Systemic Docs

Name	Type	Description
First Dataset	floatarray	- Description; The first dataset typically represents a time series of values that could be a moving average (e.g., a short-term moving average like a 5-day SMA) or any other indicator used in trading.
Second Dataset	floatarray	- Description; The second dataset represents another time series of values, often a longer-term moving average (e.g., a 20-day SMA) or a different trading indicator.

Name	Type	Description
CrossOver	booleanarray	- (Bullish Crossover);

The Crossover module detects the precise moment when one data series crosses above another—a classic bullish signal in technical analysis. This simple but powerful concept underpins some of the most widely-used trading strategies in the world.

What Is a Crossover?

A crossover occurs when two lines (typically moving averages, indicators, or price vs. a reference) switch positions:

graph LR
    subgraph Before["Before Crossover"]
        A1["Fast Line: BELOW"]
        A2["Slow Line: ABOVE"]
    end
    
    subgraph Cross["⚡ Crossover Moment"]
        B["Lines Intersect"]
    end
    
    subgraph After["After Crossover"]
        C1["Fast Line: ABOVE"]
        C2["Slow Line: BELOW"]
    end
    
    Before --> Cross --> After

The module outputs True at the exact moment the first dataset crosses above the second (a bullish cross), False at every other bar where the comparison is possible, and null where it is not (see Missing Data below). For the bearish direction, use the Crossunder module.

The Mathematics

The crossover compares each bar against the last observed bar before it — call it $p$ :

\text{CrossOver}_t = \begin{cases} \text{True}, & \text{if } (A_{p} - B_{p}) \le 0 \text{ and } (A_t - B_t) > 0 \\ \text{False}, & \text{otherwise} \end{cases}

Where:

$A_t$ is the first dataset at time $t$
$B_t$ is the second dataset at time $t$
$p$ is the most recent bar before $t$ where both datasets have data

Note: This is a bullish-only signal — True only when the first dataset moves from at-or-below to above the second (standard ta.crossover semantics). A downward cross returns False; use the Crossunder module to detect it. On an uninterrupted daily series $p$ is simply $t-1$ ; across a weekend or data gap it is the last bar that actually traded (see Missing Data).

Missing Data

A missing (null) datapoint — a data gap or a closed-market slot — produces a null at the same position in the output. The signal is never faked with substitute values.

Gaps are bridged, not broken: the cross is evaluated between the last two bars that actually have data. A Friday-close-to-Monday-open cross fires True on Monday — the weekend nulls stay null, and no signal is lost.
The first bar is always null: a crossover needs a previous bar to compare against, and the window's oldest bar has none. The same applies to the first bar with data when the series starts with a gap.
Sporadic outage gaps: if data drops out mid-session, the cross is computed against the last bar before the gap, so a cross that happened during the gap surfaces on the first bar after it — delayed, never destroyed.
Live execution returns exactly one datapoint — the newest — which is null when the current bar's data is missing.

Classic Trading Strategies

The Golden Cross

Perhaps the most famous crossover strategy in equities trading:

Fast Line	Slow Line	Signal
50-day SMA	200-day SMA	Golden Cross (Bullish)

flowchart TD
    SMA50["50-Day SMA"]
    SMA200["200-Day SMA"]
    CO["Crossover Module"]
    Signal{"Golden Cross?"}
    Buy["📈 Bullish Signal"]
    Wait["Wait..."]
    
    SMA50 --> CO
    SMA200 --> CO
    CO --> Signal
    Signal -->|True| Buy
    Signal -->|False| Wait

The Golden Cross has historically preceded major bull runs in indices like the S&P 500 and Bitcoin. However, it's a lagging signal—by the time it triggers, significant price movement has already occurred.

MACD Signal Line Crossover

The MACD crossing above its signal line is a momentum-based bullish signal:

Fast Line	Slow Line	Interpretation
MACD Line	Signal Line (9-EMA of MACD)	Momentum turning bullish

RSI Centerline Cross

RSI crossing above 50 indicates momentum shifting from bearish to bullish territory.

Building a Crossover System

Here's how crossovers fit into a complete trading system:

flowchart TD
    subgraph Data["Price Data"]
        Price["Close Prices"]
    end
    
    subgraph Indicators["Moving Averages"]
        EMA12["EMA(12)"]
        EMA26["EMA(26)"]
    end
    
    subgraph Detection["Signal Detection"]
        CO["Crossover Module"]
        CU["Crossunder Module"]
    end
    
    subgraph Actions["Trading Actions"]
        Buy["🟢 Buy Signal"]
        Sell["🔴 Sell Signal"]
    end
    
    Price --> EMA12 & EMA26
    EMA12 & EMA26 --> CO & CU
    CO --> Buy
    CU --> Sell

Practical Considerations

Combining with Volume

A crossover backed by high volume is more reliable:

Scenario	Volume	Reliability
Golden Cross	High	Strong confirmation
Golden Cross	Low	Potential false signal

Avoiding Whipsaws

In sideways markets, crossovers can trigger repeatedly without meaningful price movement. Consider:

Adding ADX filter: Only take crossover signals when ADX > 25 (trending market)
Waiting for confirmation: Require the crossover to hold for N periods
Using longer timeframes: Weekly crossovers are more reliable than hourly

Cryptocurrency Considerations

Crypto markets operate 24/7 with high volatility. Crossovers on 4-hour or daily timeframes tend to be more reliable than those on shorter intervals where noise dominates.

Advantages

Simple and intuitive — Easy to understand and implement
Time-tested — Decades of use across all asset classes
Objective — No ambiguity about when a signal occurs
Combinable — Works well with filters and confirmation indicators

Disadvantages

Lagging indicator — Signals come after the move has started
Whipsaws — Frequent false signals in range-bound markets
No magnitude information — A tiny cross and a massive cross look the same
Requires context — Works best with trend filters and volume confirmation

Indicator Assessment

---
config:
  xyChart:
    width: 600
    height: 400
  themeVariables:
    xyChart:
      plotColorPalette: "#1abc9c, #e74c3c"
---
xychart-beta horizontal
    title "Bullish Crossover Assessment (Scale: 1-10)"
    x-axis ["Popularity", "Reliability", "Complexity", "Versatility", "Recent Interest"]
    y-axis "Score" 0 --> 10
    bar [10, 6, 2, 10, 7]
    bar [9, 5, 2, 10, 8]

Legend: First bar (teal) = Equities/Forex | Second bar (red) = Cryptocurrency

Dimension Explanations

Dimension	Equities/Forex	Crypto	Rationale
Popularity	10	9	The Golden Cross is one of the most famous signals in trading. Universal recognition across all platforms and trader education.
Reliability	6	5	Lagging signal that works well in trending markets but produces whipsaws in sideways conditions. Crypto volatility increases false signals.
Complexity	2	2	Extremely simple concept—does line A cross above line B? No advanced math required.
Versatility	10	10	Applicable to any two comparable series: moving averages, indicators, price vs. threshold. Works on any timeframe or asset.
Recent Interest	7	8	Remains a staple of trading education. Very popular in crypto trading communities discussing Golden/Death Cross events.

(Bullish) CrossOver

Inputs

Outputs