BATT | DMAT | BATT / DMAT | |
Gain YTD | 48.864 | 74.160 | 66% |
Net Assets | 88.6M | 9.99M | 887% |
Total Expense Ratio | 0.59 | 0.59 | 100% |
Turnover | 69.00 | 22.42 | 308% |
Yield | 2.16 | 0.94 | 231% |
Fund Existence | 7 years | 4 years | - |
BATT | DMAT | |
---|---|---|
RSI ODDS (%) | 2 days ago76% | 2 days ago75% |
Stochastic ODDS (%) | 2 days ago90% | 2 days ago76% |
Momentum ODDS (%) | 2 days ago89% | 2 days ago81% |
MACD ODDS (%) | 2 days ago83% | 2 days ago84% |
TrendWeek ODDS (%) | 2 days ago88% | 2 days ago86% |
TrendMonth ODDS (%) | 2 days ago85% | 2 days ago82% |
Advances ODDS (%) | 16 days ago89% | 13 days ago83% |
Declines ODDS (%) | 2 days ago89% | 2 days ago83% |
BollingerBands ODDS (%) | 2 days ago77% | 2 days ago77% |
Aroon ODDS (%) | 2 days ago88% | 2 days ago83% |
A.I.dvisor indicates that over the last year, BATT has been closely correlated with BHP. These tickers have moved in lockstep 70% of the time. This A.I.-generated data suggests there is a high statistical probability that if BATT jumps, then BHP could also see price increases.
Ticker / NAME | Correlation To BATT | 1D Price Change % | ||
---|---|---|---|---|
BATT | 100% | -1.21% | ||
BHP - BATT | 70% Closely correlated | -1.23% | ||
ALB - BATT | 66% Loosely correlated | -2.68% | ||
SQM - BATT | 65% Loosely correlated | -1.71% | ||
NIU - BATT | 57% Loosely correlated | -3.89% | ||
SGML - BATT | 57% Loosely correlated | -8.41% | ||
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A.I.dvisor tells us that DMAT and ALB have been poorly correlated (+24% of the time) for the last year. This A.I.-generated data suggests there is low statistical probability that DMAT and ALB's prices will move in lockstep.
Ticker / NAME | Correlation To DMAT | 1D Price Change % | ||
---|---|---|---|---|
DMAT | 100% | -3.17% | ||
ALB - DMAT | 24% Poorly correlated | -2.68% | ||
AMG - DMAT | 14% Poorly correlated | +0.75% | ||
LAC - DMAT | 14% Poorly correlated | -8.12% | ||
EAF - DMAT | 11% Poorly correlated | +6.24% | ||
NIC - DMAT | 9% Poorly correlated | +2.22% | ||
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