Milestone map
Milestone map
3 milestones
Build a clean return series
1 week
Download real market or macro data, convert prices to returns, and check for gaps, outliers and stationarity. Every later result depends on this data being right.
Proof required
Submit the notebook that loads the data, cleans it and plots returns, with a note on gaps, outliers and a stationarity check.
What gets checked
- Real data with source and dates
- Returns, not raw prices, modelled
- Cleaning choices written down
Common mistakes
- Modelling prices instead of returns
- Silently dropping bad rows
- No data source
Powstik Guide
A clean, documented return series.
Steps
- Pick a free data source.
- Load and align dates.
- Compute log or simple returns.
- Check gaps and outliers.
- Run a stationarity test and note the result.
Template
Source: Dates: Frequency: Gaps handled: Outliers: Stationarity test result:
What gets sent back
- No source.
- Price-level modelling.
- Undocumented cleaning.
Resources
Foundationstart here
Depthgo deeper
What a verifier looks for
- Checked by the verifiers you invite to your panel (up to 3). Pick people who can judge the work, not friends.
- Check the data source and date range
- Ask why returns and not prices
You'll sign in first, then come straight back here.
Fit and test out of sample
2 weeks
Fit a baseline and one better model (for example ARIMA). Test only on later data the model never saw, using a rolling time-based split.
Proof required
Submit out-of-sample error for the baseline and your model on a time-based split, with the code.
What gets checked
- Beats or honestly fails to beat a naive baseline
- Test data strictly after training data
- Error metric stated
Common mistakes
- Shuffled cross-validation on time series
- No baseline
- Reporting in-sample fit
Powstik Guide
An honest out-of-sample comparison.
Steps
- Make a naive baseline.
- Fit your model on the early part.
- Roll forward and predict the next period.
- Compare errors.
- Say plainly if the baseline wins.
Template
Baseline error: Model error: Split method: Winner:
What gets sent back
- Shuffled split.
- No baseline.
- In-sample results only.
Resources
Foundationstart here
Depthgo deeper
What a verifier looks for
- Checked by the verifiers you invite to your panel (up to 3). Pick people who can judge the work, not friends.
- Check no future data leaks into training
- Ask how the model compares to 'tomorrow = today'
You'll sign in first, then come straight back here.
Defend the model live
1 week
Walk a reviewer through your data, model and results. They pick a new time period or asset and you rerun the test live.
Proof required
Submit the rerun on the reviewer's chosen period and the review log.
What gets checked
- Rerun works on a period you did not choose
- Limits of the model named
- Reviewer challenges answered
Common mistakes
- Model only works on the tuned period
- Reviewer only watched
- Overstating accuracy
Powstik Guide
A model that survives a new period.
Steps
- Book a session.
- Let the reviewer choose a period or asset.
- Rerun live.
- Discuss where it fails.
- Log the session.
Template
Review session log Date: Duration: Reviewer name: Reviewer role and experience: Challenge 1 (time-series model on a new period): What they asked: My answer: Challenge 2: What they asked: My answer: Change I made after the session:
What gets sent back
- No live rerun.
- No new period.
- No log.
Resources
Foundationstart here
Depthgo deeper
Masteryfor the dedicated
What a verifier looks for
- Checked by the verifiers you invite to your panel (up to 3). Pick people who can judge the work, not friends.
- Pick a new period or asset
- Ask where the model breaks
You'll sign in first, then come straight back here.
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