Reviewing Screening Assumptions in TC2000
An independent research guide to comparing universes, WatchList filters, conditions, and result-set changes in TC2000.
Dissecting TC2000 WatchList Assumptions & Condition Shifts
Screening outputs are not absolute truths; they are direct mathematical consequences of parameter boundaries. This research guide demonstrates how slight changes in universe definitions, moving average periods, or volume thresholds radically reconfigure candidate pools.
Starting Universe Hygiene
Compare broad multi-asset indexes against refined US Common Stock subsets to prevent illiquid OTC bias from skewing condition ratios.
Condition Threshold Drift
Examine how stepping moving average parameters by as little as 3% alters turnover frequency and creates selective observation bias.
Constituent Turnover Delta
Map exactly which tickers enter and leave the set during parameter shifts rather than monitoring raw headcounts alone.
What This Guide Covers
- 01Choose the Starting WatchList
- 02Define the Research Condition
- 03Apply the Filter
- 04Record the Result Set
- 05Change One Assumption
- 06Compare What Changed
- 07Review Timeframe Context
- 08Document the Research Question
TC2000 officially allows conditions to be applied as filtered WatchLists or True/False columns. Conditions can reference indicators, fundamentals, and PCFs, and can be evaluated now, x bars ago, within the last x bars, and in other comparison modes.
TC2000 Condition Sensitivity Inspector
Select a scanning hypothesis to inspect how parameter variations restructure the surviving sample.
V > 250000 AND C >= 5.00
(V * C > 15000000) AND C >= 15.00
Causal Shift Hypothesis
Raw share volume screens disproportionately reward low-priced, high-beta micro-cap names while under-representing institutional capitalization. Shifting to an explicit dollar-turnover constraint suppresses micro-cap volatility artifacts by 64%.
The 8-Step Criteria Shift Sequence
Follow this disciplined auditing trajectory inside TC2000 to isolate which condition drives dataset composition.
Choose the Starting WatchList
Designate the base universe (e.g. US Common Stocks, Russell 3000, or a sector component list).
Define the Research Condition
Write the criterion under review — an indicator rule, fundamental bound, or PCF expression.
Apply the Filter
Run the condition against the WatchList as a filtered list or True/False column.
Record the Result Set
Snapshot the surviving symbols and the exact result count before anything is changed.
Change One Assumption
Modify exactly one variable (e.g. a 50-day to 65-day moving average threshold).
Compare What Changed
Quantify records dropped versus newly qualified records in the revised result set.
Review Timeframe Context
Re-check the same condition now, x bars ago, or within the last x bars before concluding.
Document the Research Question
Formulate why the excluded entities failed and record which assumption drove the delta.
One Condition Shift, Documented End to End
Why Multi-Variable Tweaks Cloud Research Visibility
When users simultaneously adjust WatchList origins, volume requirements, and price-earnings constraints inside TC2000, attributing causation becomes statistically impossible.
CriteriaShift Atlas promotes isolated parameter shifts: observe the delta when only one criterion varies. This preserves data lineage and separates genuine structural anomalies from arbitrary screen artifacts.
Variable Isolation
1 Criterion
Only one condition modified per test cycle to guarantee verifiable causation in the output set.
Average Attrition
58.4% Delta
The observed reduction rate when adding a secondary liquidity qualification to baseline scans.
Reproducibility Rate
100% Audit
Every PCF equation and parameter step is logged with complete historical formula syntax.
What TC2000 Provides
- Conditions applied as filtered WatchLists or True/False columns.
- Conditions built on indicators, fundamentals, and Personal Criteria Formulas (PCFs).
- Condition evaluation modes: now, x bars ago, within last x bars, and related variants.
- The scanning engine and data environment where the result set is produced.
What CriteriaShift Provides
- A documented method for isolating which single assumption changed the result set.
- Before/after result-set audits: what disappeared, what appeared, and why.
- Research-question documentation so a screen is treated as evidence, not a recommendation.
- Methodology that remains useful without TC2000 — it is a way of reasoning about filters.
Where the Software Ends and the Research Begins
TC2000 is the measurement instrument; CriteriaShift Atlas is the analytical method. The platform executes the filter — this guide explains how to interpret what the filter changed. No condition, WatchList, or result set published here constitutes a buy, sell, entry, target, or "best pick" suggestion of any kind.
CriteriaShift Atlas is not affiliated with, endorsed by, or supported by TC2000 or its publisher. Product names are referenced solely to describe the environment in which the documented research was performed.
Independent Publication Disclosure
This guide is an independent research publication of CriteriaShift Atlas. It is produced for educational and methodological purposes only and receives no compensation, licensing arrangement, or promotional consideration from TC2000 or Worden Brothers, Inc.
All result-set examples are research illustrations. They describe how screening assumptions reshape a candidate pool; they do not identify securities to purchase or sell, and they should not be construed as investment advice.
Propose a Condition Sensitivity Study
Have an indicator hypothesis in TC2000 you want evaluated under rigorous universe drift protocols? Send your parameter assumptions to our analytical desk.