How Oxido Solutions’ Market Situation Detector May Mitigate Less Favorable Market Conditions
1. INTRODUCTION
The crypto market moves fast, and building an algorithmic trading strategy that can handle significant capital while withstanding all market conditions isn’t something you can figure out by reading a book. It takes hands-on experience, and live trading is where you find your edge.
In our blog, “The Evolution of Our Trading Strategy,” we dive into how periods of drawdown have driven continuous improvements to our trading setups and IT infrastructure. Over time, we’ve seen a clear reduction in both the average monthly drawdowns and the frequency of larger drawdowns. However, there’s always room for improvement—something made particularly clear by the performance during the fall seasons of 2023 and 2024.
The drawdowns we experienced during these periods pushed us to develop a new innovation: the Market Situation Detector (MSD). It has been an integral part of our live trading strategies since December 6, 2024.
In this blog, you’ll learn:
- How our trend classification system kickstarted the MSD
- The key changes we’ve made to address problem areas
- The Interaction between the MSD, our Sideways Filter and Double Trailing Stop Loss (DTSL)
- What specific issue the MSD resolves
- How this improvement strengthens the hedge within our multi-strategy approach
- A comparison of price action with and without the MSD
- Backtest results of the MSD during challenging periods versus live performance
This blog features data from the low-risk version of Bitcoin Perpetual Futures USDT-margin on Binance Futures, our most popular trading strategy. It includes historical live data and backtest results with the MSD. We’re also planning to include comparisons from other exchanges and collateral types, such as BTC, to give a broader perspective on how performance can differ across platforms.
2. How Our Classification System Sparked the MSD
At the start of 2024, we began analyzing Bitcoin’s price movements and market conditions, which led to the creation of a Trend Classification System (TCS). This system allows us to identify and classify price movements across any asset class. Through the TCS, we discovered that our Bitcoin Perpetual Futures trading strategies perform well in seven out of ten classified price conditions:
- Flag and Pennant Pattern
- Weak Trend
- Extreme Move
- Zig-Zag Move
- Mixed Volatility
- High Volatility Choppy
- Whipsaw Move
However, the setup often struggles with strong trends, range-bound price action, and periods of consolidation. These findings, detailed in our use case, gave us clear insight into where the strategy could improve. With a better understanding of the pain points, we had a focused area to work on.
3. What is the MSD?
The MSD is a technical indicator designed to analyze and classify Bitcoin market conditions. Its main goal is to determine whether these conditions are favorable or less favorable for our trading strategies. To do this, the MSD evaluates key metrics such as volatility (how much prices fluctuate), velocity (the speed of price changes), and the frequency of specific trend patterns in Bitcoin.
Operating on a daily time frame, the MSD identifies broader market conditions and translates this information into actionable insights. These insights are then fed into our trading strategies, which operate on lower time frames, to refine the precision and quality of their trading signals.
3.1. Dynamic Sensitivity Range
One of the core functions of the MSD is to classify Bitcoin’s market conditions within what we call a Dynamic Sensitivity Range (DSR). This range spans a spectrum of sensitivity, allowing the MSD to account for the variability and nuances present in market conditions. It’s important to note that the DSR does not predict outcomes with certainty but rather provides a probabilistic framework to guide strategic adjustments.
For example, the MSD doesn’t just identify whether the market is zig-zagging, whipsawing, or consolidating—it also evaluates the intensity of these phases. Within the 10 defined market conditions, factors such as volatility (the magnitude of price changes), velocity (the speed of price movements), and trend patterns can range from mild to extreme. By mapping these conditions along a sensitivity spectrum, the MSD captures the breadth of market dynamics while recognizing that variations within each condition can significantly influence performance.
This structured approach provides a more granular understanding of market behavior. It enables strategies to adjust their sensitivity dynamically in response to real-time conditions, optimizing how each strategy interacts with the market. While this method aims to reduce the likelihood of less favorable trades and capitalize on opportunities, it’s important to emphasize that no system can completely eliminate risks or ensure profitability under all circumstances. The DSR’s purpose is to provide structured adaptability rather than guaranteed outcomes.
3.2. A High-Level Filter for More Adaptive Strategies
In simple terms, the MSD acts as a high-level filter designed to enhance how our trading strategies interact with the market. By leveraging the insights derived from the DSR, the MSD helps ensure that trading signals are aligned with the nuances of current market conditions. This alignment aims to reduce unnecessary exposure to less favorable environments while maximizing the potential to capitalize on favorable ones.
The MSD’s ability to tailor signals to specific market nuances does not guarantee successful trades in every scenario. Instead, it works as a probabilistic filter, guiding our strategies toward conditions where they historically perform better. This differentiation between favorable and less favorable environments, based on the MSD’s classifications, allows for more calculated decision-making.
The MSD’s integration also supports strategic adaptability. For example, during periods of strong trends, the MSD can fine-tune the inputs for our multi-trading strategy to react more efficiently. Conversely, in periods of consolidation or high volatility, the MSD can prioritize stability by delaying entries or tightening filters.
4. Core features empowered by the MSD
The MSD integrates with three essential features in our trading system: the sideways filter, dynamic position sizing (DPS), and our double trailing stop loss (DTSL). Together, these tools form the core of our trading strategy, and the MSD may enhance their functionality with logic that adapts dynamically to different market conditions. To understand how the MSD may improve our system, it’s important to understand the role of each of these features.
The DPS was introduced in late 2021 to address significant drawdowns caused by slippage. At the time, our system used fixed position sizes, which made it vulnerable to sudden spikes in market volatility. High volatility often led to frequent stop-outs, while low volatility prevented optimal use of capital. DPS resolved this by adjusting position sizes in real-time based on market conditions. When volatility increased, DPS reduced position sizes to mitigate risk, and when markets calmed, it allowed for larger positions, improving performance during stable conditions. This innovation helped reduce slippage and made the system more resilient to sudden market swings.
In 2022, prolonged periods of choppy price action posed a new challenge. These sideways movements resulted in unnecessary trades that led to significant drawdowns. To counter this, we developed the sideways filter, a technical indicator designed to detect and filter out weak or directionless price movements early. By avoiding trades during uncertain conditions and waiting for stronger signals, the sideways filter improved profitability and reduced the noise from erratic price action.
Fast forward to 2023, when zig-zag price action and quick reversals created additional challenges. These market conditions contributed to significant drawdowns over several months. To address this, we introduced the double trailing stop loss (DTSL) in January 2024. Unlike a traditional trailing stop, which adjusts to the market price but is prone to being triggered by minor fluctuations, the DTSL uses two stops: one closer to the market price for capturing quick gains or limiting losses, and another further away to secure profits from larger price movements. This two-tiered setup added a layer of protection, ensuring trades weren’t prematurely closed while still locking in profits effectively.
5. How the MSD May Enhance These Features
The MSD builds on these three features, potentially making them smarter and more adaptable. With DPS, position sizing previously relied solely on market volatility, which was effective but limited in scope. The MSD now adds a layer of market favorability analysis. In favorable conditions, it allows for larger positions to maximize returns. In less favorable conditions, smaller positions are used to minimize exposure. Importantly, consistent trade risk levels remain in place, with fixed limits of 1% for low risk, 2% for medium risk, and 3% for high risk, excluding slippage.
The sideways filter also benefits significantly from the MSD. In strong trending markets, the MSD prompts the filter to signal entries more quickly, ensuring trades capitalize on favorable momentum. In slower markets, such as during consolidation phases, the MSD makes the filter wait for additional confirmation, improving the alignment of trades with market conditions and reducing unnecessary entries.
Similarly, the DTSL gains additional flexibility through the MSD. In strong trends, the MSD adjusts the stops more aggressively to secure profits as the price moves favorably. During slower price action, the stops are adjusted more cautiously, allowing trades to mature without being prematurely closed by small fluctuations.
By integrating the MSD into these three features, our system has become significantly more dynamic and responsive to market conditions. While the MSD doesn’t eliminate all drawdowns, it may greatly improve the system’s ability to navigate challenging environments and maintain consistent performance. The result is a trading strategy that could be more resilient, efficient, and capable of adapting to the dynamic order books of Bitcoin Perpetual Futures.
6. Comparing Price Action With and Without the MSD
By now, you have a clear understanding of what the MSD is and how it’s designed to work in theory. But how does it perform in practice?
Our trading system is based on a multi-strategy approach, with each system comprising two separate strategies: Strategy 1 and Strategy 2. Both strategies generate signals using unique combinations of our ATR and Range Maker algorithms, each operating across different lower time frames.
The example below provides a visual representation of how the ATR-based version of our strategy functions. While the example focuses on ATR, the same principles apply to the Range Maker version.
6.1. Example 1
On the left side of the illustration, you’ll see the new MSD setup. On the right, the old setup is displayed for comparison. This side-by-side view highlights the improvements introduced by the MSD and its impact on signal generation. The new setup has already entered the position and locked in profits, while the old setup is just getting ready to place its long order.
6.2. Example 2.
In this example, the new setup enters the short trade one bar earlier, securing a better entry. It takes profit, opens another position, and wins that trade as well. On the right side, the old setup completes just one trade.
LIVE DEMO
7. How the MSD May Enhance Multi-Strategy Hedging
In trading, hedging is a risk management technique that involves using one strategy or position to offset potential losses in another. When market conditions favor one approach over another, hedging ensures that the underperforming strategy doesn’t drag down the system as a whole. This balance creates a safety net, reducing the likelihood of significant losses during unpredictable or challenging market environments.
Hedging is especially important in multi-strategy systems like ours. Instead of relying on a single approach to succeed in all market conditions—a nearly impossible task—hedging allows different strategies to focus on distinct market behaviors. This diversification increases the chances of consistent performance, even during periods of high volatility or uncertainty.
7.1. MSD Backtest Analysis Challenging Months
Backtesting the MSD-powered version of our multi-strategy system showed potential improvements in overall performance, particularly when Strategy 1 and Strategy 2 were fine-tuned to operate within slightly different parts of the sensitivity range. Strategy 1, adjusted to be less sensitive, focuses on smaller but more consistent wins, minimizing reactions to market noise. On the other hand, Strategy 2, tuned to a higher sensitivity, aims to capture larger moves, though this comes with slightly increased exposure to short-term risks.
By leveraging the MSD’s data in distinct ways for each strategy, the two approaches “claim” different portions of the sensitivity range. This diversification helps the system respond more effectively to the nuanced shifts in market conditions, improving the likelihood of success across varied scenarios.
Analysis of the 10 most challenging months in the MSD-powered system revealed that in 50% of cases, the hedge between the two strategies turned a losing month for one or both into an overall positive outcome. The assumption here is that the portfolios in Strategy 1 and Strategy 2 are equally rebalanced at 00:00 UTC on the last day of the month, since this approach provides the best overall performance. So, if at that time Strategy 1 is valued at 300,000 USDT and Strategy 2 is valued at 200,000 USDT, both accounts should be adjusted to 250,000 USDT each.
Refer to the table below for more details:
| Month | Strategy 1 | Strategy 2 | Combined Performance |
|---|---|---|---|
| 01-2021 | 0.85% | -0.25% | 0.30% |
| 04-2021 | 2.28% | -1.86% | 0.21% |
| 10-2022 | 1.42% | -1.03% | 0.19% |
| 02-2023 | -0.04% | -1.20% | -0.62% |
| 05-2023 | -2.16% | -0.60% | -1.38% |
| 09-2023 | -1.45% | -0.64% | -1.05% |
| 10-2023 | 7.52% | -0.54 | 3.49% |
| 11-2023 | -0.77% | 3.25% | 1.24% |
| 06-2024 | -4.05% | 1.62% | -1.21% |
| 11-2024 | -1.79% | -0.85% | -1.32% |
This may represent a notable improvement over the prior version of the system, where Strategy 1 generally outperformed Strategy 2 over the past two years. The MSD-powered setup appears to create a stronger hedge, potentially allowing the strategies to collaborate more effectively in managing risk and seizing opportunities.
Driven by the MSD’s Dynamic Sensitivity Range, this setup offers increased adaptability, which may help the system navigate market uncertainties with greater assurance. By strategically dividing the sensitivity range between two complementary strategies, the system becomes more versatile and resilient in a broad spectrum of market conditions.
7.2. Autumn Performance MSD VS Live
For the past two years, autumn has been the most challenging season for our multi-strategy system. However, as shown in the table below, the MSD-powered version may significantly outperform the current setup during this period.
| Month | Old | MSD |
|---|---|---|
| 09-2023 | -3.08% | -1.05% |
| 10-2023 | 7.39% | 3.49% |
| 11-2023 | -8.18% | 1.24% |
| 12-2023 | 0.94% | 6.30% |
| 09-2024 | 0.64% | 2.69% |
| 10-2024 | -5.15% | 1.22% |
| 11-2024 | -2.79% | -1.32% |
The ability to accurately detect market conditions and adjust how the sideways filter, DPS, and DTSL are fed for Strategy 1 and Strategy 2 seems to make a noticeable difference. By fine-tuning these inputs, the MSD creates a more adaptive system that may handle the unique challenges of autumn market dynamics far more effectively.
8. Takeaways: Why the MSD May Represent a Key Improvement
The MSD has the potential to become a key improvement in enhancing the performance and resilience of our trading system. While no trading system is guaranteed to perform consistently under all conditions, here are the key observations from its implementation:
A. Improved Performance-to-Drawdown Ratio
The MSD has demonstrated the potential to improve the balance between performance and risk. By classifying market conditions more accurately and adjusting how our strategies operate within the sensitivity range, the system seeks to achieve better results with fewer drawdowns. This structure aims to help our strategies capture more opportunities while mitigating losses during challenging periods.
B. Smarter Trade Filtering in Volatile and Consolidating Markets
A major benefit of the MSD is its ability to filter out unnecessary trades during high-volatility or consolidating markets. By providing targeted inputs to the sideways filter, DPS, and DTSL, the MSD focuses on quality over quantity, resulting in fewer but more profitable trades.
C. Enhanced Hedging Between Strategies
The MSD has strengthened the interaction between Strategy 1 and Strategy 2. By fine-tuning each strategy to target different parts of the sensitivity range, they now complement each other more effectively. In backtesting, this improved hedge turned a losing month into an overall positive outcome in 50% of the most challenging months. This synergy delivers greater consistency across a wide range of market conditions.
D. Better Handling of Tough Market Periods
Autumn has historically been the weakest season for our multi-strategy system. However, the MSD shows potential to improve performance during this challenging period. By adjusting inputs for Strategy 1 and Strategy 2, the system may perform better in these conditions. This adaptability aims to improve results without compromising performance during more favorable periods.
E. Not a Magic Fix, But a Big Step Forward
While the MSD isn’t a magic fix that eliminates all drawdowns, it addresses long-standing weaknesses in our system. The 3 out of 10 market conditions that previously caused issues—such as range-bound price action and consolidation—may now be much better managed. This improvement creates a more resilient and well-rounded trading system capable of navigating various market challenges.
9. Disclaimer
This blog is intended for informational, educational and entertainment purposes only. It provides insights into our proprietary trading strategies, including the MSD, and its implementation within our multi-strategy trading system. However, the content should not be interpreted as financial advice, investment advice, or an endorsement of any specific trading strategy or system.
A. No Guarantee of Future Performance
The performance data, examples, and backtest results presented in this blog are based on historical data and specific assumptions. Past performance is not indicative of future results. While the MSD and our multi-strategy system aim to improve risk management and enhance trading outcomes, all trading involves inherent risks, including the potential for significant financial loss. There is no guarantee that the strategies or techniques discussed will be successful in all market conditions.
B. Assumptions and Limitations
The results shown in this blog are based on specific backtesting parameters and market conditions, which may not reflect real-world trading scenarios. The blog assumes accurate and complete market data; however, market conditions are subject to rapid and unpredictable changes. These changes may affect the applicability and effectiveness of the strategies and systems described.
C. Risk Disclosure
Trading cryptocurrencies, including Bitcoin, and engaging in algorithmic trading strategies, involves substantial risks. These risks include, but are not limited to, market volatility, slippage, technology failures, regulatory changes, and liquidity issues. Traders should only invest funds they are willing and able to lose. The strategies discussed herein are not suitable for all investors and should be employed only after careful consideration of individual financial circumstances and risk tolerance.
D. Proprietary Systems and Intellectual Property
The MSD, Trend Classification System (TCS), and other trading innovations referenced in this blog are proprietary to our organization. Unauthorized use, reproduction, or dissemination of this intellectual property is strictly prohibited. This blog does not grant any rights to use or implement these concepts and systems outside of our proprietary framework.
E. Forward-Looking Statements
Certain statements in this blog may constitute forward-looking statements or reflect our expectations of future outcomes. These statements are based on our current understanding and assumptions, which may change over time. Actual results may differ significantly from those expressed or implied in the blog.
F. No Professional Advice
This blog does not constitute legal, financial, tax, or other professional advice. Readers are encouraged to seek independent professional advice tailored to their specific needs before making any investment or trading decisions.
G. No Liability
Our organization and its representatives expressly disclaim any liability for any loss or damage, including, but not limited to, direct, indirect, incidental, or consequential losses, arising from the use or reliance on the information presented in this blog. This disclaimer applies even if such losses are foreseeable or if we were advised of the possibility of such damages.
H. Compliance
The content in this blog is prepared in compliance with applicable laws as of the date of publication. Readers are responsible for ensuring that any trading activities they engage in are compliant with the laws and regulations in their respective jurisdictions.
By reading this blog, you acknowledge and agree to the terms of this disclaimer. If you do not agree, you should not rely on or act upon the information provided in this blog.
