Study Logic

Study Logic.

How a probability study is defined, filtered, measured, and reported. This page is for readers who want the function logic behind the research, not just the result.

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Pipeline

From raw bars to a published probability.

Every study follows the same sequence. First define the event. Then qualify it with filters. Then measure the outcome inside a fixed forward window. Finally aggregate the observations into probability, expectancy, and distribution statistics.

Define Event

Specify the session, trigger, context, and time window.

Define Conditions

Declare the structural rules that qualify the event.

Filter Data

Apply data quality, session, and exclusion filters.

Compute Outcome

Measure whether the target, stop, or other endpoint occurs.

Validate Sample

Check counts, contamination risk, and rule compliance.

Report Results

Summarize probability, expectancy, and limitations.

Function Structure

01 Identify Session Ranges

Define session boundaries and segment the dataset.

for each day D in dataset:
  for each session S in sessions:
    start = session_start(D, S)
    end   = session_end(D, S)
    bars[S] = bars where time >= start and time < end

Output: session_bars[S]

02 Detect First Break

Locate the first valid break satisfying the structural rules.

for each session S:
  ib = initial_balance(S)
  for each bar b after ib window:
    if break_condition(b, ib):
      first_break = b
      break

Output: first_break_event[S]

03 Measure Target Hit

Evaluate if and when the target is reached inside the outcome window.

for each event E:
  window = bars after E up to W
  if target_level reached in window:
    outcome[E].hit = True
    outcome[E].time = first_hit_bar
  else:
    outcome[E].hit = False

Output: target_hit[E]

04 Calculate R-Multiple

Convert the outcome into a normalized risk unit.

for each event E:
  R = (outcome_price - entry_price)
      / risk_per_trade
  outcome[E].R = R
  outcome[E].sign = sign(R)

Output: R_stats[E]

Variables and Inputs

Variable	Description	Type / Format	Example	Notes
Instrument	Financial instrument under study	String	ES, NQ, MNQ	One instrument per study
Session	Trading session definition	Time Range	RTH 09:30–16:00 ET	Must be fixed within a study
Timeframe	Bar resolution for analysis	Enum	1m, 5m, 30s	Affects sensitivity
Trigger Definition	Logic that defines the event	Rule Set	IB High Break First	See Study Rules
Outcome Window	Max forward bars/time after event	Integer / Time	120 bars / 2h	Fixed per study
Target / Stop	Profit target and risk reference	Price / ATR / Ticks	2R target / 1R stop	Relative or absolute
Filters	Qualifying rules	Rule Set	Volume > X, Spread < Y	Applied before outcome
Sample Requirements	Minimum event count	Integer	≥ 300 events	Per-study threshold

Study Rules

Sequential Only

Events are processed in chronological order with no reordering.

No Lookahead

No future data is used at any stage of identification or measurement.

Filter Before Outcome

All qualifying filters are applied before outcomes are measured.

One Event Per Context

Only the first valid event per session or context is counted.

Consistent Definition

Definitions and parameters remain fixed within a study.

Complete Transparency

Inputs, rules, and limitations are documented and reproducible.

Related Resources

Methodology

The high-level research framework, bias controls, and publishing standards.

View Methodology →

Math Notes

The probability, expectancy, and confidence interval math behind each result.

View Math Notes →

Walkthrough

A page that shows a single study being built step by step.

View Walkthrough →