Publikationen
Forschung zu KI-Agenten, Backtesting und Prüfung von Marktprognosen sowie zur Architektur der Plattform.
In Wahrscheinlichkeiten denken
Ignoring how often something usually happens is one of the most common forecasting mistakes. What the base rate fallacy is, the classic example, and how good forecasters avoid it.
3 Min. Lesezeit5 Abschnitte
In Wahrscheinlichkeiten denken
A forecast becomes useful only when you compare its probability to a price. Here is how expected value works, why positive EV is never a promise, and the calibration it depends on.
4 Min. Lesezeit5 Abschnitte
In Wahrscheinlichkeiten denken
A prior is your starting belief before new evidence arrives. What priors are, why they make or break forecasts, and how to build one — explained in plain English with football examples.
4 Min. Lesezeit6 Abschnitte
In Wahrscheinlichkeiten denken
Learn what a prior is in Bayesian forecasting, how it shapes predictions, and why it matters for AI-driven market analysis. Jargon-free explanation.
7 Min. Lesezeit8 Abschnitte
In Wahrscheinlichkeiten denken
Volatility and risk are not the same thing. Understanding the difference can change how you think about markets, decisions, and uncertainty itself.
8 Min. Lesezeit8 Abschnitte
In Wahrscheinlichkeiten denken
Learn how professional forecasters use Bayesian thinking, signal filtering, and calibration to update beliefs with new data — and why it matters in markets.
7 Min. Lesezeit9 Abschnitte
In Wahrscheinlichkeiten denken
Learn how to read probability distributions in markets — from bell curves to skew and fat tails — and use them to make more structured, informed decisions.
8 Min. Lesezeit8 Abschnitte
In Wahrscheinlichkeiten denken
Forecasting and prediction are not the same thing. Learn the critical distinctions and why they matter when evaluating AI tools in financial markets.
7 Min. Lesezeit10 Abschnitte
In Wahrscheinlichkeiten denken
Understand frequentist vs Bayesian probability — two frameworks for reasoning under uncertainty, and why the difference matters in AI and markets.
8 Min. Lesezeit8 Abschnitte
In Wahrscheinlichkeiten denken
Risk and uncertainty are not the same thing. Learn the Knightian distinction, why markets conflate them, and what it means for AI-assisted decision-making.
7 Min. Lesezeit8 Abschnitte
In Wahrscheinlichkeiten denken
Markets generate endless data. The challenge is knowing what matters. Signal vs noise in market data — and why transparency changes everything.
8 Min. Lesezeit8 Abschnitte
In Wahrscheinlichkeiten denken
Learn the most common cognitive biases that distort market decisions and how awareness combined with systematic thinking can help you act with clearer judgment.
7 Min. Lesezeit6 Abschnitte
In Wahrscheinlichkeiten denken
Most traders think in outcomes. The best think in probabilities. Learn the mental framework that separates disciplined decision-makers from the rest.
8 Min. Lesezeit7 Abschnitte
