Swap Kapidex Hex processes large volumes of on-chain and market data to identify recurring configurations and adjust the allocation of a portfolio based on the observed risk/return pair.
Before any recommendation, the platform goes through a process structured in three stages. Each aims to reduce the amount of approximation in the analysis of cryptoasset markets.
Transaction flows, trading volumes and liquidity indicators are continuously aggregated from multiple market sources to provide a consistent basis for analysis.
Statistical models identify correlations between historical variables and price movements, without assuming a guaranteed repetition of past trends.
The results are weighted according to defined volatility constraints, which directs the distribution of assets towards a profile consistent with the stated objectives.
The tools made available are primarily used to document a decision, not to rush it.
Exposure levels are recalculated at each significant market variation, which allows a position to be adjusted before a trend takes hold.
Each strategy is compared to past market cycles, including phases of sharp decline, in order to evaluate its performance under contrasting conditions.
The key indicators are presented in a hierarchical manner, to allow quick reading without having to interpret raw data.
The results presented below come from simulations applied to historical market data. They do not constitute a guarantee of future performance.
Simplified illustration of a backtest over several market cycles. The exact values depend on the time period and risk parameters chosen.
The simulations include correction and high volatility phases, in order to verify that the optimization models maintain a logic of exposure reduction in unfavorable periods, rather than assuming continuous growth.
Cryptoassets remain volatile instruments. Past performance, simulated or actual, is no guarantee of future results. The intervention of artificial intelligence aims to mitigate certain identified risks, without eliminating them.
The following points come up most often among investors evaluating a data-driven approach.
Market data and account information is encrypted during transmission and storage. Access to scanning environments is restricted and logged, following industry standard practices.
Models are retrained at regular intervals with the most recent data, and revised more frequently when market conditions deviate significantly from observed historical regimes.
Risk parameters include volatility thresholds that trigger a gradual reduction in exposure. The objective is to limit the magnitude of losses, without claiming to completely neutralize a market movement.
No. The analyzes provided constitute data-based decision support, and do not replace the advice of an approved advisor taking into account your personal situation.
Join investors who value data analysis over intuition.