volas benchmark report

OHLCV technical-indicator computation across libraries · 2026-06-12T01:15:04.096965+00:00 · AMD EPYC 7763 64-Core Processor · Python 3.12.13
Lower time is better; Perf shows the slowest candidate as 1.00× and each faster candidate as {slowest ÷ this}×.

pandasstock_pandaspolarstalibvolas

Append one new bar → updated indicator

A new bar arrives. volas / stock_pandas refresh their cached column incrementally (O(lookback)); the libraries with no indicator cache (pandas / polars / talib) must recompute the series (O(n)). Every candidate is measured with the same round count so the rounds column is comparable.

atr:14

Candidate	Mean	Median	OPS	rounds	Perf
volas	3.68 µs	3.79 µs	271,940	500	304.93×
talib	17.94 µs	17.66 µs	55,747	500	65.38×
polars	240.24 µs	235.81 µs	4,162	500	4.90×
stock_pandas	847.15 µs	845.33 µs	1,180	500	1.37×
pandas	1.16 ms	1.15 ms	860	500	1.00×

bbw

Candidate	Mean	Median	OPS	rounds	Perf
volas	6.50 µs	6.27 µs	153,867	500	114.36×
talib	21.89 µs	21.42 µs	45,688	500	33.48×
polars	189.32 µs	192.05 µs	5,282	500	3.73×
pandas	360.84 µs	354.14 µs	2,771	500	2.03×
stock_pandas	717.13 µs	717.14 µs	1,394	500	1.00×

boll.upper

Candidate	Mean	Median	OPS	rounds	Perf
volas	6.39 µs	6.21 µs	156,426	500	115.97×
talib	18.54 µs	18.24 µs	53,951	500	39.49×
polars	197.83 µs	194.01 µs	5,055	500	3.71×
pandas	352.79 µs	345.48 µs	2,835	500	2.09×
stock_pandas	718.39 µs	720.42 µs	1,392	500	1.00×

ema:12

Candidate	Mean	Median	OPS	rounds	Perf
volas	4.06 µs	3.97 µs	246,304	500	181.47×
talib	9.87 µs	9.73 µs	101,300	500	74.11×
polars	46.71 µs	44.73 µs	21,410	500	16.12×
pandas	109.63 µs	105.73 µs	9,121	500	6.82×
stock_pandas	719.74 µs	720.90 µs	1,389	500	1.00×

ma:20

Candidate	Mean	Median	OPS	rounds	Perf
volas	5.99 µs	5.78 µs	166,832	500	125.31×
talib	8.00 µs	7.86 µs	124,948	500	92.03×
polars	51.16 µs	48.56 µs	19,546	500	14.90×
pandas	133.03 µs	128.53 µs	7,517	500	5.63×
stock_pandas	723.57 µs	723.71 µs	1,382	500	1.00×

macd

Candidate	Mean	Median	OPS	rounds	Perf
volas	3.75 µs	3.48 µs	266,662	500	207.15×
talib	24.00 µs	23.56 µs	41,661	500	30.57×
polars	145.09 µs	134.28 µs	6,892	500	5.36×
pandas	241.99 µs	235.20 µs	4,132	500	3.06×
stock_pandas	718.27 µs	720.25 µs	1,392	500	1.00×

macd.signal

Candidate	Mean	Median	OPS	rounds	Perf
volas	2.17 µs	1.97 µs	461,657	500	363.23×
talib	24.01 µs	23.49 µs	41,657	500	30.50×
polars	178.26 µs	173.29 µs	5,610	500	4.14×
pandas	323.54 µs	316.33 µs	3,091	500	2.27×
stock_pandas	716.83 µs	716.66 µs	1,395	500	1.00×

rsi:14

Candidate	Mean	Median	OPS	rounds	Perf
volas	4.45 µs	4.16 µs	224,890	500	270.07×
talib	16.67 µs	16.41 µs	59,977	500	68.43×
polars	416.77 µs	412.88 µs	2,399	500	2.72×
stock_pandas	716.39 µs	717.78 µs	1,396	500	1.56×
pandas	1.13 ms	1.12 ms	885	500	1.00×

Core DataFrame API (construct / slice / mask / assign / copy)

The data-handling plumbing a live system runs around every indicator call — frame construction, column access, row slicing, boolean masking, column assignment, copy — timed against pandas / polars. Not indicator math; the surrounding core APIs.

construct

Candidate	Mean	Median	OPS	rounds	Perf
volas	6.09 µs	5.93 µs	164,099	13362	20.63×
polars	39.39 µs	38.39 µs	25,387	8301	3.19×
pandas	126.76 µs	122.37 µs	7,889	2814	1.00×

copy

Candidate	Mean	Median	OPS	rounds	Perf
volas	454.4 ns	441.0 ns	2,200,859	74047	173.36×
polars	799.1 ns	782.0 ns	1,251,416	77737	97.77×
pandas	79.78 µs	76.45 µs	12,535	2756	1.00×

getcol

Candidate	Mean	Median	OPS	rounds	Perf
volas	538.0 ns	531.0 ns	1,858,822	116605	23.08×
polars	1.06 µs	1.04 µs	945,597	32898	11.76×
pandas	12.70 µs	12.25 µs	78,728	5195	1.00×

mask

Candidate	Mean	Median	OPS	rounds	Perf
volas	10.72 µs	10.51 µs	93,291	20218	17.38×
polars	167.05 µs	162.53 µs	5,986	2101	1.12×
pandas	189.54 µs	182.65 µs	5,276	1662	1.00×

setitem

Candidate	Mean	Median	OPS	rounds	Perf
volas	2.08 µs	2.05 µs	479,626	50590	14.94×
pandas	19.49 µs	18.54 µs	51,308	2928	1.65×
polars	31.95 µs	30.68 µs	31,301	3474	1.00×

slice

Candidate	Mean	Median	OPS	rounds	Perf
polars	3.24 µs	3.17 µs	308,257	18375	3.37×
volas	3.42 µs	3.34 µs	292,455	38688	3.20×
pandas	11.09 µs	10.68 µs	90,173	11544	1.00×

Batch indicator computation

Compute the indicator over the whole series, across every library.

atr:14

Candidate	Mean	Median	OPS	rounds	Perf
volas	5.10 µs	5.02 µs	195,929	28891	233.57×
talib	17.92 µs	17.62 µs	55,798	24591	66.52×
stock_pandas	221.41 µs	214.88 µs	4,517	3140	5.46×
polars	238.49 µs	234.66 µs	4,193	1612	5.00×
pandas	1.20 ms	1.17 ms	834	544	1.00×

bbw

Candidate	Mean	Median	OPS	rounds	Perf
volas	17.04 µs	16.80 µs	58,673	29795	21.27×
talib	21.24 µs	20.83 µs	47,088	12915	17.16×
polars	173.37 µs	165.20 µs	5,768	2357	2.16×
stock_pandas	256.27 µs	253.65 µs	3,902	2937	1.41×
pandas	374.50 µs	357.46 µs	2,670	1424	1.00×

boll.upper

Candidate	Mean	Median	OPS	rounds	Perf
volas	16.69 µs	16.45 µs	59,931	22206	21.06×
talib	18.19 µs	17.92 µs	54,978	22988	19.33×
polars	195.52 µs	193.34 µs	5,114	2080	1.79×
stock_pandas	257.00 µs	252.94 µs	3,891	2973	1.37×
pandas	354.77 µs	346.43 µs	2,819	1371	1.00×

ema:12

Candidate	Mean	Median	OPS	rounds	Perf
volas	5.70 µs	5.61 µs	175,340	42277	18.46×
talib	9.88 µs	9.71 µs	101,167	30127	10.67×
polars	43.83 µs	42.18 µs	22,818	5102	2.46×
stock_pandas	85.84 µs	82.98 µs	11,649	5476	1.25×
pandas	117.49 µs	103.56 µs	8,511	2841	1.00×

hhv:10

Candidate	Mean	Median	OPS	rounds	Perf
volas	4.10 µs	4.04 µs	243,709	30367	31.04×
talib	8.31 µs	8.17 µs	120,366	22044	15.35×
polars	55.98 µs	48.32 µs	17,864	4526	2.59×
stock_pandas	110.33 µs	106.28 µs	9,064	3699	1.18×
pandas	132.77 µs	125.32 µs	7,532	2546	1.00×

llv:10

Candidate	Mean	Median	OPS	rounds	Perf
volas	4.95 µs	4.87 µs	202,155	23720	26.82×
talib	8.02 µs	7.87 µs	124,662	23026	16.58×
polars	50.08 µs	48.26 µs	19,968	3837	2.71×
stock_pandas	109.09 µs	105.52 µs	9,167	3414	1.24×
pandas	135.36 µs	130.59 µs	7,388	2506	1.00×

ma:20

Candidate	Mean	Median	OPS	rounds	Perf
talib	7.93 µs	7.80 µs	126,166	29400	15.83×
volas	16.45 µs	16.25 µs	60,790	21134	7.60×
polars	49.47 µs	47.02 µs	20,215	4050	2.63×
stock_pandas	122.61 µs	118.09 µs	8,156	4583	1.05×
pandas	128.11 µs	123.55 µs	7,806	2435	1.00×

macd

Candidate	Mean	Median	OPS	rounds	Perf
volas	8.16 µs	8.23 µs	122,538	40592	28.21×
talib	23.97 µs	23.54 µs	41,719	14368	9.86×
stock_pandas	99.37 µs	95.98 µs	10,064	5339	2.42×
polars	142.04 µs	137.14 µs	7,040	2544	1.69×
pandas	239.48 µs	232.05 µs	4,176	1940	1.00×

macd.signal

Candidate	Mean	Median	OPS	rounds	Perf
volas	12.45 µs	12.26 µs	80,337	31418	25.27×
talib	24.05 µs	23.75 µs	41,572	15193	13.05×
stock_pandas	111.21 µs	107.59 µs	8,992	4433	2.88×
polars	174.31 µs	168.80 µs	5,737	2219	1.84×
pandas	320.92 µs	309.90 µs	3,116	1516	1.00×

rsi:14

Candidate	Mean	Median	OPS	rounds	Perf
volas	14.69 µs	14.54 µs	68,091	32640	77.39×
talib	16.67 µs	16.47 µs	59,984	23765	68.31×
stock_pandas	109.49 µs	105.90 µs	9,133	5170	10.62×
polars	418.32 µs	416.64 µs	2,390	1143	2.70×
pandas	1.13 ms	1.13 ms	881	616	1.00×

Full coverage — volas vs TA-Lib

Every indicator both volas and TA-Lib implement (the set the parity suite aligns), one row per indicator. The default volas vs TA-Lib column is the Tencent fixture; optional generated lengths and cached append refresh appear as additional ratio columns. Values > 1.00× mean volas is faster.

volas beats TA-Lib on 136 / 158 covered indicators by the default ratio (0 exactly even, 22 slower).

Indicator	volas	TA-Lib	volas vs TA-Lib	volas vs TA-Lib (100)	volas vs TA-Lib (250)	volas vs TA-Lib (20000)	volas vs TA-Lib (after append)
cdl.stalledpattern	5.25 µs	29.06 µs	5.54×	n/a	n/a	n/a	4.42×
ht_dcphase	185.94 µs	891.67 µs	4.80×	n/a	n/a	n/a	193.06×
linearreg_intercept:14	6.90 µs	31.21 µs	4.52×	n/a	n/a	n/a	5.31×
linearreg:14	7.40 µs	31.85 µs	4.30×	n/a	n/a	n/a	6.17×
ht_sine.leadsine	226.10 µs	969.68 µs	4.29×	n/a	n/a	n/a	225.64×
ht_sine.sine	226.64 µs	969.72 µs	4.28×	n/a	n/a	n/a	229.44×
tsf:14	7.44 µs	31.83 µs	4.28×	n/a	n/a	n/a	5.75×
plus_dm:14	3.68 µs	13.61 µs	3.70×	n/a	n/a	n/a	3.73×
minus_dm:14	3.69 µs	13.43 µs	3.64×	n/a	n/a	n/a	3.89×
linearreg_slope:14	6.93 µs	25.01 µs	3.61×	n/a	n/a	n/a	4.08×
tema:30	5.63 µs	19.70 µs	3.50×	n/a	n/a	n/a	5.05×
ht_trendmode	289.36 µs	1.01 ms	3.49×	n/a	n/a	n/a	202.04×
rocr:10	1.56 µs	5.22 µs	3.34×	n/a	n/a	n/a	1.54×
atr:14	4.80 µs	15.64 µs	3.26×	n/a	n/a	n/a	5.77×
rocr100:10	1.67 µs	5.30 µs	3.17×	n/a	n/a	n/a	1.53×
cdl.longleggeddoji	4.49 µs	14.15 µs	3.15×	n/a	n/a	n/a	2.52×
rocp:10	1.65 µs	5.20 µs	3.15×	n/a	n/a	n/a	1.53×
cdl.3whitesoldiers	10.10 µs	30.79 µs	3.05×	n/a	n/a	n/a	5.10×
macd	7.41 µs	21.46 µs	2.89×	n/a	n/a	n/a	6.88×
macdfix	7.44 µs	21.08 µs	2.83×	n/a	n/a	n/a	6.95×
minmax.max:30	5.20 µs	14.60 µs	2.81×	n/a	n/a	n/a	2.27×
natr:14	5.74 µs	16.02 µs	2.79×	n/a	n/a	n/a	5.07×
minmax.min:30	5.32 µs	14.75 µs	2.77×	n/a	n/a	n/a	2.12×
cdl.hangingman	6.40 µs	17.44 µs	2.72×	n/a	n/a	n/a	2.98×
typprice	1.49 µs	3.98 µs	2.66×	n/a	n/a	n/a	1.17×
midpoint:14	9.34 µs	24.27 µs	2.60×	n/a	n/a	n/a	4.05×
trix:30	8.39 µs	21.39 µs	2.55×	n/a	n/a	n/a	6.19×
minmaxindex.max:30	6.42 µs	16.01 µs	2.49×	n/a	n/a	n/a	4.45×
cdl.advanceblock	18.29 µs	45.48 µs	2.49×	n/a	n/a	n/a	7.66×
dema:30	5.82 µs	14.32 µs	2.46×	n/a	n/a	n/a	3.84×
medprice	1.23 µs	2.93 µs	2.39×	n/a	n/a	n/a	0.94×
cdl.3starsinsouth	4.83 µs	10.96 µs	2.27×	n/a	n/a	n/a	1.84×
wclprice	1.44 µs	3.27 µs	2.27×	n/a	n/a	n/a	0.94×
cdl.kicking	7.86 µs	17.70 µs	2.25×	n/a	n/a	n/a	3.00×
mom:10	1.27 µs	2.85 µs	2.25×	n/a	n/a	n/a	0.94×
linearreg_angle:14	25.35 µs	56.24 µs	2.22×	n/a	n/a	n/a	9.56×
cdl.rickshawman	7.17 µs	15.76 µs	2.20×	n/a	n/a	n/a	2.95×
cdl.kickingbylength	7.76 µs	16.91 µs	2.18×	n/a	n/a	n/a	2.92×
cdl.mathold	6.82 µs	14.50 µs	2.12×	n/a	n/a	n/a	2.26×
plus_di:14	7.51 µs	15.81 µs	2.10×	n/a	n/a	n/a	4.26×
minus_di:14	7.62 µs	15.76 µs	2.07×	n/a	n/a	n/a	3.89×
avgprice	1.73 µs	3.57 µs	2.06×	n/a	n/a	n/a	1.11×
cdl.identical3crows	5.84 µs	11.98 µs	2.05×	n/a	n/a	n/a	2.17×
cdl.highwave	4.98 µs	10.20 µs	2.05×	n/a	n/a	n/a	1.63×
minmaxindex.min:30	8.07 µs	16.03 µs	1.99×	n/a	n/a	n/a	3.99×
cci:14	26.30 µs	51.83 µs	1.97×	n/a	n/a	n/a	7.82×
cdl.takuri	6.91 µs	13.52 µs	1.96×	n/a	n/a	n/a	2.55×
tr	1.82 µs	3.56 µs	1.95×	n/a	n/a	n/a	0.95×
cdl.tristar	4.96 µs	9.29 µs	1.87×	2.80×	2.03×	1.82×	1.48×
cdl.ladderbottom	4.16 µs	7.73 µs	1.86×	n/a	n/a	n/a	1.35×
aroon.up:14	8.50 µs	15.69 µs	1.85×	3.06×	2.32×	1.80×	2.56×
cdl.gravestonedoji	6.84 µs	12.63 µs	1.85×	n/a	n/a	n/a	2.17×
cdl.dragonflydoji	6.89 µs	12.58 µs	1.83×	n/a	n/a	n/a	2.08×
macd.signal	11.94 µs	21.55 µs	1.80×	n/a	n/a	n/a	6.63×
cdl.eveningstar	5.83 µs	10.35 µs	1.77×	n/a	n/a	n/a	1.79×
macdfix.signal	11.95 µs	21.12 µs	1.77×	n/a	n/a	n/a	6.24×
macd.histogram	12.41 µs	21.49 µs	1.73×	n/a	n/a	n/a	6.01×
cdl.inneck	5.36 µs	9.27 µs	1.73×	n/a	n/a	n/a	1.51×
cdl.piercing	5.18 µs	8.94 µs	1.73×	n/a	n/a	n/a	1.47×
cdl.morningstar	5.96 µs	10.20 µs	1.71×	n/a	n/a	n/a	1.76×
macdfix.histogram	12.43 µs	21.09 µs	1.70×	n/a	n/a	n/a	5.30×
cdl.spinningtop	5.19 µs	8.76 µs	1.69×	n/a	n/a	n/a	1.46×
correl:30@high,low	11.40 µs	19.20 µs	1.68×	n/a	n/a	n/a	3.30×
cdl.shootingstar	7.20 µs	12.11 µs	1.68×	n/a	n/a	n/a	1.91×
cdl.hikkakemod	5.19 µs	8.64 µs	1.66×	n/a	n/a	n/a	1.46×
cdl.invertedhammer	7.29 µs	12.11 µs	1.66×	n/a	n/a	n/a	1.94×
hhv:10	3.88 µs	6.40 µs	1.65×	3.06×	2.58×	2.09×	1.03×
cdl.counterattack	7.36 µs	12.13 µs	1.65×	n/a	n/a	n/a	1.92×
wma:30	3.76 µs	6.15 µs	1.64×	n/a	n/a	n/a	1.02×
cdl.2crows	4.89 µs	7.99 µs	1.64×	n/a	n/a	n/a	1.40×
dx:14	12.84 µs	20.94 µs	1.63×	n/a	n/a	n/a	6.39×
cdl.harami	6.03 µs	9.76 µs	1.62×	n/a	n/a	n/a	1.73×
cdl.hammer	10.29 µs	16.63 µs	1.62×	n/a	n/a	n/a	2.65×
aroon.down:14	9.80 µs	15.70 µs	1.60×	2.81×	2.46×	1.81×	2.46×
var:5	5.03 µs	8.04 µs	1.60×	n/a	n/a	n/a	1.31×
cdl.doji	4.30 µs	6.81 µs	1.58×	n/a	n/a	n/a	1.19×
cdl.breakaway	5.72 µs	8.99 µs	1.57×	2.87×	2.31×	2.51×	1.52×
cdl.homingpigeon	4.79 µs	7.48 µs	1.56×	n/a	n/a	n/a	1.31×
cdl.matchinglow	4.49 µs	7.01 µs	1.56×	n/a	n/a	n/a	1.11×
cdl.unique3river	5.23 µs	8.16 µs	1.56×	n/a	n/a	n/a	1.26×
cdl.marubozu	7.01 µs	10.91 µs	1.56×	n/a	n/a	n/a	1.90×
cdl.darkcloudcover	4.45 µs	6.91 µs	1.55×	n/a	n/a	n/a	1.24×
midprice:14	9.37 µs	14.52 µs	1.55×	n/a	n/a	n/a	2.61×
cdl.gapsidesidewhite	8.18 µs	12.47 µs	1.53×	n/a	n/a	n/a	2.15×
cdl.shortline	10.88 µs	16.19 µs	1.49×	n/a	n/a	n/a	2.69×
adx:14	15.47 µs	22.93 µs	1.48×	n/a	n/a	n/a	6.28×
adxr:14	16.02 µs	23.70 µs	1.48×	n/a	n/a	n/a	6.28×
ema:12	5.38 µs	7.91 µs	1.47×	n/a	n/a	n/a	2.18×
kama:30	5.44 µs	7.98 µs	1.47×	n/a	n/a	n/a	2.71×
cdl.upsidegap2crows	5.67 µs	8.28 µs	1.46×	n/a	n/a	n/a	1.22×
ultosc	17.14 µs	24.90 µs	1.45×	n/a	n/a	n/a	4.13×
cdl.hikkake	4.80 µs	6.96 µs	1.45×	2.92×	2.18×	1.00×	1.13×
cdl.eveningdojistar	7.23 µs	10.48 µs	1.45×	n/a	n/a	n/a	1.53×
cdl.3outside	4.51 µs	6.47 µs	1.44×	n/a	n/a	n/a	1.15×
cdl.longline	10.46 µs	14.89 µs	1.42×	n/a	n/a	n/a	2.34×
bop	3.88 µs	5.50 µs	1.42×	n/a	n/a	n/a	0.72×
cdl.tasukigap	6.35 µs	8.98 µs	1.41×	n/a	n/a	n/a	1.43×
maxindex:30	6.51 µs	9.20 µs	1.41×	n/a	n/a	n/a	2.09×
aroonosc:14	10.27 µs	14.47 µs	1.41×	2.76×	2.09×	1.07×	2.25×
cdl.onneck	7.00 µs	9.84 µs	1.40×	n/a	n/a	n/a	1.52×
minindex:30	8.16 µs	11.37 µs	1.39×	n/a	n/a	n/a	2.64×
roc:10	3.79 µs	5.20 µs	1.37×	3.14×	2.17×	1.05×	1.73×
cdl.morningdojistar	7.24 µs	9.87 µs	1.36×	n/a	n/a	n/a	1.72×
cdl.haramicross	7.26 µs	9.83 µs	1.35×	n/a	n/a	n/a	1.63×
cdl.closingmarubozu	6.99 µs	9.27 µs	1.33×	n/a	n/a	n/a	1.62×
beta:5@high,low	12.60 µs	16.68 µs	1.32×	n/a	n/a	n/a	2.81×
cdl.belthold	7.03 µs	9.26 µs	1.32×	n/a	n/a	n/a	1.60×
cdl.3blackcrows	7.23 µs	9.46 µs	1.31×	n/a	n/a	n/a	1.58×
stochf.k	10.43 µs	13.59 µs	1.30×	n/a	n/a	n/a	2.30×
cdl.engulfing	5.13 µs	6.66 µs	1.30×	n/a	n/a	n/a	1.00×
t3:5	7.45 µs	9.64 µs	1.29×	n/a	n/a	n/a	2.95×
llv:10	4.76 µs	6.13 µs	1.29×	n/a	n/a	n/a	1.00×
adosc	5.75 µs	7.28 µs	1.27×	n/a	n/a	n/a	2.10×
sum:30	4.85 µs	6.08 µs	1.25×	n/a	n/a	n/a	0.95×
mfi:14	7.07 µs	8.87 µs	1.25×	2.48×	2.03×	1.20×	1.38×
cdl.thrusting	6.91 µs	8.66 µs	1.25×	n/a	n/a	n/a	1.34×
cdl.3linestrike	7.93 µs	9.74 µs	1.23×	2.57×	1.74×	1.54×	1.60×
cdl.separatinglines	9.70 µs	11.64 µs	1.20×	n/a	n/a	n/a	2.03×
trima:30	6.70 µs	7.94 µs	1.19×	n/a	n/a	n/a	1.34×
cdl.dojistar	8.35 µs	9.83 µs	1.18×	n/a	n/a	n/a	1.68×
stochf.d	11.72 µs	13.60 µs	1.16×	2.58×	1.92×	1.02×	2.32×
cdl.3inside	8.28 µs	9.58 µs	1.16×	n/a	n/a	n/a	1.61×
willr:14	10.71 µs	12.14 µs	1.13×	n/a	n/a	n/a	2.19×
cmo:14	12.89 µs	14.50 µs	1.12×	n/a	n/a	n/a	4.00×
cdl.risefall3methods	15.36 µs	16.64 µs	1.08×	n/a	n/a	n/a	3.06×
stochrsi.k	22.95 µs	24.84 µs	1.08×	n/a	n/a	n/a	6.50×
cdl.xsidegap3methods	5.44 µs	5.87 µs	1.08×	n/a	n/a	n/a	1.08×
accbands:20	16.24 µs	17.08 µs	1.05×	n/a	n/a	n/a	3.24×
stddev:5	10.14 µs	10.63 µs	1.05×	n/a	n/a	n/a	1.71×
stoch.d	16.67 µs	17.39 µs	1.04×	2.32×	1.69×	1.07×	3.09×
cdl.abandonedbaby	10.34 µs	10.62 µs	1.03×	n/a	n/a	n/a	1.74×
rsi:14	14.14 µs	14.47 µs	1.02×	n/a	n/a	n/a	4.07×
boll.lower	15.95 µs	16.28 µs	1.02×	n/a	n/a	n/a	2.96×
boll.upper	15.94 µs	16.08 µs	1.01×	n/a	n/a	n/a	2.83×
boll.middle	16.15 µs	16.27 µs	1.01×	n/a	n/a	n/a	2.63×
stochrsi.d	24.83 µs	24.85 µs	1.00×	1.95×	1.41×	1.19×	6.53×
accbands.upper:20	17.11 µs	17.11 µs	1.00×	n/a	n/a	n/a	3.29×
accbands.lower:20	17.12 µs	17.10 µs	1.00×	n/a	n/a	n/a	3.30×
ht_trendline	113.62 µs	107.33 µs	0.94×	n/a	n/a	n/a	28.34×
cdl.concealbabyswall	8.82 µs	8.33 µs	0.94×	n/a	n/a	n/a	1.44×
ht_phasor.inphase	102.95 µs	96.89 µs	0.94×	n/a	n/a	n/a	26.50×
ht_phasor.quadrature	103.17 µs	96.92 µs	0.94×	n/a	n/a	n/a	29.06×
mama.fama	112.13 µs	103.91 µs	0.93×	n/a	n/a	n/a	22.41×
mama	112.13 µs	103.90 µs	0.93×	1.21×	1.04×	1.08×	23.98×
ht_dcperiod	105.52 µs	97.59 µs	0.92×	1.20×	1.01×	0.90×	24.16×
sar	9.25 µs	7.39 µs	0.80×	n/a	n/a	n/a	2.16×
sarext	9.35 µs	7.36 µs	0.79×	n/a	n/a	n/a	1.92×
stoch.k	25.65 µs	17.40 µs	0.68×	n/a	n/a	n/a	3.27×
ad	8.73 µs	5.54 µs	0.63×	n/a	n/a	n/a	1.74×
cdl.sticksandwich	14.34 µs	7.61 µs	0.53×	n/a	n/a	n/a	1.41×
obv	8.46 µs	4.27 µs	0.50×	n/a	n/a	n/a	1.42×
macdext	32.84 µs	15.67 µs	0.48×	n/a	n/a	n/a	2.14×
ma:20	15.96 µs	6.24 µs	0.39×	n/a	n/a	n/a	1.04×
ppo	33.91 µs	12.96 µs	0.38×	n/a	n/a	n/a	2.09×
mavp@close,periods	445.98 µs	147.03 µs	0.33×	n/a	n/a	n/a	8.90×
macdext.signal	47.86 µs	15.63 µs	0.33×	n/a	n/a	n/a	2.33×
apo	32.86 µs	10.66 µs	0.32×	n/a	n/a	n/a	1.67×
macdext.histogram	49.98 µs	15.61 µs	0.31×	n/a	n/a	n/a	1.97×

Generated by scripts/benchmark_report.py from pytest-benchmark output.