ml4t-horizon-design skillA
ml4t-horizon-design is agent-read markdown (skill) from ml4t/skills: Choose prediction horizon by analyzing IC decay, turnover cost, and feature-horizon alignment. Use when determining the optimal lookahead window for labels..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Horizon Design
An arbitrary 1-day horizon forces daily rebalancing, which costs 2-5% annually in transaction costs. If the signal's IC peaks at 20 days, you are paying for turnover that destroys the edge.
## The Problem
The prediction horizon determines everything downstream: label construction, feature relevance, turnover, and whether transaction costs leave any alpha. Choosing it arbitrarily - or defaulting to "1 day because that is what everyone uses" - misaligns the model with the actual signal dynamics.
## The Pattern
### WRONG
```python
import numpy as np
# Arbitrary 1-day horizon - no evidence this matches the signal
labels = np.roll(returns, -1) # forward 1-day return as label
# Result: high turnover, transaction costs eat the edge
```
### CORRECT
```python
from scipy.stats import spearmanr
import numpy as np
def find_optimal_horizon(
signal: np.ndarray, returns: np.ndarray, horizons: list[int] = None,
) -> dict:
"""Analyze IC decay to find the horizon where the signal is strongest."""
if horizons is None:
horizons = [1, 2, 5, 10, 20, 40, 60]
results = {}
for h in horizons:
fwd_ret = np.full_like(returns, np.nan)
…Read the whole file at its exact version.
How to install
mdr add ml4t/skills/ml4t-horizon-design@git:20260901.c415df0mdr add ml4t/skills/ml4t-horizon-design@sha256:5e08a141f8d5c06cPin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_a5kwu2tlieu7euz2)
1 badge views in 30 days
Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260901.c415df0 latest | 2026-09-01 | c415df0 | 4,150 B | A | view · diff |
| git:20260528.303089e | 2026-05-28 | 303089e | 4,164 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (4150 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
ml4t/skills · 19 stars · license Apache-2.0 · pushed 2026-09-24 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_a5kwu2tlieu7euz2 GET https://markdownregistry.com/api/v1/resolve?ref=ml4t/skills/ml4t-horizon-design GET https://markdownregistry.com/api/v1/blob/5e08a141f8d5c06cdff79cca286315fe1c36eaa9070deb43c14bad21c85371b5
Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.