Tuesday, October 17, 2017

Where Trump is failing to fix the economy with monetary policy

(Elite E Services) 10/17/2017 — Dover, DE — It’s no secret that the US economy has diverged into a massive 2 world system where there is also a massive gap in between; the employed and the wealthy have increasingly good lives while the poor and unemployed have a deteriorating quality of life.  As we have explained in Splitting Pennies, it is monetary policy that ‘Trumps’ all else.  Using The Gini Coefficient we can visualize what this means:
In economics, the Gini coefficient (sometimes expressed as a Gini ratio or a normalized Gini index) (/d?ini/ jee-nee) is a measure of statistical dispersion intended to represent the income or wealth distribution of a nation’s residents, and is the most commonly used measure of inequality. It was developed by the Italian statistician and sociologist Corrado Gini and published in his 1912 paper Variability and Mutability (ItalianVariabilit√† e mutabilit√†).
Taking a look at basic 2013 data (it’s worse since then) we get a picture of reality vs. what is said in the media.  Using Russia as a good example to stay with the Trump theme, USA (41) has roughly the same Gini as Russia (40.9):
forex
Remember that Russia is the unfair system that is a top-down Byzantine oligarchy, right?  Then why Russia and USA share almost identical Gini, being surpassed only by the Banana Republics in South America?
Everyone in finance knows there are several things that Trump can do to fix the economic problems of USA in about 5 minutes:
  • Surprise increase interest rates to 5% or 10%
  • Import tariffs on Chinese crap
  • Unwind USA’s Petro Dollar system (drink it!)
  • Repeal the Dodd-Frank Consumer Rip-Off Fraud Act that has caused billions to flow out of USA.  Make America the world’s banker once again.  (This is our industry – FX – we know that this alone would create thousands and thousands of jobs and be a huge boost for the economy – billions would flow into USA and we’d again be the world’s banker.  But this same approach likely applies to many industries.  Dodd-Frank regulations killed FX and have cost millions of jobs.)  We’ve outlined this in previous articles.
It’s not really practical to bring factories back to USA, however we have robot technology and the financial sector is a great example of how we can create high skilled high paid white collar jobs.  But Trump seems to be more obsessed with form not essence (and his form is not good).
Oh – you’re thinking that a President can’t do that, right?  President is a figurehead, only Congress can pass laws.  That’s true.  But Nixon did it.  Somehow, Nixon was able to accomplish all these things in 1 day and created the floating FX market as it exists today.  It was not Nixon’s only genius move, there were many.  Was Nixon’s real genius just listening to his advisors like Henry?  Either way, in practice, it fixed the problem – only to be unwound by future administrations.  Was it a temporary fix?  Of course – but that’s what we need.  We need to unwind QE which is practically impossible, so jacking up rates is a first good start.  Wall St. and the stock market will suffer.  But they’ve had a long bull run.
Winter is coming – it’s bear time.

Monday, October 16, 2017

Black Monday 2.0: The Next Machine-Driven Meltdown

Brian Stauffer
Black Monday. Although the event to which those two words refer occurred 30 years ago, they still carry the weight of that day—Oct. 19, 1987—when the Dow Jones Industrial Average shed nearly a quarter of its value in wave after wave of selling.
No one in living memory had seen anything like it, at least not in the U.S., and in the postmortems conducted to understand just how the Dow managed to drop 508 points in one day, experts found a culprit: so-called portfolio insurance, a quantitative tool designed to use futures contracts to protect against market losses. Instead, it created a poisonous feedback loop, as automated selling begat more of the same.
Since that day, markets have rallied and markets have tumbled, and still we marvel at the unintended consequences of what, in hindsight, was an obviously misguided strategy. Yet in the ensuing years, market participants have come to rely increasingly on computers to run quantitative, rules-based systems known as algorithms to pick stocks, mitigate risk, place trades, bet on volatility, and much more—and they bear a resemblance to those blamed for Black Monday.
The proliferation of computer-driven investing has created an illusion that risk can be measured and managed. But several anomalous episodes in recent years involving sudden, severe, and seemingly inexplicable price swings suggest that the next market selloff could be exacerbated by the fact that machines are at the controls. “The system is more fragile than people suspect,” says Michael Shaoul, CEO of Marketfield Asset Management.
THE RISE OF COMPUTER-DRIVEN, rules-based trading mirrors what has happened across nearly every facet of society. As computers have grown more powerful, they have been able to do what humans were already doing, only better and faster. That’s why Google has replaced encyclopedias in the search for information, why mobile banking is slowly replacing bank branches, and why—someday—our cars will be able to drive us to work. And it is also why Wall Street has embraced computers to help with everything from structuring portfolios and trading securities to making long-term investment decisions.
In the years since 1987, huge strides have been made in understanding what drives stock performance and how to apply it to portfolio construction. At first, researchers focused on “factors,” such as a stock’s volatility relative to the market—known as beta; whether a stock is large-cap or small—the size factor; and whether it is cheap or expensive—the value factor. More recently, the use of factors has proliferated to include many others, such as quality and momentum. (The latter involves buying the best-performing stocks and shunning the worst performers.)
Quantitative investors understood early on that betting on stocks based on their characteristics—and not the underlying business fundamentals of a particular company—was a good way to outperform the market. So good, in fact, that many fundamental, or “active,” money managers now use quantitative tools to help construct their portfolios and ensure that they don’t place unintended bets. Nomura Instinet quantitative strategist Joseph Mezrich says that 70% of an active manager’s performance can be explained by quantitative factors. “Factors drive a lot of the returns,” Mezrich says. “Over time, this has dawned on people.”
Has it ever. One result has been the rise of indexing and exchange-traded funds. The ability to buy an index fund based on the Standard & Poor’s 500—effectively a bet that large companies will outperform small ones—made the need for traditional fundamental research and stock-picking unnecessary. Since then, indexes and ETFs have been created to reflect just about any factor imaginable—low volatility and momentum among them. Some funds even combine multiple factors in a quest for better performance.
As a result, an increasing amount of money is being devoted to rules-based investing. Quantitative strategies now account for $933 billion in hedge funds, according to HFR, up from $499 billion in 2007. And there’s some $3 trillion in index ETFs, which are, by definition, rules-based. The upshot: Trillions of dollars are now being invested by computers. “We’ve never seen so many investment decisions driven by quantitative systems,” says Morningstar analyst Tayfun Icten.
That’s quite a change from the 1980s. If you wanted to place a trade 30 years ago, you picked up the phone and called your broker; your broker called the firm’s trader; the trader would ring up a specialist, the person in charge of running trading in a given stock; and the trade would be executed. The process was slow, cumbersome, and inefficient. As computer technology advanced, machines gradually took most of these steps out of the hands of humans. Today, nearly every trade is handled by an algorithm of some sort; it is placed by a computer and executed by computers interacting with one another.
The entity handling trades isn’t the only thing that has changed in the past 30 years. Trading now occurs in penny intervals, not fractions such as eighths and 16ths. While that has made it cheaper for investors to buy and sell a stock, pennies made trading far less lucrative for market makers, who historically profited by playing the “spread” between the highest bid to buy and the lowest offer to sell. Consequently, market makers have been replaced by algorithms programmed to instantaneously recognize changes in liquidity, news flow, and other developments, and respond accordingly. At the same time, the proliferation of exchanges helped to lower trading costs but also created a fragmented market that can make shares hard to find during dislocations.
Most of the time, none of this matters. If you want to buy a stock, you boot up your computer, log in to your brokerage account, and place an order that gets filled almost immediately. The fee you pay is so low that it would have been unimaginable 30 years ago. The system has worked well for individual investors, and will continue to do so—as long as nothing goes wrong.
BUT MISTAKES HAPPEN. In 1998, the “quants” at Long-Term Capital Management, led by Nobel Prize winners Myron Scholes and Robert Merton, nearly caused a massive market selloff when the hedge fund’s highly leveraged trades, based on quantitative models of expected market behavior, suddenly lost money after Russia unexpectedly defaulted on its debt. The damage was magnified by the borrowing that LTCM had used to supersize its bets. Only a bailout organized by the Federal Reserve prevented the broad market from plummeting.
In August 2007, a selloff occurred in quantitative funds that would become known as the “quant quake.” To this day, no one knows what sparked the selling, but once it began, computer models kicked in, causing further selling. Humans added to the mess as risk managers looking at losses dumped shares. Funds specializing in quantitative investment strategies reportedly suffered massive losses: The Renaissance Institutional Equities fund was thought to have lost nearly 9% early in that month, while Goldman Sachs ’ Global Alpha suffered a double-digit decline.
The impact on the market wasn’t huge—the S&P 500 dropped just 3.3% during the first two weeks of August—but the event demonstrated what happens when a trade sours and too many funds are forced by their models to sell at the same time. It was a wake-up call for quants, who have since created more-sophisticated systems to reduce the kind of crowding that led to the selloff.
More recently, problems have been caused by algorithms that are supposed to provide stock for investors to buy, or buy when investors sell, creating liquidity. On May 6, 2010, the S&P 500 dropped 7% in just 30 minutes, as bids and offers for stocks moved far away from where stocks had been trading, in some cases leaving bids down as low as a penny and offers as high as $100,000.
Again, no one knows what caused the sudden decline. Investors had been on edge because of an unfolding European debt crisis, but that alone seemed unlikely to have triggered the flight of automated market makers. The U.S. Commodity Futures Trading Commission blamed the swoon on fake orders placed by a futures trader, while the Securities and Exchange Commission fingered a massive sell order in the futures market allegedly placed by a mutual fund company seeking to protect itself from a potential downturn. That order, it argued, had been handled by a poorly designed algorithm—yet another reminder that an algorithm is only as good as the inputs used by the people designing it.
While the rout was over quickly, and the S&P 500 finished the session down a more modest 3.2%, the episode raised concerns about the potential for computerized trading to exacerbate selloffs.
REGULATORS AND EXCHANGES have made changes since then, but so-called flash crashes continue to happen, even if they are no longer quite as disruptive as the 1987 selloff. On Aug. 24, 2015, for instance, the Dow dropped almost 1,100 points during the first five minutes of trading. The selloff was spurred by a plunge in China’s stock market, which led to a drop in Europe. All of this happened when U.S. markets were closed, which meant that investors turned to the futures and options markets to place their trades.
Chaos prevailed when the stock market opened: Only about half of the stocks in the S&P 500 had started trading by 9:35 a.m.; a quarter of the Russell 3000 index was down 10% or more intraday, and many large ETFs traded far below the value of their underlying assets. Algorithms, sensing something amiss, simply stepped back from the market. Once again, the S&P 500 recovered much of its sudden loss, but savvy market observers detected eerie echoes of an earlier era. In a much-read note at the time,JPMorgan strategist Marko Kolanovic cited the feedback loop of selling and compared it to the Black Monday selloff of 1987.
Flash crashes have not been limited to stocks—or even crashes. On Oct. 15, 2014, the price of the 10-year Treasury note soared, causing yields to tumble 0.35 of a percentage point in mere minutes before quickly reversing. The SEC blamed the increasing role of automated high-frequency algorithms for the sudden move.
The most recent scare occurred on May 18, when the iShares MSCI Brazil Capped ETF(ticker: EWZ) dropped as much as 19% in a single trading session before closing the day down 16%. To put that move in perspective, the Brazil ETF’s worst single-day decline at the height of the financial crisis in 2008 had been 19%. While there was bad news in May—reports that Brazilian President Michel Temer had been ensnared in a corruption scandal—that seemed insufficient cause for such a precipitous decline.
Shaoul, of Marketfield, attributes the Brazil ETF’s plunge to a combination of factors, including the growth of passive investing, which has made it easy to buy and sell an entire country’s market with the press of a button, combined with computer-driven trading. “There was no way of knowing what was a human being pressing a button, or a computer pressing a button,” he says. “But it generates the potential for sudden spikes in volatility that come out of nowhere.”
The Brazil ETF recovered its losses fairly quickly. By the end of August, it was trading above its May 17 close.
U.S. markets haven’t suffered declines like that, but have experienced numerous “fragility events”—sudden one-day declines—during the current rally, says Chintan Kotecha, an equity derivatives strategist at Bank of America Merrill Lynch. But because stocks have been in a bull market, there has been little follow-through after the initial selloff. As a result, some quantitative strategies reposition for more volatility, but none arrives. Kotecha attributes the lack of follow-through, in part, to central bankers’ continued bond-buying, which has provided much-needed support for the markets.
Follow-through was all the market had in 1987, as selling automatically triggered more selling. To some observers, the risks of a similar scenario are growing. One particular area of concern: volatility-targeting strategies, which try to hold a portfolio’s volatility constant, and risk-parity strategies, which attempt to equalize the risk in a portfolio among bonds, stocks, and other assets—and sometimes use leverage to do it. When volatility is low, these portfolios can hold more-risky assets than when volatility is high. But as soon as volatility rises—and stays high—these types of funds will need to start selling stocks and other assets to keep the risk of their portfolios at the same level. If they sell enough, volatility could spike higher, leading to even more selling.
The PROLIFERATION of COMPUTER-DRIVEN INVESTING has created an illusion that RISK can be measured and managed. But several anomalous episodes in recent years involving sudden, severe, and seemingly INEXPLICABLE PRICE SWINGS suggest the next MARKET SELLOFF could be exacerbated by the fact that the MACHINES are at the controls.
In a market selloff, commodity-trading advisors similarly could exit their long positions quickly and look to short stocks, creating further selling pressure as they head for the exits. “Action leads to more action,” says Richard Bookstaber, chief risk officer at the University of California and author of The End of Theory, a book about financial crises caused by positive feedback loops.
PERHAPS THE BIG QUESTION is who might be left to buy. Warren Buffett once quipped that investors should be fearful when others are greedy and greedy when others are fearful, but the current market structure has turned that maxim on its head. Algorithms provide less liquidity in a downturn than a human market maker, who might be thinking about how to profit from a dislocation.
The rise of momentum and passive strategies has caused some $2 trillion to shift away from active money managers, who could be counted on to look for bargains as stocks sold off, says Kolanovic, the JPMorgan strategist. “We think the main attribute of the next crisis will be severe liquidity disruptions resulting from market developments since the last crisis,” he says.
But most strategists acknowledge that such an occurrence isn’t a high-probability event. Much will depend on the cause of any disruption, as well as seasonal factors—stocks are more thinly traded in summer, for example. Also, computers aren’t the only cause of selling cycles; bear markets, after all, long predate machine-driven trading.
Quantitative investors argue that they have learned from past mistakes and are less likely to be leveraged or crowded into the same trades. Moreover, regulators and exchanges have instituted rules that could help arrest a bout of unchecked selling, with trading halts imposed when the S&P 500 falls 7%, 13%, and 20%.
Maybe these precautions will work to stem a tidal wave of selling. One of these days—possibly soon, given stocks’ lofty valuation and the Fed’s plan to shrink its balance sheet—we’ll find out. 
http://www.barrons.com/articles/black-monday-2-the-next-machine-driven-meltdown-1507956435?shareToken=sta34fcb09ee6a423fa9e0acc127844d01&utm_source=newsletter&utm_medium=email&utm_campaign=sendto_newslettertest&stream=top-stories

Sunday, October 15, 2017

The New Bit Currency Crypto FX paradigm

(GLOBALINTELHUB.COM) — 10/15/2017 Dover, DE — The Bit Paradigm has arrived; with billions being thrown into projects that no one knows who are the founders, or if the profiles they use for their ‘team’ pages are guys working from home or have day-jobs at the local grocery store.  It is transforming the landscape so rapidly, we compiled a sequel to Splitting Pennies entitled Splitting Bits – Understanding Bitcoin and the Blockchain – available on Amazon Kindle for $2.99 and Paperback $9.99.
As Currency experts, we found nothing unusual in the Bit World, it’s just FX 2.0 and hopefully a catalyst for real global financial reform beyond the scope of the myopic Dodd-Frank Consumer Rip Off and Exploitation Regulation that have plagued the US consumer going on 5 years now.  As we’ve explained in our previous work, Splitting Pennies – FX is the basis for the global financial system.  Don’t forget that Bitcoin is denominated in US Dollars.  While FX is the least understood market in the world it is also the most important.
Just remember one thing – customers (business) need currency, they don’t need stocks or Crypto.  Take any business as an example, McDonalds (MCD) is always a great FX example – they need foreign currency as they accept it in more than 110 countries worldwide.
forex
And being based in Chicago, they need to repatriate those currencies into US Dollars, making them one of the biggest FX traders in the world.  So where does Bitcoin fit into all this?  At the moment, it doesn’t.  Of course that’s all changing – and changing quickly.  The news changes by the day – as the Bit Paradigm goes mainstream.  The current market cap of the entire CryptoCurrency Market is $170 Billion according to Coinmarketcap.com.
While that is still far away from traditional markets, the growth rate is beyond parabolic.  Skeptical traders should remember the late 90’s when fears about the Euro kept investors away.  Just take a look at this Monthly EUR/USD chart showing the Euro’s rise against the dollar from lows of .83 to highs of 1.58 before settling into the range that it’s been in recently:
Euro Historical
The Red line from .83 to 1.58 is about 190% or double – and traders should also bear in mind in FX there is a lot of leverage, so the 100% return in 6 years could have been 1000% or greater (many funds did profit from this simple trade).
Of course, the real money in FX is in algorithmic trading, what the banks learned the hard way.. But the Euro is a great example of a synthetic currency that was created artificially, and finally succeeded to be an alternative to the US Dollar as a world reserve.  Although the technicalities of Bitcoin are far different, the gestalt is the same – Bitcoin is a currency created artificially, backed by nothing, and is increasing in value because people believe that it will be used in the future and that the price will go up.  Just like there’s nothing behind Bitcoin, there’s really nothing behind the Euro – with one key difference.  It’s possible for the ECB to print (mint) as many Euros as they want, but it’s not possible to do this with Bitcoin because of the design (there is a limited number of Bitcoin) and because there’s no central bank behind it.
The big story of currency trading Crypto is of course, new alt-coins other than Bitcoin, which are being issued so rapidly it’s impossible to even keep track of them.  Coinmarketcap.com lists 1170 different Cryptocurrencies, you can see the full list here.
For a detailed breakdown of how you can profit from trading Bitcoin, checkout our new book Splitting Bits.

Tuesday, October 10, 2017

EES: Splitting Bits Digital Book released - Understanding Bitcoin and the Blockchain

(Eliteeservices.net) - 10/10/2017 Dover, DE -- Elite E Services, a FinTech virtual corporation in the Currency business for 15 years, has today published a digital book about Bitcoin and the Blockchain entitled "Splitting Bits : Understanding Bitcoin and the Blockchain" available on Kindle exclusively, for $2.99 digitally.  Get it now from www.pleaseorderit.com

With the world of Bitcoin and Blockchain moving faster than ever, EES felt an urgent need to research this Currency niche and publish our findings in a book.  Bitcoin is a Currency, and EES has been in the Currency management business for 15 years.  What we learned is fascinating, that Bitcoin isn't just a 'fad' but quite the opposite - Blockchain technology seems that soon it will be used everywhere.  Get it now from www.pleaseorderit.com

Book Description:

Splitting Bits takes the Bit World of Bitcoin and the Blockchain and splits it into bite sized pieces for your digestion pleasure. We explain Bitcoin for what it is - a digital currency, not so different from fiat currencies such as the Euro or Yen. Splitting Bits is the natural sequel to Splitting Pennies - Understanding Forex. A new Bit Paradigm has begun and the computer arms race to mine and hash and mint your own coin is important for everyone to understand. Blockchain is the most explosive, potent technology ever which is about to change the world, starting with Wall St. Bitcoin may be a 'fad' but the underlying Distributed Ledger Technology (DLT) is the new standard in Currency Trading, Banking, Securities, and new markets yet to be created. Old systems will be renovated and re-invented. Blockchain is spreading faster than a virus around the world where soon a "Kodak Moment" will make businesses obsolete (such as when Smartphones make Kodak irrelevant). If you're feeling as you missed the opportunity to make 500,000% return by not buying some Bitcoin in 2011, now is an even greater opportunity - as we explain in this book. Bitcoin isn't actually going up in price, it's the US Dollar going down - there is a limited supply of Bitcoin, but the supply of US Dollar is unlimited. If you want to integrate Bitcoin for your business, Splitting Bits is your practical guide to simple steps of how you can accept Bitcoin payments and manage the risk of a volatile currency. For traders and investors, we explore the markets as they exist now and what the short term future holds. Splitting Bits has something for everyone, including our own proprietary Better Coin - learn how to make your own Coin logically, algorithmically. Learn how to avoid the fraud, which exists everywhere. Splitting Bits also includes how to guide for Bitcoin mining, and practical information for anyone who is confused, curious, or otherwise wants to improve their Bitcoin knowledge. Of course, we describe many Cryptocurrencies but use Bitcoin as the prime example. Join the Bit Paradigm and buyer beware - you won't think the same about investing after reading. WARNING: Crypto trading is contagious!

Get it now from www.pleaseorderit.com


Sunday, October 8, 2017

Insider Trading and Financial Anomalies Surrounding the Las Vegas Attack

Authored by Kip Herriage of VRAletter.com | October 7, 2017
Note: This is an update to my article of 10/7/17. Nothing has been removed or edited from the original article. This updated article includes additional financial/trading anomalies I have uncovered since posting the original piece.
Included in this updated article:
1) Additional trading research on OSIS (OSI Systems), the global leader in baggage, shipping and people detection systems (airports and now MUCH more, like hotels/casinos). Like the other 4 co’s that I have found, OSIS also began to rise on 9/11/17 (remember this date as you will see it in each company) and it rose on large share/option volume increases. The shares of OSIS would rise as much as 16% from its 9/11/17 lows to just after the attack.
2) OLN (Olin Corp) makes Winchester ammunition. Beginning on 9/11/17 their shares began to rise on a large increase in volume and a HUGE increase in call option purchases (so far I’ve found more than 6000 calls were purchased in OIH the week prior to the attack with someone making a ton of money in these calls). The shares of OLN would soar as much as 23% from their 9/11/17 lows to just after the attack.
Insider Trading and Financial Anomalies Surrounding the Las Vegas Attack
Note: With this report, I make no claim to specific knowledge of any wrongdoing or improprieties. Instead, this report includes trading patterns, news releases and/or public record SEC filings.
We will examine the share price movements of two gun manufacturers (American Outdoor Brands and Sturm Ruger) and the share price movement of MGM (which owns Mandalay Bay). We will also examine additional financial events surrounding MGM, including what can only be referred to as massive levels of insider selling in the shares of MGM, by the CEO/Chairman and MGM officers/directors. As you’ll see, more than $200 million in MGM shares were sold in the weeks leading up to the attack.
Background. Interesting Trading Patterns in AOBC, RGR and MGM.
Over the course of my 32 years in the investment industry I have constructed a proprietary investing model that I refer to as the “VRA Trading & Investing System”. In short, its design is to track money flows in the stock market and detect sector and stock analysis/movements that then alert me as to when/where money is flowing in the markets.
For example, prior to the 2016 Presidential Elections, the VRA System noticed that the share price of gun manufacturers had begun to decline rapidly. This was one of our first financial clues that Trump might beat Clinton (Trump’s strong support of 2A). As you can see below, American Outdoor Brands (AOBC, formerly Smith & Wesson), hit a high of $31/share in August of 2016. As the bottom began to fall out, it would ultimately drop 55% in price, before hitting its low price of just over $13 on 9/11/17.
The market is referred to as a “discounting mechanism” and as such, it often predicts future events. It certainly did so in the case of the election and the share price of AOBC.
We see the same trading pattern in gun manufacturer Sturm Ruger (RGR). RGR traded as high as $73 in March of 2016 before ultimately dropping 37%, when it too bottomed within one trading day of AOBC hitting it’s lows (9/8/17). Again, my system noted the rapid decline in gun stocks, which led me to believe that Trump may in fact win the election. Remember this point; both AOBC and RGR hit their lows at the same time, just over two weeks prior to the Las Vegas shooting.
Something Changed in September
Let’s now examine the trading patterns of AOBC and RGR in detail, just over two weeks “prior” to the attack. As you can see, AOBC bottomed on 9/11/17 at $13.30 before the spike higher began. From 9/11 to just after the attack, AOBC rose 23% in price. It did so on a noticeable increase in buy-side trading volumes.
Below, we see the same chart and reaction in the shares of Sturm Ruger (RGR). From its 9/8/17 lows, RGR bottomed at $46.24 and then spiked to $55.90 just after the attack, for a move higher of 21%.
After falling in price from early-mid 2016 to their early September 2017 lows, the two largest publicly traded gun manufacturers bottomed, then spiked higher, at almost exactly the same time. In addition, buy-side volume increases rose sharply as well.And, while not covered in this report (more work is needed), we also saw a spike in call option purchases in both AOBC and RGR, in the days/weeks leading up to the attack.
This final chart shows the share price of MGM (owner of Mandalay Bay) in the days leading up to the attack to present. MGM shares declined more than 10%, from 9/7/17 to recent lows. This decline occurred as some $200 million in insider selling was taking place.
Bottom line: Beginning in early-mid September to this report, gun manufactures AOBC and RGR rose in price 23% and 21% (on higher trading volumes), while the shares of MGM fell in price by 11% (as $200 million in insider selling occurred).
MGM: Heavy Levels of Insider Selling
As the SEC insider transaction reports below detail, from 9/5/17 to 9/12/17, approximately 6 million shares of MGM were sold by officers and/or directors of the company, totaling approximately $200 million in proceeds to sellers. Included in this group is the selling of approximately 450,000 shares by MGM CEO and Chairman James Murren (a seller of size since late July) and who appears to have sold more than 85% of all holdings. We also see that MGM Board member Grounds William Warwick sold 176 million shares of his MGM stock on 9/6/17.
We have no indication that MGM insiders sold these 6 million shares due to any advance knowledge of the 10/1 attack. I am not making that claim. I am simply pointing out facts that cannot be in question.
But I will make a few observations:
1) If MGM/Mandalay Bay were to lose law suits associated with this attack, the downside risks to MGM share price may be extensive.
2) We also know that MGM CEO James Murren was appointed to the Homeland Security National Infrastructure Advisory Council by President Obama in December 2013. This fact could make for some interesting depositions, as it relates to exactly what type of advanced security systems Mandalay Bay had in place, leading up to and on the night of 10/1/17.
“The National Infrastructure Advisory Council is tasked with providing the president with advice on the “security of the critical infrastructure sectors and their information systems.” The council is composed of a maximum of 30 members, appointed by the president, from private industry, academia and state and local government.”
3) I am also aware of the fact that MGM put options activity spiked as well (needs more work), beginning at the same time gun stocks were rising and MGM was falling in price.
4) For those curious about the trading in other major Las Vegas Hotel casino stocks, during this same time frame, this also needs more work. However, I can report that at the same time MGM’s share price was falling, the share prices of Las Vegas Sands (LVS) and Wynn Resorts (WYNN) were actually rising.
There’s more…like the recent trading pattern in OSIS, which makes “detection systems” of all kinds (similar to their subsidiary “Rapiscan”, which makes the TSA body scanners that were put in place following 9/11). Many are wondering how long it might be before we are forced to walk through similar devices, as we enter hotels/casinos.
In my original piece I only mentioned OSI Systems (OSIS) and their trading pattern around the Las Vegas attack. I’m updating this to include the chart from the same time frame and additional comments.
Below is the chart of OSIS. From the lows of 9/11/17 to after the attack, the shares of OSIS have jumped 16%. In addition (more work is being done here), call option volume also spiked higher, 2 weeks before the attack.
I have also confirmed that OSIS is working on plans to place their baggage/people detection systems in hotels/casinos around the world. Deepak Chopra is the CEO and Founder of OSIS.
Here’s another interesting piece to the puzzle. Olin Corp (OIH) makes Winchester ammunition (among other things). Beginning on 9/11/17 their shares began to rise on a large increase in volume and a HUGE increase in call option purchases (so far I’ve found more than 6000 calls were purchased in OIH the week prior to the attack. Someone is making a ton of money in these calls). The shares of OLN would soar as much as 23% from their 9/11/17 lows to just after the attack.
I am also including the anonymous 4 chan post (below) that everyone is talking about. As I see it, these are (among) the 5 publicly traded companies that the planner of the Las Vegas attack would want to target. It is most interesting that each of these stocks began their moves on 9/11/17, just one day after the 4chan post. This is what we know after less than 1 week after the attack. What might we know in another week?
Closing:
In closing, let me repeat; I make no claims or assertions that anyone mentioned in this piece has done anything nefarious. They likely did not.
The question I might ask is, “Did someone else profit from the heinous acts of 10/1/17? Possibly the planners?”
Like many of you, I am interested and I am asking questions. I also remember that during 9/11/01, reports surfaced widely in the financial media that “many, many millions” in profits were made off of the purchase of put options in the shares of United Airlines and American Airlines, the two airliners that operated the four aircraft that were hijacked on 9/11 (among other well-documented reports of large put option purchases in numerous companies that had the most exposure to a shocked US economy).
There’s more…like the recent trading pattern in OSIS, which makes “detection systems” of all kinds (similar to their subsidiary “Rapiscan”, which makes the TSA body scanners that were put in place following 9/11). Many are wondering how long it might be before we are forced to walk through similar devices, as we enter hotels/casinos.
I will continue to follow this story. Should you have information that might assist in my research, you can reach me at kip@vraletter.com.
I am a proud American. I want the best for our country. Wherever the truth leads us, that is where we must go. Follow the money.
Kip Herriage
VRALetter.com