Tareluntik combines algorithmic decision making with historically proven strategies, so you can manage investments from any time zone, without constantly monitoring the screen.
Get started nowThe platform continuously processes market, macroeconomic and business data and converts them into concrete recommendations for action. Each signal is backed by statistical analysis, not prediction based on current market sentiment.
Instead of a single general model, Tareluntik uses a set of specialized forecasting models that are benchmarked against each other and calibrated against market conditions. The result is a recommendation that considers several scenarios at once, not just one.
The system does not operate on assumptions. Each step is verifiable and documented so you can understand why the recommendation was designed the way it is.
The system combines market, macroeconomic and sector data from multiple sources into a single, structured set suitable for further analysis.
A set of statistical and machine-learned models estimate the likelihood of different outcomes, weighting the results against each other based on reliability.
Each strategy is tested on past market periods before being included in the recommendations, reducing the risk of fitting the model to a single scenario.
The purpose of the platform is not to predict the market in an absolute sense, but rather to reduce uncertainty in decision-making. Each model expresses its results as a range of probabilities, not a guarantee, allowing the user to assess the risk before making any decision.
Backtesting results are always shown together with the conditions under which they were achieved, as the same strategy may perform differently in a different market environment.
The system performs routine adjustments automatically, and manual review is only required for decisions with a greater impact on the portfolio.
Key alerts are designed for quick review on the phone, without the need to access the entire dashboard.
Because the analytics work continuously, a change in location or time zone does not affect the timeliness of recommendations.
The dashboard is designed for regular but brief checking - a summary of portfolio status, active recommendations and reasons for them are all visible on one screen.
More detailed analytics are available on demand, but not loaded by default, which reduces data consumption when working over mobile networks while traveling.
Risk is not considered after the fact, but is included in every modeling step, from strategy selection to individual position size.
When the model detects increased volatility, the system automatically suggests hedging positions that reduce exposure without completely exiting the strategy.
Each strategy is evaluated against a range of possible outcomes, not just against an average expected value, allowing for a more realistic risk assessment.
The models take into account the historical maximum decline in value and include it as a limiting parameter when making recommendations.
Recommendations consider diversification across investment classes so that risk is not concentrated in a single strategy or industry.
Join a group of investors who base investment decisions on data and proven models, not random market signals.