Hartford Insurance Group Inc (HIG) Earning Prediction
Hartford Insurance Group Inc (HIG) is set to release its earnings performance on 01/29 16:05:00 ET in After Hours trading. Consensus forecasts predict a revenue of 5.14B and an earnings per share (EPS) of 3.17 for the . With Intellectia's exclusive AI algorithms, users can predict whether the earnings will beat or miss expectations before the report drops. Leverage this powerful tool to strategize and position your trades ahead of the earnings release!
Earnings Surprise Analysis
HIG Transcript
The earnings call reflects strong financial performance, strategic growth plans, and shareholder-friendly actions. The company reported premium growth, dividend increases, and a solid investment outlook. Despite some uncertainties, management's optimism about future growth, technology investments, and market expansion suggests a positive sentiment. The Q&A indicates confidence in managing risks and maintaining margins. Overall, these factors support a positive stock price outlook.
HIG Slides
HIG Report
Frequently Asked Questions
What is the Hartford Insurance Group Inc {quarter} Earnings Release Date and Time?
Hartford Insurance Group Inc (HIG) is scheduled to release its {quarter} earnings report on Jan 29, 2026, After Hours (approximately 4:00 PM ET). This timing allows investors to react during after-hours trading, with a conference call typically following shortly after.
What Are the Consensus Forecasts for Hartford Insurance Group Inc {quarter} Revenue and EPS?
Analysts' consensus predicts 5.14B in revenue and an EPS of 3.17 for Hartford Insurance Group Inc's {quarter}.
What Does Intellectia's AI Predict for Hartford Insurance Group Inc {quarter} Earnings?
Intellectia's exclusive AI algorithms forecast a {conclusion} for Hartford Insurance Group Inc's {quarter} earnings, with a prediction date of Jan 29, 2026. Hartford Insurance Group Inc {summary}
How Can I Use This Earnings Prediction to Trade HIG Stock?
Leverage Intellectia's AI forecast to position trades ahead of the Jan 29, 2026 release—consider calls for a beat scenario or protective puts for misses. Focus on pre-market volatility, and use the scenario probabilities to build strategies around revenue and guidance updates.
How Accurate Is Intellectia's AI for Earnings Predictions Like Hartford Insurance Group Inc {quarter}?
Intellectia's predictions are backed by rigorous backtesting, showing a high hit rate for Beat and Miss calls compared to traditional analysis. While no forecast is 100% certain, we provide probability-based scenarios (e.g., 50% chance of a *Beat*) and detailed rationales to help you make informed decisions. Combine our insights with your strategy for the best results—it's like having a co-pilot for earnings season! Empowering users to strategize trades before reports drop.
How does AI Earnings Prediction generate its forecasts?
AI Earnings Prediction uses advanced Large Language Models (LLMs) to analyze a wealth of data, including past earnings transcripts, real-time market sentiment, analyst insights, and company news from the last three months. It focuses on key indicators like revenue, EPS, and margins to predict whether a company will *Beat*, *Miss*, or remain Neutral relative to market expectations. Think of it as a super-smart analyst crunching numbers and news 24/7 to give you a trading edge!
When are the predictions available, and how often are they updated?
Predictions are generated two days before a company's earnings release (e.g., 5:00 PM ET on Feb 13 for a Feb 15 report) to capture the latest market and company data. They're updated in real-time if significant news breaks, ensuring you get fresh insights.
Can I use AI Earnings Prediction for all types of stocks?
Currently, AI Earnings Prediction focuses on companies with market caps above $40 billion, covering major players like SPG, AAPL, MSFT, and NVDA for the 2025-2026 earnings seasons. We prioritize high-impact stocks with robust data to ensure reliable forecasts. Stay tuned as we expand coverage to more companies based on user demand!
