Archive for Opinions – Page 17

We tracked illegal fishing in marine protected areas – satellites and AI show most bans are respected, and could help enforce future ones

By Jennifer Raynor, University of Wisconsin-Madison Marine protected areas cover more than 8% of the world’s oceans today, but they can get a bad rap as being protected on paper only.

While the name invokes safe havens for fish, whales and other sea life, these areas can be hard to monitor. High-profile violations, such as recent fishing fleet incursions near the Galapagos Islands and ships that “go dark” by turning off their tracking devices, have fueled concerns about just how much poaching is going undetected.

But some protected areas are successfully keeping illegal fishing out.

In a new global study using satellite technology that can track large ships even if they turn off their tracking systems, my colleagues and I found that marine protected areas where industrial fishing is fully banned are largely succeeding at preventing poaching.

What marine protected areas aim to save

Picture a sea turtle gliding by as striped butterfly fish weave through coral branches. Or the deep blue of the open ocean, where tuna flash like silver and seabirds wheel overhead.

These habitats, where fish and other marine life breed and feed, are the treasures that marine protected areas aim to protect.

The value of marine protected areas for people and nature.

A major threat to these ecosystems is industrial fishing.

These vessels can operate worldwide and stay at sea for years at a time with visits from refrigerated cargo ships that ferry their catch to port. China has an extensive global fleet of ships that operate as far away as the coast of South America and other regions.

The global industrial fishing fleet – nearly half a million vessels – hauls in about 100 million metric tons of seafood each year. That’s about a fivefold increase since 1950, though it has been close to flat for the past 30 years. Today, more than one-third of commercial fish species are overfished, exceeding what population growth can replenish.

When well designed and enforced, marine protected areas can help to restore fish populations and marine habitats. My previous work shows they can even benefit nearby fisheries because the fish spill over into surrounding areas.

That’s why expanding marine protected areas is a cornerstone of international conservation policy. Nearly every country has pledged to protect 30% of the ocean by 2030.

Big promises – and big doubts

But what “protection” means can vary.

Some marine protected areas ban industrial fishing. These are the gold standard for conservation, and research shows they can be effective ways to increase the amount of sea life and diversity of species.

However, most marine protected areas don’t meet that standard. While governments report that more than 8% of the global ocean is protected, only about 3% is actually covered by industrial fishing bans. Many “protected” areas even allow bottom trawling, one of the most destructive fishing practices, although regulations are slowly changing.

The plentiful fish in better-protected areas can also attract poachers. In one high-profile case, a Chinese vessel was caught inside the Galápagos Marine Reserve with 300 tons of marine life, including 6,000 dead sharks, in 2017. This crew faced heavy fines and prison time. But how many others go unseen?

Shining a light on the ‘dark fleet’

Much of what the world knows about global industrial fishing comes from the automatic identification system, or AIS, which many ships are required to use. This system broadcasts their location every few seconds, primarily to reduce the risk of collisions at sea. Using artificial intelligence, researchers can analyze movement patterns in these messages to estimate when and where fishing is happening.

But AIS has blind spots. Captains can turn it off, tamper with data or avoid using it entirely. Coverage is also spotty in busy areas, such as Southeast Asia.

New satellite technologies are helping to see into those blind spots. Synthetic aperture radar can detect vessels even when they’re not transmitting AIS. It works by sending radar pulses to the ocean surface and measuring what bounces back. Paired with artificial intelligence, it reveals previously invisible activity.

Synthetic aperture radar still has limits – primarily difficulty detecting small boats and less frequent coverage than AIS – but it’s still a leap forward. In one study of coastal areas using both technologies, we found in about 75% of instances fishing vessels detected by synthetic aperture radar were not being tracked by AIS.

New global analysis shows what really happens

Two studies published in the journal Science on July 24, 2025, use these satellite datasets to track industrial fishing activity in marine protected areas.

Our study looked just at those marine protected areas where all industrial fishing is explicitly banned by law.

We combined AIS vessel tracking, synthetic aperture radar satellite imagery, official marine protected area rules, and implementation dates showing exactly when those bans took effect. The analysis covers nearly 1,400 marine protected areas spanning about 3 million square miles (7.9 million square kilometers) where industrial fishing is explicitly prohibited.

Two images show lots of fishing activity around the edges of the protected area, but little activity inside it.
AIS transponder signals over 2017-2021 (top) and synthetic aperture radar data (bottom) both show industrial fishing activity (yellow) mostly avoiding Carrington Point State Marine Reserve, a protected area off California’s Santa Rosa Island.
Jennifer Raynor, Sara Orofino and Gavin McDonald

The results were striking:

  • Most of these protected areas showed little to no signs of industrial fishing.
  • We detected about five fishing vessels per 100,000 square kilometers on average in these areas, compared to 42 on average in unprotected coastal areas.
  • 96% had less than one day per year of alleged illegal fishing effort.

The second study uses the same AIS and synthetic aperture radar data to examine a broader set of marine protected areas – including many that explicitly allow fishing. They document substantial fishing activity in these areas, with about eight times more detections than in the protected areas that ban industrial fishing.

Combined, these two studies lead to a clear conclusion: Marine protected areas with weak regulations see substantial industrial fishing, but where bans are in place, they’re largely respected.

We can’t tell whether these fishing bans are effective because they’re well enforced or simply because they were placed where little fishing happened anyway. Still, when violations do occur, this system offers a way for enforcement agencies to detect them.

A reason for optimism

These technological advances in vessel tracking have the potential to reshape marine law enforcement by significantly reducing the costs of monitoring.

Agencies such as national navies and coast guards no longer need to rely solely on costly physical patrols over huge areas. With tools such as the Global Fishing Watch map, which makes vessel tracking data freely available to the public, they can monitor activity remotely and focus patrol efforts where they’re needed most.

That can also have a deterrent effect. In Costa Rica’s Cocos Island National Park, evidence of illegal fishing activity decreased substantially after the rollout of satellite and radar-based vessel tracking. Similar efforts are strengthening enforcement in the Galapagos Islands and Mexico’s Revillagigedo National Park.

Beyond marine protected areas, these technologies also have the potential to support tracking a broad range of human activities, such as oil slicks and deep-sea mining, making companies more accountable in how they use the ocean.The Conversation

About the Author:

Jennifer Raynor, Assistant Professor of Natural Resource Economics, University of Wisconsin-Madison

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Some pro athletes keep getting better as they age − neuroscience can explain how they stay sharp

By Fiddy Davis Jaihind Jothikaran, Hope College 

In a world where sports are dominated by youth and speed, some athletes in their late 30s and even 40s are not just keeping up – they are thriving.

Novak Djokovic is still outlasting opponents nearly half his age on tennis’s biggest stages. LeBron James continues to dictate the pace of NBA games, defending centers and orchestrating plays like a point guard. Allyson Felix won her 11th Olympic medal in track and field at age 35. And Tom Brady won a Super Bowl at 43, long after most NFL quarterbacks retire.

The sustained excellence of these athletes is not just due to talent or grit – it’s biology in action. Staying at the top of their game reflects a trainable convergence of brain, body and mindset. I’m a performance scientist and a physical therapist who has spent over two decades studying how athletes train, taper, recover and stay sharp. These insights aren’t just for high-level athletes – they hold true for anyone navigating big life changes or working to stay healthy.

Increasingly, research shows that the systems that support high performance – from motor control to stress regulation, to recovery – are not fixed traits but trainable capacities. In a world of accelerating change and disruption, the ability to adapt to new changes may be the most important skill of all. So, what makes this adaptability possible – biologically, cognitively and emotionally?

The amygdala and prefrontal cortex

Neuroscience research shows that with repeated exposure to high-stakes situations, the brain begins to adapt. The prefrontal cortex – the region most responsible for planning, focus and decision-making – becomes more efficient in managing attention and making decisions, even under pressure.

During stressful situations, such as facing match point in a Grand Slam final, this area of the brain can help an athlete stay composed and make smart choices – but only if it’s well trained.

In contrast, the amygdala, our brain’s threat detector, can hijack performance by triggering panic, freezing motor responses or fueling reckless decisions. With repeated exposure to high-stakes moments, elite athletes gradually reshape this brain circuit.

They learn to tune down amygdala reactivity and keep the prefrontal cortex online, even when the pressure spikes. This refined brain circuitry enables experienced performers to maintain their emotional control.

Creating a brain-body loop

Brain-derived neurotrophic factor, or BDNF, is a molecule that supports adapting to changes quickly. Think of it as fertilizer for the brain. It enhances neuroplasticity: the brain’s ability to rewire itself through experience and repetition. This rewiring helps athletes build and reinforce the patterns of connections between brain cells to control their emotion, manage their attention and move with precision.

BDNF levels increase with intense physical activity, mental focus and deliberate practice, especially when combined with recovery strategies such as sleep and deep breathing.

Elevated BDNF levels are linked to better resilience against stress and may support faster motor learning, which is the process of developing or refining movement patterns.

For example, after losing a set, Djokovic often resets by taking deep, slow breaths – not just to calm his nerves, but to pause and regain control. This conscious breathing helps him restore focus and likely quiets the stress signals in his brain.

In moments like these, higher BDNF availability likely allows him to regulate his emotions and recalibrate his motor response, helping him to return to peak performance faster than his opponent.

Rewiring your brain

In essence, athletes who repeatedly train and compete in pressure-filled environments are rewiring their brain to respond more effectively to those demands. This rewiring, from repeated exposures, helps boost BDNF levels and in turn keeps the prefrontal cortex sharp and dials down the amygdala’s tendency to overreact.

This kind of biological tuning is what scientists call cognitive reserve and allostasis – the process the body uses to make changes in response to stress or environmental demands to remain stable. It helps the brain and body be flexible, not fragile.

Importantly, this adaptation isn’t exclusive to elite athletes. Studies on adults of all ages show that regular physical activity – particularly exercises that challenge both body and mind – can raise BDNF levels, improve the brain’s ability to adapt and respond to new challenges, and reduce stress reactivity.

Programs that combine aerobic movement with coordination tasks, such as dancing, complex drills or even fast-paced walking while problem-solving have been shown to preserve skills such as focus, planning, impulse control and emotional regulation over time.

After an intense training session or a match, you will often see athletes hopping on a bike or spending some time in the pool. These low-impact, gentle movements, known as active recovery, help tone down the nervous system gradually.

Outside of active recovery, sleep is where the real reset and repair happen. Sleep aids in learning and strengthens the neural connections challenged during training and competition.

Over time, this convergence creates a trainable loop between the brain and body that is better equipped to adapt, recover and perform.

Lessons beyond sport

While the spotlight may shine on sporting arenas, you don’t need to be a pro athlete to train these same skills.

The ability to perform under pressure is a result of continuing adaptation. Whether you’re navigating a career pivot, caring for family members, or simply striving to stay mentally sharp as the world changes, the principles are the same: Expose yourself to challenges, regulate stress and recover deliberately.

While speed, agility and power may decline with age, some sport-specific skills such as anticipation, decision-making and strategic awareness actually improve. Athletes with years of experience develop faster mental models of how a play will unfold, which allows them to make better and faster choices with minimal effort. This efficiency is a result of years of reinforcing neural circuits that doesn’t immediately vanish with age. This is one reason experienced athletes often excel even if they are well past their physical prime.

Physical activity, especially dynamic and coordinated movement, boosts the brain’s capacity to adapt. So does learning new skills, practicing mindfulness and even rehearsing performance under pressure. In daily life, this might be a surgeon practicing a critical procedure in simulation, a teacher preparing for a tricky parent meeting, or a speaker practicing a high-stakes presentation to stay calm and composed when it counts. These aren’t elite rituals – they’re accessible strategies for building resilience, motor efficiency and emotional control.

Humans are built to adapt – with the right strategies, you can sustain excellence at any stage of life.The Conversation

About the Author:

Fiddy Davis Jaihind Jothikaran, Associate Professor of Kinesiology, Hope College

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Data centers consume massive amounts of water – companies rarely tell the public exactly how much

By Peyton McCauley, University of Wisconsin-Milwaukee and Melissa Scanlan, University of Wisconsin-Milwaukee As demand for artificial intelligence technology boosts construction and proposed construction of data centers around the world, those computers require not just electricity and land, but also a significant amount of water. Data centers use water directly, with cooling water pumped through pipes in and around the computer equipment. They also use water indirectly, through the water required to produce the electricity to power the facility. The amount of water used to produce electricity increases dramatically when the source is fossil fuels compared with solar or wind.

A 2024 report from the Lawrence Berkeley National Laboratory estimated that in 2023, U.S. data centers consumed 17 billion gallons (64 billion liters) of water, and projects that by 2028, those figures could double – or even quadruple. The same report estimated that in 2023, U.S. data centers consumed an additional 211 billion gallons (800 billion liters) of water indirectly through the electricity that powers them. But that is just an estimate in a fast-changing industry.

We are researchers in water law and policy based on the shores of Lake Michigan. Technology companies are eyeing the Great Lakes region to host data centers, including one proposed for Port Washington, Wisconsin, which could be one of the largest in the country. The Great Lakes region offers a relatively cool climate and an abundance of water, making the region an attractive location for hot and thirsty data centers.

The Great Lakes are an important, binational resource that more than 40 million people depend on for their drinking water and supports a US$6 trillion regional economy. Data centers compete with these existing uses and may deplete local groundwater aquifers.

Our analysis of public records, government documents and sustainability reports compiled by top data center companies has found that technology companies don’t always reveal how much water their data centers use. In a forthcoming Rutgers Computer and Technology Law Journal article, we walk through our methods and findings using these resources to uncover the water demands of data centers.

In general, corporate sustainability reports offered the most access and detail – including that in 2024, one data center in Iowa consumed 1 billion (3.8 billion liters) gallons of water – enough to supply all of Iowa’s residential water for five days.

The computer processors in data centers generate lots of heat while doing their work.

How do data centers use water?

The servers and routers in data centers work hard and generate a lot of heat. To cool them down, data centers use large amounts of water – in some cases over 25% of local community water supplies. In 2023, Google reported consuming over 6 billion gallons of water (nearly 23 billion liters) to cool all its data centers.

In some data centers, the water is used up in the cooling process. In an evaporative cooling system, pumps push cold water through pipes in the data center. The cold water absorbs the heat produced by the data center servers, turning into steam that is vented out of the facility. This system requires a constant supply of cold water.

In closed-loop cooling systems, the cooling process is similar, but rather than venting steam to the air, air-cooled chillers cool down the hot water. The cooled water is then recirculated to cool the facility again. This does not require constant addition of large volumes of water, but it uses a lot more energy to run the chillers. The actual numbers showing those differences, which likely vary by the facility, are not publicly available.

One key way to evaluate water use is the amount of water that is considered “consumed,” meaning it is withdrawn from the local water supply and used up – for instance, evaporated as steam – and not returned to the ecosystem.

For information, we first looked to government data, such as that kept by municipal water systems, but the process of getting all the necessary data can be onerous and time-consuming, with some denying data access due to confidentiality concerns. So we turned to other sources to uncover data center water use.

Sustainability reports provide insight

Many companies, especially those that prioritize sustainability, release publicly available reports about their environmental and sustainability practices, including water use. We focused on six top tech companies with data centers: Amazon, Google, Microsoft, Meta, Digital Realty and Equinix. Our findings revealed significant variability in both how much water the companies’ data centers used, and how much specific information the companies’ reports actually provided.

Sustainability reports offer a valuable glimpse into data center water use. But because the reports are voluntary, different companies report different statistics in ways that make them hard to combine or compare. Importantly, these disclosures do not consistently include the indirect water consumption from their electricity use, which the Lawrence Berkeley Lab estimated was 12 times greater than the direct use for cooling in 2023. Our estimates highlighting specific water consumption reports are all related to cooling.

Amazon releases annual sustainability reports, but those documents do not disclose how much water the company uses. Microsoft provides data on its water demands for its overall operations, but does not break down water use for its data centers. Meta does that breakdown, but only in a companywide aggregate figure. Google provides individual figures for each data center.

In general, the five companies we analyzed that do disclose water usage show a general trend of increasing direct water use each year. Researchers attribute this trend to data centers.

A closer look at Google and Meta

To take a deeper look, we focused on Google and Meta, as they provide some of the most detailed reports of data center water use.

Data centers make up significant proportions of both companies’ water use. In 2023, Meta consumed 813 million gallons of water globally (3.1 billion liters) – 95% of which, 776 million gallons (2.9 billion liters), was used by data centers.

For Google, the picture is similar, but with higher numbers. In 2023, Google operations worldwide consumed 6.4 billion gallons of water (24.2 billion liters), with 95%, 6.1 billion gallons (23.1 billion liters), used by data centers.

Google reports that in 2024, the company’s data center in Council Bluffs, Iowa, consumed 1 billion gallons of water (3.8 billion liters), the most of any of its data centers.

The Google data center using the least that year was in Pflugerville, Texas, which consumed 10,000 gallons (38,000 liters) – about as much as one Texas home would use in two months. That data center is air-cooled, not water-cooled, and consumes significantly less water than the 1.5 million gallons (5.7 million liters) at an air-cooled Google data center in Storey County, Nevada. Because Google’s disclosures do not pair water consumption data with the size of centers, technology used or indirect water consumption from power, these are simply partial views, with the big picture obscured.

Given society’s growing interest in AI, the data center industry will likely continue its rapid expansion. But without a consistent and transparent way to track water consumption over time, the public and government officials will be making decisions about locations, regulations and sustainability without complete information on how these massive companies’ hot and thirsty buildings will affect their communities and their environments.The Conversation

About the Authors:

Peyton McCauley, Water Policy Specialist, Sea Grant UW Water Science-Policy Fellow, University of Wisconsin-Milwaukee and Melissa Scanlan, Professor and Director of the Center for Water Policy, School of Freshwater Sciences, University of Wisconsin-Milwaukee

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Speculators push Brazilian Real Bets rise to 5-Week High, US Dollar Index Bets edge up

By InvestMacro

Speculators OI FX Futures COT Chart

Here are the latest charts and statistics for the Commitment of Traders (COT) data published by the Commodities Futures Trading Commission (CFTC).

The latest COT data is updated through Tuesday August 12th and shows a quick view of how large market participants (for-profit speculators and commercial traders) were positioned in the futures markets. All currency positions are in direct relation to the US dollar where, for example, a bet for the euro is a bet that the euro will rise versus the dollar while a bet against the euro will be a bet that the euro will decline versus the dollar.

Weekly Speculator Changes led by Brazilian Real & US Dollar Index

Speculators Nets FX Futures COT Chart
The COT currency market speculator bets were overall lower this week as just four out of the eleven currency markets we cover had higher positioning while the other seven markets had lower speculator contracts.

Leading the gains for the currency markets was the Brazilian Real (14,984 contracts) with the US Dollar Index (783 contracts), Bitcoin (759 contracts) and the New Zealand Dollar (146 contracts) also showing positive weeks.

The currencies seeing declines in speculator bets on the week were the Canadian Dollar (-10,657 contracts), the Japanese Yen (-7,772 contracts), the Australian Dollar (-4,345 contracts), the British Pound (-5,790 contracts), the Mexican Peso (-6,816 contracts), the Swiss Franc (-666 contracts) and with the EuroFX (-528 contracts) also registering lower bets on the week.

Brazilian Real Bets rise to 5-Week High, US Dollar Index Bets edge up

Leading the speculator changes this week for the major currency markets was the Brazilian Real, which saw a gain of almost 15,000 speculator contracts on the week. This was the second straight week of gains for the Brazilian Real and the third time out of the last four weeks that speculator bets have increased. Overall, the Real position is at +39,582 contracts, which is the best mark over the last five weeks. The Real has been at least +20,000 or above speculator contracts for the last 24 weeks in a row.

The Brazilian Real exchange rate versus the U.S. Dollar rose for a second straight week this week and continues to be in an uptrend after falling to a record low to end December. Overall, for the year of 2025, the Brazilian Real is up by over 12% while since the December bottoming, the Brazilian Real is up by over 16.65%.

Next up, the U.S. Dollar Index saw a small edge higher in their weekly speculator bets. The U.S. Dollar Index speculator positions rose by 783 contracts this week following two weeks of decreases. At the moment, the U.S. Dollar Index standing is at -6,247 contracts, and overall the USD positioning has now been in a negative or bearish level for nine consecutive weeks with a speculator strength score of just 1.8% (out of a 0 to 100 range), illustrating the current weakness of the U.S. Dollar.

In the exchange rate markets, the U.S. Dollar Index fell for a second straight week and closed the week at 97.695 exchange rate. The dollar had rebounded all the way up to the 100 level a couple of weeks ago but found resistance and got pushed back down. Overall, since the beginning of the year, the U.S. Dollar Index is down by over 12%.

British Pound Sterling led weekly market prices

The major currency market prices did not see much movement this week with no currency rising or falling by over 1%. The leader in price gains was the British Pound Sterling which was higher by 0.78% on the week. The Euro came in next with a rise of 0.50%, followed by the Brazilian Real at 0.44%. Bitcoin was higher by 0.42%, the Japanese Yen was slightly higher by 0.35%, followed by the Swiss Franc at 0.20%.

On the downside, the Australian Dollar was slightly lower at -0.23%, followed by the US Dollar Index, which saw a dip by -0.33%. The Canadian Dollar was at -0.41%, the New Zealand Dollar at -0.43%, and the biggest loser in the week was the Mexican Peso at -0.77%.


Currencies Data:

Speculators FX Futures COT Data Table
Legend: Open Interest | Speculators Current Net Position | Weekly Specs Change | Specs Strength Score compared to last 3-Years (0-100 range)


Strength Scores led by Brazilian Real & EuroFX

Speculators Strength Scores FX Futures COT Chart
COT Strength Scores (a normalized measure of Speculator positions over a 3-Year range, from 0 to 100 where above 80 is Extreme-Bullish and below 20 is Extreme-Bearish) showed that the Brazilian Real (77 percent) and the EuroFX (73 percent) lead the currency markets this week. The Japanese Yen (71 percent), Mexican Peso (60 percent) and the New Zealand Dollar (59 percent) come in as the next highest in the weekly strength scores.

On the downside, the US Dollar Index (2 percent), the British Pound (14 percent) and the Australian Dollar (14 percent) come in at the lowest strength levels currently and are in Extreme-Bearish territory (below 20 percent).

3-Year Strength Statistics:
US Dollar Index (1.8 percent) vs US Dollar Index previous week (0.0 percent)
EuroFX (72.7 percent) vs EuroFX previous week (72.9 percent)
British Pound Sterling (13.8 percent) vs British Pound Sterling previous week (16.5 percent)
Japanese Yen (71.1 percent) vs Japanese Yen previous week (73.3 percent)
Swiss Franc (44.1 percent) vs Swiss Franc previous week (45.4 percent)
Canadian Dollar (48.2 percent) vs Canadian Dollar previous week (53.0 percent)
Australian Dollar (13.9 percent) vs Australian Dollar previous week (17.0 percent)
New Zealand Dollar (59.0 percent) vs New Zealand Dollar previous week (58.9 percent)
Mexican Peso (60.0 percent) vs Mexican Peso previous week (63.5 percent)
Brazilian Real (76.7 percent) vs Brazilian Real previous week (64.5 percent)
Bitcoin (37.0 percent) vs Bitcoin previous week (20.9 percent)


Bitcoin, Peso & EuroFX top the 6-Week Strength Trends

Speculators Trends FX Futures COT Chart
COT Strength Score Trends (or move index, calculates the 6-week changes in strength scores) showed that the Bitcoin (21 percent), the Mexican Peso (3 percent) and the EuroFX (3 percent) lead the past six weeks trends for the currencies.

The British Pound (-34 percent) leads the downside trend scores currently with the Japanese Yen (-15 percent), Australian Dollar (-13 percent) and the Canadian Dollar (-12 percent) following next with lower trend scores.

3-Year Strength Trends:
US Dollar Index (-4.6 percent) vs US Dollar Index previous week (-2.3 percent)
EuroFX (3.0 percent) vs EuroFX previous week (1.8 percent)
British Pound Sterling (-33.5 percent) vs British Pound Sterling previous week (-32.2 percent)
Japanese Yen (-14.6 percent) vs Japanese Yen previous week (-13.8 percent)
Swiss Franc (-8.5 percent) vs Swiss Franc previous week (-13.0 percent)
Canadian Dollar (-12.1 percent) vs Canadian Dollar previous week (-11.9 percent)
Australian Dollar (-12.6 percent) vs Australian Dollar previous week (-7.8 percent)
New Zealand Dollar (-10.2 percent) vs New Zealand Dollar previous week (-8.8 percent)
Mexican Peso (3.4 percent) vs Mexican Peso previous week (8.5 percent)
Brazilian Real (-10.3 percent) vs Brazilian Real previous week (-16.3 percent)
Bitcoin (21.5 percent) vs Bitcoin previous week (14.0 percent)


Individual COT Forex Markets:

US Dollar Index Futures:

US Dollar Index Forex Futures COT ChartThe US Dollar Index large speculator standing this week totaled a net position of -6,247 contracts in the data reported through Tuesday. This was a weekly advance of 783 contracts from the previous week which had a total of -7,030 net contracts.

This week’s current strength score (the trader positioning range over the past three years, measured from 0 to 100) shows the speculators are currently Bearish-Extreme with a score of 1.8 percent. The commercials are Bullish-Extreme with a score of 96.4 percent and the small traders (not shown in chart) are Bearish with a score of 45.7 percent.

Price Trend-Following Model: Downtrend

Our weekly trend-following model classifies the current market price position as: Downtrend.

US DOLLAR INDEX StatisticsSPECULATORSCOMMERCIALSSMALL TRADERS
– Percent of Open Interest Longs:41.937.413.8
– Percent of Open Interest Shorts:62.420.510.1
– Net Position:-6,2475,1221,125
– Gross Longs:12,72911,3704,202
– Gross Shorts:18,9766,2483,077
– Long to Short Ratio:0.7 to 11.8 to 11.4 to 1
NET POSITION TREND:
– Strength Index Score (3 Year Range Pct):1.896.445.7
– Strength Index Reading (3 Year Range):Bearish-ExtremeBullish-ExtremeBearish
NET POSITION MOVEMENT INDEX:
– 6-Week Change in Strength Index:-4.60.026.6

 


Euro Currency Futures:

Euro Currency Futures COT ChartThe Euro Currency large speculator standing this week totaled a net position of 115,431 contracts in the data reported through Tuesday. This was a weekly fall of -528 contracts from the previous week which had a total of 115,959 net contracts.

This week’s current strength score (the trader positioning range over the past three years, measured from 0 to 100) shows the speculators are currently Bullish with a score of 72.7 percent. The commercials are Bearish with a score of 24.3 percent and the small traders (not shown in chart) are Bullish-Extreme with a score of 83.5 percent.

Price Trend-Following Model: Uptrend

Our weekly trend-following model classifies the current market price position as: Uptrend.

EURO Currency StatisticsSPECULATORSCOMMERCIALSSMALL TRADERS
– Percent of Open Interest Longs:29.955.511.6
– Percent of Open Interest Shorts:15.975.85.4
– Net Position:115,431-167,06351,632
– Gross Longs:246,299458,03796,093
– Gross Shorts:130,868625,10044,461
– Long to Short Ratio:1.9 to 10.7 to 12.2 to 1
NET POSITION TREND:
– Strength Index Score (3 Year Range Pct):72.724.383.5
– Strength Index Reading (3 Year Range):BullishBearishBullish-Extreme
NET POSITION MOVEMENT INDEX:
– 6-Week Change in Strength Index:3.0-2.2-3.2

 


British Pound Sterling Futures:

British Pound Sterling Futures COT ChartThe British Pound Sterling large speculator standing this week totaled a net position of -39,093 contracts in the data reported through Tuesday. This was a weekly fall of -5,790 contracts from the previous week which had a total of -33,303 net contracts.

This week’s current strength score (the trader positioning range over the past three years, measured from 0 to 100) shows the speculators are currently Bearish-Extreme with a score of 13.8 percent. The commercials are Bullish with a score of 78.6 percent and the small traders (not shown in chart) are Bullish with a score of 69.7 percent.

Price Trend-Following Model: Uptrend

Our weekly trend-following model classifies the current market price position as: Uptrend.

BRITISH POUND StatisticsSPECULATORSCOMMERCIALSSMALL TRADERS
– Percent of Open Interest Longs:34.150.514.0
– Percent of Open Interest Shorts:52.234.112.4
– Net Position:-39,09335,5173,576
– Gross Longs:73,736109,21730,321
– Gross Shorts:112,82973,70026,745
– Long to Short Ratio:0.7 to 11.5 to 11.1 to 1
NET POSITION TREND:
– Strength Index Score (3 Year Range Pct):13.878.669.7
– Strength Index Reading (3 Year Range):Bearish-ExtremeBullishBullish
NET POSITION MOVEMENT INDEX:
– 6-Week Change in Strength Index:-33.532.9-18.9

 


Japanese Yen Futures:

Japanese Yen Forex Futures COT ChartThe Japanese Yen large speculator standing this week totaled a net position of 74,234 contracts in the data reported through Tuesday. This was a weekly decrease of -7,772 contracts from the previous week which had a total of 82,006 net contracts.

This week’s current strength score (the trader positioning range over the past three years, measured from 0 to 100) shows the speculators are currently Bullish with a score of 71.1 percent. The commercials are Bearish with a score of 32.3 percent and the small traders (not shown in chart) are Bearish with a score of 43.9 percent.

Price Trend-Following Model: Strong Downtrend

Our weekly trend-following model classifies the current market price position as: Strong Downtrend.

JAPANESE YEN StatisticsSPECULATORSCOMMERCIALSSMALL TRADERS
– Percent of Open Interest Longs:46.941.910.0
– Percent of Open Interest Shorts:25.863.010.1
– Net Position:74,234-73,895-339
– Gross Longs:164,693147,17035,172
– Gross Shorts:90,459221,06535,511
– Long to Short Ratio:1.8 to 10.7 to 11.0 to 1
NET POSITION TREND:
– Strength Index Score (3 Year Range Pct):71.132.343.9
– Strength Index Reading (3 Year Range):BullishBearishBearish
NET POSITION MOVEMENT INDEX:
– 6-Week Change in Strength Index:-14.619.4-53.9

 


Swiss Franc Futures:

Swiss Franc Forex Futures COT ChartThe Swiss Franc large speculator standing this week totaled a net position of -28,043 contracts in the data reported through Tuesday. This was a weekly decrease of -666 contracts from the previous week which had a total of -27,377 net contracts.

This week’s current strength score (the trader positioning range over the past three years, measured from 0 to 100) shows the speculators are currently Bearish with a score of 44.1 percent. The commercials are Bullish with a score of 53.7 percent and the small traders (not shown in chart) are Bullish with a score of 56.8 percent.

Price Trend-Following Model: Uptrend

Our weekly trend-following model classifies the current market price position as: Uptrend.

SWISS FRANC StatisticsSPECULATORSCOMMERCIALSSMALL TRADERS
– Percent of Open Interest Longs:7.675.516.3
– Percent of Open Interest Shorts:42.434.222.7
– Net Position:-28,04333,224-5,181
– Gross Longs:6,09160,68913,086
– Gross Shorts:34,13427,46518,267
– Long to Short Ratio:0.2 to 12.2 to 10.7 to 1
NET POSITION TREND:
– Strength Index Score (3 Year Range Pct):44.153.756.8
– Strength Index Reading (3 Year Range):BearishBullishBullish
NET POSITION MOVEMENT INDEX:
– 6-Week Change in Strength Index:-8.518.7-31.0

 


Canadian Dollar Futures:

Canadian Dollar Forex Futures COT ChartThe Canadian Dollar large speculator standing this week totaled a net position of -90,077 contracts in the data reported through Tuesday. This was a weekly reduction of -10,657 contracts from the previous week which had a total of -79,420 net contracts.

This week’s current strength score (the trader positioning range over the past three years, measured from 0 to 100) shows the speculators are currently Bearish with a score of 48.2 percent. The commercials are Bullish with a score of 52.8 percent and the small traders (not shown in chart) are Bearish with a score of 34.0 percent.

Price Trend-Following Model: Weak Uptrend

Our weekly trend-following model classifies the current market price position as: Weak Uptrend.

CANADIAN DOLLAR StatisticsSPECULATORSCOMMERCIALSSMALL TRADERS
– Percent of Open Interest Longs:9.573.610.6
– Percent of Open Interest Shorts:50.231.312.1
– Net Position:-90,07793,571-3,494
– Gross Longs:20,898162,83323,352
– Gross Shorts:110,97569,26226,846
– Long to Short Ratio:0.2 to 12.4 to 10.9 to 1
NET POSITION TREND:
– Strength Index Score (3 Year Range Pct):48.252.834.0
– Strength Index Reading (3 Year Range):BearishBullishBearish
NET POSITION MOVEMENT INDEX:
– 6-Week Change in Strength Index:-12.114.0-17.1

 


Australian Dollar Futures:

Australian Dollar Forex Futures COT ChartThe Australian Dollar large speculator standing this week totaled a net position of -87,905 contracts in the data reported through Tuesday. This was a weekly decrease of -4,345 contracts from the previous week which had a total of -83,560 net contracts.

This week’s current strength score (the trader positioning range over the past three years, measured from 0 to 100) shows the speculators are currently Bearish-Extreme with a score of 13.9 percent. The commercials are Bullish-Extreme with a score of 80.1 percent and the small traders (not shown in chart) are Bullish with a score of 58.8 percent.

Price Trend-Following Model: Uptrend

Our weekly trend-following model classifies the current market price position as: Uptrend.

AUSTRALIAN DOLLAR StatisticsSPECULATORSCOMMERCIALSSMALL TRADERS
– Percent of Open Interest Longs:15.066.814.1
– Percent of Open Interest Shorts:66.317.611.9
– Net Position:-87,90584,2333,672
– Gross Longs:25,631114,39624,097
– Gross Shorts:113,53630,16320,425
– Long to Short Ratio:0.2 to 13.8 to 11.2 to 1
NET POSITION TREND:
– Strength Index Score (3 Year Range Pct):13.980.158.8
– Strength Index Reading (3 Year Range):Bearish-ExtremeBullish-ExtremeBullish
NET POSITION MOVEMENT INDEX:
– 6-Week Change in Strength Index:-12.610.9-1.1

 


New Zealand Dollar Futures:

New Zealand Dollar Forex Futures COT ChartThe New Zealand Dollar large speculator standing this week totaled a net position of -4,687 contracts in the data reported through Tuesday. This was a weekly gain of 146 contracts from the previous week which had a total of -4,833 net contracts.

This week’s current strength score (the trader positioning range over the past three years, measured from 0 to 100) shows the speculators are currently Bullish with a score of 59.0 percent. The commercials are Bearish with a score of 40.7 percent and the small traders (not shown in chart) are Bearish with a score of 39.3 percent.

Price Trend-Following Model: Weak Uptrend

Our weekly trend-following model classifies the current market price position as: Weak Uptrend.

NEW ZEALAND DOLLAR StatisticsSPECULATORSCOMMERCIALSSMALL TRADERS
– Percent of Open Interest Longs:23.157.97.9
– Percent of Open Interest Shorts:32.945.910.2
– Net Position:-4,6875,799-1,112
– Gross Longs:11,16027,9373,806
– Gross Shorts:15,84722,1384,918
– Long to Short Ratio:0.7 to 11.3 to 10.8 to 1
NET POSITION TREND:
– Strength Index Score (3 Year Range Pct):59.040.739.3
– Strength Index Reading (3 Year Range):BullishBearishBearish
NET POSITION MOVEMENT INDEX:
– 6-Week Change in Strength Index:-10.213.0-34.7

 


Mexican Peso Futures:

Mexican Peso Futures COT ChartThe Mexican Peso large speculator standing this week totaled a net position of 61,239 contracts in the data reported through Tuesday. This was a weekly lowering of -6,816 contracts from the previous week which had a total of 68,055 net contracts.

This week’s current strength score (the trader positioning range over the past three years, measured from 0 to 100) shows the speculators are currently Bullish with a score of 60.0 percent. The commercials are Bearish with a score of 40.9 percent and the small traders (not shown in chart) are Bearish with a score of 42.8 percent.

Price Trend-Following Model: Uptrend

Our weekly trend-following model classifies the current market price position as: Uptrend.

MEXICAN PESO StatisticsSPECULATORSCOMMERCIALSSMALL TRADERS
– Percent of Open Interest Longs:58.437.23.6
– Percent of Open Interest Shorts:24.872.81.6
– Net Position:61,239-64,8483,609
– Gross Longs:106,53967,8766,499
– Gross Shorts:45,300132,7242,890
– Long to Short Ratio:2.4 to 10.5 to 12.2 to 1
NET POSITION TREND:
– Strength Index Score (3 Year Range Pct):60.040.942.8
– Strength Index Reading (3 Year Range):BullishBearishBearish
NET POSITION MOVEMENT INDEX:
– 6-Week Change in Strength Index:3.4-2.6-9.0

 


Brazilian Real Futures:

Brazil Real Futures COT ChartThe Brazilian Real large speculator standing this week totaled a net position of 39,582 contracts in the data reported through Tuesday. This was a weekly boost of 14,984 contracts from the previous week which had a total of 24,598 net contracts.

This week’s current strength score (the trader positioning range over the past three years, measured from 0 to 100) shows the speculators are currently Bullish with a score of 76.7 percent. The commercials are Bearish with a score of 22.0 percent and the small traders (not shown in chart) are Bearish with a score of 40.5 percent.

Price Trend-Following Model: Strong Uptrend

Our weekly trend-following model classifies the current market price position as: Strong Uptrend.

BRAZIL REAL StatisticsSPECULATORSCOMMERCIALSSMALL TRADERS
– Percent of Open Interest Longs:57.534.74.2
– Percent of Open Interest Shorts:19.276.40.8
– Net Position:39,582-43,0693,487
– Gross Longs:59,38835,7884,287
– Gross Shorts:19,80678,857800
– Long to Short Ratio:3.0 to 10.5 to 15.4 to 1
NET POSITION TREND:
– Strength Index Score (3 Year Range Pct):76.722.040.5
– Strength Index Reading (3 Year Range):BullishBearishBearish
NET POSITION MOVEMENT INDEX:
– 6-Week Change in Strength Index:-10.38.114.1

 


Bitcoin Futures:

Bitcoin Crypto Futures COT ChartThe Bitcoin large speculator standing this week totaled a net position of -742 contracts in the data reported through Tuesday. This was a weekly increase of 759 contracts from the previous week which had a total of -1,501 net contracts.

This week’s current strength score (the trader positioning range over the past three years, measured from 0 to 100) shows the speculators are currently Bearish with a score of 37.0 percent. The commercials are Bullish with a score of 59.2 percent and the small traders (not shown in chart) are Bullish with a score of 69.7 percent.

Price Trend-Following Model: Uptrend

Our weekly trend-following model classifies the current market price position as: Uptrend.

BITCOIN StatisticsSPECULATORSCOMMERCIALSSMALL TRADERS
– Percent of Open Interest Longs:84.24.95.8
– Percent of Open Interest Shorts:86.84.53.6
– Net Position:-742118624
– Gross Longs:23,4381,3711,624
– Gross Shorts:24,1801,2531,000
– Long to Short Ratio:1.0 to 11.1 to 11.6 to 1
NET POSITION TREND:
– Strength Index Score (3 Year Range Pct):37.059.269.7
– Strength Index Reading (3 Year Range):BearishBullishBullish
NET POSITION MOVEMENT INDEX:
– 6-Week Change in Strength Index:21.5-26.48.8

 


Article By InvestMacroReceive our weekly COT Newsletter

*COT Report: The COT data, released weekly to the public each Friday, is updated through the most recent Tuesday (data is 3 days old) and shows a quick view of how large speculators or non-commercials (for-profit traders) were positioned in the futures markets.

The CFTC categorizes trader positions according to commercial hedgers (traders who use futures contracts for hedging as part of the business), non-commercials (large traders who speculate to realize trading profits) and nonreportable traders (usually small traders/speculators) as well as their open interest (contracts open in the market at time of reporting). See CFTC criteria here.

Speculator Extremes: Nasdaq-Mini & MSCI EAFE lead weekly Bullish Positions

By InvestMacro

The latest update for the weekly Commitment of Traders (COT) report was released by the Commodity Futures Trading Commission (CFTC) on Friday for data ending on August 12th.

This weekly Extreme Positions report highlights the Most Bullish and Most Bearish Positions for the speculator category. Extreme positioning in these markets can foreshadow strong moves in the underlying market.

To signify an extreme position, we use the Strength Index (also known as the COT Index) of each instrument, a common method of measuring COT data. The Strength Index is simply a comparison of current trader positions against the range of positions over the previous 3 years. We use over 80 percent as extremely bullish and under 20 percent as extremely bearish. (Compare Strength Index scores across all markets in the data table or cot leaders table)


Extreme Bullish Speculator Table


Here Are This Week’s Most Bullish Speculator Positions:

Nasdaq

Extreme Bullish Leader
The Nasdaq speculator position comes in as the most bullish extreme standing this week with the Nasdaq-Mini speculator level currently at a maximum 100 percent score of its 3-year range.

The six-week trend for the percent strength score totaled an increase by 22 percentage points this week. The overall net speculator position was a total of 42,312 net contracts this week with a gain of 8,476 contract in the weekly speculator bets.


Speculators or Non-Commercials Notes:

Speculators, classified as non-commercial traders by the CFTC, are made up of large commodity funds, hedge funds and other significant for-profit participants. The Specs are generally regarded as trend-followers in their behavior towards price action – net speculator bets and prices tend to go in the same directions. These traders often look to buy when prices are rising and sell when prices are falling. To illustrate this point, many times speculator contracts can be found at their most extremes (bullish or bearish) when prices are also close to their highest or lowest levels.

These extreme levels can be dangerous for the large speculators as the trade is most crowded, there is less trading ammunition still sitting on the sidelines to push the trend further and prices have moved a significant distance. When the trend becomes exhausted, some speculators take profits while others look to also exit positions when prices fail to continue in the same direction. This process usually plays out over many months to years and can ultimately create a reverse effect where prices start to fall and speculators start a process of selling when prices are falling.

 


MSCI EAFE MINI

Extreme Bullish Leader
The MSCI EAFE MINI speculator position comes next in the extreme standings this week. The MSCI EAFE-Mini speculator level is now at a 99 percent score of its 3-year range.

The six-week trend change for the percent strength score was 0 percentage points this week. The speculator position registered 7,794 net contracts this week with a weekly increase by 1,940 contracts in speculator bets.


Ultra U.S. Treasury Bonds

Extreme Bullish Leader
The Ultra U.S. Treasury Bonds speculator position comes up number three in the extreme standings this week. The Ultra Long T-Bond speculator level is at a 93 percent score of its 3-year range.

The six-week trend for the speculator strength score totaled a change of 7 percentage points this week. The overall speculator position was -209,132 net contracts this week with a rise of 19,235 contracts in the speculator bets.


Lean Hogs

Extreme Bullish Leader
The Lean Hogs speculator position rounds out the top four in this week’s bullish extreme standings. The Lean Hogs speculator level sits at a 83 percent score of its 3-year range. The six-week trend for the speculator strength score was a drop by -16 percentage points this week.

The speculator position was 73,927 net contracts this week with a small boost by 789 contracts in the weekly speculator bets.


Live Cattle



The Live Cattle speculator position rounds out the top five in this week’s bullish extreme standings. The Live Cattle speculator level sits at a 83 percent score of its 3-year range. The six-week trend for the speculator strength score was a gain of 2 percentage points this week.

The speculator position was 106,141 net contracts this week with a dip of -234 contracts in the weekly speculator bets.


Extreme Bearish Speculator Table


This Week’s Most Bearish Speculator Positions:

5-Year Bond

Extreme Bearish Leader
The 5-Year Bond speculator position comes in tied as the most bearish extreme standing this week as the 5-Year speculator level sits at a 0 percent score of its 3-year range.

The six-week trend for the speculator strength score was a decline of -4 percentage points this week. The overall speculator position was -2,566,369 net contracts this week with a drop by -29,492 contracts in the speculator bets.


WTI Crude Oil

Extreme Bearish Leader
The WTI Crude Oil speculator position comes in tied for the most bearish extreme standing on the week. The WTI Crude speculator level is at a 0 percent score of its 3-year range.

The six-week trend for the speculator strength score was a decrease by -51 percentage points this week. The speculator position was 116,742 net contracts this week with a reduction by -25,087 contracts in the weekly speculator bets.


US Dollar Index

Extreme Bearish Leader
The US Dollar Index speculator position comes in as third most bearish extreme standing of the week with the USD Index speculator level resides at a 2 percent score of its 3-year range.

The six-week trend for the speculator strength score was -5 percentage points this week. The overall speculator position was -6,247 net contracts this week with a gain of 783 contracts in the speculator bets.


Sugar

Extreme Bearish Leader
The Sugar speculator position comes in as this week’s fourth most bearish extreme standing. The Sugar speculator level is at a 2 percent score of its 3-year range.

The six-week trend change for the speculator strength score was 0 percentage points this week. The speculator position was -68,512 net contracts this week with a boost by 8,460 contracts in the weekly speculator bets.


2-Year Bond

Extreme Bearish Leader
Next, the 2-Year Bond speculator position comes in as the fifth most bearish extreme standing for this week. The 2-Year speculator level is at a 9 percent score of its 3-year range.

The six-week trend for the speculator strength score was a dip by -8 percentage points this week. The speculator position was -1,379,597 net contracts this week with a drop by -54,074 contracts in the weekly speculator bets.


Article By InvestMacroReceive our weekly COT Newsletter

*COT Report: The COT data, released weekly to the public each Friday, is updated through the most recent Tuesday (data is 3 days old) and shows a quick view of how large speculators or non-commercials (for-profit traders) were positioned in the futures markets.

The CFTC categorizes trader positions according to commercial hedgers (traders who use futures contracts for hedging as part of the business), non-commercials (large traders who speculate to realize trading profits) and nonreportable traders (usually small traders/speculators) as well as their open interest (contracts open in the market at time of reporting). See CFTC criteria here.

Week Ahead: US30 faces Jackson Hole & retail earnings showdown

By ForexTime 

  • US30 ↑ 6% year-to-date, futures pointing to fresh ATH
  • Home Depot + Walmart = 7.3% of US30 weight 
  • Jackson Hole Symposium + US data could trigger more volatility
  • Technical levels: 45,500, 45,000 & 44,000  

A cocktail of high-risk events may serve up fresh trading opportunities in the week ahead.

All eyes will be on the annual Jackson Hole Economic Symposium, key data and earnings from the largest retail companies in the United States:

Monday, 18th August 

  • CAD: Canada housing starts
  • JP225: Japan tertiary industry index
  • SG20: Singapore trade

Tuesday, 19th August 

  • AUD: Australia consumer confidence
  • CAD: Canada CPI
  • US30: Home Depot earnings

Wednesday, 20th August 

  • CN50: China loan prime rates
  • EUR: Eurozone CPI
  • JP225: Japan trade, machinery orders
  • NZD: New Zealand rate decision
  • GBP: UK CPI
  • USDInd:  US FOMC meeting minutes, Fed President Raphael Bostic speech

Thursday, 21st August 

  • EU50: Eurozone HCOB manufacturing PMI, consumer confidence
  • GER40: Germany HCOB manufacturing PMI
  • JPY: Japan S&P Global manufacturing PMI
  • UK100: UK S&P Global manufacturing PMI
  • US30: US initial jobless claims, Conference Board leading index, existing home sales, S&P Global manufacturing PMI, Walmart earnings.

Friday, 22nd August 

  • CAD: Canada retail sales
  • GER40: Germany GDP
  • JPY: Japan CPI
  • GBP: UK retail sales
  • US30: Fed Chair Powell speech at Jackson Hole

FXTM’s US30 is up almost 6% year-to-date, with futures pointing to a fresh all-time high when US markets open this afternoon.

Imagen
us30 w1w

Note: FXTM’s US30 tracks the benchmark Dow Jones Industrial Average index.

US equities appear to be recovering from the inflation-induced selloff after US PPI data accelerated in July by the most in three years. Still, traders are pricing in a 93% probability of a Fed cut by September.

 

Here are 3 factors that may rock the US30:

 

1) Jackson Hole Economic Symposium 

This is an annual event organized by the Kansas City Fed in Jackson Hole, Wyoming, and will be held from August 21st – August 23rd.

Anything discussed during the symposium could trigger market volatility, especially if it has to do with monetary policy. The spotlight shines on Jerome Powell on Friday amid repeated calls from President Donald Trump to cut interest rates. 

  • Should Powell strike a dovish note and signal that the Fed will cut rates in September, the US30 could push higher.
  • If Powell expresses concern over inflation risks and sounds more hawkish, this may weigh on the US30 as traders cut back Fed cut bets.

 

2) Home Depot & Walmart earnings

Earnings from two behemoths in the US retail industry could provide key insight into the strength of consumer spending in the face of Trump’s tariffs.

  • Home Depot releases its earnings before US markets open on Tuesday, 19th August, and accounts for 5.5% of the US30 index. 

     

  • Walmart reveals its Q2 earnings before US markets open on Thursday, 21st August, and accounts for 1.4% of the US30 index. 

Ultimately, a positive set of earnings from these retail giants may boost confidence in the US economy – supporting the US30 as risk sentiment jumps. If earnings disappoint, the US30 may dip, but losses could be cushioned by Fed cut bets.

Note: Beyond earnings, watch out for the FOMC meeting minutes on Wednesday, PMIs on Thursday, all of which could influence the US30 index. 

 

3) Technical forces

The US30 has experienced a bullish breakout above resistance at 45,000. 

Prices are trading above the 50, 100, and 200-day SMA. However, the Relative Strength Index (RSI) is venturing close to overbought territory.

  • Should 45,000 prove reliable support regions, prices may venture toward fresh all-time highs at 45,500 and 46,000. 
  • A move back below 45,000 may trigger a selloff back toward 44,400 and 44,000. 
Imagen
US30 - D1O

Forex-Time-LogoArticle by ForexTime

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Where America’s CO2 emissions come from – what you need to know, in charts

By Kenneth J. Davis, Penn State 

Earth’s atmosphere contains carbon dioxide, which is good for life on Earth – in moderation. Plants use CO2 as the source of the carbon they build into leaves and wood via photosynthesis. In combination with water vapor, CO2 insulates the Earth, keeping it from turning into a frozen world. Life as we know it on Earth would not exist without CO2 in the atmosphere.

Since the industrial revolution began, however, humans have been adding more and more carbon dioxide to the Earth’s atmosphere, and it has become a problem.

The atmospheric concentration of CO2 has risen by more than 50% since industries began burning coal and other fossil fuels in the late 1700s, reaching concentrations that haven’t been found in the Earth’s atmosphere in at least a million years. And the concentration continues to rise.

A line chart shows atmospheric carbon dioxide concentrations mostly stable for hundreds of years and then rising with the start of the industrial revolution, and accelerating their rise starting in the mid-1900s.
Chart from Scripps Institution of Oceanography at UC San Diego, CC BY

Excess CO2 drives global warming

Who cares? Everyone should.

More CO2 in the air means temperatures at the Earth’s surface rise. As temperature rises, the water cycle accelerates, leading to more floods and droughts. Glaciers melt, and warmer ocean water expands, raising sea levels.

We are living with an increasing frequency or intensity of wildfires, heat waves, flooding and hurricanes, all influenced by increasing CO2 concentrations in the atmosphere.

The ocean also absorbs some of that CO2, making the water increasingly acidic, which can harm species crucial to the marine food chain.

Where is this additional CO2 coming from?

The biggest source of additional CO2 is the combustion of fossil fuels – oil, natural gas and coal – to power vehicles, electricity generation and industries. Each of these fuels consists of hydrocarbons built by plants that grew on the Earth over the past few hundred million years.

These plants took CO2 out of the planet’s atmosphere, died, and their biomass was buried in water and sediments.

Today, humans are reversing hundreds of millions of years of carbon accumulation by digging these fuels out of the Earth and burning them to provide energy.

Let’s dig a little deeper.

Where do CO2 emissions come from in the US?

The Environmental Protection Agency has tracked U.S. greenhouse gas emissions for years.

The U.S. emitted 5,053 million metric tons of CO2 into the atmosphere in 2022, the last year for which a complete emissions inventory is available. We also emit other greenhouse gases, including methane, from natural gas production and animal agriculture, and nitrous oxide, created when microbes digest nitrogen fertilizer. But carbon dioxide is about 80% of all U.S. greenhouse gas emissions.

Of those 5,053 million metric tons of CO2 emitted by the U.S. in 2022, 93% came from the combustion of fossil fuels.

More specifically: about 35% of the CO2 emissions were from transportation, 30% from the generation of electric power, and 16%, 7% and 5% from on-site consumption of fossil fuels by industrial, residential and commercial buildings, respectively. Electric power generation served industrial, residential and commercial buildings roughly equally.

What fossil fuels are being burned?

Transportation is dominated by petroleum products, or oil – think gasoline and diesel fuel.

Nationwide, power plants consume roughly equal fractions of coal and natural gas. Natural gas use has been increasing and coal decreasing in this sector, with this trend driven by the rapid expansion of the shale gas industry in the U.S.

U.S. forests are removing CO2 from the atmosphere, but not rapidly enough to offset human emissions. U.S. forests removed and stored about 920 million metric tons of CO2 in 2022.

How US CO2 emissions have changed

Emissions from the U.S. peaked around 2005 at 6,217 million metric tons of CO2. Since then, emissions have been decreasing slowly, largely driven by the replacement of coal by natural gas in electricity production.

Some additional notable trends will impact the future:

First, the U.S. economy has become more energy efficient over time, increasing productivity while decreasing emissions.

Second, solar and wind energy generation, while still a modest fraction of total energy production, has grown steadily in recent years and emits essentially no CO2 into the atmosphere. If the nation increasingly relies on renewable energy sources and reduces burning of fossil fuels, it will dramatically reduce its CO2 emissions.

Solar and wind energy became cheaper as a new energy source than natural gas and coal, but the Trump administration is cutting federal support for renewable energy and is doubling down on subsidies for fossil fuels. The growth of data centers is also expected to increase demand for electricity. How the U.S. meets that demand will impact national CO2 emissions in future years.

How US emissions compare globally

The U.S. ranked second in CO2 emissions worldwide in 2022, behind China, which emitted about 12,000 million metric tons of CO2. China’s annual CO2 emissions surpassed U.S. emissions in 2005 or 2006.

Added up over time, however, the U.S. has emitted more CO2 into the atmosphere than any other nation, and we still emit more CO2 per person than most other industrialized nations. Chinese and European emissions are both roughly half of U.S. emissions on a per capita basis.

Greenhouse gases in the atmosphere mix evenly around the globe, so emissions from industrialized nations affect the climate in developing countries that have benefited very little from the energy created by burning fossil fuels.

The takeaway

There have been some promising downward trends in U.S. CO2 emissions and upward trends in renewable energy sources, but political winds and increasing energy demands threaten progress in reducing emissions.

Reducing emissions in all sectors is needed to slow and eventually stop the rise of atmospheric CO2 concentrations. The world has the technological means to make large reductions in emissions. CO2 emitted into the atmosphere today lingers in the atmosphere for hundreds to thousands of years. The decisions we make today will influence the Earth’s climate for a very long time.The Conversation

About the Author:

Kenneth J. Davis, Professor of Atmospheric and Climate Science, Penn State

This article is republished from The Conversation under a Creative Commons license. Read the original article.

For America’s 35M small businesses, tariff uncertainty hits especially hard

By Peter Boumgarden, Washington University in St. Louis and Dilawar Syed, The University of Texas at Austin 

Imagine it’s April 2025 and you’re the owner of a small but fast-growing e-commerce business. Historically, you’ve sourced products from China, but the president just announced tariffs of 145% on these goods. Do you set up operations in Thailand – requiring new investment and a lot of work – or wait until there’s more clarity on trade? What if waiting too long means you miss your chance to pull it off?

This isn’t a hypothetical – it’s a real dilemma faced by a real business owner who spoke with one of us over coffee this past spring. And she’s not alone. As of 2023, of those U.S. companies that import goods, more than 97% of them were small businesses. For these companies, tariff uncertainty isn’t just frustrating – it’s paralyzing.

As a family business researcher and former deputy administrator of the U.S. Small Business Administration and entrepreneur, we hear from a lot of small-business owners grappling with these challenges. And what they tell us is that tariff uncertainty is stressing their time, resources and attention.

The data backs up our anecdotal experience: More than 70% of small-business owners say constant shifts in trade policy create a “whiplash effect” that makes it difficult to plan, a recent national survey showed.

Unlike larger organizations with teams of analysts to inform their decision-making, small-business owners are often on their own. In an all-hands-on-deck operation, every hour spent focusing on trade policy news or filling out additional paperwork means precious time away from day-to-day, core operations. That means rapid trade policy shifts leave small businesses especially at a disadvantage.

Planning for stability in an uncertain landscape

Critics and supporters alike can agree: The Trump administration has taken an unpredictable approach to trade policy, promising and delaying new tariffs again and again. Consider its so-called “reciprocal” tariffs. Back in April, Trump pledged a baseline 10% tariff on imports from nearly everywhere, with extra hikes on many countries. Not long afterward, it hit pause on its plans for 90 days. That period just ended, and the administration followed up with a new executive order on July 31 naming different tariff rates for about 70 countries. The one constant has been change.

Bloomberg TV covers the administration’s “surprise announcements” on trade the day before a key self-imposed deadline.

This approach has upended long-standing trade relationships in a matter of days or weeks. And regardless of the outcomes, the uncertainty itself is especially disruptive to small businesses. One recent survey of 4,000 small-business owners found that the biggest challenge of tariff policies is the sheer uncertainty they cause.

This isn’t just a problem for small-business owners themselves. These companies employ nearly half of working Americans and play an essential role in the U.S. economy. That may partly explain why Americans overwhelmingly support small businesses, viewing them as positive for society and a key path for achieving the American dream. If you’re skeptical, just look at the growing number of MBA graduates who are turning down offers at big companies to buy and run small businesses.

But this consensus doesn’t always translate into policies that help small businesses thrive. In fact, because small businesses often operate on thinner margins and have less capacity to absorb disruptions, any policy shift is likely to be more difficult for them to weather than it would be for a larger firm with deeper pockets. The ongoing tariff saga is just the most recent example.

Slow, steady policies help small-business owners

Given these realities, we recommend the final negotiated changes to trade policy be rolled out slowly. Although that wouldn’t prevent businesses from facing supply chain disruptions, it would at least give them time to consider alternate suppliers or prepare in other ways. From the perspective of a small-business owner, having that space to plan can make a real difference.

Similarly, if policymakers want to bring more manufacturing back to the U.S., tariffs alone can accomplish only so much. Small manufacturers need to hire people, and with unemployment at just over 4%, there’s already a shortage of workers qualified for increasingly high-skilled manufacturing roles.

Making reshoring a true long-term policy objective would require creating pathways for legal immigration and investing significantly in job training. And if the path toward reshoring is more about automation than labor, then preparing small-business owners for the changes ahead and helping them fund growth strategically will be crucial.

Small businesses would benefit from more government-backed funding and training. The Small Business Administration is uniquely positioned to support small firms as they adjust their supply chains and manufacturing – it could offer affordable financing for imports and exports, restructure existing loans that small businesses have had to take on, and offer technical support and education on new regulations and paperwork. Unfortunately, the SBA has slashed 43% of its workforce and closed offices in major cities including Atlanta, Chicago, Denver, New Orleans and Los Angeles. We think this is a step in the wrong direction.

Universities also have an important role to play in supporting small businesses. Research shows that teaching core management skills can improve key business outcomes, such as profitability and growth. We recommend business and trade schools increase their focus on small firms and the unique challenges they face. Whether through executive programs for small-business owners or student consulting projects, universities have a significant opportunity to lean into supporting Main Street entrepreneurs.

Thirty-five million small businesses are the engine of the U.S. economy. They are the job creators in cities and towns across this country. They are the heartbeat of American communities. As the nation undergoes rapid and profound policy shifts, we encourage leaders in government and academia to take action to ensure that Main Streets across America not only endure but thrive.

The authors would like to thank Gretchen Abraham and Matt Sonneborn for their support.The Conversation

About the Author:

Peter Boumgarden, Professor of Family Enterprise, Washington University in St. Louis and Dilawar Syed, Associate Professor of Instruction, Department of Business, Government and Society, The University of Texas at Austin

This article is republished from The Conversation under a Creative Commons license. Read the original article.

 

My research team used 18 years of sea wave records to learn how destructive ‘rogue waves’ form – here’s what we found

By Francesco Fedele, Georgia Institute of Technology 

Rogue waves have captivated the attention of both seafarers and scientists for decades. These are giant, isolated waves that appear suddenly in the open ocean.

These puzzling giants are brief, typically lasting less than a minute before disappearing. They can reach heights of 65 feet (20 meters) or greater and often more than twice the height of surrounding waves. Once a nautical myth, rogue waves have now been observed around the world. Because they’re so tall and powerful, they can pose a danger to ships and offshore structures.

To rethink what rogue waves are and what causes them, I gathered an international team of researchers. Our study, published in Nature Scientific Reports, sheds light on these oceanic giants using the most comprehensive dataset of its kind.

By analyzing 18 years of high-frequency laser measurements from the Ekofisk oil platform in the central North Sea, we reached the surprising conclusion that rogue waves aren’t just freak occurrences. They arise under the natural laws of the sea. They are not mysterious, but somewhat simple.

27,500 sea states

We analyzed nearly 27,500 half-hour wave records, or sea states, collected between 2003 and 2020 in the central North Sea. These records, taken every 30 minutes, describe how elevated the sea surface was compared to the average sea level. They include major storms, such as the Andrea wave event in 2007.

Several structures standing in the sea.
A complex of platforms on the Ekofisk oil field in the North Sea.
BoH/Wikimedia Commons, CC BY-SA

Under normal conditions, waves arise from wind blowing over the sea surface. It’s like when you blow over your cup of coffee and form small ripples on the surface. At sea, with enough time and space, those ripples can turn into large waves.

We focused on understanding what causes waves to suddenly go rogue and rise far above their neighboring waves. One proposed theory is based on modulational instability, a phenomenon described by complex mathematical models. I’ve revised these models in the past, as my work suggests that this theory doesn’t fully explain what causes rogue waves in the open ocean.

A diagram showing the height of waves in different sea states, with the tallest reaching about half the height of a large commercial boat.
Sea states record the height of waves and show when some waves rise high above sea level.
U.S. Government Accountability Office

When waves are trapped within a narrow channel, the modulational instability theory describes their rippling movement well. However, it starts to fall apart when you look at the real ocean. In open environments such as the North Sea, waves are free to propagate from multiple directions.

To understand the difference, imagine a crowd of spectators leaving a stadium after a football game. If the exit is a long, narrow hallway with tall walls, people are forced to move in a single direction. Those at the back push forward, and some may even climb over others, piling up between the confining walls. This catastrophic pileup would resemble a rogue wave, caused by their confinement.

In contrast, if the stadium’s exit opens onto a wide field, spectators can disperse freely in all directions. They don’t push on each other, and they avoid pileups.

Similarly, researchers can generate rogue waves in a confined channel in the lab, where they obey modulational instability. But without the confinement of a channel, rogue waves usually won’t follow those physics or form the same way in the open sea.

Our team knew we had to study the open sea directly to figure out what was really going on. The real-world data my team examined from the North Sea doesn’t line up with modulational instability – it tells a different story.

It’s just a bad day at sea

We analyzed the sea state records using statistical techniques to uncover patterns behind these rare events. Our findings show that instead of modulational instability, the extreme waves observed more likely formed through a process called constructive interference.

Constructive interference happens when two or more waves line up and combine into one big wave. This effect is amplified by the natural asymmetry of sea waves – their crests are typically sharper and steeper than their flatter troughs.

Rogue waves form when lots of smaller waves line up and their steeper crests begin to stack, building up into a single, massive wave that briefly rises far above its surroundings. All it takes for a peaceful boat ride to turn into a bad day at sea is a moment when many ordinary waves converge and stack.

These rogue waves rise and fall in less than a minute, following what’s called a quasi-deterministic pattern in space and time. This type of pattern is recognizable and repeatable, but with touches of randomness. In an idealized ocean, that randomness would almost vanish, allowing rogue waves to grow to nearly infinite heights. But it would also take an eternity to witness one of these waves, since so many would have to line up perfectly. Like waiting for Fortuna, the goddess of chance, to roll a trillion dice and have nearly all of them land on the same number.

In the real ocean, nature limits how large a rogue wave can grow thanks to wave breaking. As the wave rises in height and energy, it can’t hold itself beyond a certain point of no return. The tip of the wave spills over and breaks into foam, or whitecap, releasing the excess energy.

The quasi-deterministic pattern behind rogue waves

Rogue waves aren’t limited to the sea. Constructive interference can happen to many types of waves. A general theory called the quasi-determinism of waves, developed by oceanographer Paolo Boccotti, explains how rogue waves form, both in the ocean and in other wave systems.

For example, for turbulent water flowing through a confined channel, a rogue wave manifests in the form of an intense, short-lived spike in vortices – patterns of spinning swirls in the water that momentarily grow larger as they move downstream.

While ocean waves seem unpredictable, Boccotti’s theory shows that extreme waves are not completely random. When a really big wave forms, the waves in the sea around it follow a recognizable pattern formed through constructive interference.

We applied Boccotti’s theory to identify and characterize these patterns in the measured North Sea wave records.

The giant waves observed in these records carry a kind of signature or fingerprint, in the form of a wave group, which can reveal how the rogue wave came to life. Think of a wave group like a small package of waves moving together. They rise, peak and then fade away through constructive interference. Tracking these wave groups allows researchers to understand the bigger picture of a rogue event as it unfolds.

As one example, a powerful storm hit the North Sea on Nov. 24, 2023. A camera at the Ekofisk platform captured a massive 55 foot (17 meter) rogue wave. I applied the theory of quasi-determinism and an AI model to investigate the origin of this extreme wave. My analysis revealed that the rogue event followed these theories – quasi-determinism and constructive interference – and came from multiple smaller waves repeatedly stacking together.

Left: Stereo video footage of a powerful storm in the North Sea on Nov. 24, 2023, recorded at the Ekofisk platform.
Right: The wave group signature of the recorded rogue wave.

Recognizing how rogue waves form can help engineers and designers build safer ships and offshore platforms – and better predict risks.The Conversation

About the Author:

Francesco Fedele, Associate Professor of Civil and Environmental Engineering, Georgia Institute of Technology

This article is republished from The Conversation under a Creative Commons license. Read the original article.

 

Global stocks rally on Fed easing hopes

By ForexTime 

  • US500 & NAS100 hit fresh all-time highs
  • In-line US inflation boosts Fed cut bets, September cut priced in
  • USDInd tumbles below 98.00, USD down against all G10
  • GBPUSD trades higher ahead of upcoming UK GDP data

Equities across the globe extended gains on Wednesday as mounting Fed cuts stimulated appetite for risk assets.

The US annual inflation rate held steady at 2.7% in July, defying expectations of a tariff-induced rise to 2.8%. This essentially sealed the deal for the Fed to cut rates in September and boosted the odds of another cut by October to 60%.

Markets are buzzing with activity:

  • The S&P500 and Nasdaq100 surged to fresh all-time highs.
  • FXTM’s USDInd tumbled below 98.00 for the first time since late July.
  • Bitcoin rebounded back toward $120,000.
  • Gold prices stabilized above the 50-day SMA.

The risk-on rally has also been supported by:

  • President Donald Trump extending a trade truce with Beijing until 10 November.
  • Optimism over Trump-Putin talks leading to an end to Russia’s war in Ukraine.

USDInd set to extend losses?

The USD has depreciated against every single G10 currency this week, with the USDInd dipping below 98.00.

Prices are bearish with more soft data fuelling the downside. Much attention will be on the incoming US PPI, initial jobless claims, and speeches by Fed officials, which may provide further insight into Fed cuts.

Looking at the charts, the negative momentum may drag prices toward 97.00.

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GBPUSD higher ahead of GDP

GBPUSD jumped as much as 100 pips yesterday after in-line US inflation readings weakened the dollar and boosted bets around the Fed cutting rates in September.

Sterling was already supported by the BoE’s hawkish rate cut last week and may see more volatility due to the incoming Q2 GDP report on Thursday.

A stronger-than-expected figure may boost confidence in the UK economy. If this reduces bets around the BoE cutting rates, the pound could rally.

A weaker-than-expected figure is likely to support the argument for lower UK interest rates, weakening the pound as a result.

  • Bullish: A solid breakout above the 50-day SMA may encourage a move toward 1.3600.
  • Bearish: Weakness below the 50-day SMA may trigger a decline toward 1.3415.
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