The Clarity AMM Focus Strategy

Window Finance's AI-enabled algorithm for optimizing a portfolio of concentrated market-making positions

Disclaimer: Nothing in this research post constitutes investment advice or an invitation to invest. In addition, the information and results herein are preliminary, indicative, and shared solely for research purposes. This preliminary research should not be relied upon to make any investment decisions.

TL;DR

• Window Finance’s Clarity platform — data infrastructure that builds, backtests, simulates, tracks, and optimizes DeFi strategies–now includes dynamic range selection and recalibration for concentrated liquidity pools.
• Leveraging Clarity, Window Finance researchers produced an automated market maker (AMM) liquidity pool (LP) portfolio optimization strategy that outperforms a benchmark index by 5,497 basis points (+54.97%) over a 1-year period.
• Investment funds are actively developing data-driven investment strategies through the Clarity closed beta, now open for waitlist access.

Dynamic Decentralized Finance Investing

Window Finance aims to reduce risk and amplify returns for sophisticated crypto users with Clarity, its advanced data infrastructure and platform.

Training upon a vast proprietary data set, Clarity now enables dynamic range setting and recalibration for concentrated liquidity positions popularized by Uniswap v3, providing a comprehensive solution that continually adapts to market conditions.

This article discusses how Clarity produced an optimized risk-adjusted return strategy for AMM LP portfolios.

Intro to the Clarity AMM Focus Strategy

The Clarity AMM Focus strategy aims to select diversified liquidity pools with a strong expected risk-adjusted return profile.

Our results during the backtest period show that the Clarity AMM Focus strategy generated a 1-year return of 69.42% — an outperformance of 5,497 basis points over the Clarity AMM Index and 6,150 basis points over the S&P Cryptocurrency Broad Digital Market Index (S&P CBDM).

Figure 1. Performance of Clarity AMM Focus and AMM Index vs. the S&P CBDM.

The results also indicate that when investing in an AMM strategy, it is possible to generate additional returns without necessarily increasing the level of risk. The table below shows that not only did Clarity AMM Focus outperform considering total return, but it does so with 20 percentage points less volatility than the general crypto market.

Table 1. Investment metrics of Clarity AMM Focus vs. Clarity AMM Index and S&P CBDM benchmarks.

Concentrated Liquidity AMMs: More return means more complexity

Investing in concentrated liquidity AMMs presents unique complexities that necessitate specialized management strategies.

• Pool Overload: With thousands of liquidity pool options, constructing a suitable portfolio can be overwhelming. The difficulty further compounds this complexity in ascertaining details around the pool’s underlying holdings, expected return, and volatility.
• Market Variability: Yield generated from liquidity pool trading volume and incentive fees can change or degrade significantly over time. Additionally, new opportunities can arise, which can be challenging to track, while protocols can upgrade to new versions, requiring continuous user monitoring and maintenance.
• Range Selection: The newer generation of concentrated AMMs requires continuous, complex capital allocation and range selection optimization.
• Impermanent Loss: The prices of the assets in the liquidity pool can diverge, exposing the liquidity provider to an unbalanced portfolio and potentially significant Impermanent Loss.

Addressing Impermanent Loss

Forecasting the long-term price movement of digital assets is notoriously tricky.

Clarity has been tracking thousands of AMM LP positions since the beginning of 2022. Based on this data, 25% of LP positions have experienced an impermanent loss greater than 10%.

Figure 2. Histogram of historical impermanent loss for the various pools in our dataset.

The Clarity AMM Focus strategy accounts for the expected impermanent loss in the context of each liquidity pool’s expected yield performance. In other words, high impermanent loss is tolerable if offset by sufficient yield income.

To do this, Clarity employs a probabilistic asset pricing model focused on predicting relative price movements for liquid tokens.

AMM Portfolio Optimization: Pitfalls to consider

Optimizing a portfolio in the AMM space adds another layer of strategic considerations beyond individual pool management.

• Rebalancing: Periodic rebalancing is essential for maintaining optimal performance. The portfolio should be optimized for factors such as fee income/yield, capital allocation range calibration, and periodic rebalancing on a forward-looking basis.
• Variability: Managing the churn and variability in yield across multiple pools is vital. To manage these challenges, Clarity employs probabilistic models that consider factors like total value locked, trading volume, and incentive fees, thereby providing a range for future yield expectations.
• Risk Management: A balanced mix of pools is crucial for risk mitigation and maximizing returns. The Clarity AMM Focus strategy selects diversified liquidity pools with a strong expected risk-adjusted return profile to maintain an optimal position across the universe of AMMs.

Window Finance engineered Clarity to tackle these issues directly and on a forward-looking basis, enabling the construction of low-correlated strategies with solid risk-adjusted returns like the Clarity AMM Focus algorithm detailed below.

Portfolio Construction and Calibration

The Clarity AMM Focus strategy automatically generates a portfolio based on the expected performance of the underlying liquidity pools and rebalances every two weeks.

If a specific pool falls out of the predetermined range within a given cycle, the algorithm recalibrates the optimal range for liquidity provision. Proprietary tools are used to maintain oversight and provide insight into asset diversification, market exposure, and historical and expected yields.

Figure 3 shows a sample of auto-generated portfolios at different periods.

Figure 3. Token exposures across rebalance periods

While this long-biased strategy exposes investors to market volatility, some investors leverage Clarity in constructing hedged portfolios with non-correlated and negatively correlated positions that drastically reduce market exposure to market fluctuations.

Parameters

• The strategy picks from a universe of liquidity pools using investment criteria catering to professional investors on the Ethereum, Polygon, and Arbitrum blockchains, such as Uniswap, QuickSwap, and Balancer.
• The algorithm filtered out positions holding tokens with a small market cap or low TVL from August 2022 to August 2023.
• To simplify our analysis, we omitted gas and trading costs as these costs can mitigated using certain low-cost chains and aggregated trading strategies.

Benchmarks: The Clarity AMM Index and Digital Asset Market

In our simulation, we assess the performance of the Clarity AMM Focus strategy by comparing it to two benchmarks.

The first is the Clarity AMM Index, which serves as a performance gauge for liquidity pools containing highly liquid tokens.

The second is the S&P Cryptocurrency Broad Digital Market Index, a market-weighted index representing the top 250 cryptocurrencies by market cap.

Get Access and Dive Deeper

The Clarity AMM Focus strategy successfully outperformed the selected benchmarks during a volatile market period. Funds and other sophisticated investors are developing and deploying Clarity-developed strategies similar to AMM Focus through our private beta.

Join the waitlist for Clarity or email hello@window.finance to learn how intelligent investors leverage our technology.