We aim to provide maximum transparency in all aspects of our service. This article outlines, in technical detail, the process behind our system's trading strategy.
Table of Contents
Getting started
Strategy Overview
Market Analysis Tools
Trade Execution Process
Limit Order Scaling Dollar Cost Averaging (LOSDCA) Strategy
Position Direction & Market top / bottom Indicators.
Risk Management
Understanding Derivatives
Convexity and Leverage
Counterparty Risks
Emotional Management
Legal and Regulatory Considerations
1. Getting started
The Automated trading system starts once your funds are deposited in an exchange and your trading API keys are submitted to us via the (activate bot) action.
The system then connects your account and begins executing trades based on our volatility-harnessing strategy, capitalizing on day-to-day asset price fluctuations in the cryptocurrency markets.
2. Strategy Overview
Our algorithm leverages volatility clustering theory to predict market movements through standard deviations. The strategy adjusts for both bullish and bearish conditions by aligning with broader market trends, often indicated by business cycles.
3. Market Analysis Tools
We use various indicators to gauge market conditions, including:
Liquidity cluster maps
Heat maps
Proprietary indicators
These tools help determine the optimal placement of limit orders.
4. Trade Execution Process
Initial Order:
The trade is initiated with a foundational "base" order, which is sized as a small percentage of the overall account balance.
Profit Taking and Additional Purchases:
In the event of a price increase, profits are promptly realized. Conversely, if prices go against the direction of the position, additional assets are acquired at discounted rates using the "smart sizing" limit order scaling method.
The placement of limit orders is guided by a mathematical formula derived from the previously discussed indicator readings. The distance covered to spread out these orders will depend on the specific assets being traded and the corresponding indicator values.
Rebound Sales:
Assets are sold as prices change direction, with target profit levels determined by indicator readings and overall position size.
Efficient Trade Management:
The "smart sizing" limit order scaling system is engineered to facilitate the effective management of large trade volumes while ensuring robust risk management practices. This approach employs a conservative use of leverage, (up to 1.5x) which provides users with a substantial safety net. Additionally, it allows ample time for the implementation of further risk management strategies, should the need arise.
5. Limit Order Scaling Dollar Cost Averaging (LOSDCA) Strategy
LOS-DCA (Limit Order Scaling Dollar Cost Averaging) involves systematically purchasing assets with a scaling rate applied to the order size.
This approach aims to average the purchase price as closely as possible to the current market price.
By utilizing limit orders, our system can effectively manage entry points and mitigate the impact of sudden price fluctuations.
The scaling mechanism allows for adjustments in order sizes based on market conditions, ensuring that purchases occur at various price levels. This strategy not only helps in averaging down costs during market dips but also enhances potential gains when prices rise.
Overall, LOSDCA provides a structured method for building a position over time while managing risk effectively and helps the strategy harness the market's volatility but in some occasions, requires patience as recovery times can vary.
Key points include:
Drawdowns: Periods of decline are common and should be expected.
Negative P&L: Temporary losses are part of the process, emphasizing the need for patience and continued investment.
When using LOSDCA, users should be aware that there's no guarantee the asset price will reach the "exit signal" (take-profit trigger) within a specific timeframe or at all.
Users must be comfortable with the risk of entering a position that could remain loss-making or only become profitable after an extended holding period.Important!
When it comes to derivative strategies, users should be aware that, due to convexity and leverage, there is a price at which the position will be liquidated unless additional margin is added to the account, also known as a margin call.
This accounts for both the initial margin used and the effects of convexity.At cryptobots.io, we adopt a conservative approach to risk management by limiting leverage to a maximum of 1.5x out of 125x possible.
This conservative leverage level provides approximately a 40% safety net (measured from the average price) before additional margin is required to maintain the position.
6. Position direction and Market Top & Bottom Indicators.
The strategy's direction is based on long-term market trends, using the "Pi cycle top and bottom indicator on the BTC global index" as a primary indicator.
The other two indicator the system uses to base the position direction are the Puell Multiple and the MVRV Z-Score.
The system adapts by closing current deals and switching the strategies positions direction when the time is due.
Pi Cycle Top Indicator:
Pi cycle top and bottom indicator: The Pi Cycle Top and Bottom Bitcoin Indicators are technical analysis tools used to identify potential market tops and bottoms in Bitcoin's price history.
Here's a brief history of how it was developed and its application:
Concept and Development:
The Pi Cycle Top Indicator was created by Philip Swift, a cryptocurrency analyst. It was introduced in 2019 and is based on the observation that Bitcoin's price tops have historically aligned with specific moving averages crossing over each other.
The indicator uses two exponential moving averages (EMAs): the 111-day EMA and the 350-day EMA, which is multiplied by 2 (effectively the 700-day EMA). The "Pi" name comes from the mathematical constant π (pi), approximating 3.14, which represents the relationship between the two moving averages.
Functionality:
When the 111-day EMA crosses above the 350-day EMA (times 2), it signals a potential market top. Historically, this crossover has occurred near the peak of major Bitcoin bull markets.
The indicator gained popularity because it has successfully predicted the exact top or near the top in several major bull runs, including the 2013 and 2017 cycles.
Limitations:
While the Pi Cycle Top Indicator has been accurate in predicting market tops in the past, it is not infallible and should not be used in isolation. Market conditions change, and the indicator may not always provide timely or accurate signals.
Historical Performance
The Pi Cycle Top Indicator successfully called the tops in April 2013, December 2013, and December 2017. However, it should be noted that in the 2021 cycle, it indicated a top in April, but Bitcoin continued to rise to a new all-time high in November, showing that the indicator may not always capture market nuances.
In this example, we can see how a bot continuously positioned long right until the "Pi cycle" top indicator flashed.
Right after the top is confirmed, the system then switches the positions direction to follow the overall market trend.
Pi Cycle Bottom Indicator:
Concept and Development:
The Pi Cycle Bottom Indicator is a relatively newer tool, also developed by Philip Swift. It was designed to complement the Pi Cycle Top Indicator by identifying potential market bottoms.
This indicator uses two different moving averages: the 471-day simple moving average (SMA) and the 150-day exponential moving average (EMA).
Functionality:
When the 150-day EMA crosses above the 471-day SMA, it signals a potential market bottom. Like the top indicator, this crossover has historically aligned with significant bottoms in Bitcoin's price.
Limitations:
While the Pi Cycle bottom Indicator has been accurate in predicting market bottoms in the past, it is not infallible and should not be used in isolation. Market conditions change, and the indicator may not always provide timely or accurate signals.
Historical Performance:
The Pi Cycle Bottom Indicator has been less frequently discussed but has shown promise in identifying significant lows in Bitcoin's price history, such as the 2015 and 2018 bear market bottoms.
example of a bot with a short strategy stopping after the "Pi cycle" bottom indicator flashed, followed by an example of a long strategy bot starting after the bottom flash.
Right after the bottom is confirmed, the system then switches the positions direction to follow the overall market trend.
MVRV Z-Score
Concept and Development:
The MVRV Z-Score is an on-chain metric that evaluates Bitcoin’s valuation by comparing its market capitalization to its realized capitalization, normalized as a Z-score to account for historical trends. It was developed by analysts David Puell and Murad Mahmudov to quantify how overvalued or undervalued Bitcoin is relative to its "fair value."
Market Value (MV): Bitcoin’s total market cap (price × circulating supply).
Realized Value (RV): The aggregate value of all coins at the price they last moved on-chain, reflecting the cost basis of holders.
MVRV Ratio: MV ÷ RV, showing whether the market is overpaying (ratio > 1) or underpaying (ratio < 1).
Z-Score: Standardizes the MVRV ratio by measuring how many standard deviations it is from its historical mean, making it easier to spot extremes.
This indicator leverages Bitcoin’s on-chain data to capture speculative euphoria (tops) and capitulation (bottoms).
Functionality:
The MVRV Z-Score signals potential market tops and bottoms based on historical thresholds:
Tops: A Z-score above 7-8 indicates extreme overvaluation, often aligning with bull market peaks when holders’ unrealized profits are unsustainable.
Bottoms: A Z-score below 0-1 suggests undervaluation, typically seen at bear market lows when holders are at a loss.
The indicator is calculated daily using on-chain data from sources like Glassnode or CoinMetrics. For example, a Z-score of 8 means the MVRV ratio is 8 standard deviations above its historical average, a rare and extreme event.
Historical Performance:
Tops:
2011: Z-score peaked around 7-8, aligning with the early cycle top.
2013: Hit ~8 during the April and December peaks, accurately signaling overvaluation.
2017: Reached ~9 at the $20,000 peak, one of the highest readings ever, confirming the bubble.
2021: Peaked at ~7 in April and ~6.5 in November, flagging the $69,000 top, though it was slightly early in April due to institutional buying extending the cycle.
Bottoms:
2011-2012: Dropped below 1, marking the bear market low.
2015: Fell to ~0.5, signaling the bottom around $200.
2018-2019: Hit ~0.3 at $3,100, accurately identifying the bear market low.
2022: Reached ~0.2 at $17,000, confirming capitulation.
The MVRV Z-Score has a strong track record for both tops and bottoms, though it can give early signals in complex cycles (e.g., 2021) when external factors like institutional adoption delay reversals.
Puell Multiple
Concept and Development:
The Puell Multiple, created by analyst David Puell, measures Bitcoin miners’ revenue relative to its historical average to gauge market health. It reflects the interplay between mining economics and price cycles, as miners are key sellers who influence supply dynamics.
Formula: Daily miner revenue (block rewards + fees, in USD) ÷ 365-day moving average of daily miner revenue.
A high Puell Multiple indicates miners are earning far more than their yearly average, often due to price spikes, leading to potential sell-offs. A low multiple suggests miners are under financial stress, often at market bottoms.
This indicator is rooted in Bitcoin’s unique proof-of-work mechanism, where miners’ behavior directly impacts circulating supply.
Functionality:
The Puell Multiple signals market extremes based on miner revenue trends:
Tops: A multiple above 4-5 suggests miners are earning excessive profits, often coinciding with price peaks as they sell to lock in gains, increasing supply pressure.
Bottoms: A multiple below 0.5 indicates miners are earning far less than their average, signaling undervaluation and potential capitulation.
Data is sourced from on-chain analytics platforms like Glassnode, tracking miner outflows and revenue.
Historical Performance:
Tops:
2011: Peaked around 4-5, aligning with the early cycle top.
2013: Hit ~5 during the April and December peaks, reflecting miner profit-taking.
2017: Reached ~4.5 at the $20,000 top, signaling overvaluation.
2021: Peaked at ~4 in April and ~3.8 in November, slightly early in April but still effective for the $69,000 top.
Bottoms:
2011-2012: Dropped to ~0.4, marking the bear market low.
2015: Fell to ~0.3 at $200, confirming capitulation.
2018-2019: Hit ~0.35 at $3,100, pinpointing the bottom.
2022: Reached ~0.3 at $17,000, signaling miner distress and a market low.
The Puell Multiple has been highly consistent for both tops and bottoms, though its signals can lag slightly during extended rallies driven by non-miner factors (e.g., institutional buying in 2021).
7. Risk Management
Risks in automated trading include:
Black swan events
Stable coin de-peg
Exchange counterparty risk
Regulatory changes
Security breaches
Overextension of price decline.
Mitigation strategies include diversification, thorough risk assessments, and maintaining a funded margin account.
8. Understanding Derivatives:
Derivatives offer exposure without owning the asset. cryptobots.io uses:
Inverse Perpetual Contracts/Swaps: For holding Bitcoin and buying USD-priced derivatives.
Linear Contracts: For USD collateralized trades.
Understanding the Unit of Account in Inverse Derivatives Trading:
When trading inverse derivatives contracts priced in USD with Bitcoin, Ether, or Solana as collateral, it's vital to grasp the concept of the unit of account. In this context, while the USD value of your collateral (BTC, ETH, or SOL) may fluctuate, the actual amount of cryptocurrency you hold remains constant.
9. Convexity and Leverage
Convexity, in this case, involves the relationship between futures and spot prices of the underlying asset when engaging in derivatives or swap trades.
Using Bitcoin as collateral for contracts priced in USD, can double leverage if the market moves against the trade by 50%. Cryptobots.io maintains conservative leverage limits to mitigate risk.
10. Counterparty Risks
Risks arise from exchanges and stable coins. Mitigation includes:
Using regulated, audited stable coins
Working with reputable exchanges
11. Emotional Management
The following are our recommendations to manage investment-related emotional stress:
Diversification: Consider diversifying your assets across different strategies, exchanges, assets, sectors, and asset classes. This strategy can mitigate risks and provide stability during market fluctuations. Our SPOT USD products can be part of this approach, which carries no liquidation risks.
Downsizing and Rebalancing: Reflect on the possibility of downsizing holdings you might consider heavily invested in. This involves reducing the size of your positions in assets that constitute a large portion of your portfolio. By doing so, you can mitigate the risk associated with over-concentration in a single asset or strategy.
At cryptobots.io, we understand the significant impact that emotions can have on investment decisions and overall well-being. Our commitment to transparency and your peace of mind is at the core of what we do.
Addressing the topic of emotions is important. Our objective is to provide you with a sense of security and control throughout your engagement with our service. We take any instance of emotional stress related to investments seriously, as it aligns with our goal of ensuring your well-being while engaging with our service.
In many cases, emotional reactions stem from over investment, and while managing substantial assets is a priority for us, the peace of mind of our users remains paramount—an ethos that extends to our own lives as well. This means we will always prefer that you downsize your investment and enhance your peace of mind rather than have a significant portion of your portfolio at risk.
It's not uncommon for clients to feel fear during fast-moving market moves due to a lack of comprehensive understanding of Bitcoin's historical data. This includes potential drawdown lengths and durations, their occurrence timelines, and associated probabilities throughout the market cycle.
The creators of the algorithm possess years of extensive research on this data, granting them a profound understanding that enables them to establish a strategy that boasts both safety, scalability, and performance. This strategy has been tailored to accommodate its viability in the future.
12. Legal and Regulatory Considerations
Cryptocurrency trading involves significant risk. cryptobots.io provides information and tools but does not offer personalized financial advice. Users should consult investment professionals and understand the associated risks before trading.
Do you need more information?
Explore these resources:
FAQ: Quick answers to common questions.
Setup Guide: Step-by-step instructions for new users.
Strategy Guides: Detailed explanations of our trading products.
Exchanges: Explore our supported list of exchanges.
Bot Explorer: Select and activate your preferred strategy.
API Key Guides: Learn to generate and manage API keys.
Trading Guidelines: Understand our policies and expectations.
Automated Trading Guide: Insights on mechanics and risks.
All about cryptobots.io: Learn about our company and mission.
Profit Share: Manage your earnings and payments.
Affiliate Network: Track your referrals and commissions.
My Bots: Monitor your active trades and their performance.
In-app Help: Access tutorial videos and help guides.
Glossary: Definitions for cryptocurrency and trading terms.