Is Downtrend

Warmup Window

Minimum bars needed: slow_ema_period bars (default params: 200 bars (slow_ema_period=200))

The slow EMA needs slow_ema_period bars to initialize. The fast EMA fills much sooner. After warmup, the trend check updates in real-time.

✅ After the warmup window is filled, this indicator produces a new value on every incoming bar in real-time.

Lagging Indicator

Uses EMA death cross which has very high lag.

Event	Lag	Detail
Downtrend detected (fast EMA < slow EMA)	≈ (slow_ema_period − 1) / 2 bars	Dominated by the slow EMA's smoothing lag

Formula for custom params: lag ≈ (slow_ema_period − 1) / 2

The is_downtrend function is used to determine if a downtrend occurred in the last N data points. It returns a boolean value indicating if a downtrend occurred in the last N data points. The function can be used to check for downtrends in a DataFrame that was previously calculated using the crossover function.

def is_down_trend(
    data: Union[PdDataFrame, PlDataFrame],
    use_death_cross: bool = True,
) -> bool:

Example

from investing_algorithm_framework import CSVOHLCVMarketDataSource

from pyindicators import is_down_trend

pl_df = download(
    symbol="btc/eur",
    market="binance",
    time_frame="1d",
    start_date="2023-12-01",
    end_date="2023-12-25",
    save=True,
    storage_path="./data"
)
pd_df = download(
    symbol="btc/eur",
    market="binance",
    time_frame="1d",
    start_date="2023-12-01",
    end_date="2023-12-25",
    pandas=True,
    save=True,
    storage_path="./data"
)

print(is_down_trend(pl_df))
print(is_down_trend(pd_df))