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Understanding Bar Types

This document explains the different bar types available in Flox and when to use each one.

The Problem with Time Bars

Traditional time-based bars (1-minute, hourly, daily) have a fundamental issue: information content varies with market activity.

  • During high activity: bars pack lots of information
  • During low activity: bars contain little information (noise)

This inconsistency creates problems:

  • Indicators behave differently at different times
  • Backtests may not reflect live performance
  • Overnight gaps distort analysis

Alternative bar types address this by normalizing what closes a bar rather than when.

Bar Types Overview

Type Closes When Best For
Time Fixed time interval Traditional analysis, backtesting
Tick N trades occur HFT, eliminating time bias
Volume Notional volume threshold Volume-weighted analysis
Renko Price moves by brick size Trend following, noise elimination
Range High-low exceeds threshold Volatility-based analysis
Heikin-Ashi Fixed time interval (smoothed) Trend clarity, noise reduction

Time Bars

TimeBarAggregator aggregator(TimeBarPolicy(std::chrono::seconds(60)), &bus);

How it works: Close after a fixed time interval (e.g., 1 minute).

Pros:

  • Familiar, widely used
  • Easy to compare across instruments
  • Works with most existing tools

Cons:

  • Information content varies
  • Overnight gaps create distortions
  • Low-activity periods add noise

Use when:

  • Backtesting strategies designed for time bars
  • Comparing to external data sources
  • Building indicators that expect regular intervals

Tick Bars

TickBarAggregator aggregator(TickBarPolicy(100), &bus);  // 100 trades per bar

How it works: Close after N trades occur, regardless of time.

Pros:

  • Consistent information per bar
  • No time-based distortions
  • Better for statistical analysis

Cons:

  • Bar duration varies wildly
  • Can't easily compare across instruments
  • May produce many bars during high activity

Use when:

  • High-frequency strategies
  • Statistical arbitrage
  • Eliminating time-of-day effects

Example insight: A 100-tick bar during high volatility might span 1 second; during quiet periods, 10 minutes. But each bar represents the same amount of "market activity."

Volume Bars

VolumeBarAggregator aggregator(VolumeBarPolicy::fromDouble(1000000.0), &bus);

How it works: Close after notional volume (price × quantity) reaches threshold.

Pros:

  • Normalizes for trade size variation
  • Better represents institutional activity
  • Consistent economic significance per bar

Cons:

  • Threshold needs tuning per instrument
  • Price changes affect bar frequency

Use when:

  • Analyzing institutional flow
  • Volume-weighted strategies
  • Markets with varying trade sizes

Example: $1M volume bars on BTC might close every few seconds during active trading, but take hours overnight.

Renko Bars

RenkoBarAggregator aggregator(RenkoBarPolicy::fromDouble(10.0), &bus);

How it works: New bar only when price moves by "brick size" from previous close.

Pros:

  • Eliminates noise
  • Clear trend visualization
  • No time or volume dependency

Cons:

  • Loses timing information
  • Can miss reversals within brick
  • Gaps create multiple bricks

Use when:

  • Trend following strategies
  • Support/resistance identification
  • Filtering out market noise

Unique property: Renko bars only move one direction until reversal. A series of up-bricks means consistent upward movement without significant pullbacks.

Range Bars

RangeBarAggregator aggregator(RangeBarPolicy::fromDouble(5.0), &bus);

How it works: Close when high-low range exceeds threshold.

Pros:

  • Consistent volatility per bar
  • Adapts to market conditions
  • Good for breakout detection

Cons:

  • Can produce many small bars in trending markets
  • Range threshold needs tuning

Use when:

  • Volatility-based strategies
  • Breakout trading
  • Options-related strategies

Example: $5 range bars will close quickly during volatile periods (many bars) and slowly during consolidation (fewer bars).

Heikin-Ashi Bars

HeikinAshiBarAggregator aggregator(HeikinAshiBarPolicy(std::chrono::seconds(60)), &bus);

How it works: Uses smoothed OHLC calculations based on previous bar:

  • HA_Close = (Open + High + Low + Close) / 4
  • HA_Open = (prev_HA_Open + prev_HA_Close) / 2
  • HA_High = max(High, HA_Open, HA_Close)
  • HA_Low = min(Low, HA_Open, HA_Close)

Pros:

  • Smoother trends, easier to identify
  • Reduces noise from individual bars
  • Bullish bars always have close > open
  • Great for visual trend analysis

Cons:

  • Loses exact price information
  • Not suitable for precise entries
  • Lags behind actual price
  • Requires previous bar for calculation

Use when:

  • Trend following strategies
  • Visual trend confirmation
  • Reducing false signals in choppy markets
  • Swing trading with trend filters

Unique property: In a strong uptrend, Heikin-Ashi bars will show no lower wicks (or very small ones). Conversely, strong downtrends show no upper wicks. This makes trend strength immediately visible.

Multi-symbol support: The Heikin-Ashi aggregator maintains independent state per symbol, so a single aggregator instance can correctly handle multiple symbols simultaneously.

Choosing the Right Bar Type

Decision Framework

What matters most for your strategy?

├── Time consistency?
│   └── Use TIME bars
│
├── Trade activity?
│   └── Use TICK bars
│
├── Dollar volume?
│   └── Use VOLUME bars
│
├── Price movement?
│   ├── Trend direction → Use RENKO bars
│   └── Volatility → Use RANGE bars

By Strategy Type

Strategy Recommended Bar Type
Mean reversion Time or Volume
Momentum Time, Renko, or Heikin-Ashi
Scalping/HFT Tick
Trend following Renko, Heikin-Ashi, or Time
Volatility trading Range
Statistical arb Tick or Volume
Swing trading Time (H1, D1) or Heikin-Ashi

By Market Condition

Condition Better Choice
High volatility Range or Renko
Low liquidity Volume
24/7 markets Tick or Volume
Session-based Time
Trending Renko or Heikin-Ashi
Ranging Time or Range
Noisy markets Heikin-Ashi

Multi-Timeframe with Mixed Types

Combine bar types for better analysis:

MultiTimeframeAggregator<4> aggregator(&bus);
aggregator.addTimeInterval(std::chrono::seconds(60));   // M1 for timing
aggregator.addTimeInterval(std::chrono::seconds(3600)); // H1 for trend
aggregator.addTickInterval(100);                         // Tick for activity
aggregator.addVolumeInterval(1000000.0);                 // Volume for flow

Strategy example:

  • H1 time bars for trend direction
  • Volume bars for institutional activity
  • Tick bars for precise entry timing

Performance Comparison

All bar types have similar computational cost:

Operation Time Tick Volume Renko Range Heikin-Ashi
shouldClose() O(1) O(1) O(1) O(1) O(1) O(1)
update() O(1) O(1) O(1) O(1) O(1) O(1)

The main difference is bar frequency, not computational overhead.

Summary

  • Time bars: Traditional, familiar, but information-inconsistent
  • Tick bars: Consistent activity, good for HFT
  • Volume bars: Consistent economic significance
  • Renko bars: Noise-free trend visualization
  • Range bars: Volatility-normalized
  • Heikin-Ashi bars: Smoothed trends, noise reduction

Choose based on what your strategy needs to hold constant: time, activity, volume, price movement, volatility, or trend clarity.

See Also