Direct Answer

Algorithmic traders use a combination of real-time tick data, historical datasets, order book depth, and execution-quality data to build, test, and run strategies.

The specific mix depends on strategy type. High-frequency systems need microsecond-precision tick data and full depth of book. Longer-horizon strategies rely on cleaned historical data and may incorporate fundamental inputs.

NxCore provides the core data stack for algorithmic trading: tick-level real-time feeds, 20+ years of historical archives, and order book depth – all in one normalized format.

Why Data Selection Matters

The type and quality of data you choose directly affects strategy performance.

Choosing the wrong granularity is a common mistake. A tick-sensitive execution algorithm built on minute bars will fail. A weekly momentum strategy processing tick data is overengineered.

Match data to strategy requirements. NxCore’s single format across granularities and asset classes simplifies this alignment.

Core Data Types for Algorithmic Trading

Data Type What It Contains Primary Use Case
Real-time tick data Every trade and quote live Signal generation, execution
Historical tick data Archived tick records Backtesting, model training
Level 2 / order book Multiple price levels with size Liquidity analysis, execution
Trade prints Executed transactions Volume analysis, trade flow
Corporate actions Splits, dividends, mergers Price adjustment, survivorship
Reference data Symbol metadata, exchange codes Normalization, identification
Execution data Fills, slippage, latency TCA, execution quality

 

Most algorithmic traders work with multiple types simultaneously. A single strategy might use historical ticks for development, live ticks for signals, and depth for execution.

How NxCore Supports Algorithmic Trading

NxCore provides the complete data stack:

  •       Real-time tick data – all U.S. equities, options, futures
  •       Historical tick data – 20+ years, same format as live
  •       Order book depth – full Level 2 from supported exchanges
  •       Corporate actions – splits, dividends applied
  •       Reference data – symbol mapping, exchange codes
  •       Single format – consistent across all asset classes and time periods

One integration covers research, backtesting, and production.

Data Requirements by Trader Type

Trader Type Essential Data Why It’s Needed
HFT / Market making Tick + full Level 2 + microsecond timestamps Execution in microseconds, queue position matters
Intraday quantitative Tick + 1-second bars + depth Signals depend on spread dynamics
Statistical arbitrage Historical + real-time tick + corporate actions Pair relationships need calibration and live monitoring
Execution algo developer Depth + trade prints + latency metrics Fill quality requires order book understanding
Swing / position Daily bars + corporate actions Longer holding reduces tick needs

 

NxCore covers all these use cases with one data source.

NxCore vs. Assembling Multiple Data Vendors

Approach NxCore Multiple Vendors
Integration effort Single API Multiple APIs, formats
Format consistency One schema Normalization required
Asset coverage Equities + options + futures Often separate vendors
Historical + live alignment Same format Format mismatches common
Pricing Flat fee Multiple contracts
Vendor management One relationship Multiple relationships

 

Assembling data from multiple vendors introduces format mismatches, timestamp inconsistencies, and integration overhead. NxCore provides a unified solution.

Real-World Example

A statistical arbitrage fund trading correlated ETF pairs needs:

  •       Historical tick data – identify mean-reversion relationships across thousands of pairs
  •       Real-time tick data – detect spread deviations triggering live signals
  •       Level 2 depth – assess liquidity before entering positions
  •       Corporate actions – adjust for ETF rebalances and distributions
  •       Execution data – measure slippage and refine execution

With NxCore, the fund accesses all of this through one integration. Historical and live data use identical formats – backtests directly transfer to production without format conversion.

Common Mistakes

  •       Using bar data for tick-sensitive strategies – minute bars hide spread dynamics
  •       Ignoring timestamp precision – second-level timestamps corrupt signal logic
  •       Not adjusting for corporate actions – splits create false signals
  •       Mixing data sources without normalization – format differences cause errors
  •       Underestimating Level 2 importance – strategies ignoring depth face worse execution
  •       Using survivorship-biased history – inflates backtest returns
  •       Overengineering data for strategy needs – daily strategies don’t need nanosecond data

Frequently Asked Questions

Do all algorithmic traders use tick data?
 Most do for intraday strategies. Longer-horizon strategies can use bars. NxCore provides both granularities in consistent format.

Is Level 2 data required for all strategies?
 No. It matters for strategies depending on liquidity or order book dynamics. NxCore provides Level 2 for users who need it.

Can I build profitable strategies with only minute bars?
 Yes, for swing or position strategies. Anything trading frequently or reacting to spreads needs tick data.

What’s the difference between historical and real-time data?
 Historical is archived and cleaned. Real-time is live. NxCore provides both in the same format – backtests match production.

How do I handle data from multiple exchanges?
 Normalize into consistent format. NxCore does this automatically – one format for NYSE, NASDAQ, OPRA, CME.

What to Do Next

Identify your strategy type and match it with appropriate data granularity.

NxCore provides the complete stack – tick data, depth, history, corporate actions – in one format. Research, backtesting, and production use the same data source.