Oxido Solutions’ Ultra Low-Risk Strategy: Stabilizing Crypto for Conservative Institutions
1. Introduction
Oxido Solutions specializes in automated crypto trading bots designed for institutional clients. Our most popular offering has been a low-risk strategy for Bitcoin Perpetual Futures on Binance Futures, the leading platform for derivatives trading by volume. Many clients are drawn to this strategy for its potential of 30% + annual returns, with an annual drawdown limit between 10-15%.
However, we’ve noticed a growing demand for an even lower drawdown, especially among family offices and traditional investment groups that prioritize minimal risk. They want crypto exposure without high drawdown levels. Many hedge funds, market makers, and other institutional players are also seeking strategies with risk profiles closer to market-neutral and statistical arbitrage approaches.
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To meet these needs, we’ve developed a new ultra low-risk strategy. In this article, you’ll learn:
- What the ultra low-risk trading strategy aims to offer
- How our trading system features are optimized for ultra low risk
- A backtested annual performance overview of our ultra low-risk and low-risk strategies with FCFS
- Key metrics of the ultra low-risk approach
- Benefits of ultra low-risk for users
- Key takeaways
This analysis uses backtested data from the latest version of our low-risk and ultra low-risk trading strategy (with FCFS) on Bitcoin Perpetual Futures with USDT collateral on Binance Futures, the most extensive historical dataset we have from 2021 to the present. We plan to add comparisons from other exchanges and collateral types, like BTC, to provide a broader context as performance may vary across platforms
2. What Is the Ultra Low-Risk Strategy?
In this section, we provide an overview of Oxido Solutions’ ultra low-risk strategy for Binance Futures. Before diving into specific features and configurations, let’s look at the fundamentals: the strategy type, collateral, risk per trade, algorithms, timeframes, trade frequency, average trade duration, and rebalancing approach. This overview will lay the groundwork for the deeper analysis in the following chapters.
2.1. Trading Strategy Type
The ultra low-risk strategy is a fully automated, trend-following, scalping multi-strategy developed for Bitcoin Perpetual Futures. It combines two core trading methods: trend-following, which initiates trades based on identifiable upward or downward price trends, and scalping, which focuses on capturing smaller gains over short timeframes. The multi-strategy setup includes two strategies that hedge each other to a certain extent, each with unique algorithm and timeframe combinations. This setup is intended to capture consistent returns in trending markets while managing risk during periods of volatility or sideways price movement.
2.2. Collateral
The ultra low-risk strategy supports BTC or USDT as collateral, trading on Bitcoin Inverse Perpetual Futures when using BTC and Bitcoin USDT-Margined Perpetual Futures when using USDT. This dual collateral option allows us to serve clients seeking passive Bitcoin income, regardless of market conditions, as well as those who prefer more stable collateral, such as USDT. Although this analysis uses data for USDT as collateral, our strategy’s performance has been consistent with BTC as collateral, showing no significant differences in backtesting.
2.3. Risk per Trade in Worst-Case Scenario
Our ultra low-risk strategy for Binance Futures shares the same core structure as our low, medium, and high-risk strategies on this platform, executing the same trades across all risk levels. The primary difference lies in the risk per trade, which is lower for the ultra low-risk version.
Under typical market conditions, the risk per trade for the low, medium, and high-risk versions is 1%, 2%, and 3%, respectively, while the ultra low-risk strategy is set to 0.5% per trade (excluding slippage). Slippage refers to the difference between the expected trade price and the actual execution price, often due to volatility or liquidity issues.
To further manage capital risk during adverse conditions, our setups employ isolated margin on each trade. Isolated margin limits the maximum capital at risk for each trade, allocating only a fixed percentage of the sub-account balance to cover potential losses. This setup ensures that a pre-defined portion of the account balance remains protected, regardless of market conditions.
While we have not encountered situations where stop losses failed on Binance Futures, it’s useful to consider a hypothetical worst-case scenario. In such a case, the ultra low-risk strategy is structured to cap the maximum potential loss per sub-account at 5% of trading capital. By comparison, the caps for the low, medium, and high-risk versions are 10%, 20%, and 30%, respectively.
If a sub-account holds 500,000 USDT, the maximum loss with a 5% cap would be limited to 25,000 USDT, assuming collateral value remains stable. This structure helps protect the majority of capital, even in unfavorable market scenarios.
2.4. Algorithms
The ultra low-risk strategy relies on a dual-algorithm system to identify trades, combining Oxido Solutions’ proprietary Average True Range (ATR) algorithm and the Range Maker (RM) algorithm. This two-algorithm approach enables the system to better adapt to varying market conditions than if it relied on a single algorithm, although drawdowns cannot be entirely avoided. The ATR algorithm is best suited for handling rapid price changes, sharp zig-zag movements, quick reversals, pump-and-dump patterns, and other fast-paced scenarios. Meanwhile, the Range Maker is more effective in slower, cleaner price swings and gradual upward or downward movements.
The main component of the ATR algorithm is the widely used Average True Range (ATR) indicator, a public technical indicator that measures market volatility by averaging the true range over a set period. Using the ATR indicator, our ATR algorithm defines the probable range within which Bitcoin’s price is expected to move. The Range Maker, on the other hand, determines its price range using Oxido Solutions’ proprietary technology.
In both cases, if the price breaks out of the defined range—whether upward or downward—and this action aligns with other trading conditions, the algorithms generate a buy or sell signal. This complementary approach enables our system to capture a range of trading opportunities in different market environments.
2.5. Time Frames
Many trading strategies use common time frames like 15, 30, and 60 minutes. Oxido Solutions has found that these popular time frames can become crowded, which may lead to slower order fills or, in some cases, orders not being filled at all. This crowding can also increase slippage, which negatively impacts performance and leads to higher drawdowns. Based on our data and experience, we have concluded that our ultra low-risk trading setup for Binance performs best within a time frame range of 6 to 14 minutes.
It’s essential that each of the two individual strategies within the multi-strategy setup runs a unique combination of our two algorithms and time frames. This approach results in a more effective hedge, meaning that the two strategies can offset each other’s risks. When one strategy is exposed to potential losses due to unfavorable market conditions, the other can counterbalance it, resulting in greater profit potential and a lower average drawdown.
The table below shows the specific time frame and algorithm combinations used for each strategy. This setup minimizes the impact of market noise and increases the likelihood that trades occur in favorable conditions, helping to keep drawdowns low.
2.6. Number of Trades
The ultra low-risk strategy operates with a low to medium trading frequency, achieved through its dual-algorithm structure, broad timeframes, and other components discussed in Chapter 3. The strategy averages around 102 trades per month. On days when Bitcoin’s price action meets the trading conditions of our setup, it’s possible to see five or more trades, while there may also be several days with no trades at all.
2.7. Trade Duration
Each trade in the ultra low-risk strategy is designed for quick execution, with the average trade duration set at around 3 hours and 56 minutes. This approach focuses on small, consistent gains over short periods, reducing the chance of losses in volatile markets. By keeping trades brief, the strategy minimizes market exposure and helps prevent substantial drawdowns.
2.8. Rebalancing
To use our ultra low-risk multi-trading strategy, two Binance Futures sub-accounts are required, each funded with a minimum of 500,000 USDT or the equivalent in Bitcoin. Strategy 1 runs on one sub-account and Strategy 2 on the other. Our historical backtest data indicates that it is best to rebalance the wallet balances on these sub-accounts at the end of each month. This ensures that each new month starts with both sub-accounts holding an equal amount of capital.
For example, if Strategy 1 has a balance of 600,000 USDT at the end of the month and Strategy 2 has 400,000 USDT, the balances can be equalized to 500,000 USDT each by transferring 100,000 from Strategy 1 to Strategy 2. This rebalancing maximizes the benefits of the hedge between the two strategies, allowing for better performance.
3. Ultra Low-Risk Strategy Features
Now that we’ve covered the high-level overview of our ultra low-risk strategy, let’s dive deeper into five key features. These improvements didn’t happen overnight; each was developed in response to market drawdowns that challenged our multistrategy when it only supported low, medium and high risk. These tough times pushed us to rethink, refine, and innovate.
3.1. Dynamic Position Sizing
In 2021, we saw drawdowns ranging from 9.8% (low risk) to 25.6% (high risk), partially due to slippage. Back then, our system relied on fixed position sizes, which meant that when market volatility spiked, positions weren’t always optimally sized to handle it. This setup led to more stop-outs in volatile conditions.
To tackle this, we introduced dynamic position sizing (DPS) in late 2021. DPS adjusts position sizes in real-time based on current market volatility. When volatility is high, position sizes are reduced; in calmer markets, they increase. This adjustment minimizes slippage and helps keep drawdowns in check, making the strategy more resilient during rapid market swings.
3.2. Sideways Filter
In 2022, we faced significant choppy price action, leading to drawdowns between 8.5% (low risk) and 21.7% (high risk). This turbulence made it clear that we needed a way to avoid weak trends in sideways markets. Enter the sideways filter, developed in late 2022, which analyzes the strength of trends and detects when prices are stuck in a range. By ignoring weak trends and waiting for stronger signals, this filter reduces unnecessary trades and helps improve profitability during uncertain market conditions.
3.3. Post-Only Limit Orders
Following the previous drawdown periods, we updated our strategy in 2023 to include post-only limit orders. These orders are placed on the order book as “maker” trades rather than immediately executed against an existing order as “taker” trades. This change reduces slippage by ensuring orders only execute at the set price or better. If a price match is about to happen, the order cancels to prevent a less favorable execution. By reducing slippage and avoiding taker fees, this update improves trade efficiency and helps lower drawdowns by executing trades at optimal prices.
3.4. Double Stop Loss Mechanism
In 2023, market conditions often featured zig-zag price action with quick reversals. This setup contributed to four losing months and maximum drawdowns ranging from 9.7% to 23.3%, depending on risk level. To tackle this, we introduced a double trailing stop loss in January 2024.
A standard trailing stop loss moves with the market price, closing positions if the price reverses enough to reach the stop level. Our double trailing stop loss adds another layer of security: one stop is set closer to the market price for quick gains or loss limits, while a secondary stop is set further back to capture larger price movements without being affected by minor fluctuations. This two-tiered setup better protects profits during volatile periods, helping secure gains and reduce drawdowns.
3.5. First Come First Serve
Throughout 2024, we experienced a mix of trending and choppy price action, especially as BTC approached a new all-time high in November. To improve stability in these conditions, we introduced the First Come First Serve (FCFS) feature. FCFS expanded the timeframes for buy and sell signals from the previous narrow 8-9 minute windows to a broader range of 6-14 minutes. It also integrates two algorithms, ATR and Range Maker (RM), which now operate across different timeframes.
With the FCFS setup, trades are initiated on a first-come, first-served basis, allowing only one trade to stay open until it closes before another is initiated. This orderly trade flow, combined with a minimum 75% win rate for each trade, significantly reduces drawdowns and boosts profitability. The integration of RM also makes trades less predictable and reduces the chance of copycats, while the wider timeframe window increases trading opportunities, delivering a more stable equity curve.
4. Annual Performance: Ultra Low vs. Low-Risk
This section provides a comparative look at the historical backtest performance of our ultra low-risk strategy versus our low-risk version, focusing on annual performance and the maximum yearly drawdown observed in each case. This analysis highlights how each strategy aligns with different risk preferences, offering insights into why the ultra low-risk option may appeal to investors who prioritize return potential while aiming for minimized exposure.
| Year | Ultra Low Risk Performance | Ultra Low Risk DD | Low Risk Performance | Low Risk DD |
|---|---|---|---|---|
| 2021 | 73.83% | 1.99% | 133.8% | 4.0% |
| 2022 | 75.57% | 1.31% | 148.5% | 3.6% |
| 2023 | 55.89% | 3.59% | 94.7% | 5.6% |
| 2024 YTD | 39.74% | 3.01% | 74.4% | 5.1% |
BACKTEST
5. Other Key Metrics
To provide a clear perspective on the ultra low-risk strategy’s historical backtested performance, we’ve outlined several key metrics below. These metrics offer insights into the strategy’s simulated risk-adjusted returns, volatility, and resilience in recovering from drawdowns. Together, they illustrate why the ultra low-risk strategy may appeal to institutional investors looking for a crypto approach with a controlled risk profile. Each measure reflects aspects of stability, consistency, and effective loss management.
| Metric | Value |
|---|---|
| Sharpe | 3.99 |
| Sortino | 10.70 |
| Calmar | 3.25 |
| Avg monthly performance | 4.20% |
| Avg monthly drawdown | 1.29% |
| Beta | 0.0112 |
| Strategy volatility | 8.46% |
| Fastest recovery from drawdown | 7 days |
| Slowest recovery from drawdown | 58.5 days |
| Avg Profit Factor | 2.69 |
6. Interpretation key metrics
Here’s an explanation of what each metric indicates about the ultra low-risk strategy’s historical backtested performance and why it might appeal to institutional crypto investors like tradititonal family offices with a lower risk appetite than other types of investors:
6.1. Sharpe Ratio (3.99)
This metric indicates how well the strategy compensates investors for the risk taken, with a higher value suggesting a more favorable return-to-risk ratio. A Sharpe ratio of 3.99 is considered high, indicating that the strategy has historically delivered strong returns relative to its risk, appealing to investors focused on risk-adjusted performance.
6.2. Sortino Ratio (10.70)
The Sortino ratio, similar to the Sharpe ratio, focuses on downside risk only, ignoring positive volatility. A high Sortino ratio of 10.70 suggests that the strategy has been effective in minimizing losses, which is attractive to investors looking for consistent, stable performance with limited downside.
6.3. Calmar Ratio (3.25)
The Calmar ratio compares annualized return to maximum drawdown, with higher values preferred. With a Calmar ratio of 3.25, the strategy has demonstrated the ability to achieve returns while keeping drawdowns relatively low, which is essential for investors prioritizing capital preservation.
6.4. Average Monthly Performance (4.20%)
This metric shows the strategy’s average monthly return, indicating that it has historically achieved positive monthly performance, with an average of 4.20%. This level of consistent growth can be attractive to investors seeking reliable returns.
6.5. Average Monthly Drawdown (1.29%)
This figure reflects the strategy’s average monthly decline during down periods. An average drawdown of 1.29% implies that the strategy has kept monthly losses relatively minor, aligning with the low-risk approach that institutional investors often prefer.
6.6. Beta (0.0112)
Beta measures the strategy’s correlation to broader market movements, with lower values indicating lower correlation. A beta of 0.0112 suggests that the strategy is minimally impacted by overall market movements, appealing to investors looking for performance that’s independent of broader crypto market volatility.
6.7. Strategy Volatility (8.46%)
This metric reflects the general risk or variability in the strategy’s returns. A volatility of 8.46% indicates controlled fluctuations, showing that the strategy has been stable, which is beneficial for investors seeking to limit extreme ups and downs.
6.8. Fastest Recovery from Drawdown (7 days)
This measures how quickly the strategy has historically bounced back after losses. A recovery period of 7 days demonstrates its resilience, which may reassure investors concerned about prolonged recovery times.
6.9. Slowest Recovery from Drawdown (58.5 days)
While the slowest recovery period is 58.5 days, this metric is still within a reasonable range for many institutional investors. This demonstrates that, even in tougher periods, the strategy historically recovers in a relatively short time, highlighting its ability to manage risk effectively over time.
6.10. Average Profit Factor (2.69)
The profit factor is the ratio of gross profits to gross losses. A value of 2.69 indicates that, on average, the strategy has generated significantly more profit than loss, further reinforcing its appeal as an ultra low-risk approach with a favorable risk-reward profile.
In summary, these metrics reflect the ultra low-risk strategy’s consistent, stable performance with controlled drawdowns and resilience, making it suitable for conservative institutional investors who prioritize a balanced risk-return profile in crypto trading.
7. Strategy Comparison: Ultra Low-Risk vs. Neutral and Statistical Arbitrage
Our low-risk strategy for Binance Futures sometimes had drawdown levels that were higher than preferred by some institutional clients. In such cases, we would refer them to our quant partners, who offer market-neutral, delta-neutral, or statistical arbitrage strategies with stricter drawdown management. To address this need directly within our own offerings, we developed the ultra low-risk version.
Below is a comparative analysis of Oxido Solutions’ ultra low-risk strategy alongside commonly used market-neutral strategies, including statistical arbitrage (stat arb), market-neutral, and delta-neutral approaches. This comparison focuses on drawdowns and profit potential. The data, based on historical performance analyses, backtests, and market observations, suggests that the ultra low-risk version may offer stronger profit potential while aiming to keep drawdowns within levels competitive with other low-risk strategies.
| Strategy | Avg Yearly profit | Avg Max Yearly drawdown |
|---|---|---|
| Ultra Low-Risk Strategy | 61.26% | 2.72% |
| Statistical Arbitrage Start Arb | 10-20% | 2-5% |
| Market Neutral Strategy | 8-15% | 5-10% |
| Delta Neutral Strategy | 10-25% | 3-8% |
8. Takeaways
Oxido Solutions’ ultra low-risk strategy represents a sophisticated, low-volatility approach to trading Bitcoin Perpetual Futures on Binance. It is tailored to meet the needs of institutional clients who prioritize capital preservation while pursuing steady returns. Here are the key points to keep in mind:
7.1. Balanced Profit and Drawdown
The ultra low-risk strategy aims to deliver potentially high returns—targeting an average annual profit of 61.3%—while maintaining maximum yearly drawdowns around 2.7%. This balance may offer a profitable solution for clients seeking low-risk crypto exposure, though outcomes are not guaranteed.
7.2. Comprehensive Risk Management
Using isolated margin, dynamic position sizing, and a double stop-loss mechanism, the strategy aims to actively manage capital risk. This risk management structure seeks to safeguard capital from extreme market scenarios, providing reassurance to clients focused on stability. However, while these measures are intended to reduce risk, they do not eliminate it.
7.3. Multi-Algorithm Hedge for Stability
By employing two algorithms (ATR and Range Maker) and varying timeframes, the strategy seeks to hedge against diverse market conditions. This approach is designed to balance gains and losses, providing potential protection against rapid market changes,
7.4. Precision Execution and Minimal Slippage
The use of post-only limit orders minimizes slippage, allowing trades to execute at intended prices. This feature is particularly advantageous in high-volume scenarios, enhancing trading efficiency and potentially reducing unnecessary drawdowns.
7.5. Reduced Vulnerability to Copying
The unique combination of algorithms, timeframes, and the FCFS feature provides additional measures to reduce the risk of replication by other trading bots, helping to keep the strategy exclusive for Oxido’s clients.
7.6. Seamless Portfolio Integration
Designed to complement a wide range of low-risk strategies, including market-neutral and delta-neutral approaches, the ultra low-risk strategy may add diversified value to institutional portfolios without overlapping existing risk profiles..
This strategy demonstrates that while crypto markets can be volatile, it is designed to manage risks through advanced algorithms, strategic configurations, and sophisticated technology. The ultra low-risk approach may suit institutional clients who seek a structured and lower-risk method of gaining exposure to crypto, with the potential for favorable returns.
9. DISCLAIMER
The information and opinion provided in this blog is for general purposes only and should not be considered as specific financial advice or recommendations for any individual, exchange, security, or investment product. No rights can be derived from the live performance, backtest data, or any other data mentioned in this blog. Remember, past performance is not a guarantee of future results.
