Markets

Forecasting works where the data have structure. Stocks have weak structure. ⸻ Weak patterns Trends break on news. Seasonality is minimal. Cycles are unstable. Autocorrelations are low. The data behave like noise. ⸻ The main drivers are outside the time series Future prices depend on what is not in the history: regulator decisions, earnings, liquidity, events, market sentiment. The time series does not contain causes. ⸻ Predictors are unknown or unpredictable It’s not enough to know the variables — you must forecast them. With stocks, that’s hard or impossible. ...

On prediction markets the key is to judge how predictable the event itself is. There are four conditions that determine this. Understanding the drivers. If the structure of the event is clear, you can assign a probability. If the factors are fuzzy, forecasting turns into guessing. Availability of data. The more data and repeatable patterns, the better. If data is scarce, the market becomes a psychological game. Similarity of the future to the past. Typical events are predictable. Unique events are almost not. ...

Polymarket is a prediction market. The stakes here are not about gambling, but about probabilities. Each market is a question about the future: elections, the economy, technology, sports, or world events. The price of a contract reflects the crowd’s probability estimate of the outcome. If a contract trades at 0.23, the market implies about a 23% chance the event will occur. The core idea is simple: when people put money on the line, they pay closer attention to information. That’s why these markets often react faster than analysts and media. ...