Weekend Reading: Just Buy Everything

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Authored by Lance Roberts via RealInvestmentAdvice.com,

On Wednesday, as I discussed yesterday, the Fed hiked rates and despite the fact that hiking interest rates further tightens monetary policy, thereby reducing liquidity to the markets, the markets rallied anyway.

With the hopes of accelerated earnings recovery being muted by falling oil prices, higher borrowing costs, and a strong dollar, investors seem willing to forgo the basic fundamentals of investing to chase an already extended and aging bull market cycle.

This was noted yesterday in a note from Goldman’s Jan Hatzius, the chief economist warns that the market is over-interpreting the Fed’s statement, and Yellen’s presser, and cautions that it was not meant to be the “dovish surprise” the market took it to be.

“Surprisingly, financial markets took the meeting as a large dovish surprise—the third-largest at an FOMC meeting since 2000 outside the financial crisis, based on the co-movement of different asset prices.

 

The committee may have worried that a rate hike—especially a rate hike that was not priced in the markets or predicted by most forecasters as recently as three weeks ago—might lead to a large adverse reaction on the day, and wanted to avoid such an outcome by erring slightly on the dovish side. But we feel quite confident that they were not aiming for a large easing in financial conditions. After all, the primary point of hiking rates is to tighten financial conditions, perhaps not suddenly but at least gradually over time. And even before today’s meeting, at least our own FCI was already fairly close to the easiest levels of the past two years and this was likely one reason why the committee decided to go for another hike just three months after the last one.”

He’s right. The Fed, which is now tightening financial conditions (which should/will push asset prices lower), got the exact opposite result as everything rose Wednesday from stocks, to bonds, to gold.

In other words, market participates took the rate hike as another reason to “just buy everything.” 

Of course, with bullish trends still very much in place, it has been, and remains, very challenging to dispute that point.

Just realize, eventually the mantra of “just buy everything” from overly complacent bullish investors, will change to “just sell everything.” 

Of course, just understanding that particular point is just winning the battle.

Recognizing, and acting, on the change is what “Wins the war.”

Just some things I am thinking about this weekend as I catch up on my reading.

Trump/Fed/Economy

Markets

Financial Planning/Retirement

Research / Interesting Reads

“It is well that the people of the nation do not understand our banking and monetary system, for if they did, I believe there would be a revolution before tomorrow morning.” – Henry Ford



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Why The Fate Of The World Economy Is In The Hands Of China's Housing Bubble

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A couple of research reports released overnight by Deutsche Bank and Bank of America, respectively, come to a sobering conclusion: the fate of the global economy may be in the hands of the Chinese housing bubble. As a reminder, China is a serial bubble inflator courtesy of a closed (capital account) economy, and nearly $30 trillion in bank deposits which slosh from one asset class to another, be it the stock market, bitcoin, commodities, farm animals or - most often - housing.

As all China watchers knows, and as DB confirms, the root cause of this bubble is "excessively loose monetary policy set to achieve growth above its potential." Furthermore, while the most recent housing bubble, the third in a row, appears to have recently popped as annual home price growth declined in January for the first time after 19 months of continuous acceleration, the question is how hard will Beijing push to prevent the same hard landing that took place in late 2014 when the bursting of the second housing bubble led to substantial slowdown in China, and sent rippled effects around the globe. 

 

So why is it so important for China to periodically and consistently reflate this bubble? The answer is simple: a gargantuan wealth effect, to the tune of 24 trillion yuan, or roughly $3.5 trillion.

As Deutsche's Zhiewi Zhang writes when discussing the macro and market consequences of the Chinese bubble, it is nothing more (or less) than "a massive wealth effect":

We estimate that in 2016 the rise of property price boosted household wealth in 37 tier 1 and tier 2 cities by RMB24 trillion, almost twice their total disposable income of RMB12.9 trillion (fig.11).

Such effect even spread to many tier 3 cities (Figure 13).

And, as Deutsche further points out, the (rather fleeting) wealth effect "may be helping to sustain consumption in China despite slowing income growth. A decline of property price would obviously have a large negative impact." And not just in China, but around the globe, as this incremental $3+ trillion in demand provide a material boost to not only China's direct trading partners, but set the economic pulse around the globe via various "soft" sentiment surveys, via transposition of the "EM to DM" growth narrative, as well as via direct purchases of offshore assets by capital controls-circumventing Chinese residents.

In fact, as the German bank explicitly states, the "property sector has become the critical pillar for fiscal revenue and the economy." A sector which as both the Chinese government, and DB, call a bubble.

But why would the government tolerate the bubble - knowing its bursting could have dire consequences on the economy if not contained - instead of seeking to deflate it gradually? There are three reasons:

  • The property and construction sectors accounted for 33% and 15% of local government tax revenue growth between 2010 and 2015. They contributed 43% of local government tax revenue in 2015,  compared to 11% from manufacturing (Figure C3). Besides taxes, local governments also heavily rely on land sales to finance infrastructure projects.
  • Banks, developers, urban property owners, and government all benefited tremendously from the property sector so far. This makes it difficult for the government to tighten monetary policy or roll out straightforward measures such as property tax to contain the bubble. The reluctance to prick the bubble only makes it larger.
  • The government may have the confidence that they can avoid a property bubble burst. It does appear that China has a stronger control over property prices than other countries, because it has a closed capital account, high saving rate, low CPI inflation, high level of reserves, a current account surplus, monopolized land supply, and a financial system largely controlled by the government. Some may argue “why can’t Beijing and Shanghai become Hong Kong?”

So the question the is simple: with the fate of the domestic, and therefore global, economy in the hands of China's housing sector, what happens next. The answer is unclear, however as DB warns, "property bubble bursts in other countries were often preceded by higher interest rates." And in what direction is the world headed? That's right: one where gradually every central bank is starting to tighten and raise interest rates.  As DB further adds, "the chance of rate hikes in China rises in 2018 as we expect higher inflation in China and six more rate hikes in the US over 2017/18. In the longer term, unfavorable demographic trend and slowdown of urbanization are the ultimate constraints."

So while it is clearly Beijing's desire to keep the housing bubble as inflated as possible, it may not have a choice absent further, much looser monetary conditions. The reason for that is as Bank of America's David Cui writes, "China’s housing market is among the least affordable globally. Although this doesn’t necessarily mean a sharp price correction anytime soon, it leaves the government with less scope than most others in our view to manage housing price, should interest rate jump or income growth slow. In addition, we believe that high asset prices, including housing price, is one of the main drivers of capital outflow."

Some further thoughts on what may be the world's least affordable housing market:

Many use the housing-value to GDP ratio to gauge whether a country’s housing market is reasonably priced. We believe that the ratio of housing value over household income is more telling – after all, households spend their income buying houses, not businesses nor the government. Based on this ratio, China’s is the second most expensive market among the countries that we track, all with a reputation of excessive housing price at various times (Chart 1). Other than the high housing price (relative to income), another major contributor to China’s high ratio is a low share of household income in GDP (which, by the way, goes to the heart of China’s imbalanced growth problem in our view).

 

Does this unprecedented unaffordability mean that a crash is imminent? According to Cui, China’s high ratio currently doesn’t necessarily mean that housing price will drop sharply anytime soon – Japan’s and Ireland’s had reached far higher levels before theirs corrected while Australia’s, Korea’s, and indeed, China’s have stayed at high levels for years without any major price correction so far. However, a few factors could make housing price in China over the next few years more vulnerable than most, including financial system risk posed by a rapid rise of leverage economy-wide, and a lack of exchange rate flexibility.

A far more immediate problem as a result of China's housing bubble may be the acceleration of Yuan outflows.  According to Cui, a major driver of China's capital outflow is high asset prices.

In another word, the local rich may prefer NY condos to Shanghai apartments for better value, for example. From this perspective, for the outflow pressure to ease, either housing price in Rmb terms has to decline or Rmb devalues. This assumes that the government cannot control capital outflow effectively in the long run, a reasonable assumption in our view given how open the Chinese economy is.

How will the government react? BofA predicts that "if it comes down to it, we expect the government to choose Rmb devaluation over asset price deflation" aka a housing hard landing. " Arguably the biggest driver behind high asset prices in China is leverage in our opinion. As a result, any major asset price decline may quickly trigger a debt deflation spiral and financial system instability."

The take home summary: keep a close eye on how Beijing manages to deflate the existing bubble: if it fails to be aggressive enough, home prices will once again spike, leading to an even more precarious bubble. If it is too aggressive, a hard landing is in store, coupled with what a crash in the country's financial system, where the bulk of the banks' $35 trillion in assets is collateralized by housing values. While such a crash may not necessarily lead to a catastrophe for China, where the government ultimately backstops all the banks, the deflationary wave spread around the globe from a housing crash would be dire.

Which is why those who are looking for key inflection points to determine the future trajectory of the global economy, in addition to the global (read Chinese) credit impulse...

... we suggest keeping a close eye on what happens with Chinese housing, which has become a - if not the - top variable for the fate of the both the great inflation-deflation debate, as well as the overall fate of the world economy.



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Guess where Barack Obama is right now

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Back in Washington, President Donald Trump continues to suggest, without proof, that Obama wiretapped him and Republicans are busy trying to dismantle his signature health reform law. Nevertheless, former President Barack Obama is unwinding nicely from the most important job in the world.

He's been to sunny California for some golf, a private island in the Caribbean, where he kite-surfed with billionaire Richard Branson; he went to New York to take in a Broadway play, and then again, to dine with U2's Bono.

He lunched in Omaha last week with Warren Buffett and then hopped a flight to California, and then on to Hawaii (more golf). And today, Obama may be sitting pretty, in the middle of the Pacific Ocean, on a tiny French Polynesian island called Tetiaroa.

There are reports, unconfirmed by CNN, that Obama is going to spend a month on the island, which is north of Tahiti and features only one luxury hotel, aptly named "The Brando" because the Island was once owned by Marlon Brando. The eco-friendly hotel has one-, two- and three-bedroom villas, according to its website. It's been a favorite destination for more current celebrities like Leonardo DiCaprio. Prices range from $2,000 per night, depending on accommodations and date. Their Instagram feed makes the place look quite nice.

An Obama spokesman tells CNN that the former president is now a private citizen and his schedule, therefore, is also private.

Whether or not life after the White House includes an island respite, it also likely now includes writing a book. Penguin Random House last month announced it had won the bidding for memoirs from both Barack and Michelle Obama, a deal that could net the former first couple tens of millions of dollars.

The announcement also indicated the Obamas would donate a "significant portion" of that money to charities, including the Obama Foundation.

When not on vacation, the Obamas are living in Washington; they've moved into a posh $5.3 million home in the Kalorama neighborhood of Northwest DC. They intend to stay until their younger daughter, Sasha, graduates high school in 2019. Older daughter, Malia,18, is taking a gap year and scheduled to attend Harvard University this fall.



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'Anonymous' Joins Hacker Crusade To Steal Millions From Global Central Banks

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Roughly a year ago we wrote about perhaps the most notable bank heist in history in which a group of hackers used Swift, the interbank messaging system, to steal $81 million from the Central Bank of Bangladesh.  Here's our recap: 

For those who missed the story, you can review it in all its James Bond-ish glory in the four posts linked below, but here is a brief summary of what happened to the $81 million: 1) it was transferred to four accounts at the Jupiter Street, Makati City, branch of Rizal Commercial Banking Corp (RCBC) in the Philippines, 2) $470,000 in cash went into the branch manager's trunk and the rest went to a possibly forged (but possibly not) account registered to one William Go, 3) the money was transferred to an FX broker called Philrem, 4) $50 million was split between two casinos and the remaining $31 was delivered to a "Weikang Xu" in cash.

 

From there, the trail goes cold.

But Bangladesh isn't the only country whose Central Bank has been targeted by a growing number of hackers seeking to score a quick, and massive, loot.  As Bloomberg notes, hacks on global financial systems soared in 2016 and claimed Russia, Poland, Uruguay and Mexico, just to name a few, as victims. 

Over the course of last year, hackers looted up to $21 million from accounts opened with the Bank of Russia.

 

Poland’s financial regulator was targeted in January by a suspected “watering hole” attack, where hackers target an often-used website, according to research from BAE Systems. In this instance, the hack originated from the website of Polish Financial Supervision Authority (KNF), where code was planted that would serve malware to certain visitors of the site. The malicious code was selectively targeted at financial institutions, and multiple banks were compromised via their users simply browsing the KNF website.

 

Similar code was also believed to be present on the website of the state-owned Banco de la República Oriental del Uruguay, and the National Banking and Stock Commission of Mexico in late 2016, according to analysis from BAE Systems and U.S. software company Symantec Corp.

Anonymous

 

Now, the hacking collective “Anonymous,” known for its activism against big corporations, security forces, and governments, has decided it wants to get in on the massive central bank scores and is actively recruiting new hackers that can assist in the effort.

While the people wouldn’t say which banks are being targeted, they said the group has been busy recruiting new hackers to aid it in its forays, and renewed its attack against a number of central banks in February.

 

The group last year attacked at least eight monetary authorities, including the Dutch Central Bank, the Bank of Greece, and the Bank of Mexico, the two people said. In a change of tack, it is also considering plans to sell on any confidential information it obtains, according to one of the people.

 

The actions by non-state hacking and hacktivist groups such as Anonymous “are a wake-up call that should alert us to the critical weaknesses of global financial systems,” said Stefano Zanero, a professor of computer security at Italian university Politecnico di Milano.

Janet Yellen recently warned in testimony before the congressional Joint Economic Committee in November that a successful cyber-security attack on the U.S. banking system is “one of the most significant risks our country faces."  In fact, central banks all around the world are spending millions on cybersecurity experts and even buying startup companies to avoid being the next embarrassing victim of a multi-million dollar cyber heist. 

In response, central banks and related agencies have been busy attempting to stem the increasing number of attacks. In June Swift hired BAE Systems and U.K. cybersecurity adviser NCC Group Plc in a bid to improve its security defenses. BAE has since helped Swift analyze whether it needs to flag potential issues to correspondent banks.

 

The Bank of England is even scooping up startups to help it battle online threats. It is currently running an accelerator, launched in June 2016, and is to start working with Anomali in order to “hunt and investigate cyber security intelligence data in a highly automated fashion,” according to a case study published in February by the Bank.

Of course, try as they might, we suspect the world's bureaucratic central banks may be ill-equipped for a battle against an army of anonymous, international hackers fed up with their destructive policies aimed at continously inflating assets bubbles which serve only to help the rich get richer while enslaving the masses...

Image result for project mayhem



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Why China Unexpectedly Hiked Rates 10 Hours After The Fed

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As we reported on Wednesday evening, something interesting took place on Thursday morning in Beijing: in a case of eerie coordination, China tightened monetary conditions across many of the PBOC's liquidity-providing conduits just 10 hours after the Fed raised its own interest rate by 0.25% for only the third time in a decade.

The oddly matched rate hikes, prompted Bloomberg to think back to the mysterious "Shanghai Accord" of February 2016, which took place during the peak days of last year's global capital markets crisis, and whose closed-door decisions - to this day kept away from the public - prompted the market rally that continues to this day. As Bloomberg wrote, the coordinated "response suggests that pledges by the Group of 20 economies a little over a year ago in Shanghai to "carefully calibrate and clearly communicate" policies may not have been hollow after all."

That said, it was not the first time the People’s Bank of China has acted on the heels of a Fed move. At the peak of the financial crisis, the PBOC cut lending rates after six of its counterparts, including the Fed, had announced a simultaneous rate cut. That October 2008 move enhanced China’s emerging reputation as a global player on the international economic-policy circuit. “Growth divergence is morphing into growth synchronization," said Chua Hak Bin, a Singapore-based senior economist with Maybank. "Policy divergence was also a narrative for those expecting a strong dollar, but that is moving now to policy synchronization.”

Coordinated or not, as of last night financial conditions in China, like in the US, have become incrementally tighter even if both the Chinese and US stock markets failed to respond accordingly.

So, for those curious what China did - after all the days of shotgun Interest rate or RRR moves appear to be on hibernation for the time being - here is a convenient primer from SocGen's Wei Yao explaining not only the mechanics, but the reason why.

As Yao notes, the PBoC followed the Fed closely, at least timing-wise, and raised the rates on its major liquidity management tools by 10bp across the curve today, earlier than many had expected. After the hikes, the rate on the 7D reverse repo operations - the most critical of all - is now at 2.45%.

 

The central bank, in its press release, stressed that these interbank rate hikes simply follow the market's development, thus not true policy rate hikes, and only hikes of benchmark lending and deposit rates count. Nevertheless, it also listed four classical rate-hike reasons for the interbank rate changes: the economic recovery, rising inflation (particularly that of housing), strong credit growth and Fed's rate hikes.

SocGen's interpretation of this statement is:

  1. The PBoC is responding to the fundamentals of growth, inflation and financial stability. And it is looking through the low food prices, which have suppressed CPI, and paying due attention to domestic asset bubbles and credit growth.
  2. But it still prefers a tightening approach so as to match its neutral stance, which means that adjusting interbank liquidity and interbank rates will likely remain the main actions. This may be because the headline CPI is muted after all, or because it has to change its policy rates from benchmark deposit/lending rates to interbank-linked rates sooner or later and so better start practicing now. In any case, it does not want the market to get ahead itself and price in too much tightening, just like the Fed.
  3. Fed's policy and US-China interest rate differentials do play a role in PBoC's consideration. It may not be a very big role, as offering 10bp for every 25bp from the Fed is at best half-hearted help to the RMB. However, the Fed's action offered the PBoC a timing to make the move, appearing to support the argument that the interbank rate hikes are “following the market”.

Given PBoC's latest move and our view that growth stability will stay until the end of 2017, SocGen now expects further interbank rate hikes: 20bp in 2Q, 10bp in 3Q and no change in 4Q.

The equally critical development to watch is the evolution of interbank market rates as resulted from PBoC's daily liquidity management. The trend of these market rates leads the changes of rates on PBoC's instruments, thus a more timely indication of PBoC's intention. Before today's moves, the 28-day moving average of the 7d repo was already 50bp above the low back in August 2016.

Finally, while China has traditionally shied away from criticizing the Fed using conventional channels, in a surprising editorial in the Economic Information Daily, the authors said that China should be wary of a "spillover effect" from the Fed rate hikes, warning that “selfish” US interest rate policies have historically triggered crises in many other nations, the newspaper says in its front-page commentary. Finally, it warned that frequent Fed rate hikes may have “serious impact” on global economy.

Keep a close eye on tonight's reverse repo facility: if China is really concerned, it very well may "hike" again.



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Brain Aging Gene Discovered

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Summary: Researchers have identified a genetic variant that can accelerate normal brain aging in older people by up to 12 years.

Source: Columbia University Medical Center.

Genetic variant accelerates normal brain aging in older people by up to 12 years.

Columbia University Medical Center (CUMC) researchers have discovered a common genetic variant that greatly impacts normal brain aging, starting at around age 65, and may modify the risk for neurodegenerative diseases. The findings could point toward a novel biomarker for the evaluation of anti-aging interventions and highlight potential new targets for the prevention or treatment of age-associated brain disorders such as Alzheimer’s disease.

The study was published online today in the journal Cell Systems.

“If you look at a group of seniors, some will look older than their peers and some will look younger,” said the study’s co-leader Asa Abeliovich, PhD, professor of pathology and neurology in the Taub Institute for Alzheimer’s Disease and the Aging Brain at CUMC. “The same differences in aging can be seen in the frontal cortex, the brain region responsible for higher mental processes. Our findings show that many of these differences are tied to variants of a gene called TMEM106B. People who have two ‘bad’ copies of this gene have a frontal cortex that, by various biological measures, appears 12 years older that those who have two normal copies.”

Studies have identified individual genes that increase one’s risk for various neurodegenerative disorders, such as apolipoprotein E (APOE) for Alzheimer’s disease. “But those genes explain only a small part of these diseases,” said study co-leader Herve Rhinn, PhD, assistant professor of pathology and cell biology in the Taub Institute. “By far, the major risk factor for neurodegenerative disease is aging. Something changes in the brain as you age that makes you more susceptible to brain disease. That got us thinking, ‘What, on a genetic level, is driving healthy brain aging?'”

In the current study, Drs. Abeliovich and Rhinn analyzed genetic data from autopsied human brain samples taken from 1,904 people without neurodegenerative disease. First, the researchers looked at the subjects’ transcriptomes (the initial products of gene expression), compiling an average picture of the brain biology of people at a given age. Next, each person’s transcriptome was compared to the average transcriptome of people at the same age, looking specifically at about 100 genes whose expression was found to increase or decrease with aging. From this comparison, the researchers derived a measure that they call differential aging: the difference between an individual’s apparent (biological) age and his or her true (chronological) age. “This told us whether an individual’s frontal cortex looked older or younger than expected,” said Dr. Abeliovich.

The researchers then searched the genome of each individual, looking for genetic variants that were associated with an increase in differential age.

“One variant stood out: TMEM106B,” said Dr. Rhinn. “It’s very common. About one-third of people have two copies and another third have one copy.”

“TMEM106B begins to exert its effect once people reach age 65,” said Dr. Abeliovich. “Until then, everybody’s in the same boat, and then there’s some yet-to-be-defined stress that kicks in. If you have two good copies of the gene, you respond well to that stress. If you have two bad copies, your brain ages quickly.”

Image shows a dna strand.Image shows a dna strand.

The researchers then searched the genome of each individual, looking for genetic variants that were associated with an increase in differential age. NeuroscienceNews image is for illustrative purposes only.

The researchers found a second variant–inside the progranulin gene–that contributes to brain aging, though less so than TMEM106B. Progranulin and TMEM106B are located on different chromosomes but are involved in the same signaling pathway. Both have also been associated with a rare neurodegenerative disease called frontotemporal dementia.

The study did not address what role the two genetic variants might have in neurodegenerative disease. “We were studying healthy individuals, so it is not about disease, per se,” said Dr. Abeliovich. “But of course, it’s in healthy tissue that you start to get disease. It appears that if you have these genetic variants, brain aging accelerates and that increases vulnerability to brain disease. And vice versa: if you have brain disease, the disease accelerates brain aging. It’s a vicious cycle.”

About this genetics and aging research article

Funding: The study was supported by grants from the National Institute of Aging (AG042317), the National Institute of Neurological Disorders and Stroke, and the Michael J. Fox Foundation for Parkinson’s Research.

Dr. Abeliovich is a co-founder of and consultant for Alector. Dr. Rhinn is a consultant for Alector. The researchers declare no other financial conflicts of interest.

Source: Karin Eskenazi – Columbia University Medical Center
Image Source: NeuroscienceNews.com image is in the public domain.
Original Research: The study will appear in Cell Systems.

Cite This NeuroscienceNews.com Article

Columbia University Medical Center “Brain Aging Gene Discovered.” NeuroscienceNews. NeuroscienceNews, 15 March 2017.
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Columbia University Medical Center (2017, March 15). Brain Aging Gene Discovered. NeuroscienceNew. Retrieved March 15, 2017 from http://ift.tt/2mJShHi

Columbia University Medical Center “Brain Aging Gene Discovered.” http://ift.tt/2mJShHi (accessed March 15, 2017).

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On Hockey & Success: 5 Steps to Help You Stick With It

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If you want to be successful at anything you must accept that your success will not come overnight. The most successful people have spent many hours of practice, dedication, and hard work to reach their level.

Instant gratification and overnight success are few and far between. Many people are motivated by a great idea and decide to go for it. They often fail because they don’t stick to it long enough. They are not willing to put in the time and the hard work.

How many of you know Kentucky Fried Chicken? Have you heard about the Colonel, the founder of KFC? After operating restaurants for many years Colonel Harlan Sanders at 65 years old found himself broke. Most people retire at 65! The Colonel developed a fried chicken recipe and began going door to door and from restaurant to restaurant trying to sell his recipe. Everyone said “NO”! The Colonel stuck with it and kept going and finally his first “yes” came after 1,009 tries!

Success Does Not Come Overnight

By 1964 the Colonel had 600 restaurants selling his chicken, he sold his business for $2 million dollars. He remained a spokesman for the company and in 1976 he was the world’s 2nd most recognized celebrity. The key for Colonel Sanders’ success? He stuck with it.

Now you might not savour the thought of selling chicken door to door. That’s fine, I get that. How about Michael Jordan? Arguably the greatest basketball player in history did not make his high school basketball team. Joe Sakic did not make his Midget team. These guys stuck with it and the rest is history!

Becoming a top athlete, business person, or a top professional in your field is a marathon and not a sprint. Great things take time, hard work and you have to stick with it!

Here are 5 steps to help you stick to your goals:

1. Find Your Passion

Passion is defined as “love; a strong liking or desire for or devotion to some activity, object, or concept.”

Do you have a dog? Do you ever play fetch using a tennis ball with your dog? Your dog gets focused on the tennis ball, he gets obsessed with the tennis ball, becomes passionate over the tennis ball. What is your tennis ball? Is it hockey? Is it another sport or a subject in school? Find your tennis ball!

2. Find Your Why

Why are you doing this? Why is it important to me? How will my idea impact my life? How will my why help others? What is your purpose?

Your why is your foundation for all your whats, whens, wheres, whos, and hows. When you are clear on your why, you will find a way. When you are passionate about your why, you will find your how.

You will achieve any what.

You will meet the right whos.

You will end up in the right where and overcome any challenging how.

Dig deep and discover your personal why. It has to be meaningful to you.

3. Write Your Plan Down

Stay connected to your why by keeping a record. Write it down. Setting goals creates a roadmap for yourself. You won’t know where to go unless you plan and follow the plan. Be specific and set a time frame.

There is scientific evidence that proves you have a chance to get where you want to go by writing out your plan.

4. Commit to Your Plan Every Day

“We are what we repeatedly do. Excellence then, is not an act, but a habit.” Aristotle said that. How true these words are! If you want to be great at something you have to prioritize and make sure you get things done on a daily basis.
People who reach great heights are not normal people as being great requires personal sacrifice and being comfortable being uncomfortable. It is not easy.

Make your practice a part of every day. Eliminate the excuses – why wait until tomorrow?

Break things down into small goals that you do every day no matter what and the little things will become big things at the end. Shoot 50 pucks per day. Run 2 miles every day. Read 1 chapter of your book every day or do 30 minutes per day of your homework project.

5. Just Stick With It

Keep your “why” in mind and don’t let anyone discourage you. Just stick to it on your own terms.

And just like your overall plan:

  1. Schedule your small tasks each day – keep yourself organized and accountable
  2. Track your progress – write down how your workout sessions went and what you did
  3. Find a friend or a coach or get one of your parents help you be accountable
  4. Visualize – see yourself reaching your goal using your mind’s eye!

 

The post On Hockey & Success: 5 Steps to Help You Stick With It appeared first on Hockey Coaching Tips & Drills.



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"Where's The Safe Space?" Inside The Most Censorious College Campuses

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The 2017 Free Speech University Rankings have been released, and it turns out that London is a hotbed of campus censorship.

To find out what’s going on, spiked-online.com's writer Jacob Furedi talked to fellow students about the state of free speech at their universities...

And in the US, it's just as bad... Free speech on campus is facing a profound threat. Not at the hands of President Trump, nor even at the hands of the administrators and lawyers who have done so much to erode academia’s respect for freedom of expression.

No, as highlighted by the violent disruption and end of Charles Murray’s visit to Middlebury College in Vermont last week, the immediate crisis comes from one of freedom’s most ancient enemies: the angry mob.

It’s time for college leaders and law enforcement to take a stand: In our nation, this is not what democracy looks like.

While Americans rightly tend to focus on threats to freedom of speech from the authorities, we cannot overlook the danger of allowing people to be silenced by groups prepared to be violent.



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Teach Yourself Computer Science

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Frequently asked questions

What about AI/graphics/pet-topic-X?

We’ve tried to limit our list to computer science topics that we feel every practicing software engineer should know, irrespective of specialty or industry. With this foundation, you’ll be in a much better position to pick up textbooks or papers and learn the core concepts without much guidance. Here are our suggested starting points for a couple of common “electives”:

  • For artificial intelligence: do Berkeley’s intro to AI course by watching the videos and completing the excellent Pacman projects. As a textbook, use Russell and Norvig’s Artificial Intelligence: A Modern Approach.
  • For machine learning: do Andrew Ng’s Coursera course. Be patient, and make sure you understand the fundamentals before racing off to shiny new topics like deep learning.

How strict is the suggested sequencing?

Realistically, all of these subjects have a significant amount of overlap, and refer to one another cyclically. Take for instance the relationship between discrete math and algorithms: learning math first would help you analyze and understand your algorithms in greater depth, but learning algorithms first would provide greater motivation and context for discrete math. Ideally, you’d revisit both of these topics many times throughout your career.

As such, our suggested sequencing is mostly there to help you just get started… if you have a compelling reason to prefer a different sequence, then go for it. The most significant “pre-requisites” in our opinion are: computer architecture before operating systems or databases, and networking and operating systems before distributed systems.

Who is the target audience for this guide?

We have in mind that you are a self-taught software engineer, bootcamp grad or precocious high school student, or a college student looking to supplement your formal education with some self-study. The question of when to embark upon this journey is an entirely personal one, but most people tend to benefit from having some professional experience before diving too deep into CS theory. For instance, we notice that students love learning about database systems if they have already worked with databases professionally, or about computer networking if they’ve worked on a web project or two.

How does this compare to Open Source Society or freeCodeCamp curricula?

The OSS guide has too many subjects, suggests inferior resources for many of them, and provides no rationale or guidance around why or what aspects of particular courses are valuable. We strove to limit our list of courses to those which you really should know as a software engineer, irrespective of your specialty, and to help you understand why each course is included.

freeCodeCamp is focused mostly on programming, not computer science. For why you might want to learn computer science, see above.

What about language X?

Learning a particular programming language is on a totally different plane to learning about an area of computer science — learning a language is much easier and much less valuable. If you already know a couple of languages, we strongly suggest simply following our guide and fitting language acquisition in the gaps, or leaving it for afterwards. If you’ve learned programming well (such as through Structure and Interpretation of Computer Programs), and especially if you have learned compilers, it should take you little more than a weekend to learn the essentials of a new language.

What about trendy technology X?

No single technology is important enough that learning to use it should be a core part of your education. On the other hand, it’s great that you’re excited to learn about that thing. The trick is to work backwards from the particular technology to the underlying field or concept, and learn that in depth before seeing how your trendy technology fits into the bigger picture.

Why are you still recommending the Dragon book?

The Dragon book is still the most complete single resource for compilers. It gets a bad rap, typically for overemphasizing certain topics that are less fashionable to cover in detail these days, such as parsing. The thing is, the book was never intended to be studied cover to cover, only to provide enough material for an instructor to put together a course. Similarly, a self-learner can choose their own adventure through the book, or better yet follow the suggestions that lecturers of public courses have made in their course outlines.

How can I get textbooks cheaply?

Many of the textbooks we suggest are freely available online, thanks to the generosity of their authors. For those that aren’t, we suggest buying used copies of older editions. As a general rule, if there has been more than a couple of editions of a textbook, it’s quite likely that an older edition is perfectly adequate. It’s certainly unlikely that the newest version is 10x better than an older one, even if that’s what the price difference is!

Who made this?

This guide was written by Ozan Onay and Myles Byrne, instructors at the Bradfield School of Computer Science in San Francisco. It is based on our experience teaching foundational computer science to hundreds of mostly self-taught engineers and bootcamp grads. Thank you to all of our students for your continued feedback on self-teaching resources. Thanks too to Alek Sharma, Omar Rayward, Ammar Mian and Tyler Bettilyon for feedback on this guide.



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Polymath Stephen Wolfram Defends His Computational Theory of Everything

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Stephen Wolfram seems to see himself as Newton upgraded with programming chops and business savvy, but it’s not hubris if you back it up. As he points out on his website, he published papers on particle physics in his mid-teens, earned a Ph.D. in physics from Caltech when he was 20 and won a MacArthur “genius” grant at 22. In his late 20s he invented and began successfully marketing Mathematica, software for automating calculations. Wolfram contends that Wolfram Language—which underpins Mathematica and Wolfram|Alpha, a knowledge engine he released in 2009—represents a “new paradigm for computation” that will enable humans and machines to “interact at a vastly richer and higher level than ever before.” This vision dovetails with the theme of Wolfram’s 2002 opus A New Kind of Science, which argues that simple computer programs, like those that generate cellular automata, can model the world more effectively than traditional mathematical methods. Physicist Steven Weinberg called the book an interesting “failure,” and other scientists griped that Wolfram had rediscovered old ideas. Critics have also accused Wolfram of hyping his computational products.* Yet Wolfram, when I saw him speak last fall at “Ethics of Artificial Intelligence,” exuded confidence, suggesting how Wolfram Language might transform law and politics. We recently had the following email exchange.–-John Horgan

Horgan: Can you summarize, briefly, the theme of A New Kind of Science? Are you satisfied with the book’s reception?

Wolfram: It’s about studying the computational universe of all possible programs and understanding what they can do.  Exact science had been very focused on using what are essentially specific kinds of programs based on mathematical ideas like calculus.  My goal was to dramatically generalize the kinds of programs that can be used as models in science, or as foundations for technology and so on.

The big surprise, I suppose, is that when one just goes out into the computational universe without any constraints, one finds that even incredibly simple programs can do extremely rich and complex things.  And a lot of the book is about understanding the implications of this for science.

I’ve been very happy with the number and diversity of people who I know have read the book.  There’ve been thousands of academic papers written on the basis of it, and there’s an increasing amount of technology that’s based on it.  It’s quite amazing to see how the idea of using programs as models in science has caught on.  Mathematical models dominated for three centuries, and in a very short time, program-based models seem to have become the overwhelming favorites for new models.

When the book came out, there was some fascinating sociology around it.  People in fields where change was “in the air” seemed generally very positive, but a number of people in fields that were then more static seemed to view it as a threatening paradigm shift.  Fifteen years later that shift is well on its way, and the objections originally raised are beginning to seem bizarre.  It’s a pity social media weren’t better developed in 2002, or things might have moved a little faster.

Horgan: Can the methods you describe in A New Kind of Science answer the question of why there is something rather than nothing?

Wolfram: Not that I can see so far.

Horgan: Can they solve "the hard problem"? That is, can they explain how matter can become conscious?

Wolfram: One of the core discoveries that I discussed in the book is what I call the Principle of Computational Equivalence—which implies that a very wide range of systems are equivalent in their computational sophistication.  And in particular, it means that brains are no more computationally sophisticated than lots of systems in nature, and even than systems with very simple rules.  It means that “the weather has a mind of its own” isn’t such a primitive thing to say: the fluid dynamics of the weather is just as sophisticated as something like a brain.

There’s lots of detailed history that makes our brains and their memories the way they are.  But there’s no bright line that separates what they’re doing from the “merely computational.” There are many philosophical implications to this.  But there are also practical ones.  And in fact this is what led me to think something like Wolfram|Alpha would be possible.

Horgan: The concept of computation, like information, presupposes the existence of mind. So when you suggest that the universe is a computer, aren't you guilty of anthropomorphism, or perhaps deism (assuming the mind for whom the computation is performed is God)?

Wolfram: The concept of computation doesn’t in any way presuppose the existence of mind... and it’s an incorrect summarization of my work to say that I suggest “the universe is a computer.”

Computation is just about following definite rules.  The concept of computation doesn’t presuppose a “substrate,” any more than talking about mathematical laws for nature presupposes a substrate.  When we say that the orbit of the Earth is determined by a differential equation, we’re just saying that the equation describes what the Earth does; we’re not suggesting that there are little machines inside the Earth solving the equation. 

About the universe: yes, I have been investigating the hypothesis that the universe follows simple rules that can be described by a program.  But this is just intended to be a description of what the universe does; there’s no “mechanism” involved.  Of course, we don’t know if this is a correct description of the universe.  But I consider it the simplest hypothesis, and I hope to either confirm or exclude it one day.

Horgan: What's the ultimate purpose of the Wolfram Language? Can it fulfill Leibniz's dream of a language that can help us resolve all questions, moral as well as scientific? Can it provide a means of unambiguous communication between all intelligent entities, whether biological or artificial?

Wolfram: My goal with the Wolfram Language is to have a language in which computations can conveniently be expressed for both humans and machines—and in which we’ve integrated as much knowledge about computation and about the world as possible.  In a way, the Wolfram Language is aimed at finally achieving some of the goals Leibniz had 300 years ago.  We now know—as a result of Gödel’s theorem, computational irreducibility, etc.—that there are limits to the scientific questions that can be resolved.  And as far as moral questions are concerned: well, the Wolfram Language is going in the direction of at least being able to express things like moral principles, but it can’t invent those; they have to come from humans and human society.

Horgan: Are autonomous machines, capable of choosing their own goals, inevitable? Is there anything we humans do that cannot—or should not—be automated?

Wolfram: When we see a rock fall, we could say either that it’s following a law of motion that makes it fall, or that it’s achieving the “goal” of being in a lower-potential-energy state.  When machines—or for that matter, brains—operate, we can describe them either as just following their rules, or as “achieving certain goals.”  And sometimes the rules will be complicated to state, but the goals are simpler, so we’ll emphasize the description in terms of goals.

What is inevitable about future machines is that they'll operate in ways we can't immediately foresee.  In fact, that happens all the time already; it's what bugs in programs are all about.  Will we choose to describe their behavior in terms of goals?  Maybe sometimes.  Not least because it'll give us a human-like context for understanding what they're doing.

The main thing we humans do that can't meaningfully be automated is to decide what we ultimately want to do.

Horgan: What is the most meaningful goal that any intelligence, human or inhuman, can pursue?

Wolfram: The notion of a “meaningful goal” is something that relies on a whole cultural context—so there can’t be a useful abstract answer to this question.

Horgan: Have you ever suspected that God exists, or that we live in a simulation?

Wolfram: If by “God” you just mean something beyond science: well, there’s always going to be something beyond science until we have a complete theory of the universe, and even then, we may well still be asking, “Why this universe, and not another?”

What would it mean for us to “live in a simulation”?  Maybe that down at the Planck scale we’d find a whole civilization that’s setting things up so our universe works the way it does.  Well, the Principle of Computational Equivalence says that the processes that go on at the Planck scale—even if they’re just “physics” ones—are going to be computationally equivalent to lots of other ones, including ones in a “civilization.”  So for basically the same reason that it makes sense to say “the weather has a mind of its own,” it doesn’t make any sense to imagine our universe as a “simulation.”

Horgan: What's your utopia?

Wolfram: If you mean: what do I personally want to do all day?  Well, I’ve been fortunate that I’ve been able to set up my life to let me spend a large fraction of my time doing what I want to be doing, which usually means creating things and figuring things out.  I like building large, elegant, useful, intellectual and practical structures---which is what I hope I’ve done over a long period of time, for example, with Wolfram Language. 

If you’re asking what I see as being the best ultimate outcome for our whole species---well, that’s a much more difficult question, though I’ve certainly thought about it.  Yes, there are things we want now---but how what we want will evolve after we’ve got those things is, I think, almost impossible for us to understand.  Look at what people see as goals today, and think how difficult it would be to explain many of them to someone even a few centuries ago.  Human goals will certainly evolve, and the things people will think are the best possible things to do in the future may well be things we don’t even have words for yet.

Further Reading:

*See critical reviews of A New Kind of Science by Scott Aaronson and Cosma Shalizi.

See Q&As with Steven Weinberg, George Ellis, Carlo Rovelli, Edward Witten, Scott Aaronson, Sabine Hossenfelder, Priyamvada Natarajan, Garrett Lisi, Paul Steinhardt, Lee Smolin, Robin Hanson, Eliezer Yudkowsky, Stuart Kauffman, Christof Koch, Rupert Sheldrake and Sheldon Solomon.

How Would AI Cover an AI Conference?

Can Engineers and Scientists Ever Master "Complexity"?

So Far, Big Data Is Small Potatoes

Is "Social Science" an Oxymoron? Will That Ever Change?



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