
Calibration and Brier Scores: Measuring Your Prediction Market Accuracy
Discover how calibration and Brier scores assess the accuracy of prediction markets.
- trading
- kalshi
Kalshi modeling, prediction markets, earnings mention markets, market making, and data-driven trading.
54 posts

Discover how calibration and Brier scores assess the accuracy of prediction markets.

Explore the math behind Kalshi's binary event contracts using Python.

Learn to trade US CPI markets with real-time data using macro modeling techniques.

Discover how to build a Phrase Hit-Rate Database to enhance trading strategies in earnings markets.

Explore the hidden complexities of settlement logic and its impact on trading resolution delays.

Learn how NLP techniques can help predict market outcomes from earnings calls on Kalshi.

Discover how order book imbalance provides traders an edge in Kalshi markets and the role Python plays in analyzing it.

Explore how prediction markets can hedge your crypto portfolio amidst volatility.

Discover how to provide liquidity and earn profits in Kalshi's prediction markets.

Explore strategies for selecting profitable prediction markets to enhance your trading outcomes.

Learn to leverage odds converters for identifying +EV trades in sports trading.

Explore the parallels between six-card PLO bots and prediction markets through the lens of reinforcement learning.

Learn to avoid look-ahead bias in backtesting prediction strategies to ensure accurate performance metrics.

Discover how AI agents are transforming event trading by enhancing prediction speed and accuracy.

Explore how to find and capitalize on price discrepancies between Kalshi and Polymarket.

Explore keyword extraction and sentiment scoring from earnings transcripts for actionable insights.

Explore cross-exchange arbitrage opportunities in prediction markets like Kalshi, Polymarket, and PredictIt.

Explore data sources and models for understanding Fed Funds and rate decision markets, enhancing trading strategies and risk management.

Learn how to automate trading with the Kalshi API to streamline your operations.

Explore position sizing strategies for binary options and prediction markets to enhance returns and manage risk effectively.

Explore the complexities of prediction market resolution, including delays and disputes.

Explore how prediction markets can effectively hedge equity and crypto exposure, improving risk management strategies.

Learn the differences between American and Decimal odds, and how to convert them for better sports betting decisions.

Explore how LLMs enhance market discovery by automating event extraction from news sources.

Explore how liquidity and slippage impact trading decisions and strategies in the market.

Explore probability elicitation and transform beliefs into numerical probabilities for informed trading decisions.

Discover why earnings dates are crucial for traders in phrase markets and how to incorporate them into effective strategies.

Explore the regulatory landscape and compliance challenges of prediction markets in the US.

Explore the Kelly Criterion and Fractional Kelly in prediction markets to maximize your betting strategy effectively.

Explore how real-time data feeds enhance decision-making in macro event trading.

Explore NLP techniques like ASR, diarization, and entity recognition for enhancing insights from earnings calls.

Explore the essentials of market making, focusing on bid-ask spreads and inventory risk with practical examples.

Explore market correlation and its impact on diversification and hedging strategies.

Discover how historical resolution data can enhance your trading strategies and performance evaluation.

Explore the tax implications of gains and losses in prediction markets.

Learn how to scale your quant trading strategy on Kalshi.

Explore how integrating news and social signals into trading strategies can improve decision-making and predictive accuracy.

Explore the differences between binary options and multi-outcome markets to enhance your trading strategies.

Discover techniques for feature engineering in earnings phrase prediction to enhance trading strategies.

Explore the true cost of execution in prediction markets, focusing on slippage and fees.

Explore conditional probability's role in financial markets and its importance for traders and analysts in analyzing dependent markets.

Explore the role of event contracts in portfolio theory and their impact on modeling risk and return.

Explore scraping Kalshi market pages for insights into market sentiment and pricing.

Explore how prediction markets aggregate information to outperform traditional polls in forecasting events.

Explore how earnings surprises affect stock prices pre- and post-announcement.

Learn to build a simple +EV scanner for Kalshi using Python to identify profitable trading opportunities.

Explore the principle of being 'roughly right' over 'precisely wrong' in quant trading and financial modeling.

Discover how Kalshi ensures trust in prediction markets through its handling of ambiguous outcomes.

Explore time decay and event horizon in short-dated markets, essential for effective trading strategies.

Learn how to efficiently deploy prediction models in quantitative trading.

Explore how prediction markets leverage collective wisdom to forecast outcomes and their value in various fields.

Explore phrase patterns in earnings calls between Tech and Healthcare sectors for predictive trading strategies.

Learn effective bankroll management strategies to minimize drawdowns in event trading.

Explore how APIs and webhooks enhance trading workflows with real-time market and position data.