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The MTS EGBs Cash Tick-by-Tick - Historical Archive (2011 to Purchase Date) is the ultimate dataset for European Government Bonds (EGBs), delivering a fixed, tick-level repository of trading data from the MTS Cash Central Limit Order Book, spanning January 2011 up to the date of purchase. With peaks of ~100 million rows, this comprehensive archive captures every new and changed price, aggressive orders (fill-and-kill, all-or-nothing), and trade-by-trade cash fills. Key Features: Historical Daily Files: Access to 5 daily files.

Coverage: Full depth of the Order Book. Content: Includes Proposals (Complete tick-by-tick data from order book), Fills (All cash trades on trade-by-trade basis), Orders (Aggressive Orders (FAK, AON)), Bond Reference data, Market Calendar data detailing information on trading holidays. , buy on May 1, 2025, get 2011 to April 30, 2025).

Tailored for deep retrospective analysis, regulatory audits, and academic research, it enables users to explore over 13 years of billions of ticks to uncover market turnover patterns, assess historical volatility, or build robust financial models. For data beyond the purchase date, the Continuous Subscription is required. Dive into a comprehensive EGB market history with MTS’s trusted data quality.

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Intelligence Score
19/100
Your Rating
Platforms

1

Data Quality SignalsF

Freshness

Single-source

API Status

No API

33Completeness

Compliance (vendor-reported)

SOC 2
ISO 27001
GDPR
CCPA

Quality Breakdown

Data Coverage
20
Documentation
45
Compliance
0
Pricing Clarity
0

Signal Analysis

Categories

FinancialQuantitative Analysis

Listed On

snowflake_marketplace
Intelligence Scores3/7 pillars scored
Market Presence
15
Integration
20
Business Maturity
3
Extended Analytics

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About MTS

MTS is an alternative data vendor. MTS specializes in financial, quantitative analysis data. This vendor has a Vedex Intelligence Score of 19 out of 100, reflecting market presence, compliance posture, integration readiness, and business maturity.

Data Categories

MTS operates in the following alternative data categories.

FinancialQuantitative Analysis

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