The results of the survey by the London Bullion Market Association of analysts' predictions for the gold price in 2019 is another example of just how unpredictable financial markets have become.
The LBMA, a standards setting body for the industry, says the average forecast by the 30 analysts polled calls for a modest 1.8% gain in the price this year. However, two-thirds of the analysts see gold reaching or surpassing the $1,400 mark at some point during the year.
Gold was a bolthole for investors in the second half of 2018, but a return to more concerted growth should mean that prices will start to drift lower again in 2019
Individual views of the direction of the gold price all over the place with a trading range of $325 per ounce or a full 25% of the average forecast price:
“Whilst markets have factored in some of the downside risks of Brexit and US-China trade wars, other factors such the level of US real interest rates, strength/weakness of the dollar, the likely impact of geopolitical factors and the pace of global economic growth continues to provide some uncertainty.”
Eddie Nagao of Sumitomo in Tokyo is the most bullish, forecasting a high of $1,475 saying gold is likely to be one of the favoured asset classes among institutional and private investors as the likelihood of a US recession increases.
Only six analysts predict an average for the year below $1,300 with Adam Williams of Fastmarkets MB (Metal Bulletin) the most bearish. Williams predicts a high for gold of $1,355 a dip to below $1,200 and an average of $1,242:
“With a US/China trade deal expected before too long, a return to more broad-based growth may well come to the rescue. If so, demand for haven assets may diminish. Gold was a bolthole for investors in the second half of 2018, but a return to more concerted growth should mean that prices will start to drift lower again in 2019, especially if the Fed’s more dovish stance proves short-lived.”
Ross Norman of Sharps Pixley, London's top bullion broker, forecasts a tight range for gold; $1,280 on the downside, a $1,410 high and $1,337 average. Norman has been the most accurate forecaster in recent years coming in as the outright winner five times and a runner up four times.
The winner of the 2015 competition who came within $1 of that year’s average, Bernard Dahdah of French investment bank Natixis, is more bullish about gold’s prospects in 2019 than in previous years, forecasting an average of $1,330.
Palladium has the capacity to surprise even further to the upside, especially if the supply deficit attracts speculators. More so, if the political risk from its biggest producer, Russia, becomes inflamed
Gold ended Monday in New York on Friday bang on Dahdah’s forecast average for the year of $1,330.
Silver is forecast to increase by over 4% in 2019 to average $16.28 an ounce. The range of forecasts include a low of $12.25 and a high of $20 for the metal which has lagged gold’s performance in recent years and may be ripe for a rerating.
Forecasters are most bullish about the prospects for platinum which is predicted to add more than 5% on average after the precious metal fell to multi-year lows last year. Platinum last traded at $808 an ounce in New York.
High-flying palladium will ease back to $1,267 during the year, but even more than gold, the palladium market has become very difficult to read.
Predictions range from a low of $900 to a high of $1,715. The latter is Norman’s view of the palladium price adding that the metal used in autocatalysts “has the capacity to surprise even further to the upside, especially if the supply deficit attracts speculators. More so, if the political risk from its biggest producer, Russia, becomes inflamed.”
Palladium on Monday exchanged hands at $1,433, a fresh record high.
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For the first time ever, scientists from Los Alamos National Laboratory had a peek inside the structure of the Ram's Horn, a 263 gram, 12-centimeter tall wire gold specimen considered one of the few of its kind.
Using neutron characterization techniques, the researchers were able to take a look to try to better understand how the shiny object was formed.
"Almost nothing other than the existence of the specimen is known about wire gold," said Sven Vogel, a physicist at Los Alamos National Laboratory's neutron science center.
According to Vogel, wire silver is more common in nature but its yellow counterpart is so rare that this particular specimen is almost invaluable.
"Wire silver is a mosaic-like polycrystalline aggregate with many hundreds to thousands of crystals in a single wire," explained John Rakovan, Professor of Mineralogy at Miami University and one of the researchers involved in the experiment. "The gold appears to be composed of only a few single crystals. Furthermore, we discovered that these samples are not pure gold, but rather gold-silver alloys with as much as 30 percent silver substituting for gold in the atomic structure."
The sample will be the centerpiece of a new exhibit at the Harvard Museum of Natural History in the spring of 2020.
Using the lab's neutron source, which is normally utilized to study materials like uranium alloys or nuclear fuels, the experts were able to verify that this sample is homogeneous, meaning the whole sample is a 70-30 mix of gold to silver.
In their view, this could mean that the silver is bonding to the gold in the crystalline structure at the atomistic level.
"The results of this study will have implications for geoscientists who are trying to understand the geochemical processes that are at play in the formation of gold deposits, and for materials scientists and engineers who may use the unique properties of these materials in technological applications," the scientists said in a media statement.
The Ram's Horn belongs to the collection of the Mineralogical and Geological Museum at Harvard University and it was initially found in 1887 at the Ground Hog mine in Red Cliff, Colorado.
According to the museum curators, the mysteriously shaped artifact that resembles a twisted bunch of wires and not the usual golden nugget has baffled mineralogists since its discovery.
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The Angas zinc mine, just outside Adelaide and currently under care and maintenance, is about to become the site of 5 MW advanced compressed air energy storage or A-CAES project which will provide synchronous inertia, load shifting and frequency regulation to the area's electrical grid.
The developer is Toronto-based Hydrostor, a firm that was awarded $9 million in grants to build the facility, which would allow for variable renewable energy resources such as solar and wind to be integrated into Australia’s National Electricity Market.
According to Hydrostor, the project will repurpose Angas’ existing underground mining infrastructure as the A-CAES system’s sub-surface air storage cavern.
In a media brief, company experts explained that the way the technology works is that it uses electricity from the grid to run a compressor, which produces heated compressed air. Heat is then extracted from the air stream and saved inside a thermal store preserving the energy for use later in the cycle.
The compressed air is then stored in a purpose-built underground cavern, which is kept at a constant pressure using hydrostatic heat from a water column. During charging, compressed air displaces water out of the cavern up a water column to a surface reservoir, and during discharge water flows back into the cavern forcing air to the surface under pressure where it is re-heated using the stored heat and then expanded through a turbine to generate electricity on demand.
“Compressed air storage has the potential to provide similar benefits to pumped hydro energy storage, however, it has the added benefits of being flexible with location and topography, such as utilising a cavern already created at a disused mine site,” said Darren Miller, CEO of the Australian Renewable Energy Agency, the institution that provided $6 million for the project.
The Angas zinc mine, first discovered in 1991 and acquired by local miner Terramin (ASX: TZN) in 1997, is located on the Fleurieu Peninsula in South Australia. It was placed under care and maintenance in late 2013 as a result of a prolonged drop in metal prices and the current economic reserve being depleted.
The processing plant at Angas was decommissioned but Terramin has been maintaining it with the idea of processing there the ore from its Bird-in-Hand gold project, which is located approximately 30 kilometres north of the zinc mine.
According to the miner, if it gets the required regulatory approvals, its team would modify the plant to process gold-bearing material, while also making use of the existing tailings dam.
Based on Terramin’s December 2018 quarterly activities report, the possibility of restarting the processing plant at Angas does not collide with Hydrostor’s work at the site.
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Much has been said lately about how IBM’s cognitive exploration and content analysis platform, known as Watson, is helping major miners, such as Goldcorp and Newcrest, in a number of ways, from mine planning and operational performance optimization to sharpening takeover strategies.
A less touted, but equally helpful advantage of this and other artificial intelligence (AI) applications is the role they are playing — or expected to play— in the health and safety area of mining companies.
For Mark Fawcett, a partner with IBM Global Business Services, the answer is clear. Available technologies, he tells MINING.com, go beyond helping mining companies predict when their equipment is going to fail, they can also monitor biometric and environmental data to identify whether employees are at risk of danger.
Data can be gathered in near real time from wearables, smart devices, and environmental sensors to help firms respond to problems or react to changing environmental conditions.
The problem is that many organizations do not have an automated safety system in place, Fawcett says. Often, they are paper-based or rely on systems where the data is unstructured. Even when there are systems in place, they usually vary from mine to mine. Ultimately, safety departments are left with an incomplete view of incidents across their organization.
“AI has the ability to quickly consume the data regardless of source and easily provide insights on the top issues, major trends that are occurring, and share insights on data that may have been missed. In addition, historical data can be consumed to trend historically over time,” Fawcett notes.
IBM believes that in the “very near” future, AI will provide a full analysis on working conditions before an employee even takes a work order.
Fawcett believes that in the “very near” future, AI will provide a full analysis on working conditions before an employee even takes a work order. This will include a complete summary on where the task is going to be performed spatially, forecasted weather data and relevant safety notices for the worker in that specific location.
“The freeze-thaw cycle is a common example of where we can apply spatial analytics to safety. When an employee receives a work order where the ground may be frozen, that work order would be accompanied by the relevant safety notices and other events that have happened giving the employee a relevant picture of the work, the forecast and potential risk,” he says.
“Using this data, we can prevent a lot of falls that would have otherwise happened without that notice, ultimately resulting in smarter and safer working conditions.”
That’s why IBM is developing what it calls “Watson safe”, currently in its second phase and is expected to be ready on a platform scale in the second half of the year.
IBM is also working on extending the reach of the so-called internet of things (IoT), a system of interrelated computing devices, mechanical and digital machines, objects, people and even animals embedded with sensors, software, electronics and connectivity. These allow the system to perform better by exchanging information with other connected devices without requiring human-to-human or human-to-computer interaction.
The company has recently joined wearable technology developer Garmin to offer organizations who deploy IBM’s Maximo Worker Insights platform to receive alerts based on near real-time sensor data from workers wearing Garmin activity trackers.
By embedding the Garmin Health Companion SDK in the IBM Maximo Worker Insights platform, supervisors and safety officers can receive notifications for high heart rate and man-down scenarios, as well as review historical analytics based on the biometric signals from Garmin wearables.
The IT giant is also partnering with Guardhat, Mitsufuji and SmartCone to help monitor worker safety in hazardous environments.
Guardhat's KYRA IoT platform can complement the IBM Worker Insights solution to provide situational awareness to workers and company operations through the use of Smart PPE wearables.
Mitsufuji, in turn, has launched a new wearable “shirt” made from silver conductive fibres that tracks data from workers' biometrics to help ensure safety in extreme environments.
SmartCone, a provider of smart, IoT-based safety and monitoring solutions for securing vulnerable and hazardous zones, will be integrating Maximo Worker Insights into its highly portable system to monitor worker safety in the utilities industry, community traffic, construction, mining and industrial environments with moving or dangerous no-go zones.
Response to mine disasters
IBM envisions AI being used also to improve response to mine disasters. When something like the recent deadly dam disaster in the Brazilian town of Brumadinho happens, everyone from national government leaders and the military to the small-town mayor and scores of volunteers come together to respond to the event. All those people, at every level, need to communicate, share information and coordinate their activities so that they’re doing things efficiently and not duplicating their efforts.
Many times, that doesn’t happen effectively because people can’t find or share the information they need, when they need it.
IBM is already supporting Lightship, a company that offers an intelligent fields operations tool to help organizations navigate their data to find the necessary information to help them make better, safer decisions. It pulls together all of an organization’s information, such as Geographic Information System (GIS) mapping, drone photos, satellite photos and the real-time locations of people and vehicles.
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