Methodology v4.2

The integrity of market research.

In the Philippine equities and global derivative markets, noise is abundant. At Manila Quant Data, we neutralize volatility through a rigorous multi-stage validation framework designed to isolate actionable intelligence from statistical coincidence.

Quant data processing environment

Signal Integrity Infrastructure

Before any quantitative model reaches our clients, it undergoes a tiered verification process. We treat quant data as a raw material that must be refined through three industrial-grade filters.

Survivorship Bias Removal

Many trading models fail because they only analyze companies that currently exist. Our datasets include delisted entities and failed symbols to ensure back-tests reflect the true historical reality of the market.

Look-ahead Protection

We strictly enforce point-in-time data timestamps. This prevents the model from "knowing" information that wasn't actually available at the moment of execution during historical simulations.

Liquidity Constraint Logic

A signal is only valid if it can be filled. Our standards include rigorous slippage and commission modeling based on real-world volume profiles of the PSE and regional exchanges.

Cross-Validation Framework

Our quant lab employs a "Walk-Forward" optimization strategy. Instead of training a model on a cherry-picked date range, we simulate how the model would have evolved and adjusted its parameters incrementally over decades of market conditions.

01

Monte Carlo Robustness

We stress-test every trading strategy by shuffling event sequences, ensuring the results aren't a byproduct of a specific sequence of returns.

02

Out-of-Sample Integrity

A significant portion of historical data is "blinded" during the development phase and only used for the final verification to prevent over-fitting.

03

Economic Correlation Scoring

We verify that our alpha signals are not merely proxies for existing macro-economic factors like inflation or interest rate swaps.

Advanced modeling suite

Our Four-Stage
Verification Pipeline

Ingestion & Cleaning

Raw exchange data is scrubbed for outliers, bad ticks, and corporate action adjustments (dividends, splits, mergers). This ensures the numerical foundation is perfectly accurate before analysis begins.

Status: Pre-Processing

Accuracy check: 99.99% data parity with direct exchange feeds.

Statistical Attribution

We decompose return streams to identify where the performance is truly coming from. Is it alpha, or just high-beta exposure to a rising sector? We isolate the skill from the noise.

Status: Attribution Analysis

Standard: Multi-factor Barra-style modeling.

Live Incubator Testing

No model is released solely on back-test results. Every signal must survive "Paper Trading" in live market conditions for a period of 90 days to verify that execution speeds and bid-ask spreads match theoretical assumptions.

Status: Forward Validation

Standard: Real-time API latency monitoring.

Peer Review & Deployment

A final council of lead quants reviews the code for logical errors and strategy decay risks. Only then is it integrated into our "Market Intelligence" dashboards for professional subscribers.

Result: High-signal data ready for institutional use.

In-Depth Methodology Inquiries

Experience the standard of precision.

Connect with Manila Quant Data to integrate our validated signals into your institutional workflow. We provide the data, you provide the conviction.

Manila Quant Data • Verification Protocol MQD-V4 • Updated March 2026