How My Algorithm Beat the Market 10 Times Over

On October 19, 1987 — 20 years ago last Thursday — the Dow Jones Industrial Average (DJIA) lost nearly a quarter of its value in a few hours.

Back then, that was 508 points. A similar drop today would be almost 6,000 points.

Imagine that, if you will … if you dare.

On that day, traders watched in horror as wave after wave of selling ratcheted the index downward. Like a ball bouncing down a hill, each wave seemed faster and bigger than the last.

They looked at each other blankly, since none of them seemed to be doing any of the selling. They weren’t … computers used by big institutional investors were executing automated trades based on incoming price data.

In 1987, market technology was in its infancy. Today’s computerized trading is as far ahead of that as an F-35 Lightning II is ahead of the Wright Brothers.

Should you be worried? Yes … or no … it all depends on how you use today’s technology.

Do you do it the market’s way … or my way?

Warning Signs

On Wednesday, October 14, 1987, the DJIA dropped 3.8%. It fell another 2.4% the next day. On Friday, the DJIA fell another 4.6%, on record trading volume.

All eyes were on Monday.

Now, a 10% drop in three days is significant. But it’s always worse when markets end the week down. Depending on how after-hours options trading goes … and events over the weekend … traders are often poised to sell on Monday morning.

Black Monday began with a wave of selling in the Hong Kong market. Normally, London-based bargain hunters might have counteracted this, but the Great Storm of 1987 had led London’s markets to close early on Friday; most traders were told to stay home on Monday. With nobody on watch, the London FTSE 100 had fallen over 136 points by 9.30 a.m.

That was all the newfangled computers installed at large U.S. investors needed to initiate selling orders. “Portfolio insurance” algorithms started short-selling U.S. stocks and index futures.

As other computers detected this, they started selling automatically as well. The few algorithms that were programmed to suspend trading did so, decreasingly liquidity and increasing the speed of price drops.

U.S. markets soon recovered, but those who had sold in a panic on Black Monday lost a great deal of money.

Lessons Unlearnt

Black Monday wasn’t the last time algorithms have been blamed for sudden market drops. Here are some of the more prominent examples:

  • The August 7-10 “quant quake” of 2007. Funds specializing in algorithmic investment strategies suffered massive losses.
  • In the “flash crash” of May 6, 2010, the Dow dropped 9% and the S&P 500 fell 7% in just 30 minutes, as bids and offers for stocks moved far away from previous levels — in some cases leaving bids down as low as a penny and offers as high as $100,000.
  • On August 24, 2015, the S&P 500 plummeted 5% and the Dow dropped by 6.7% in just five minutes after the opening.

How Now?

In every one of these cases, researchers have blamed the “stampede effect” of automated algorithm-based trading systems. Unattended programs designed to cut losses reinforced each other in a downward spiral that only ended when humans intervened.

Such systems now account for more than 75% of U.S. stock market volumes. One reason is that much trading now occurs in penny intervals.

That makes trading less lucrative for market makers, who profit by playing the “spread” between the highest bid to buy and the lowest offer to sell. As they have retreated from the market, algorithms have stepped in to replace their essential liquidity-providing function.

The shift to automated trading now includes actively managed mutual funds. In March, BlackRock announced it would fire human traders and rely more on stock-picking algorithms, triggering other traditional asset managers to follow suit.

Not All Algorithms Are Created Equal

Computers now manage trillions of dollars in global stock markets. But there are two ways to use them.

The first way is as I’ve described above. Big institutional investors use automated algorithmic systems because they reduce costs and the time-wasting “friction” of human decision-making. Trades can be executed in milliseconds by the millions, generating tiny profits from each that add up to a lot.

The other way is the way we use algorithms in trading services such as Alpha Stock Alertand the Smart Money portfolio in my Bauman Letter.

In those services, we use algorithms to remove only one part of the human role in trading: emotion. We make a zen-like commitment to let the rules call the shots. Empirical back testing shows that this a true market-beater — excess gains of 600%, even 900% are possible over time.

But the Alpha and Smart Money algorithms incorporate three things that the big boys don’t.

One is a hedging strategy that tells us to short the market before it corrects.

The second is algorithms that include fundamental and sentiment analysis at the company level. Using those, we don’t sell just because a stock goes down along with the market. We keep otherwise healthy positions because we know they will rebound, as markets always have after a crash.

But the third feature of our systems is the most important: Computers running our algorithms may make the calls, but we — humans, not computers — push the button to trade. Always.

That way, when a true “black swan” event arises … one that no algorithm can possibly predict … we can step in before it’s too late.

Consider it the best of both worlds.

Kind regards,

Ted Bauman
Editor, The Bauman Letter

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How to Collect $3,000+ in Dividends per Month, Every Month

Most investors with $500,000 in their portfolios think they don’t have enough money to retire on.

They do – they just need to do two things with their “buy and hope” portfolios to turn them into $3,279 monthly income streams (or much more):

  1. Sell everything – including the 2%, 3% and even 4% payers that simply don’t yield enough to matter. And,
  2. Buy my 8 favorite monthly dividend payers.

The result? $3,279.69 in monthly income every month (from an average 7.6% annual yield, paid every 30 days). Withupside on your initial $500,000 to boot!

And this strategy isn’t capped at $500,000. If you’ve saved a million (or even two), you can just buy more of my elite eight monthly payers and boost your passive income to $6,349 or even $12,698 per month.

Though if you’re a billionaire, sorry, you are out of luck. These Goldilocks payers won’t be able to absorb all of your cash. With total market caps around $1 billion or $2 billion, these vehicles are too small for institutional money.

Which is perfect for humble contrarians like you and me. This ceiling has created inefficiencies that we can take advantage of. After all, in a completely efficient market, we’d have to make a choice between dividends and upside. Here, though, we get both.

Heck, This Grandma Makes $387,000 Last Forever

Recently I was chatting with a reader of mine who manages money for a select group of clients. He’s using my No Withdrawal Portfolio to make a client’s modest savings – a nice grandmother with $387,000 – last longer than she ever dreamed:

“She brought me $387,000,” he said. “And wants to take out $3,000 per month for ten years.”

“Well she’s already withdrawn money for eight months (at $3,000 per month) and her balance has actually grown to $397,000. If the portfolio continues yielding 7% per year plus 2% per year in capital gains, and she withdraws $3,000 per month, it will pay my fees and still last her 27 years!”

Now many retirement experts pitch real estate as the best way to bank monthly income. But this grandma isn’t hustling to collect rent checks, or fix broken light bulbs. She’s simply collecting her “dividend pension” every month, which is 100% funded by her stocks and funds.

Actually her monthly salary is more than 100% financed – which is why her portfolio has grown by $10,000 as she’s withdrawn $3,000 per month.

How is This Possible? With “B-List” Monthly Payers Like These

Apple Hospitality REIT (APLE)
Dividend Yield: 6.2%

I wonder how many investors researching Apple (AAPL) have accidentally come across this lesser-known real estate investment trust, only to quickly punch in the correct ticker and get back to reading about iPhones.

Anyone who had missed out on a gem.

Apple Hospitality REIT (APLE) owns 236 hotels across 33 states for a capacity of roughly 30,000 guestrooms. The REIT’s properties are spread between two upscale hotel families – Hilton (HLT) and Marriott (MAR) – which includes their namesake brands, as well as the likes of Fairfield Inn, Embassy Suites and SpringHill Suites.

APLE has delivered an impressive growth story over the years, ballooning its top line from less than $400 million in 2013 to more than $1 billion last year. However, while the company has been rapidly expanding, management is fiscally responsible and has given the dividend a wide safety net.

Through the first six months of 2017, the company posted 90 cents per share in modified funds from operations (MFFO) – a tweaked version of FFO, which itself is an important gauge of a REIT’s operational performance and dividend health – against six dividends of 10 cents each. That equates to a payout ratio of just 67%, meaning it would take a catastrophe to keep Apple Hospitality from ponying up what it owes shareholders.

You Won’t Have to Worry About Apple Hospitality’s (APLE) Payout

Global Net Lease (GNL)
Dividend Yield: 9.6%

Global Net Lease (GNL) would seem to be a prime monthly dividend payer for several reasons.

For one, GNL is a “triple-net lease” REIT. Unlike many REITs that take responsibility for things such as taxes, insurance and maintenance, triple-net leasers instead push all those expenses onto the tenants. The tradeoff here is that they don’t charge lessees as much, but what they do bring in should be much more predictable.

GNL also has a couple other plusses, such as international diversity – it owns commercial properties not just in the U.S., but also the U.K., Germany and a few other European countries. Moreover, it doles out nearly 10% in dividends at the moment. And better still, it’s growing; Q2’s revenues, for instance, soared by more than 14% year-over-year.

However, Global Net Lease is externally managed, which requires it to pay a great many fees for property management and other services – fees that cramp the company’s funds from operations to a dangerous extent. GNL paid out 97% of its adjusted funds from operations (AFFO) as dividends last year, and through six months of 2017, this REIT has actually paid out a little more than its total AFFO.

Worse, GNL investors have watched shares decline 5% year-to-date amid a broad up-market, eating up much of their gains from income.

Global Net Lease’s (GNL) Dividend Is Merely Subsidizing Your Losses

EPR Properties (EPR)
Dividend Yield: 5.8%

EPR Properties (EPR) is a play on one of my favorite themes of the past few years: the “experience economy.”

In short, people have started to put less value in merely amassing things, stuff and junk, and instead are increasingly spending their money doing things. That – along with the rise of (AMZN) and other e-commerce operators – have torn a hole through a number of retail REITs – but has benefitted a handful of properly positioned companies, including EPR.

Do you go to the movies? Ski? Have you ever spent a few hour in one of those state-of-the-art TopGolf driving ranges, complete with high-tech games and swanky bars? If so, chances are you’ve helped pad the pockets of EPR, which boasts 378 properties across the U.S.

That said, EPR is much more than entertainment – it also holds properties used for things such as public charter schools and early childhood education centers.

This extremely diversified REIT delivers a monthly payout that just got more than 6% sweeter earlier this year. Better still, the dividend is just 82% of AFFO, so EPR has plenty of ability to meet its obligation.

EPR Properties (EPR) IS Part of a New Generation of High-Performance REITs 

SPDR Barclays High Yield Bond ETF (JNK)
SEC Yield: 5.7%

It’s not widely practiced, but a few exchange-traded funds (ETFs) do dole out income monthly instead of quarterly. Better still, some of these monthly ETF payers even pay a fairly consistent amount of income every month.

The SPDR Barclays High Yield Bond ETF (JNK) does just enough to qualify, and in fact is a generally popular ETF. But I say stay away.

The JNK is a portfolio of nearly a thousand different junk issues – corporate bonds that are below investment grade, which means they have a higher risk of default, but also means that they have to yield more to compensate for that risk. Because SPDR’s junk ETF is so diversified (and so cheap), though, it has become a very common way for investors to gain exposure to this high-income bond class.

However, the JNK doesn’t hold a candle to a number of junk-focused closed-end funds (CEFs).

SPDR’s JNK Isn’t Junk, But It’s No Treasure, Either

These funds tend to charge more in expenses because of their active management, and they’re not nearly as talked about, but on average they offer much higher yields and have delivered much better performance than this merely “OK” exchange-traded fund.

Don’t buy into JNK’s junky payouts.

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Source: Contrarian Outlook