DCA Bitcoin based on Risk
Build your own Risk-Based DCA strategy to mitigate risk and maximize your bitcoin accumulation.
You can't predict the market.
Neither can we.
Stress-free investing
Eliminate DCA anxiety today. Say goodbye to fear-of-peaks and missed opportunities during dips.
Start building your personal investment strategy today to maximize your Bitcoin accumulation and minimize the downsides of DCA.
What is risk?
Risk is a score between 0 and 100 that represents the current market risk.
Analyzing a universe of market factors using machine learning, our risk model successfully captures the real state of the market.
Key upgrades
Risk is your investment compass, guiding you to scale up your DCA investments in favorable conditions and scale down or exit during overheated phases – No predictions, prophecies, or complex strategies involved.
Worry less. Accumulate more.
See how simply adjusting the dollar-amount you DCA based on Risk drastically improves your BTC accumulation and final wealth.
Visit us on a desktop device for an interactive backtesting calculator where you can compare a normal DCA strategy to our dynamic DCA approach.
Testing Strategy
| % Profit | Final Wealth in Dollars | Final Wealth in BTC | Amount Invested | |
|---|---|---|---|---|
| Risk-based DCA | - | - | - | - |
| DCA/HODL | - | - | - | - |
The minds behind
Initially, the Risk Model was in our private toolbox. What began as an experiment in exploiting risk identification , rather than predicting prices, yielded impressive results.
Seeing the potential for a much wider application in finance than we initially anticipated, we felt compelled to share it with the world.
The minds behind
Axel Wikner
BA & Data Scientist
NTNU
Co-founder
Alessandro Parini
Economist
University of Basel
Co-founder
Initially, the Risk Model was our private toolbox. What began as an experiment in exploiting risk identification through classification yielded impressive results.
The Risk Model
- Real-time calculation
- Asset growth models, technical- and multivariate regression analysis
- Classification, not prediction.
- Proof of Profit verified
- Proven track record since 2021
Identify pristine opportunities, maximize your long-term BTC stack and leave complexity behind.
Our FAQ has you covered.
Multifactorial Design & Input Variables
The Risk Model is multifactorial, meaning it considers vast amount market factors and data points to compute the risk. Some key attributes include asset growth models for capturing asset-specific patterns, regression to model time and seasonality, and traditional TA metrics for price-based classification.
Self-Adjusting Mechanism
The model is self-adjusting, updating and refining itself daily as new data becomes available. This continuous improvement enhances its accuracy and confidence level over time. The algorithm is powered by a range of techniques including data analysis, statistical modeling, and automation.
Historical vs. Live Data
It’s crucial to understand that while the algorithm improves daily, the historical risk levels reflect the data shown on our live risk meter for each specific day. The model is not retrofitted or predictive; it classifies the current price on a daily basis.
Naturally, the exact mathematical components of our model remain proprietary. However, you can dive a lot deeper into its build, input variables, and other attributes in our whitepaper.
Proof of Profit (PoP) Framework
Before publishing any metrics or indicators, we subject them to our rigorous testing environment known as Proof of Profit (PoP). As a member, you gain access to detailed and interactive charts that show how our Risk Model has performed historically.
- Dataset Optimization
The first step in PoP involves meticulous dataset sourcing and comparison. We prioritize reliable and diverse datasets while mitigating challenges like multicollinearity, biased data, and potential data gaps. - Backtesting & Benchmarking
Our model undergoes extensive backtesting, benchmarked against three widely recognized trading and investing strategies: HODL, DCA, and a trend-following strategy. You can view these backtesting results in our whitepaper. - Forward-and Stress Testing
The model is subjected to various simulated scenarios and stressful environments to evaluate its resilience. This step allows us to assess how the model performs under a wide variety of future price trajectories. AlphaSquared is the only platform in the crypto space currently offering this level of forward-testing capabilities. You can inspect this approach in our Whitepaper.
The Risk Model is very intuitive to use. Put simply, the lower the risk level, the more advisable it is to buy. The higher the risk, the more advisable it is to sell.
By using our Dynamic Dollar Cost Averaging approach (DDCA), you adjust the size of your investment based on the risk level provided by The Risk Model. The lower the risk, the more you buy, and the higher the risk, the more you sell, or simply invest less. As an AlphaSquared member, you gain exclusive access to pre-configured, ready-to-use DDCA strategies tailored to various risk tolerances.
Personally, we use our Risk Model and DDCA as standalone tools. However, the risk identification provided by the Risk Model also serves as a great starting point for executing other strategies.
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