supports one possible strategy: OneSellToManyBuy.
scanDelay, the duration of time we wait before re-initiating a complete iteration for the bot.
maxOrderMatches, is the maximum amount of orders to be matched into a single transaction. 8 orders is near the limit that will fit into a transaction.
maxTxsPerIteration, is the maximum amount of transactions that the bot will build, sign and submit in each iteration.
randomizeMatchesFound, a boolean that dictates whether the bot chooses the tx to submit at random (to decrease collisions), or not (to maximize profit)
scanTokens, the list of token pairs to be scanned. Each element in the list specifies which token in the pair is the commodityAsset and which is the currencyAsset. The bot will arbitrage the orders to get tokens of the currencyAsset. Each token must be written with the format policyId.hexTokenName. For convenience, scanning ADAs can be done by writing lovelace or the empty string. The multi-asset order book is built using this list.

Creating Signing Key

Another important and necessary setup to make is the creation of the bot wallet. If you already have a wallet signing key to use, you just need to put the signing key in a file and properly configure signingKeyFP.

If you want to create a new wallet, you can create everything using the cardano-cli:

cardano-cli address key-gen \
	--verification-key-file bot.vkey \
	--signing-key-file bot.skey

cardano-cli address build \
    --payment-verification-key-file bot.vkey \
    --testnet-magic 1 \
    --out-file bot.preprod.addr

This will create the files bot.skey, bot.vkey, and bot.preprod.addr: the private signing key, the verification key, and the wallet address on the preprod testnet. You can claim some preprod lovelaces using the faucet.

It's recomended to create and setup a collateral. A UTxO with 5 ADAs will do the work. But as we mentioned the collateral config field is optional.

Deployed Contract

The SOR has the ability to use reference scripts on the filling transactions to help minimize the fees. To do that, we need to use the official contract information that is completely placed on the blockchain. That is the validator and minting policy.

Preprod

"validatorRefs":
  { "refAddr": "addr_test1wpgexmeunzsykesf42d4eqet5yvzeap6trjnflxqtkcf66g0kpnxt"
  , "refNftAC": "fae686ea8f21d567841d703dea4d4221c2af071a6f2b433ff07c0af2.e6a295bb83d06f53fcf91151f54acec0a63fbd6f0d924206d5d012e6da3b72af"
  , "refNftUtxoRef": "39f987a6beb9cc4c45bba149a21c28068f640f3593f15f8157f0b6022b431977#0"
  , "scriptRef": "39f987a6beb9cc4c45bba149a21c28068f640f3593f15f8157f0b6022b431977#1"
  , "nftPolicyRef": "39f987a6beb9cc4c45bba149a21c28068f640f3593f15f8157f0b6022b431977#0"
  }

Mainnet

🚧 Coming Soon 🚧

"validatorRefs":
  { "refAddr": ""
  , "refNftAC": ""
  , "refNftUtxoRef": ""
  , "scriptRef": ""
  , "nftPolicyRef": ""
  }

Running

Once we compiled and configured the order bot, you can execute using the Makefile: make orderbot-maestro, make orderbot-blockfrost or make orderbot-kupo.

Testing

The SOR is equipped with a test suite that employs QuickCheck to perform property-based testing. By implementing certain properties, we are able to verify various important aspects of the strategies, like for example, given a matching between sell and buy orders there is always a positive earning. Among others that can be found on Tests.Prop.Strategies module.

For running the tests we can just simply execute make orderbot-tests.

Design

The SOR is organized into 5 main folders:

compiled-scripts, contains the compiled validator and minting policy of the DEX.
geniusyield-dex-api, defines the DEX interface to query and build transactions.
geniusyield-orderbot-framework, implement the main abstract tools for the SOR.
geniusyield-orderbot, the executable is implemented here, together with the strategies.
impl, specific implementations of the orderbook and data-provider.

Backpack

This is an order matching bot implementation that is meant to be modular and polymorphic. It uses backpack to support this goal. Backpack is surprisingly flexible, supporting signature merging and signature thinning. This may be especially relevant for modular orderbot implementations. Signature thinning is when an indefinite library depends on a signature but only demands a subset of said signature, allowing an implementation that only implements said subset of the interface to be used merrily with the library.

Solid resource for learning backpack: GitHub - danidiaz/really-small-backpack-example: A really small example of the Backpack module system for Haskell

Strategies

On the Strategies module, you can find all the strategies implemented by the SOR. Currently, there is only one called OneSellToManyBuy, which basically takes the best sell order (the one with the lowest price) and searches for many buy orders (starting from the one with the highest price), ideally buying the total amount of offered tokens, or until it reaches the maxOrderMatches.

Adding a new strategy

In this Haskell implementation, a strategy is simply a function with type OrderAssetPair -> OrderBook -> [MatchResult]. This function returns a list of matching results from a pair of tokens and an order book, which consists of both sell and buy orders. Each matching result represents a transaction, which involves a specific set of sell and buy orders.

We can start with the most bureaucratic part of adding a new strategy. We need to define the name of the new strategy, so let's say we want to implement the "dual" strategy to the one that is already there. We want to implement then one strategy that given the best buy order, searches for many sell orders. We add then a new constructor OneBuyToManySell to the type BotStrategy

data BotStrategy = OneSellToManyBuy
                 | OneBuyToManySell

We must adjust some straightforward instances with the new constructor: FromJSON and Var. As is the case with mkIndependentStrategy, adding a new particular case for OneBuyToManySell

mkIndependentStrategy :: BotStrategy -> Natural -> IndependentStrategy
mkIndependentStrategy bs maxOrders _ bk =
    case bs of
      OneSellToManyBuy -> oneSellToManyBuy maxOrders bk
      OneBuyToManySell -> oneBuyToManySell maxOrders bk

Once we get to this point, we can focus on the implementation of the new function. In fact, we can start with a very silly implementation that doesn't find any matching with the goal of compiling everything.

oneBuyToManySell :: Natural -> OrderBook -> [MatchResult]
oneBuyToManySell _ _ = []

Even more! We can go to the Main testing module, and add the new constructor OneBuyToManySell to "Strategies tests" list and it will be enough to start testing our strategy by running the tests.

Finishing the implementation of oneBuyToManySell is left as an exercise.

Hint

Checking multiFill, can help to realize that it's enough to use oneSellToManyBuy as inspiration and "flip" something.

Questions: Choosing between one strategy or the other will always enforce some matching strategy, so will it be possible to merge the two strategies into a single one? Or it will be better to run two different SOR instances?

Troubleshooting

Providers

geniusyield-orderbot-exe: MspvApiError "SystemStart" (MaestroApiKeyMissing "Invalid authentication credentials"), you need to setup the corresponding Maestro token into atlas-config-maestro.json file.
geniusyield-orderbot-exe: BlpvApiError "LedgerGenesis" (BlockfrostTokenMissing "Invalid project token.") you need to setup the corresponding Blockfrost token into atlas-config-blockfrost.json file.

Cardano

BadInputsUTxO in the exception that is raised during tx submission, not creation/balancing, usually indicates contention. An order you are trying to match is being matched by another transaction.
ExUnitsTooBigUTxO in the exception means you are trying to match too many orders simultaneously, making the transaction size cross the limit.
BalancingErrorInsufficientFunds in the exception indicates there are not enough of one or many tokens to construct the transaction. If you see ADA in the value that is printed afterward, it means your bot is out of ADA. More often, however, this error will be raised if your matching strategy does not return proper order matches and there aren't enough tokens in the transaction bucket to pay an order.
GYTxMonadException "partiallyFillPartialOrder: amount x must be smaller than offered amount x, you are trying to partially fill an order, but the partial fill amount is the max volume of the order. Use CompleteFill instead. See GeniusYield.OrderBot.MatchingStrategy for more information.

Cabal <> Haskell

HLS will not work in signature modules, nor will it work in modules importing a signature module.
Cabal mixins can be flaky sometimes. If you're sure you're using mixins properly but still getting "Module X does not require Y", try cleaning the geniusyield-orderbot build and rebuilding from scratch.

piyushthapa/smart-order-router