MASTER RESEARCH TAXONOMY UPDATED: AUGUST 2026 · VER 2.5

Research Programs & Working Papers

The Haldankar Method Research Laboratory investigates the complete financial data pipeline across two strictly segregated analytical domains: Downstream Human Cognitive Architecture and Upstream Machine Contextual Governance.

All working papers and monographs are presented with formal versioning, methodological status tags, estimated reading times, and explicit epistemic boundaries.

DOMAIN 01 · DOWNSTREAM INTERPRETATION

Human Cognitive Architecture

Investigating biological working memory saturation, visual distortion, and cognitive latency ($C_{loss}$) at the human interface.

[FINDING] VER 2.1 · 14 MIN READ

The 4-Chunk Biological Bottleneck in High-Frequency Execution

Mathematical formulation of working memory saturation. Demonstrates why financial terminals with over four competing variable groups induce neural waste and involuntary heuristic execution errors.

MONOGRAPH CH. 02 Read Working Paper →
[EVIDENCE] VER 2.0 · 18 MIN READ

Y-Axis Scaling Distortion & Visual Slope Bias in Trading

Empirical analysis of non-isometric charting aspect ratios. Proves that dynamic auto-scaling forces a 0.5% fluctuation to look geometrically identical to a 5.0% breakout, triggering false trend confirmations.

MONOGRAPH CH. 05 Read Working Paper →
[FRAMEWORK] VER 1.4 · 12 MIN READ

White Paper Test Theory: Document Architecture Audit

Quantitative methodology for stress-testing complex disclosures, prospectus filings, and institutional white papers to measure cognitive load, legibility, and decision clarity prior to distribution.

MONOGRAPH CH. 04 Read Working Paper →
[FRAMEWORK] VER 2.0 · 10 MIN READ

The Understanding Steps: 5-Stage Situational Awareness

A sequential progression model mapping how market participants perceive, comprehend, project, evaluate, and execute decisions under acute volatility.

MONOGRAPH CH. 01 Read Working Paper →
Actual Profit: 12-Part Digital Series
The complete serialized research monograph with interactive sidebar TOC.
Enter Digital Monograph →
DOMAIN 02 · UPSTREAM VERIFICATION

Machine Contextual Architecture (DCM)

Resolving the Silent Assumption Trap and governing financial AI outputs through explicit institutional mandates.

[PROBLEM] VER 2.2 · 16 MIN READ

The Silent Assumption Trap: Causal Pathways in LLMs

Deconstruction of statistical pattern completion in financial AI. Traces how underspecified prompts cause models to hallucinate default risk constraints while producing grammatically authoritative answers.

DCM CORE SPECIFICATION Read Specification →
[EVIDENCE] VER 2.5 · 22 MIN READ

HDFC Bank Controlled Experiment: Output Geometry

Controlled evaluation holding standardized NSE banking data invariant across 4 institutional mandates (Credit, Trading, Risk, Investment). Documents the six observable dimensions of output transformation.

EMPIRICAL DATA RELEASE Inspect Dataset Matrices →
[FRAMEWORK] VER 1.8 · 15 MIN READ

AI Epistemic Boundaries & Regulatory Fit (SR 26-2)

Aligning large language model verification with institutional model risk management standards (US Federal Reserve SR 26-2 / OCC 2011-12 and SEBI AI accountability directives).

GOVERNANCE PAPER Read Working Paper →
[LIMITATION] VER 2.0 · 12 MIN READ

Deterministic Invalidation & Decision-Blocking Unknowns

Protocol for enforcing AI model execution halts when critical situational parameters are missing, replacing plausible conjecture with explicit crimson warning declarations.

INVALIDATION PROTOCOL View Unknowns Protocol →
Decision Context Model Research Hub
Architecture, silent assumption pathways, and mandate specifications.
Enter DCM AI Hub →
02 // ACADEMIC CITATION FORMATS

Cite this Research

For academic, institutional, or regulatory research papers referencing Actual Profit or Decision Context Models:

APA Format:
Haldankar, S. R. (2026). Actual Profit: The Cognitive & Microstructural Architecture of Financial Decisions. The Haldankar Method Research Laboratory. ORCID: 0009-0000-9372-059X.
BibTeX:
@techreport{haldankar2026actualprofit,
  author = {Haldankar, Suraj Rohit},
  title = {Actual Profit: The Cognitive & Microstructural Architecture of Financial Decisions},
  institution = {The Haldankar Method Research Laboratory},
  year = {2026},
  note = {ORCID: 0009-0000-9372-059X}
}
03 // EPISTEMIC BOUNDARIES

Scientific Boundaries & Scope

[EPISTEMIC BOUNDARY & NON-CLAIMS]

The working papers published herein represent theoretical and empirical investigations in behavioral quantitative finance and cognitive systems. The laboratory does not provide commercial financial execution, trading signals, or asset management services. All empirical findings reflect the designated invariant datasets (SEC / NSE HDFC Bank).

Principal Researcher: Suraj Rohit Haldankar
Permanent Identifier: 0009-0000-9372-059X ↗
Archival Access: Publications Hub →