Announcing Trading Strategy 1.0

The first open trading strategies are now available. Read to learn what the Trading Strategy team has built, how everyone can be a quant trader, and what this means.

We want to thank our partners at Enzyme Finance, 1delta, Velvet Capital, xWIN, Uniswap, Sushi, Osmosis, Aave, Circle, and ChainLink for making this release possible.


Two years ago, we set on a path to build the first algorithmic trading product for decentralised markets. While plenty of yield farming protocols and trading bot services for centralised exchanges were available, DeFi was still seen as an immature degen yield farming playground unsuitable for professional quant trading. The lack of professional tools, market data, infrastructure, liquidity, technical risk, and such were major factors - an example opinion about decentralised finance from a professional quant.

We believe decentralised finance is the future. DeFi has many unique selling points that traditional finance cannot replicate. These include, for example, less counterparty risk with good transparency, fairer public data access, and fierce competition pushing trading fees lower. "Uberification" of trading and investing is coming, as A16Z writes in their famous Open Source Finance blog post.

Our vision

Machines and AI are better than humans at analytical tasks. AI is already winning in chess, Starcraft, in some creatives, and many other sectors. Trading and investing will be no different. Most humans would be better off giving their money management to machines instead of managing it themselves or having it managed by other humans.

For a long time, most trading has been algorithmic. But until blockchains and DeFi came around, it was difficult to expose this directly to consumers. While consumers get indirect exposure to automated trading products, it usually happens through a fund, bank, or another intermediary.

In mature markets, algorithmic trading accounts for 50%—80% of the trading volume. Machines, not humans, make individual trade decisions.

Trading Strategy is the first purely machine-based protocol for algorithmic trading. After a single trading strategy is launched, the system aims to be fully self-custodial, and the only person in the process is the one who deposits the trading capital.

Financial and trading value refinement in a blockchain ecosystem and how high-level solutions are built on top of the low-level ones. The bottom half of the DeFi stack had to be built and exist before more complex services could come in. The 3rd party logos are presented for demonstration purposes only.

Consumers win when machines and AI take over in trading, as more revenue is distributed directly to them. There are fewer intermediaries to feed, and smart contracts neither need nor ask for management bonuses.

How are we different?

Trading Strategy is the first algorithmic trading protocol for decentralised finance. We popularise professional quant finance for everyday users: retail traders, CFOs, and small and medium-sized funds and trading firms, by focusing on advanced and speculative trading strategies and risk-adjusted return, although strategies can also utilise many other kinds of yield generation elements.

Most of the readers of this blog post likely have an existing decentralised finance background, so we explain it with this background in mind.

Ethena, a new stablecoin protocol, popularised cash and carry trade. In this trade, the protocol holds a delta-neutral position, having staked ETH and short ETH in a similar ratio. As writing of this, Ethena earns ~40% APR because, in perpetual cryptocurrency markets, more longs than shorts are open. Long position holders pay interest to short position holders.

Why would anyone taking the counter trade pay Ethena 40% interest? Since 2019, ETH and BTC have appreciated an average of 80% (CAGR) per annum. But this return comes with a severe risk: a 70% maximum drawdown. Traders can afford to pay 40% yearly interest because they believe there is even better trade to take.

Would you take this risk: Double your money yearly, but you might lose 70% in one year? The answer depends on your risk tolerance and how effectively you mitigate the downside. This is where Trading Strategy enters the play. By having tools to develop strategies to trade in different market conditions, and quantifying the risk, the strategies can outperform buy-and-hold, lending, yield aggregator and other markets available in DeFi today.

This is an example of an equity curve of a strategy benchmarked against BTC and ETH. This strategy trades spot BTC and ETH and mainly competes against buy-and-hold strategy. You can see how, in the strategy, the profits are more stable (dips less severe) than just buying and holding the underlying assets. While this strategy is not designed to outperform buy-and-hold cryptocurrencies, it offers a compromise on risk-adjusted returns: it outperforms savings rates, capturing most of the cryptocurrency market upside while actively managing risk of losses when the volatile cryptocurrency markets crash.

Read our Outperform ETH blog post for more in-depth examples on how the strategies are developed and how to compromise for risk-adjusted returns.

An example of risk-adjusted metrics when comparing an automated trading strategy to buying and holding different cryptocurrencies.

What are we offering

Trading Strategy is a protocol where quant finance experts can develop, backtest, and offer their trading strategies to DeFi users. DeFi users can then choose from different strategies that fit their risk profile. Quant finance experts can alternatively launch their strategies for proprietary trading as well.

For strategy end users we offer

  • A set of strategies to choose from
  • Extensive data on the performance and risks of these strategies based on real historical data
  • DeFi native Connect wallet, Deposit, and Redeem user experience, and
  • Automatically executing strategies

You can try this today.

Trading Strategy end users can choose between different trading strategies, select strategies that fits their risk profile, and deposit USDC in them to start participating in trading. Different strategies have different risk profiles and trade on different blockchains. Only a cryptocurrency wallet is needed, and no complex API key set-up or risks associated with centralised exchanges.

Expected strategy end users include DeFi traders, CFOs, wealth managers, treasuries, and small and medium-sized liquid funds.

For developers or quants, we offer

  • A place to run your trading strategies with new market opportunities
  • Generous fee collection opportunities from open strategies
  • High-quality market data covering multiple blockchains and hundreds of thousands of trading pairs
  • A Python-based strategy development and backtesting framework. No blockchain or Solidity knowledge is needed!
  • Live trade execution across multiple DEXes, lending protocols
  • Software license for proprietary trading strategies
Before, developing and deploying automated trading strategies on DeFi markets was impossible due to a lack of good data feeds, tooling and asset management. Trading Strategy solves this with an open protocol. This opens a door for all quant finance professionals from TradFi markets and centralised crypto markets to enter DeFi.

How does the protocol work?

There is not yet a powerful enough blockchain to execute sophisticated trading strategies on DeFi. Thus, the protocol runs with off-chain oracles, similar to Chainlink, which will later be expanded to be a large oracle network.

An overview of how market data feeds, Python-based trading strategies, user deposits and smart contracts all come together.

Whereas Chainlink oracles are focused on delivering off-chain price information for perps and liquidations, Trading Strategy oracles focus on making complex trading decisions based on on-chain data possible. A single trading decision may read and process megabytes of data.

Can public alpha exist?

One main argument we heard when pitching our vision was that "public alpha" does not exist. This means that any public trading strategy cannot be effective. This argument was heard especially from traditional finance representatives. The lack of public alpha implies that finding and exploiting market inefficiencies to generate excess returns requires sophisticated techniques, data, and resources typically unavailable to retail investors or closely guarded by institutional investors and hedge funds.

A professional derivatives trader unhappy about Ethena unlocking his trades to masses.

We believe this view is wrong. Decentralised finance itself is public alpha. For example, Ethena popularised the carry trade by making it easily accessible over the DeFi user interface, opening this billion-dollar opportunity for everyone. Naturally, the hedge funds that had exclusivity for this kind of trading opportunity earlier due to complex trades that needed to be wired together are now salty about their new competition. It turns out that the future markets might be less about secret alpha and more about effective execution and creating automated opportunities with easy access to capital.

How is Trading Strategy positioned?

Trading Strategy is the first algorithmic trading protocol for DeFi.

Trading Strategy protocol compared to other active trading and portfolio management solutions.
  • Trading Strategy focuses on risk-adjusted return, not delta-neutral strategies
  • All funds are held in smart contract vaults and can be redeemed at any time
  • All trading strategies have comprehensive information on their risks and potential rewards
  • We are a DeFi-native protocol, not a trading bot platform

We composed the protocol from several DeFi elements, including self-custodial wallets. This is another unique aspect of DeFi and why traditional finance can never accomplish as slick user experience and risk transparency.

We offer several value-adds to the entire ecosystem

  • For blockchains, we offer a real yield-generating application that demonstrates the best aspects of decentralised finance and its benefits - something that attracts traditional finance and institutions as well
  • For DEXes and their liquidity providers, we offer marker-taker volume through our automated strategies
  • For digital asset management and vault protocols, we offer an effective increase in the number of attractive vaults by having a vault for each different automated strategy
  • For wallets and DEXes, we offer embedded strategies and affiliate revenue deals
  • For lending protocols and DEXes, we offer extensive embeddable data services similar to TradingView (see Aave example) - our solution can be white-labelled and free from many TradingView limitations

What did we learn building the first version

When we started building Trading Strategy over two years ago, we were optimistic about the amount of time it would take to complete the first public version. Several hurdles took longer than expected, and showing the immaturity of the DeFi ecosystem.

Building a robust data ETL and trade execution layer for DeFi was not trivial. It's much appreciated, though. Trading Strategy's open-source eth-defi repository has 500+ stars on GitHub.

We had to write way more software than we hoped for. However, the software is now written and good to go.

What's the feedback we have received

We validated our product with proprietary traders and DeFi traders using private trading strategies. We are very grateful to all these partners who helped us with the early, very rough versions and the early feedback they provided.

Some of the shortcomings we had to address when validating the minimal viable product.

  • Lack of shorting: it is necessary to be able to trade market both ways - this was especially true during the grueling crypto winter of 2021-2023. The great news is the current version of Trading Strategy protocol already includes capabilities for shorting through the use of lending pools for proprietary strategies. More information about this in the next chapter.
  • Backtesting speed: The backtester needs to be fast. Otherwise, the strategy developers get frustrated. The current version is much faster than the initial prototypes and sufficient for most purposes. However, it is an event-based backtester and, in its current form, can never be as fast as vectorised alternatives.
  • The complexity of programming: most traders and quants are not very good programmers. You need to simplify the code for them and design ultimate obvious and easy-to-reason APIs. We have done a lot of work to simplify the Python notebook examples and added many useful functions to our API.

An expert trader's opinion on how difficult on-chain trading is currently. Trading Strategy is here to fix this.

The positive feedback we have received

  • Everyone is excited to be an end-user for Trading Strategy and ready to put some money in - we'd say there is a clear market demand for what we are building. We are super grateful for the positive feedback and excitement we have received.
  • Proprietary traders keep saying that our strategy development framework is better than some commercial closed-source offerings.
  • There is a queue of dozens of DEXes that want to integrate us, and in-house software development resources limit us from tackling them all.

What's still missing

Version 1.0 does not include everything we wanted. These are being addressed in the future

  • No short positions on open strategies: Currently, there isn't a single on-chain asset management protocol that supports short positions with share-based vaults(*) - thus all open strategies at the launch will be long-only, limiting their performance. We can still run long-short strategies, but these strategies are limited to proprietary trading or single user mode only, however we have made it very easy for you. This will be extended to cover open strategies in the near future as we are collaborating with on-chain vault providers to make necessary enablers available in their protocols too. Shorting on perp futures DEXes will be made available through upcoming integrations in the near future as well.
  • Limited trading universe: Current digital asset management protocols use Chainlink feeds for share pricing. This limits the tradeable token universe to tokens with a Chainlink price feed. We are exploring other price oracle alternatives that would give a much richer set of tokens to trade. Again, this is a problem only for open strategies, and the limitation is not present for proprietary strategies.

(*) Technically, Hyperliquid supports perp vaults. Hyperliquid is not decentralised yet.

What's next for you

Trading Strategy is now live. We expect to roll out better-performing strategies quickly after the launch. We have a few strategies lined up.

We are live. Please check it out yourself. We are looking forward to rewarding early users for their feedback.

Please check out the existing strategies, and if they are suitable for your circumstances and risk profile, you may make some small deposits, as we plan to reward early users.

As we are expanding the protocol's capabilities and integrations, we are also reaching out to the ecosystem partners for discussions

  • Any perp DEXes that want to integrate automated trading strategies, or have vaults developed for them a la Hyperliquid
  • DEXes and lending protocols that want to get market taker volume or new data services
  • Wallets and other frontends who could use trading strategies as an additional shared revenue source

What's next for Trading Strategy

Token. The token is next for us. operated by Trading Strategy Operations Ltd., Victoria, Mahe, Seychelles.