Indicators

Technical indicators available in Codon strategies. Two types are provided:

1. Batch indicators -- compute over entire arrays via C API (same as C++ implementations)
2. Streaming indicators -- pure Codon, update incrementally per tick (no FFI overhead)

Batch Indicators

These call the C++ indicator implementations via the C API. Use them for historical data processing.

ema(data, period) -> List[float]

Exponential Moving Average.

from flox.indicators import ema
result = ema(prices, 20)

sma(data, period) -> List[float]

Simple Moving Average.

rsi(data, period) -> List[float]

Relative Strength Index.

atr(high, low, close, period) -> List[float]

Average True Range.

from flox.indicators import atr
result = atr(highs, lows, closes, 14)

macd(data, fast=12, slow=26, signal=9) -> MacdResult

MACD indicator. Returns MacdResult with .line, .signal, .histogram fields.

from flox.indicators import macd
result = macd(prices, 12, 26, 9)
print(result.line[-1], result.signal[-1])

bollinger(data, period=20, multiplier=2.0) -> BollingerResult

Bollinger Bands. Returns BollingerResult with .upper, .middle, .lower fields.

from flox.indicators import bollinger
result = bollinger(prices, 20, 2.0)

Streaming Indicators

Pure Codon implementations compiled to native code. Use them in on_trade() callbacks for per-tick incremental computation.

StreamingEMA

from flox.indicators import StreamingEMA

ema = StreamingEMA(period=20)

# In on_trade callback:
value = ema.update(price)
if ema.ready:
    print(f"EMA: {value}")

Methods

Method	Returns	Description
__init__(period)		Create with given period
update(value)	float	Feed new value, returns current EMA
value	float	Current EMA value (property)
ready	bool	True after period values received

StreamingSMA

Uses a circular buffer for O(1) update.

from flox.indicators import StreamingSMA

sma = StreamingSMA(period=20)
value = sma.update(price)

Methods

Same API as StreamingEMA.