Think Jamie Dimon after his third felony would clean the Bank’s Manipulation of the commodity Market’s. Especially Silver.

Now with the DOJ labeling the firm as a criminal organization using Rico statutes to prosecute all involved. It will not be long before they get up the food chain!

JP Morgan and the four other thieves, Goldman Sacks, Bank Of (Clinton) America, Morgan Stanley and Citi have colluded for a long time. Long before Bear Stearns collapsed to keep the price of #silver #gold and god knows what other commodity DEPRESSED in order to control inflation and keep the free money printing at the NY Fed.


In 1792 the gold/silver price ratio was fixed by law in the United State at 15:1
One troy ounce of gold was worth 15 ounces of silver. A RATIO OF 15.5:1 was enacted in France in 1803.
The Average gold/silver price ratio during the 20th century was 47:1
The current ratio with the banks playing pass the hot potato is 85:1

In 1980 gold traded at double it’s all time high, but silver at 1/3 of it’s all time high.

In the 80’s the Hunt brothers were on to the scam and tried to break the silver short . They were stopped by the government as manipulators and lost there fortune. They where passed off as manipulators, not Freedom fighter’s like they where. They new the government game. They just went after the game without a Trump in office.
The organized crime syndicate AKA the top five banks will hang themselves to depress the metals markets, Even with JP Morgan controlling 30% of the worlds silver.
World silver reserves in 2001 was 520,000 tons. By 2017 it had reached 530,000 tons.

Whats this all means.

The short will be broken with DOJ Rico charges. Bankers are going to jail.  The silver short is massive.
THE RATIO IS OFF 5.6 X  5.6 X 18 = 102 






New York Fed Plans to Throw $2.93 Trillion at Wall Street’s Trading Houses Over Next Month as New York Times Remains Silent

By Pam Martens and Russ Martens: December 16, 2019 ~

New York Fed Headquarters Building in Lower Manhattan

New York Fed Headquarters Building in Lower Manhattan

One has to wonder how much money it would take for the New York Fed to throw at Wall Street before the New York Times reports to its readers on the biggest Wall Street bailout by the Fed since the financial crisis.

Last Thursday, December 12, the New York Fed announced that over the next month it would shower the trading houses (primary dealers) on Wall Street with a total of $2.93 trillion in short-term loans. The money is for a Wall Street liquidity crisis that has yet to be explained in credible terms to the American people and yet the New York Times does not appear to have an investigative reporter assigned to investigate what’s really going on just 11 years after those same trading houses blew themselves up in the biggest financial crash since the Great Depression and took the U.S. economy along for the ride.

The New York Fed’s repo (repurchase agreement) loan program began on September 17 when repo loan rates spiked from approximately 2 percent to 10 percent – meaning either liquid funds were not available to loan or the mega banks on Wall Street were backing away from lending to certain counterparties. Repo loans are typically between banks, hedge funds and money market funds on an overnight basis and are made against good-quality collateral. Since that time, the New York Fed has been making these loans to the tune of hundreds of billions of dollars weekly.

The New York Times covered the subject in September. Then an eerie silence took hold in October and November as the Fed continued to pump out over $3 trillion in cumulative loans to Wall Street’s trading houses. On December 8 and December 12, the New York Times simply ran articles by Reuters on the Fed’s loans, which are the first of their kind since the financial crisis.

The $2.93 trillion that the New York Fed will funnel to Wall Street over the next month consists of up to $120 billion each weekday in overnight loans through January 14 and $440 billion in term loans ranging from 3-days to 32 days. In addition, during the last week of the year (on Tuesday, Wednesday and Thursday) the Fed will bump up its overnight loan offerings to $150 billion from $120 billion, thus providing an additional $90 billion that week.

Adding to the suggestion that liquidity remains tight on Wall Street despite the Fed’s loans, the New York Fed offered a $50 billion 32-day term loan this morning and it was oversubscribed by $4.25 billion.

The Wall Street Journal’s Michael Derby reported this massive new money spigot from the Fed after it was announced last Thursday but he wrote this regarding the source of the problem:

“The apparent cause of that spike was a large tax payment date and settlements for Treasury debt auctions that affect how much money was available in the banking system.”

That was the official-speak from the Federal Reserve and relates to what happened on September 17. It does not explain why the Fed has had to continue throwing hundreds of billions of dollars each week at Wall Street’s trading houses after those corporate tax payments and Treasury auctions were long out of the picture.

Would the Federal Reserve, the central bank of the United States, actually lie to the American people? If withholding material facts from the American people constitutes a lie, then yes, the Federal Reserve has a troubled history.

In the leadup to the financial collapse on Wall Street in September 2008, the Fed created in March of that year a lending program very similar to what it is doing today. It called it the Single Tranche Open Market Operation (ST OMO) and attempted to pass it off as part of its routine open market operations. But when the Levy Economics Institute took a hard look at where the ST OMO money went, it found that “77 percent ($657.91 billion) of all transactions were conducted with foreign-based institutions.” The largest of those were Credit Suisse of Switzerland which received 30.3 percent of the funds; Germany’s Deutsche Bank, which borrowed 11.8 percent of the money; and France’s BNP Paribas, which took down 11.3 percent of the funds borrowed.

According to data compiled by the Levy Economics Institute, the Fed’s bailout of Wall Street during the financial crisis amounted to a staggering $29 trillion (including the central bank liquidity swap lines, CBLS) – a sum that neither the American people nor Congress would learn about until years after the loans had been made and a multi-year court battle by the Fed to suppress the information had been won by media outlets.

The largest amounts of the $29 trillion did not go to commercial banks to shore up the U.S. economy through consumer loan relief or business loans. It went to three of the largest trading houses on Wall Street. Citigroup received $2.65 trillion; Merrill Lynch received $2.43 trillion; and Morgan Stanley received $2.27 trillion. (See page 33 at this link.) The fourth largest was not even a bank or Wall Street firm. It was AIG, a large insurance company that Wall Street’s trading houses had buried as the counter party to their derivative bets. AIG got a cool $1 trillion in loans from the Fed.

The chart below suggests that today’s Fed loans, which are not going to commercial banks but to the trading units of those banks, are being used to artificially prop up the stock market. The Dow Jones Industrial Average has mounted a rally since the Fed turned on its money spigot on September 17. (How else can you have a stock rally in the midst of a liquidity crisis on Wall Street?) Instead of performing its mandate as a lender of last resort to the commercial banks of the U.S., the New York Fed seems to be settling into its assumed role as the stock market’s lender of last resort to facilitate a liquidity exit ramp for the one percent who own the bulk of the stock market.

Dow Jones Industrial Average, September 17, 2019 through December 13, 2019

Dow Jones Industrial Average, September 17, 2019 through December 13, 2019

Rating. Hiroshima.

These are dangerous times we live in. Crowdstrike.

Stock sells for 23 times revenue, not earnings, I said revenue.

Nobody in the free world(professionals) has any idea when the company will make money.

Crowdstrike is a home grown Ukraine intelligence company. Don’t let silicone valley fool you.

Silicon valley institutions have 20 Million shares ready for sale. 8 million of those became free trading on Monday.

They attempted with Googles upper management who are all now retired to clean all of the Clinton Emails.

Submitted a falsified report to congress that they inspected the DNC server. Claims it was a hack from Russia that broke into the server when it was really Seth Rich.

Lied to congress. (So did Hoffa)

Who knows what else they are responsible for. Ask yourself a rational question. Where do you think the stock should trading?

Cygnus position is that Peloton is a potential avalanche.

Reasons Why?

In their S1 they claimed that 2019 top line revenue estimates are 915 Million. They came in at 202 Million ending Q3 2019. Lets see if they can do nearly 700 Million in Q4 2019 and Santa comes early.

What Peloton projected to do in their S1 as compared to actual numbers is a potential avalanche.

Peloton S1 Filing.

End of Q3 Revenue 202 Million.

Lost 50 Million in Q3

We have zero clue when this company will actually be profitable.

Company has a 8.8 Billion Dollar Market Cap.

Recently launched a $12.99 App that competes with their top line $2,800 Bike.(What genius came up with this idea.)

243 Million shares are coming off restriction March 1st 2020.

Peloton costs 6 Times more than its competitors.

Pelotons EV is 2,286% more than there Peer Average.

40 Million share float is already 70% short.

Target price. A lot lower.

Our Disclaimer. We in no way shape or form telling anyone to buy or sell anything. What we do is call bullshit where we see it.

Just this morning, robotic process automation (RPA) firm Blue Prism announced enhancements to its platform. A little later, the company, which went public on the London Stock Exchange in 2016, announced it was raising £100 million (approximately $130 million) by issuing new stock. The announcement comes after reporting significant losses in its most recent fiscal year, which ended in October.

The company indicated it plans to sell the new shares on the public market, and that they will be made available to new and existing shareholders, including company managers and directors.

RPA Automation

CEO Alastair Bathgate attempted to put the announcement in the best possible light. “The outcome of this placing, which builds on another year of significant progress for the company, highlights the meteoric growth opportunity with RPA and intelligent automation,” he said in a statement.

While the company’s revenue more than doubled last fiscal year, from £24.5 million (approximately $32 million) in 2017 to £55.2 million (approximately $72 million) in 2018, losses also increased dramatically, from £10.1 million (approximately $13 million) in 2017 to £26.0 million (approximately $34 million), according to reports.

The move, which requires shareholder approval, will be used to push the company’s plans, outlined in a TechCrunch article earlier this morning, to begin enhancing the platform with help from partners, a move the company hopes will propel it into the future.

Today’s announcement included a new AI engine, an updated marketplace where companies can share Blue Prism extensions and a new lab, where the company plans to work on AI innovation in-house.

Bathgate isn’t wrong about the market opportunity. Investors have been pouring big bucks into this market for the last couple of years. As we noted, in this morning’s article, “UIPath, a NYC RPA company has raised almost $450 million. Its most recent round in September was for $225 million on a $3 billion valuation. Automation Anywhere, a San Jose Robotic Process Automation (RPA) startup, has raised $550 million including an enormous $300 million investment from SoftBank in November on a valuation of $2.6 billion.”

Automation Anywhere, a San Jose-based company that makes automation software, said Thursday that it has raised $290 million in Series B funding at a valuation of $6.8 billion.

The latest investment — just a year and a half after the San Jose-based company raised its first-ever venture round — turns Automation Anywhere into one of Silicon Valley’s highest-valued unicorn startups and follows on a $300 million funding round a year ago that valued the company at $2.6 billion.


“Never before has there been such a transformative shift in the way we work, with artificially intelligent software bots changing how people, processes and technology interact for productivity gains,” Automation Anywhere CEO Mihir Shukla said in a statement. “This new funding reinforces the promise of the RPA (robotics process automation) category and empowers our customers to achieve greater business agility and increased efficiencies by automating end-to-end business processes – bridging the gap between the front and back office.”

Series B

The Series B funding was led by Salesforce Ventures, the venture capital arm of San Francisco-based Inc. “Automation Anywhere makes it easier for Salesforce customers to automate repetitive, manual tasks and focus on what matters most — the customer,” Bill Patterson, executive vice president and general manager at Salesforce Service Cloud, said in a statement.

Additional funding came from existing investors that include Goldman Sachs and SoftBank Investment Advisers, which funded the company’s November 2018 round. At that time, Shukla told the Silicon Valley Business Journal that Automation Anywhere envisions that “this technology will change how we work, across all industries and across every function.”

He said last year that Automation Anywhere, which changed its name from Tethys Solutions LLC in 2010, was profitable before, but that explosion of bots that are automating business processes created a big new opportunity. He also said that the SoftBank investment opened up “the possibility of partnering with many of the portfolio companies that SoftBank has invested in that are having the same sort of impact.”

The funding comes on the heels of massive layoffs at UiPath, Automation Anywhere’s New York-based rival. Shukla recently published a blog post assuring customers that, unlike Uipath, AA has been hiring and said the RPA market is “extraordinary,” adding that successful competitors are good for business.

“We want and need the market to be competitive because especially competitive markets are always better for customers and partners,” he said at the time. “Working with our vast partner ecosystem, we’re on a journey unlike any other. Journeys like this are never without their twists and turns. But, on this journey, we plan to set untold records.”

As lawmakers in Brasilia debated a controversial pension overhaul for months, a robot more than 5,000 miles away in London kept a close eye on all 513 of them. The algorithm, designed by technology startup Arkera Inc., tracked their comments in Brazilian newspapers and government web pages each day to predict the likelihood the bill would pass.

Weeks before the legislation cleared its biggest obstacle in July, the machine’s data crunching allowed Arkera analysts to predict the result almost to the letter, giving hedge fund clients in New York and London the insight to buy the Brazilian real near eight-month lows in May. It’s since rallied more than 8%.

Brazil's Lower House Votes On President Bolsonaro's Flagship Pension Proposal
Lawmakers supporting the pension reform bill wave Brazilian flags in the lower house of the National Congress in Brasilia on July 10.Photographer: Andre Coelho/Bloomberg

This is the kind of edge that a new generation of researchers are betting will upend the research marketplace. For Arkera’s clients on Wall Street and in the City of London, that means getting robots to filter through the noise in faraway lands.

“There’s too many people to follow on Twitter, too many websites, too many articles,” said Nav Gupta, the 48-year-old co-founder of Arkera, which says its software can process as much information as 1,000 human analysts. “That’s a very expensive problem and everybody faces it.”

The company raised 4 million pounds ($4.9 million) last year from investors including Alan Howard of hedge fund Brevan Howard Asset Management LLP.

Using so-called artificial intelligence to automate swathes of the research process is quickly gaining traction because cost-conscious investment banks are downsizing. In the U.K. alone, there was a 30% drop in research budgets last year, Financial Conduct Authority data show. At the 12 biggest banks, there’s been a 7% drop since 2015 in the number of front-office staff covering currencies, such as traders and researchers, according to London-based research analytics consultancy Coalition Development Ltd.

That means it’s even harder than it used to be to afford analysts on the ground in developing nations, about the only places in the world where investors can get yield right now.

Data-science companies like Arkera and New York-based Sigmoidal say they can solve this problem using machines that learn as they go to dredge through tens of thousands of news articles, government statements and social media accounts in languages as varied as Spanish, Arabic and Chinese.

After an initial investment of up to $100,000, banks can save $1 million over seven years using such systems because they don’t need to hire as many data analysts, said Marek Bardonski, who was chief executive officer of Sigmoidal when he spoke with Bloomberg in July. He has since left the company. Previously, Bardonski, 27, was a computer scientist at graphics chipmaker Nvidia.

Take this year’s protests in Hong Kong. Bardonski said Sigmoidal’s software was able to track developments in the Cantonese-language press and even identify the non-verified Twitter feeds of protest leaders to monitor the risk of further unrest. The technology is useful for far-away countries wracked by political turmoil, places where investors are keen to put money but don’t have easy access to information.

“The system can give an edge over traditional analysts working for financial institutions,” said Bardonski, who said typical reports will include charts on sentiment, key word statistics and short written summaries. “Instead of getting 100,000 news articles, clients can get all the insights on one page.”

Neither Sigmoidal nor Arkera would let Bloomberg see an example of an automated report to see how readable it is compared with one produced by a human, citing rules against sharing proprietary data. 

But the quality has gone downhill because mid-level analysts have left or been pushed out, leaving junior analysts to do the work so their more senior colleagues can go to client meetings. This is giving investors even more impetus to seek out bespoke research, like paying cash to speak with experts in the field or investing in automated research to support their senior fund managers and strategists.

“Asset managers now need to assess the value of every single research service to assess if it’s worth paying for, how much they should pay for it, and trying to filter the good from the bad,” Mahmud said.

relates to Robots Are Solving Banks’ Very Expensive Research Problem
Vinit Sahni and Nav GuptaSource: Arkera

Under MiFID II, asset managers must be prepared to demonstrate they’ve done due diligence on all investments they make for their clients, something that’s always been tricky in developing countries.

It was that very problem that inspired Gupta and his business partner Vinit Sahni, whose careers spanned firms including Citadel LP, DE Shaw & Co. and Goldman Sachs, to set up Arkera in 2015. During their 20-year careers in investment banking, trying to find information to substantiate something felt “like pulling teeth,” Sahni, 50, said.

So the pair set up a team of data scientists and engineers to design a search engine that investors can use to give them an edge in places like Turkey, Mexico and Egypt. It works kind of like Google, only it’s programmed to choose the most relevant sources from tens of thousands of articles, social media feeds and government releases.

As good as robots are getting at deciphering market jargon, even their developers admit they’ll never fully replace humans. In the next decade, Sahni said smart machines will significantly enhance the capabilities of human analysts.

“We will see advancements in cognitive abilities, communication and the physical potential of humans as we collaborate closely with machines and algorithms,” he said.

Local SEO strategies may seem like they’d rely less on AI (artificial intelligence), but in reality they need it to fully thrive. Here’s why.

AI barely played a role in thebeginning of online search engines. The earliest search engines accepted payments from companies that wanted to be at the top of the listings. However, AI is becoming more important than ever.

Google is using AI to assign SERPs more than ever. Savvy SEO strategists are also using AI too. AI is also important in local SEO, because businesses need to know how to automate essential functions and identify approaches that get the best results.

How AI is Central to Modern SEO

Search Engine Journal has discussed the role of AI in modern SEO. They said that AI has the following five benefits:

  • AI helps optimize keywords better
  • AI uses cluster analytics and predictive analytics to audit pages and identify search terms that will be popular in the future
  • AI helps leverage customer reviews
  • AI predicts customer needs
  • AI drives customers to sales with better engagement

All of these AI factors directly or indirectly help with SEO. You should know how to use AI to build an SEO strategy for a local business.

Creating a Local SEO Strategy with AI

Nearly everyone searches Google to find a local business or services near them. In fact, nearly 50% of all Google searches are for local business information. While SEO professionals know the importance of incorporating organic SEO services that utilize AI into their marketing plan, especially to businesses with a physical location, there are still a lot of small businesses who do not include local SEO tactics in their marketing plan.

Create a Google My Business listing.

AI can help you make a Google My Business listing more quickly. Google My Business is a free tool for businesses and organizations to help establish and manage a business’s web presence across Google. GMB connects your business with customers.

Go to Google My Business and claim your GMB page. If you haven’t done this already, Google will send you a verification code for your address. You will take that code and follow Google’s instructions to enter the code into Google My Business so that Google can verify your business, which can take 1-2 weeks. You can use AI to make sure everything is done properly, which expedites things.READHow To Use Artificial Intelligence To Create Websites That Thrive

After you have verified your Google My Business you will then need to:

  • Ensure your name, address, and phone info is correct
  • Select the right category for your business
  • Complete your business’ description
  • Add your hours of operation
  • Upload hi-res images
  • Ask your customers/clients to write reviews for your business

Make Sure Your NAP is consistent across all platforms.

Your name, address, and phone number should be the same no matter which page of your website or other social platform your business is on. Check your Contact Us page, Home page, Footer, and social media platforms. You can use AI to identify inconsistencies and rectify them.

Use a Google Map on your website.

AI has improved user engagement, which includes offering Google Maps. Having a Google map on your website for your physical location is a given. You want visitors to be able to find you. Embedding a Google Map onto your website is a simple tactic that a local SEO company would likely use.

Use Geotags to share your location with search engines.

AI also has made geotags possible. Geo tags assign a geographical location to a photo, video, website, and social media posts. Use geotags on your specific location websites. They let search engines where you are and help improve your local business search ranking. You can use a Geo Tag Generator and place it on each page of your website.

Use schema markups.

Schema markups help search engines better understand the content on your website so that your business will appear in more relevant local searches. You can use schema markups for NAP, events, specific categories and more. You can use a Schema Markup Generator or (JSON-LD).

Optimize your website and meta tags for local keywords.

You can boost your clickthrough rates by including your business’ city and state in your meta description tags on your website, page content, logo, and images.

If you have multiple locations, create a separate web page for each of them.

If you have more than one physical location, create a separate web page for each location. You can create a specific subdomain for your various locations. You want to make sure that the content for each location’s website is unique. You could include content like:

  • Testimonials from clients specific to the location the website is for
  • Highlight services or products that you offer in one location that are not available in your other locations
  • Create a location specific blog, making sure you use alt tags for images and videos.

READAre SMEs Equipped To Master Data Science?

Submit your website to local directories.

You want your business to be listed in as many online directories as possible. You can use a tool like Yext to find many, if not most, of the locations of your existing citations and update your info so that your NAP is consistent across all business listings. If you have multiple locations, you want to make sure your location-based subdomain corresponds with the right location.

Gather as many reviews from customers and clients as possible.

Customer reviews from credible review sites like Yelp, Google My Business, and Facebook can have a positive impact on your Google local search rankings.

Update your business’ social media profiles with your location.

Your business’s location should be on every single social media platform that your business uses. You should always include your contact information so that potential customers and clients know how to reach or where to go. Make sure the information you provide on your social media pages is consistent with the information on your website. Having active social media channels could have a huge impact on your local rankings because it’s a sign that your business is credible.

If you still don’t feel confident in handling your local SEO marketing on your own, seek help from one a top tier internet marketing company who offers affordable SEO services with more than ten years’ experience and hundreds of satisfied customers.


“If people design computer viruses, someone will design AI that improves and replicates itself. This will be a new form of life that outperforms humans.”

The rise of Machines and AI  is Fast Approaching

The rise of the machines was always going to come at a cost, as each wave of technology destroys what has been put in place. The frenetic pace of technological development in the areas of artificial intelligence and robotics is causing massive shifts in the finance industry.

The impact is already being felt on Wall Street, where there have been far-reaching and significant changes, with technology eliminating many jobs by replacing hundreds of humans with either robo-advisers or software.

Many investment banks and big institutions, in a bid to cut cost and improve efficiency, use AI to automate financial tasks usually undertaken by humans, such as wealth management, operations, risk management, and algorithmic trading.

One of the areas that the Wall Street has seen the greatest disruption of robotics and AI is the execution of buy and sell orders, where robots carry out between 50% to 60% market trades, according to CNN, citing data from Art Hogan. Hogan is the chief market strategist for B. Riley FBR.

The preference for technology over human traders is premised on the inability of the vast majority of traders to act consistently rationally when trading. Often, people fail to control themselves, allowing emotions to get in the way of their thoughts and actions.

Machines don’t suffer from these psychological issues when a major trading decision is being made. This is because they remove emotion from short-term trading activity, allowing for a more objective approach to trading.

Laying a Claim to the Future of Investing

Artificial intelligence and robotics is fast advancing into the investment sector, where its incredible ability to learn and think will eventually make them the most advanced and complex investment systems capable of helping corporations to make more efficient and effective choices.

For instance, advisory bots are increasingly being used by companies to assess investments, deals, and strategies in a fraction of a second, much faster than any human quantitative analysts using traditional statistical tools.

Such is the growing dominance of robots in the finance industry that former Barclays boss, Anthony Jenkins warned they could displace half of the workers in the banking sector, and lead to branch closures.

Activities such as calculations based on structured data and other repetitive support tasks are the most susceptible to automation because robots are well-suited for them.

There’s Still a Place for Humans in a Robotic Wall Street

While AI is probably the most robust technology there is today; its ability to perform complex tasks is limited. Trading machines can only learn historical data and trade patterns. However, stock market behavior changes all the time and computers can be less adept in the face of unexpected market performance.

Humans can easily adjust themselves to these changes. Getting the robots to do the same, however, will require changing their algorithms, which can be too expensive and time-consuming. For this reason, humans will always be a step ahead and remain relevant.