Rebalancing Strategies

Rebalancing strategies have the ability to constantly adjust and maintain your desired portfolio balance, rebalancing strategies can help mitigate risk and increase long-term returns.

MARKET NEUTRAL YIELD (MNY)

A hedged yield strategy can earn yield in a number of ways, but the key point is that it's market neutral, i.e., it's indifferent to market movements up or down. This strategy earns yield on crypto assets while hedging against to be market neutral, making interest on USD while uninfluenced by crypto price volatility

Expected APY: 13%

Overall risk: high

Full description

A delta-neutral strategy involves holding equivalent assets both long and short to net out exposure to that asset, and taking advantage of potential yield opportunities from one side.

An example of this hedged yield strategy is LPing volatile crypto assets like MATIC and simultaneously taking a short position on those assets (borrowing on Aave). This means that the strategy has almost no exposure to MATIC price volatility (delta neutral), while earning trading fees and farming rewards from the LP.

As the price of MATIC moves, the strategy rebalances both the hedge and the aave positions. It rebalances the hedge by either increasing the Aave position, or increasing the LP position when a threshold is reached to rebalance the hedge. It rebalances the Aave debt position to keep the Aave Health Factor within a threshold (target Health Factor of 1.4).

With low price volatility, the strategy will require little rebalancing and can earn trading fees with minimal cost. This is how the yield is generated for the strategy.

Below is the simplified strategy output once the hedged position cancels out the LP position. Periods of lower volatility result in decreased strategy costs.

Aave+Rebalancing Costs represent the costs of Lending and rebalancing.

Given that this is a dynamic strategy like other Algoo Strategies products, the strategy will actively hunt pairs and delta hedge with those that are either highly incentivized or demonstrate low volatility to minimize volatility decay.

Estimated returns and source of yield

Target ROI: ~42%

Source of yield: Polygon, Aave

Liquidity incentivising: By providing liquidity to decentralized exchanges or liquidity pools on Polygon, this strategy earns trading fees and potential yield rewards. As users trade and interact with these platforms, a portion of the fees is distributed to liquidity providers. The yield generated through liquidity provision is based on the trading volume and liquidity utilization of the specific pools.

Yield Farming: Some protocols on Polygon offer additional incentives in the form of yield farming rewards. By participating in liquidity mining programs, and providing liquidity to specific pools, this strategy can earn additional tokens or rewards. These rewards are typically distributed by the protocol to incentivize participation and bootstrap liquidity.

Short Position Borrowing: By utilizing lending platforms like Aave on the Polygon network, this strategy can borrow volatile crypto assets like MATIC to take a short position. When the value of the borrowed asset decreases, the loan is repaid with a lower amount, thus profiting from the price decline. The difference between the borrowed amount and the repayment amount represents a potential yield.

Interest Income: When this strategy borrow assets on lending platforms like Aave, there is an interest required to be paid on the borrowed amount. However, if the interest rate on borrowed assets is lower than the yield generated from liquidity provision and yield farming, the strategy can earn a positive interest rate differential, resulting in net interest income.

Underlying coins and protocols

Coins: MATIC, USDC, AAVE

Protocols: Polygon

Capped TVL

Note - For strategy effectiveness, the Polygon Dynamic strategy is capped. The cap was $1 million at the time of documentation.

Strategy pros

Risk mitigation: The strategy aims to balance the long and short positions to provide a more stable return profile. It can also use techniques such as stop-loss orders to limit potential losses.
Reduced market exposure: The strategy aims to generate returns irrespective of the direction of the market. As a result, it can reduce exposure to market volatility, and provide a more stable return profile.
Efficient use of capital: The strategy allows for efficient use of capital by simultaneously investing in multiple assets and taking advantage of market fluctuations.
Transparency: The strategy is transparent in its execution, allowing users to monitor their investments, trades, and the performance of the strategy in real-time. You can view On-chain analytics and track the performance of the Market Neutral yield strategy (Link).

Strategy cons

Risk of liquidation: while the Algoo Strategies team will be monitoring the position to maintain a safe health factor, it is still possible for a position to get liquidated either during extreme market conditions or due to a price manipulation (which is highly unlikely) or an exploit.

Investment tips on how to blend this strategy into your portfolio

Utilize the strategy during bullish markets. If you want to make a directional bet on ETH price, consider using this strategy to earn yield on your deposit.
Combine with Midas’s 0.5x Short on ETH strategy to hedge your exposure or create a delta neutral strategy for ETH.
Combine this strategy with Midas fixed yield products to increase the risk and reward ratio of your portfolio.

Fees

Performance fee: 20% of weekly profit (only if the strategy has generated profit); fees are deducted directly from the strategy returns each week.

If the user exits the investment strategy before the settlement day, then we calculate the difference between the current price and the price of the last settlement period and take 20% of the profit. If there is no profit, then the user does not pay performance fee.

Performance fee = [Current price - last price] * 0.2

Swap Fee

From Stables to Strategy — 0% platform fee + ~0.2% market spread
From ETH to Strategy — 0.3% platform fee + ~0.2% market spread
From BTC to Strategy — 0.3% platform fee + ~0.2% market spread
From all others to Strategy — 0.2% platform fee + ~0.2-0.8% market spread

Strategy address: https://debank.com/profile/0xfc90eea22fced2adbeb70a3d23469686ccd8324a

RISK PARITY REBALANCING (RPR)

A strategy for achieving balanced risk exposure across various token asset classes in a portfolio means that the portfolio is allocated in such a way that each asset's risk contribution is equal. The strategy employs a mathematical model to determine the optimal asset allocation based on historical volatility and correlation. The Risk Parity Rebalancing strategy seeks to reduce overall portfolio risk while maintaining a reasonable rate of return.

Full description

This strategy specifies the risk allocation target for each token in the portfolio. Assume we want to allocate 30% to token A, 50% to token B, and 20% to token C. The algorithm retrieves the current market prices as well as the number of tokens in the portfolio. The volatility (risk) of each token is then calculated using historical data and statistical models. Each token's target allocation is determined based on its risk contribution. This entails calculating the weight of each token in the portfolio while accounting for its risk as well as the risk of the other tokens in the portfolio.

The algorithm compares the portfolio's current allocation to the target allocation and calculates the trades required to rebalance it. It then executes trades on the chosen DEXs to return the portfolio to the target allocation. The algorithm regularly monitors the portfolio and repeats the process as necessary to maintain the desired risk allocation.

In addition, the algorithm utilizes the yield farming capabilities of each DEX to generate yield on each asset in the portfolio:

On Convex the CRV could be used to provide liquidity to the WBTC/ETH pool to earn trading fees and CVX rewards.
On Bisq, the USDT could be used to provide liquidity to the USDT/ETH pool to earn trading fees and BQTX rewards.
On Lido, the ETH could be used to provide liquidity to the stETH pool to earn trading fees and Lido rewards.

The algorithm continuously monitors the portfolio and rebalances it to maintain the desired risk-parity allocation. For example, if the ETH increases in value and the USDT decreases in value, the algorithm could sell some ETH and buy more USDT to maintain the 25% allocation for each asset.

The Risk Parity Rebalancing strategy is a powerful tool for users looking to maintain a balanced portfolio while minimizing risks and maximizing returns. By utilizing DEXs like Convex, Lido, and IDEX, the algorithm can execute trades with minimal slippage and transaction fees, ensuring that the portfolio remains balanced according to the target allocation.

Estimated returns and sources of yield

Diversified portfolio of assets, including trading fees earned from liquidity pools

Target ROI: ~45%.

Underlying coins and protocols

Coins and tokens: USDT, ETH, CRV

Protocols: Convex, Lido, IDEX

Strategy pros

Diversification: The risk parity rebalancing strategy provides diversification across different asset classes, which can help reduce the overall risk in a portfolio. By allocating capital based on the volatility of each asset, the portfolio is balanced in a way that accounts for the risks associated with each asset.
Highly adaptive to changing market conditions: This strategy can adapt to changing market conditions, such as changes in volatility or correlations between assets. This can help ensure that the portfolio remains balanced and diversified even in changing market environments.
Leverage: This strategy has access to low borrowing costs, i.e. cheap leverage, which enables it to build a portfolio of uncorrelated assets weighted according to risk, and use that leverage to boost returns while keeping a reasonable level of volatility.

Strategy cons

Limited Flexibility: Once a risk parity strategy is implemented, it can be difficult to make changes or adjustments without significant reprogramming. This lack of flexibility can be a disadvantage in a rapidly changing market where quick adjustments are necessary to remain profitable.

Fees

Performance fee: 10% of weekly profit (only if the strategy has generated profit); fees are deducted directly from the strategy returns each week.

Swap fee:

From Stables to Strategy — 0% platform fee + ~0.2% market spread
From ETH to Strategy — 0.3% platform fee + ~0.2% market spread
From BTC to Strategy — 0.3% platform fee + ~0.2% market spread
From all others to Strategy — 0.3% platform fee + ~0.2-0.8% market spread

Strategy address: https://debank.com/profile/0x73c790f87cd889a7b1fcf18d3077fdd0227adb38

Maximum capacity: $9,000,000

DeFi TOKEN VOLATILITY TARGETING (DTVT)

This strategy monitors the volatility of assets in a Defi portfolio, and rebalances when the volatility exceeds a certain threshold. The aim is to sell assets that have become riskier and buy assets that have become less risky. This strategy is excellent because it allows the user to gain exposure to DeFi tokens while automatically mitigating the risks associated with the DeFi ecosystem. Rather than attempting to maximize returns, the strategy is intended to maintain a consistent level of risk in the portfolio.

Full description

The DTVT strategy works by measuring the volatility of the portfolio and adjusting the allocation of assets to maintain a target level of volatility. For example, if the portfolio becomes too volatile, the algorithm may reduce the allocation to higher-risk assets and increase the allocation to lower-risk assets, in order to bring the overall volatility of the portfolio back to the target level. Conversely, if the portfolio becomes less volatile, the algorithm may increase the allocation to higher-risk assets in order to maintain the target level of volatility.

Here is a breakdown of how the DTVT algorithm works:

Initial portfolio allocation: gathers a portfolio of top-performing Defi assets and allocates weights, for example: 40% WBTC, 30% ETH, 20% WBTC (fork) and 10% PLS.
Defines the volatility target: Set a target level of volatility for the portfolio. For example, the target could be 15% annualized volatility.
Calculates the current volatility: calculate the annualized volatility of the portfolio based on the historical prices of each asset. For example, let's assume the current volatility is 20%.
Adjust the weights: Calculate the optimal weights for each asset to achieve the target volatility. The optimal weights are calculated based on the inverse volatility of each asset. The higher the volatility of an asset, the lower the weight. The lower the volatility, the higher the weight.
Execute trades: The algorithm automatically executes the trades that will bring the portfolio weights in line with the optimal weights. For example, if the calculated optimal weight for ETH is 50%, but the current weight is only 40%, the bot would buy more ETH on Uniswap to bring the weight up to 50%.
Repeat: Repeat steps 3-5 at regular intervals (e.g., daily or weekly) to keep the portfolio allocation in line with the target volatility.

Estimated returns and source of yield

Target ROI: ~30%

Source of yield: dynamically adjusting the portfolio weights of WBTC, ETH, WBTC(fork), stETH and rETH tokens

Please note that the list of protocols and tokens is subject to change. Algoo team will be posting updates for this strategy allocations in community Telegram.

Underlying coins and protocols

Coins: WBTC, ETH, WBTC(fork), stETH, rETH

Protocols: Rocket Pool, LIDO, Uniswap

Strategy pros

One Strategy. A unified strategy for generating a compelling ROI from the most valuable DeFi projects in the current ecosystem.
Rebalancing. Algoo Strategies rebalances this strategy on a continuous basis, adapting it to changing market conditions.
Exposure to the upside as the price of DeFi tokens rises.
Adaptive Asset Allocation: This strategy employs an adaptive approach to asset allocation, allowing you to take advantage of the most rewarding staking opportunities in the DeFi ecosystem. By dynamically adjusting the allocation of your staked tokens based on their volatility, the strategy ensures that you are consistently exposed to the most profitable staking incentives available at any given time. This flexibility allows you to optimize your returns and adapt to changing market conditions.

Strategy cons

Highly correlated assets. Macro crypto performance will strongly influence the performance of the strategy.
Limited token selection: The algorithm is limited to the tokens available on the DEXs used in the strategy, which may not include all tokens of interest to investors.
High gas fees: The algorithm relies on DEXs, which can have high gas fees during periods of network congestion, which can reduce overall returns.

Fees

Performance fee: 15% of weekly profit (only if the strategy has generated profit); fees are deducted directly from the strategy shares each week.

Swap fee: 0.5% (into and out of this strategy).

Strategy address: https://debank.com/profile/0xbf39c33bbec985c25c645949fb6eeb7e8879fceb

Maximum capacity: $5,000,000

MEAN-VARIANCE OPTIMIZATION REBALANCING (MVO)

The MVO strategy uses statistical analysis to determine the optimal portfolio allocation based on the expected returns and standard deviations of each asset. The goal is to create a portfolio that maximizes the expected return for a given level of risk, or conversely, minimizes the risk for a given level of expected return.

Full description

In the Mean-Variance Optimization Rebalancing strategy, the portfolio is periodically rebalanced to maintain the desired allocation. This is done by adjusting the weights of each asset based on changes in their expected returns and standard deviations. Given a portfolio maximum of four assets on the optimism network: Wrapped Ethereum (WETH), Theter (USDT), DAI, and US dollar coin (USDC), The goal is to optimize the allocation of these assets to achieve a target risk level and return. The expected returns are estimated using historical data and market projections, while the volatility is estimated using historical standard deviations and implied volatility.

After obtaining these estimates, the algorithm would then calculate the optimal portfolio allocation that maximizes the expected return while minimizing the portfolio's volatility. Let's assume that the target risk level is 10% and the target return is 15%.

After applying the MVO framework, we may find that the optimal portfolio allocation is as follows: WETH - 20%, USDT - 30%, DAI - 15%, USDC - 35%. The algorithm would then execute trades on the Defi protocols that would bring the portfolio from its current allocation to the optimal allocation, in this case, it's allocating 20% of the portfolio to WETH, 30% to USDT, 15% to DAI, and 35% to USDC.

Over time, as market conditions change, the algorithm will monitor the portfolio and adjust the allocation accordingly to maintain the optimal balance of returns and risk.

Estimated returns and sources of yield

Source or return: Price appreciation of the underlying assets

Target ROI: ~27%

Underlying tokens and protocols:

Coins: WETH, USDT, DAI, USDC

Protocols: Optimism

Strategy pros

Optimized portfolio allocation: The MVO framework helps to determine the optimal allocation of assets in a portfolio to achieve a target risk level and return.
Risk management: By minimizing the risk for a given level of expected return, the MVO strategy helps manage portfolio risk.
Adaptive: The strategy is adaptable and can be optimized over time as market conditions change.
Efficient: The Mean-Variance Optimization strategy can help reduce transaction costs by optimizing portfolio weights and reducing the frequency of rebalancing.

Strategy cons

Reliance on Historical Data: The strategy relies heavily on historical data to calculate expected returns and covariance matrices. This means that if market conditions change significantly, the strategy may not perform as expected.
Sensitivity to Input Parameters: The strategy's output can be highly sensitive to the input parameters used in the optimization algorithm. Small changes in input values can lead to significant changes in portfolio weights and returns.

Fees

Performance fee: 15% of weekly profit (only if the strategy has generated profit); fees are deducted directly from the strategy shares each week.

If the user exits the investment strategy before the settlement day, then we calculate the difference between the current price and the price of the last settlement period and take 15% of the profit. If there is no profit, then the user does not pay performance fee.

Performance fee = [Current price - last price] * 0.15

Swap fee:

From Stables to Strategy — 0% platform fee + ~0.2% market spread
From ETH to Strategy — 0.3% platform fee + ~0.2% market spread
From BTC to Strategy — 0.3% platform fee + ~0.2% market spread
From all others to Strategy — 0.2% platform fee + ~0.2-0.8% market spread

Strategy address: https://debank.com/profile/0xf8b3b7c51364eaf4b5b996cb65dd0f1222d22c48

LP RATIO SWAPPING AND REBALANCING (RRR)

The aim of the LPRSR is to keep the ratio of multiple token pairs in different liquidity pools constant by swapping one token pair with another to bring the ratio back in line.

Full description

The algorithm allocates equal capital to ETH, rETH, and DAI pairs, with the goal of maintaining a 1:1:1 ratio. Let's say we start with an equal allocation of $10,000 to each of the three pairs, for a total of $30,000. This means we have 1 ETH, 1 rETH, and 5,000 DAI in each pair.
Monitoring the portfolio: The algorithm will continuously monitor the prices and balances of each pair on each DEX.
Detecting imbalances: If one of the pairs becomes imbalanced, say the price of rETH/ETH on Uniswap increases relative to the other pairs, the algorithm will rebalance the portfolio by selling some rETH/ETH on Uniswap and buying rETH/ETH on SushiSwap and Curve to maintain the equal allocation.
Execution of trades: Let's say the algorithm decides to sell 1 rETH/ETH on Uniswap, which is currently trading at $5,000. It will then use the proceeds of $5,000 to buy 1 rETH/ETH on SushiSwap, which is trading at $4,800, and 1 ETH or DAI on Curve, which is trading at $4,700.
Rebalancing the portfolio: After executing the trades, the portfolio will now be balanced again, with $10,000 allocated to each pair. We will now have 1 ETH, 1 rETH, and 4,900 DAI in each pair.
Repeat: The algorithm will continue to monitor and rebalance the portfolio based on price changes and imbalances across the three pairs on the three DEXs.

Estimated returns and source of yield

Rewards are earned from three sources

1. Trading fees: Each time a trade is executed, a small percentage of the trade value is charged as a fee. These fees are then distributed to liquidity providers on the platform, including the rebalancing algorithm that provides liquidity for ETH/DAI, rETH/ETH, and DAI/rETH liquidity pools.

2. Price differences between DEXs: Since DEXs are decentralized and operate independently, there can be price differences for the same token pair on different DEXs. The algorithm takes advantage of these price differences by buying on the DEX where the price is lower and selling on the DEX where the price is higher.

3. Price movements: If the prices of the tokens in the pairs being traded change, the algorithm can buy or sell to maintain the desired ratio, taking advantage of any price movements that generate profits.

Target ROI: ~48%

Underlying coins and protocols

Coins: ETH, rETH, DAI

Protocols: Uniswap, Sushiswap, Curve

Strategy pros

Low slippage: The constant product formula ensures that trades are executed at the prevailing market price, reducing slippage and optimizing return.
Transparency. Track strategy performance via on-chain analytics and understand where yields are derived (link below).

Strategy cons

Impermanent Loss: In liquidity provision on DEXs, there is a risk of impermanent loss, which occurs when the value of the two assets in a liquidity pool changes, causing the value of the pool to deviate from the value of the individual assets. This can result in a net loss for liquidity providers, especially during periods of high volatility.
Limited asset selection: The constant product formula works best when trading pairs have similar market capitalization and liquidity. This limits the range of assets that can be included in the portfolio.
Limited Availability. Investors always have the ability to exit their position in this strategy, however, availability of this position/strategy is calculated based on the liquidity within the strategy. In order to increase liquidity (and open up availability to additional investments), Algoo Strategies must add more balances to the strategy, which we plan to do regularly. Please reach out to support if you’re looking to gain exposure into this strategy.

Fees

Performance fee: 20% of weekly profit (only if the strategy has generated profit); fees are deducted directly from the strategy shares each week.

Performance fee = [Current price - last price] * 0.2

Swap fee:

From Stables to Strategy — 0% platform fee + ~0.2% market spread
From ETH to Strategy — 0.3% platform fee + ~0.2% market spread
From BTC to Strategy — 0.3% platform fee + ~0.2% market spread
From all others to Strategy — 0.2% platform fee + ~0.2-0.8% market spread

Strategy address: https://debank.com/profile/0x01061b0e90dde2a35de1687e6a48a7099169b2eb

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Last updated 5 months ago