Gmo Resources Fund Quote

GAAHX Fund  USD 20.35  0.19  0.94%   

Performance

0 of 100

 
Weak
 
Strong
Very Weak

Odds Of Distress

Less than 21

 
High
 
Low
Low
Gmo Resources is trading at 20.35 as of the 25th of November 2024; that is 0.94% up since the beginning of the trading day. The fund's open price was 20.16. Gmo Resources has about a 21 % chance of experiencing some form of financial distress in the next two years of operation but has generated negative returns over the last 90 days. Equity ratings for Gmo Resources are calculated daily based on our scoring framework. The performance scores are derived for the period starting the 26th of October 2024 and ending today, the 25th of November 2024. Click here to learn more.
Under normal market conditions, the fund invests at least 80 percent of its assets in the securities of companies in that sector. The funds managers consider the natural resources sector to include companies that own, produce, refine, process, transport, and market natural resources and companies that provide related equipment, infrastructure, and services. More on Gmo Resources

Moving together with Gmo Mutual Fund

  1.0GEACX Gmo TrustPairCorr
  0.76GEMEX Gmo Emerging MarketsPairCorr
  0.76GEMMX Gmo Emerging MarketsPairCorr

Gmo Mutual Fund Highlights

Fund ConcentrationGMO Funds, Large Funds, Natural Resources Funds, Natural Resources, GMO (View all Sectors)
Update Date30th of September 2024
Gmo Resources [GAAHX] is traded in USA and was established 25th of November 2024. Gmo Resources is listed under GMO category by Fama And French industry classification. The fund is listed under Natural Resources category and is part of GMO family. Gmo Resources currently has accumulated 2.1 B in assets under management (AUM) with no minimum investment requirements with the current yeild of 0.04%.
Check Gmo Resources Probability Of Bankruptcy

Instrument Allocation

Sector Allocation

Investors will always prefer to have their portfolios divercified against different sectors. The broad sector allocation increases the possibility of making a profit or at least avoiding a loss. However, this may also reduce the expected return on Gmo Mutual Fund. Generally, it depends on diversification level and type but usually, the broader the sector allocation, the less risk can be expected from holding Gmo Mutual Fund, and the less return is expected.
Institutional investors that are interested in enforcing a sector tilt in their portfolio can use exchange-traded funds, such as Gmo Resources Mutual Fund, as a low-cost alternative to building a custom portfolio. So, using sector ETFs to diversify your portfolio can be a profitable strategy. However, no matter what sectors are desirable at a given time, no single industry should ever make up more than 20 percent of your stock portfolio.

Top Gmo Resources Mutual Fund Constituents

AMRCAmerescoStockIndustrials
CLNEClean Energy FuelsStockEnergy
DARDarling IngredientsStockConsumer Staples
HESHess CorporationStockEnergy
KOSKosmos EnergyStockEnergy
MOSThe MosaicStockMaterials
SQMSociedad Quimica yStockMaterials
More Details

Gmo Resources Risk Profiles

Gmo Resources Against Markets

Other Information on Investing in Gmo Mutual Fund

Gmo Resources financial ratios help investors to determine whether Gmo Mutual Fund is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Gmo with respect to the benefits of owning Gmo Resources security.
Idea Analyzer
Analyze all characteristics, volatility and risk-adjusted return of Macroaxis ideas
Positions Ratings
Determine portfolio positions ratings based on digital equity recommendations. Macroaxis instant position ratings are based on combination of fundamental analysis and risk-adjusted market performance
Portfolio Backtesting
Avoid under-diversification and over-optimization by backtesting your portfolios
Watchlist Optimization
Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm