Project Kit / Product preview
Equity Forecasting Research Kit
A planned research kit based on my comparison of LSTM and statistical baselines for next-day forecasting across 40 NSE equities.
Explore the original project
This kit is in preparation. Explore the existing project and its documented scope below.
The problem
A complex forecasting model can appear convincing without a fair comparison against simple baselines or scrutiny of its scaling assumptions.
The approach
Explain the existing data pipeline, feature scaling and evaluation alongside Naive, Linear Regression and ARIMA baselines, including why the LSTM underperformed.
Who it’s for
Data-science learners studying time-series evaluation and reproducible model comparisons.
How it works
- Prepare the time-series inputs and inspect the scaling assumptions.
- Compare the LSTM against the statistical baselines.
- Review directional accuracy, error and out-of-range scaling behaviour.
Planned package
- Planned annotated benchmark walkthrough
- Data preparation and scaling guide
- Baseline comparison and evaluation notes
- Failure-analysis worksheet and reproduction checklist
Proposed contents; the final package will be listed at launch.
Example output / Illustrative
A benchmark that includes what did not work.
REVIEW TEMPLATE MODELS Naive / Linear Regression / ARIMA / LSTM COMPARE Directional accuracy Forecast error INVESTIGATE Do evaluation values exceed the scaler range seen during training?
A sample of the intended format, not a measured result or a screenshot of a released product.
Before you buy
Is this available now?
Not yet. This is a preview of a planned release. No payment is collected here.
Which tools will it support?
Planned for Python, TensorFlow, scikit-learn, Streamlit. Tested versions and setup instructions will be published with the release. Tool subscriptions, hosting and API usage are separate.
What about licensing and updates?
Planned usage covers personal and commercial projects, without redistribution or resale of the original package. Final license, release version and update policy will be published before checkout opens.
Is it right for a complete beginner?
This is an educational benchmark, not a trading signal or investment tool. The existing study found roughly 50% directional accuracy and 3–4× higher error for the LSTM. Public source remains available; the planned kit adds guided explanation.