Multifactorial Design & Input Variables
The Risk Model is multifactorial, meaning it considers a vast amount of 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.

Our Bitcoin model has been live since mid-2021 and has consistently shown very convincing results since. The historical data you see is not backfitted; it is the actual risk calculated on that day. You can use our strategy builder to backtest based on this real data to see performance.

In addition to real-world performance, all our models go through a 3-step framework. It involves dataset optimization, backtesting and benchmarking against other strategies, and finally forward-and stress-testing.

AlphaSquared is the only platform in the crypto space currently offering forward-testing capabilities using simulations. You can try these in the strategy builder.

No. The model does not predict what will happen in the future, as history has proven that predicting market movements is not productive. Instead, the uniqueness of it lies in its ability to tell you what is happening right now.

The model computes the current market risk with high precision. This means that whenever the market is overheated or oversold, the model will inform you. It cannot tell when in time that will occur. Being a macro model, this gives you more than enough time to either calmly DCA out of the market and take profits, or reduce your investments. This same principle also applies to major bottoms.

In short, you invest more when the risk is low, and less when the risk is high, or take profits if you wish. This earns you more BTC per dollar invested and reduces your risk. Watch tutorials in our knowledgebase.

You can follow pre-constructed strategies available in the member dashboard, or create your own strategy which is suited to your personal risk tolerance and goals.

Since the model is built for long-term gains and not for speculative trading, there’s no conflict of interest in sharing it.

Risk-Adjusted DCA is not a get-rich-quick scheme, nor is the risk model a magic buy/sell indicator that guarantees instant wealth. Instead the model helps disciplined investors with realistic time horizons improve long-term gains while reducing the emotional stress of investing.

We believe in helping other investors benefit from the same disciplined, realistic approach we've used ourselves for years.

We currently provide risk metrics for the following crypto assets:

• Bitcoin
• Ethereum
• Solana
• Cardano
• S&P 500
• Chainlink
• Polkadot
• Binance

More are being added according to our Member's votes on Telegram.