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earnings-alpha-llm
kevinkakkad168/earnings-alpha-llm
earnings-alpha-llm is a machine learning model from kevinkakkad168. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as llama3.1.
Fine-tuned Llama 3.1 8B for extracting quantitative signals from earnings call Q&A transcripts.
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At a glance
- License
- llama3.1
- Model type
- llama
- Access
- Public
- Created
- Jul 18, 2026
- Updated
- Jul 20, 2026
- SHA
- ada33e9b
Base models
Model card
From the Hugging Face model README
Earnings Call Alpha Extractor
Fine-tuned Llama 3.1 8B for extracting quantitative signals from earnings call Q&A transcripts.
What it does
Scores earnings call Q&A sections on two dimensions:
- Confidence score (1-10): How confident and direct is management?
- Evasiveness score (1-10): How evasive, hedging, or deflecting is management?
The mismatch between these scores and reported financial results (EPS surprise) forms an alpha signal with statistically significant IC.
Training
- Base model:
meta-llama/Meta-Llama-3.1-8B-Instruct - Fine-tuning: LoRA on Together AI
- Training data: ~2500 earnings calls labeled by Llama 3.3 70B (Groq)
- Dataset: Rogersurf/earnings-call-transcripts (9k+ calls, 2023-2026)
Backtest results
| Metric | Value |
|---|---|
| IC (5-day) | +0.076 |
| IC t-stat | +2.00 (significant) |
| Sharpe | 0.74 |
| N events | 700 |
| Period | 2023–2026 |
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
import torch
model = AutoModelForCausalLM.from_pretrained(
"kevinkakkad168/earnings-alpha-llm",
torch_dtype=torch.float16,
device_map="auto",
)
tokenizer = AutoTokenizer.from_pretrained("kevinkakkad168/earnings-alpha-llm")
pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
See the project GitHub for the full pipeline.
References
- Mayew & Venkatachalam (2012): The Power of Voice
- Li (2008): Annual report readability and earnings persistence
- Type
- llama
- License
- llama3.1
- Languages
- en
- Created
- Jul 18, 2026
- Updated
- Jul 20, 2026