BATT | GMET | BATT / GMET | |
Gain YTD | 25.114 | 27.268 | 92% |
Net Assets | 67.1M | 21.4M | 314% |
Total Expense Ratio | 0.59 | 0.61 | 97% |
Turnover | 69.00 | 20.00 | 345% |
Yield | 2.82 | 1.63 | 173% |
Fund Existence | 7 years | 4 years | - |
BATT | GMET | |
---|---|---|
RSI ODDS (%) | 2 days ago84% | 2 days ago90% |
Stochastic ODDS (%) | 2 days ago78% | 2 days ago90% |
Momentum ODDS (%) | 2 days ago87% | 2 days ago79% |
MACD ODDS (%) | 2 days ago85% | 2 days ago88% |
TrendWeek ODDS (%) | 2 days ago88% | 2 days ago86% |
TrendMonth ODDS (%) | 2 days ago85% | 2 days ago82% |
Advances ODDS (%) | 2 days ago89% | 3 days ago84% |
Declines ODDS (%) | 8 days ago90% | 8 days ago90% |
BollingerBands ODDS (%) | 7 days ago90% | N/A |
Aroon ODDS (%) | 2 days ago88% | 2 days ago89% |
A.I.dvisor indicates that over the last year, BATT has been closely correlated with BHP. These tickers have moved in lockstep 75% 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% | -0.58% | ||
BHP - BATT | 75% Closely correlated | +0.40% | ||
ALB - BATT | 71% Closely correlated | +7.54% | ||
SQM - BATT | 69% Closely correlated | +2.78% | ||
PLL - BATT | 66% Closely correlated | -1.80% | ||
SGML - BATT | 61% Loosely correlated | +11.46% | ||
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A.I.dvisor tells us that GMET and SQM have been poorly correlated (+15% of the time) for the last year. This A.I.-generated data suggests there is low statistical probability that GMET and SQM's prices will move in lockstep.
Ticker / NAME | Correlation To GMET | 1D Price Change % | ||
---|---|---|---|---|
GMET | 100% | -0.02% | ||
SQM - GMET | 15% Poorly correlated | +2.78% | ||
ALB - GMET | 12% Poorly correlated | +7.54% | ||
AAL - GMET | 11% Poorly correlated | -0.15% | ||
SGML - GMET | 10% Poorly correlated | +11.46% | ||
AMS - GMET | 5% Poorly correlated | -0.81% | ||
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