Category Archives: Financial Markets

HOW HYPERLOCAL ECONOMIES EVOLVE

By: William Arrington

The original intent for this follow up to Hyperlocal Social Economies (HSEs) was to focus on how businesses can participate in these targeted consumption markets. I think this is an appropriate time to discuss how HSEs may evolve. Before diving in let’s quickly recap what comprises an HSE market:

  • A group of consumers with similar lifestyle and consumption patterns (i.e. friends)
  • Common set of goods/services consumed by the group
  • Competitive market for said goods and services
  • Goods and services are geographically unbound

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THE SUM OF ALL PARTS

Optimizing Human Behavior with a STEM Model

by Moises Goldman PhD

 

The Human Conundrum

For the last 15 years I have given numerous seminars aimed at optimizing executive and managerial performance in technology driven firms. The goal is to optimize departmental performance resulting in the larger optimization of an entire firm. As the theory goes: If the whole is the sum of the parts, and each part is optimized, then the whole is optimized.

These experiences have challenged my ability to communicate with people involved in STEM fields. This group represents a highly gifted segment of the population, and they tend to be very results driven. How does one reason, interpret, and convince scientists to modify their own behavior?

At first, I struggled with the appropriate lingo. I pondered how to describe my ideas using managerial jargon. I realized that I needed another language—a language that both empirical and intuitive thinkers will readily grasp and put to good use.

Then my eureka moment came to me. STEM initiatives are defined by basic human bevavior and not the other way around.

To some, this may seem counterintuitive, so let me elaborate. If we first accept and understand any given issue at hand through basic human reasoning, we can then interpret it in a STEM format. Once we do that, we can use the tools of science to bring about an optimized outcome. Let me add some clarity with the following example:

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Kalman Filtering

My Ph.D. is in Inertial Navigation and my Masters in Control Systems. I spent many years as an executive in the aerospace industry and came to be expert in Kalman Filtering, a complex mathematical algorithm used in the guidance and navigation of aerospace vehicles. It occurred to me to apply this knowledge to the human equation.

Kalman Filtering is also known as Linear Quadratic Estimation (LQE), but it’s not necessary to go into the math here. I will attempt to make this example clear and concise. All we need is a simple diagram. I’ll describe it in layman’s terms and then apply it to the human condition.

The diagram below describes the guidance control of a space vehicle. The vehicle is at position “time-zero” or T(0). We want to get to position T(1,000,000). We calculate the location of our target relative to our present location. We recognize that any internal disturbance, such as bad sensors, electronics, and perhaps bad computations must be eliminated. (We get rid of them.)

  • We predict the trajectory of the vehicle over a short increment of time.
  • We measure the actual flight path against our target and factor in real environmental conditions (noise), such as wind speed, meteorites, etc.
  • We correct our trajectory.

The vehicle is now at T(1)—a very small part of the entire trip. T(1) is the next starting position. The algorithm repeats, bringing the vehicle to the next position T(2), then T(3), and so on. We iterate—continue to perform the same steps—predict, measure, correct—to optimize the overall trajectory to the target—T(1,000,000).

Perhaps you recognize this as a description of the way a child learns to walk. It’s commonly called a feedback loop. It governs behavior in many human pursuits. It’s the way our central nervous system directs us to negotiate a curve while driving down the road. It’s the way a baseball player catches a ball and executes a play. It’s how a circus performer walks a tightrope. It’s the way we all learn optimum behaviors.

Our minds perform this function intuitively through ordinary mental concentration, focus, or attentiveness. Concentration is an iterative process and the higher the number of iterations, the higher the degree of accuracy.

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Optimizing Human Behavior

If we can model our human behavior and reasoning in STEM format then we are able to optimize it. As an example, let’s choose a simple human behavior and describe it using Kalman Filtering:

Behavior—Tomorrow I’m taking a final exam; I need to arrive at 8 am—the target.

Method—My class always meets at that time, so I already know approximately when to wake up. Since there cannot be any internal disturbances, I eat a good dinner, plan my breakfast and what to wear to school. I give myself time to study and get to bed early. I set my alarm for 7 am. I’m at position T(0) on the diagram.

  • Prediction—I estimate the time it takes to get ready and walk to the exam. (About the same as a normal day.)
  • Measurement—I reach the door and glance at my watch. It’s raining and I’m running late.
  • Correction—I grab an umbrella while at the same time speeding up my pace.

I get to the exam location on time, and the algorithm repeats itself for the next activity (assuming my intention is to optimize the next behavior).

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A Simple Model for STEM Communication

It’s amazing how simply human behavior can be optimized using a STEM model—whatever the circumstances may be.

We know our current state. [We are on a diet, T(0).]

  • We predict the meal that we are going to eat. [A nice juicy zero carb steak.]
  • We eliminate any internal errors [If we’re cooking it, we make sure all the ingredients are there; check the labels for carbohydrate count; grill in working order; plates and glasses, etc.]
  • We set out to eat, then get a call that we’re needed immediately somewhere else. We make a correction. [Either we eat extremely fast or put the meal away for later, at T(1).]

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Optimizing Complex Behavior

Now let’s apply this same optimization process to a non-linear human behavior—investing in the stock market. We have some money to invest, T(0), in a given company stock. We eliminate all the internal disturbances by doing our homework. We read quarterly statements, look at the fundamentals, research the competition, analyze price and volume activity on a stock chart, and interpret technical indicators such as MACD and Slow Stochastics.

  • We predict our next move—[buy the stock]—T(0).
  • As we are getting ready to buy the stock we hear news of the latest unemployment report and we realize it will have a direct effect on the stock we are buying. We must correct. [We buy more, less, a different stock, or sit tight. Which correction we use will have a direct effect on the optimization.]
  • We decide to buy more of the stock. Now we are at T(1), and must predict T(2)—[sell, hold, or add to position].

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Achieving Greater Accuracy

The more we are able to reduce the size of T (time), the more we increase the Kalman iterations, and the better the optimization. In human terms, optimization is inversely proportional to the size of T, and directly proportional to Intelligence. Please note that human thinking is continuous in time, so the smaller our intervals, the closer we approximate a continuum.

As you see, I found my language for communicating optimization of human activity in any given organization. It is an amazingly powerful tool.

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MORE FROM MOISES COMING SOON

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Moises Goldman at IMSA

About the Author

Dr. Moises Goldman is uniquely involved with STEM (Science, Technology, Engineering, and Mathematics). He is a member of several advisory boards at MIT and is a founding member of the TALENT program at IMSA.

 

Kalman Diagram—Moises Goldman

Portrait of Moises & Chicago Globe—John Jonelis

Other graphics—MS Office

Chicago Venture Magazine is a publication of Nathaniel Press www.ChicagoVentureMagazine.com Comments and re-posts in full or in part are welcomed and encouraged if accompanied by attribution and a web link. This is not investment advice. We do not guarantee accuracy. Please perform your own due diligence. It’s not our fault if you lose money.
.Copyright © 2017 John Jonelis – All Rights Reserved
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IN YOUR FACE RISK

by John Jonelis

“Oh, you’re an angel investor! Isn’t that risky?” I hear such drivel all the time. Are people afraid of outsized returns? Or perhaps they don’t understand risk, don’t know how to measure it, or how to take control of it. Yet all that is quite easily done and it’s a real charge to play the game using a Monte Carlo simulation (MC). I’ll show what’s likely to happen if you follow three simple rules. Then I’ll break one rule—just a little bit—and we’ll use the simulator to see what happens.

fear-color

Rules of the Game

Rule #1 – Diversification and the Law of Large Numbers—This is the only free ride in the investment world. Invest in as many dissimilar companies as possible.

The portfolio technique known as the Efficient Frontier suggests you indulge in alternative investments to the tune of 10% of your overall portfolio to maximize return and minimize risk—that’s right, both! Angel investment is definitely in the alternative camp, so restrict your fun to 10%. No more! It’s true—angels are like anybody else. They also own stocks and bonds, futures and options, currency spreads and real estate, antique cars and art collections.

Rule #2 – Identical Minimum Sum—Nobody knows whether a company will succeed or fail. Nobody. Even the best, most experienced, wisest, most savvy investors can’t tell. So out of your alternative portfolio, invest the identical minimum sum in each and every deal—no more, no less—no exceptions! Make it as small as you can. 2% is a good number to shoot for. Ideally, with profits taken along the way, you’ll eventually own 50 to 100 companies!

Rule #3 – Join an Angel Group—Contrary to public opinion, most investors aren’t multi-millionaires. An angel group allows you to invest small sums in concert with others in the group, and coincidentally, it makes it possible to obey Rules #1 and #2.

I also assume that a personal research staff isn’t in your budget. A good angel group solves that problem by splitting the workload among its members according to their particular expertise. A strong group will accelerate your learning curve. The trust and camaraderie you build with other members makes angel investing a real joy. My own experience as a member of Heartland Angels has broadened my horizons and given me so much more than I could ever contribute.

It’s not a rule, but read the book ANGEL INVESTING by David Rose. You’ll be glad you did.

dice

Beware

If you don’t like to help companies grow from raw idea to industry leader; if you aren’t willing to participate in the fascinating and often perplexing details of a new business venture; if you can’t stand people; if you’re afraid—then invest in a mutual fund or put your money in gold coins and count them every day, just for something to do.

 

Picture Your Risk

I’m visually oriented. To paint the picture of risk, I use a Monte Carlo engine. MC is a sophisticated and arcane statistical tool that any child can use. If you’re a spreadsheet whiz, you can set it up yourself. I downloaded a program called Equity Monaco that makes it easy to enter investment outcomes, and analyze results.

NOTE: If you find yourself gazing at a bunch of confusing readouts with a vacant stare, read my paper, ALTERNATE HISTORIES. It’s written in plain language. It’s short. You’ll be an expert in no time.

angel

How Angels Make Money

Angel investing is long term—3-10 years. But like any investment class, you’ll cash out of one deal and put that money in another. It’s a continuing cycle. It’s also a homerun strategy. Can a homerun strategy be a winning strategy? Let’s run the numbers and see.

First, we need a data set of ordinary, average, run-of-the-mill trade results. Turns out, the Kauffman Foundation keeps statistics and publishes them.

Here’s the bottom line, according to Kauffman, 38.1% of startups grow and get acquired by a larger company, at which point all the investors throw a party! 11% become lifestyle businesses. These may provide a nice living for the employees but it takes the investors a really long time to cash out. 50.9% of companies go belly-up. Of those, 0.9% just disappear!

startups

Actual Angel Returns

Let’s keep this simple. From the investor’s perspective, all the returns from Kauffman’s wealth of past data boil down to five distinct outcomes. I express these as multiples of cash invested. (“10x” is a return of 10 times your investment.) Then I list the probability of each outcome.

return-vs-probability

Return as a multiple of investment vs. probability

Kauffman Foundation

 

Using these numbers, and applying our rules, it’s simple to build a simulated portfolio that represents likely outcomes.

Let’s assume that 10% of your portfolio amounts to $50K. Your angel group’s minimum investment is 10K. That means you need to plunk down 10% of your stake per deal, rather than the recommended 2%. You’re undercapitalized! Your Identical Minimum Sum, is high.

What does that mean to you? You’ll participate in fewer trades than some rich slob. All other things being equal, your results will be less predictable. The rich get richer, etc. etc. But you’re young and aggressive. Let’s say you go ahead anyway.

Now create a list of outcomes, based on Kauffman’s stats.

how-deals-shake-out

Notice that you follow all three rules. You invest exactly the same amount each time. Using an angel group, you invest the smallest amount you can get away with, and you participate in as many attractive deals as you can.

 

The Face of Risk

We’re ready to run our simulations. Feed those numbers into your MC engine and let the computer do the work. (I apologize for omitting legends from the charts, but the numbers in my program are too tiny to read. Hey, these are actual screenshots from my software package. So permit me to clue you in:

  • The X axis is about 100 deals.
  • The Y axis runs from zero to almost $2,500,000.
  • All equity lines start at $50K—your alternative portfolio.

std-10-long

10 possible equity curves

Here’s an MC output of 10 runs from the set we just built. Each line is a distinct equity curve that represents your portfolio. All are possible. Notice that two of them go negative quickly and never recover. But the rest do quite well. This isn’t enough data to draw any valid conclusions. Let’s run more simulations, using the same data set.

std-30-long

30 possible equity curves

Here we have 30 equity curves. The projections are getting clearer. Let’s run a few more, using exactly the same data set.

std-100-long

100 possible equity curves

Ah! Here we go—100 outcomes. The variation is nice and tight. Kurtosis is evident in the plot—in other words, the most likely results cluster around the mean. Looks like a good experiment to me. Let’s use this one.

 

ANALYSIS

Analyzing these plots is amazingly intuitive. For this experiment, the equity lines all start at $50K—your portfolio. A few outcomes go negative, but most look quite promising. The luckiest investor walks home with $2,450,000. MC plots don’t necessarily follow a standard distribution, but the mean looks to be about $1,450,000. Let’s focus on that number.

If we achieve the mean, we’re looking at an average return of 28 times investment. Does 28x get your attention? It gets mine! It even raises suspicions about possible survivorship bias in Kauffman’s numbers. But these are the best statistics we have so we’ll go with them.

How much is 28x as an annual percent return? That depends on turnover of deal flow. The shorter the hold time, the larger the IRR. 3 years is better than 10.

By the way, you may be wondering which curve is yours. There’s no answer to that question. But since your portfolio is so small, you’re more likely to find yourself on the fringe. An investor that’s filthy rich and participates in many more deals, enjoys a more predictable outcome and probably lands close to the mean.

 

BREAKING THE RULES

Let’s find out what happens if we break just one rule. And who doesn’t do that? So you invest $100K in a really juicy deal. It’s the best prospect you’ve ever seen and you figure it’ll make you rich. This thing can’t miss! Hey, it’s just one investment—how much difference can it make? You have just violated the Identical Minimum Sum rule. I know. I made this mistake once.

We add it to our data set and run the simulation. For this, we increase your portfolio size and retain all the same trades from the last run. This is what the hotshots call sensitivity analysis.

undis-100-long

100 possible equity curves – breaking one rule

Whoa! Look at what that one lapse in discipline does to your projections! The mean is now flat—zero times return! Half the outcomes are negative. No, I don’t’ want to play in this sandbox.

Successful investing is primarily adherence to a solid set of rules. That’s called discipline. The goal of discipline is to keep the probabilities in your favor. Discipline defines success.

That doesn’t mean that a successful angel can get by without a good skillset. You need to exercise brilliant judgement. You must perform your due diligence. Knowledge and experience are huge. Always keep the human side in mind. And you need to follow-up. Watch your companies closely as they pivot and grow. I leave you with this thought:

david-rose-quote

Also read – ALTERNATE HISTORIES

 

John Jonelis is a writer, investor, fisherman, author of the novel,

THE GAMEMAKER’S FATHER, publisher of Chicago Venture Magazine, and editor of News From Heartland.

The term IDENTICAL MINIMUM SUM is from the author.

Thanks to David Rose and his book ANGEL INVESTING.

Statistics from the Kauffman Foundation.

MC plots from Equity Monaco by TickQuest.

Graphic courtesy MS Office.

DISCLAIMER – Do your own due diligence. It’s not my fault if you lose money.

Chicago Venture Magazine is a publication of Nathaniel Press www.ChicagoVentureMagazine.com Comments and re-posts in full or in part are welcomed and encouraged if accompanied by attribution and a web link. This is not investment advice. We do not guarantee accuracy. It’s not our fault if you lose money.

.Copyright © 2016 John Jonelis – All Rights Reserved

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KILLER SHILLER

John Jonelis


Robert Shiller TAt Loop Lonagan’s urging, I’m walking his 85 pound bull terrier Clamps down the hard Chicago winter pavement. I don’t mind because it’s an opportunity to road test my two knee replacements.  That’s right; I’m the happy product of the wonders of modern orthopedic carpentry!  And I enjoy the best physical therapy known to man because I own the company!

Old Donatas Ludditis flanks my other side to make sure I don’t slip on a stray patch of ice. Despite my upbeat attitude, I hold Clamp’s heavy leather leash with some trepidation.  In my condition, I seriously doubt my ability to control such a large and volatile animal.

DSC04929e500

Clamps

I ask Loop why he insisted on this excursion.

“Hadda break you outa that place. Dem physical therapy gals is controllin’ yer whole life.  And we got business t’ discuss.  Ain’t that right, Don? ”

Old Man Ludditis slowly nods. “You listen to what he say. In old country we obey elders, not women.”

I can’t imagine anybody more elderly than Don but I object: “Everybody says my recovery is going so well.”

Don lays a hand gently across my shoulder, as if taking me into his confidence. “John, I know you invest big in this physical therapy company…but it not right.”

“Phooey! All the employees of Pavlovian PT are extremely lovely young ladies—” I catch my blunder and quickly shift gears. “I mean highly skilled physical therapists.”

Don sadly shakes his head. “John, it not look good. It seem—how you say—immoral.”

“It does plenty for my morale.”

Lonagan sighs. “Dem females got you completely bamboozled.   Yer prob’ly takin’ enough Norco so’s you don’t notice.  Brain’s like mush.  So lemme lay it out fer ya, okay? 

  • “That nutritionist feeds you fulla nothin’ but vegetables ‘n’ health food supplements. Doncha even notice what yer eatin’? Today, we’s gonna get ourselves some thick juicy steaks. How’s about that?
  • “Then there’s that Asian beauty twists ya into a pretzel twice a day ‘n’ yer too numb ‘n’ googoo eyed t’ feel any pain. C’mon, admit it—yer putty in her hands. So it ain’t yer brains behind this deal. What does that leave us with?
  • “Then that knockout Swedish masseuse gives you a hot bath ‘n’ rub down. Hoo boy, I ain’t sure I can take any more ‘o dis.

“I deeply resent these lewd insinuations.  Nothing improper is going on.”

“Resent away, John. Sheesh—I betcha never give business er economics a thought.  Prob’ly fer weeks.  Get my drift?”

He’s got me there. Economics definitely hasn’t crossed my mind at all.

Clamps lunges at a bright green Lexus sedan.  Probably targeting a tire. I haul back on the leash and quickly lose my balance.  Lonagan grabs the lead and lifts me by the collar before I tip over.  A broad smile spreads over his mug.

“But now we’s free, John boy! Take a deep breath! We can talk ‘bout anything youse guys want.  And get some real food!”

“Yah,” says Don.  “Good talk. Good food.  This is place.”

We’re at Michael Jordan’s Steak House.

“Just hook Clamp’s lead over that post.” Lonagan points toward the curb where cars whoosh past on Michigan Avenue.

“Loop, this is a rare and valuable animal. Somebody will steal him.”

“Can’t take ‘im inside. It’ll be okay.” 

We leave the dog at the curb, get ushered to comfortable red leather seats, and immediately order our steaks.

Loop leans back, takes a healthy sip of beer, and exhales in satisfaction—a clear signal he’s opening up a topic of conversation. “I saw Robert Shiller talk the other day. Big deal economist.  Know the guy?”

Robert Shiller

Robert Shiller – from Wikipedia

It takes me a moment. “Uh…financial guru? Yale, I think.  Nobel prize in econ?”

Don: “He share prize with Eugene Fama and Lars Peter Hansen. They—both of them—University Chicago boys.”

Loop slams his empty glass to the table. “Them guys never agree on nothin’. Fama gave us that crazy Perfect Market Hypothosis.”  He spins his index finger around his temple—an unmistakable and insulting gesture.

I lean back to enjoy the fireworks.

Ludditis raises his voice a notch. “Perfect Market Theory—it settled science

Loop: “Well, I guess a guy’s gotta believe in somethin’. I hate t’ contradict a good Chicago boy but that theory is a load o’ bunk.”

Don: “Big finance thinkers—they all say is true.”

Loop: “Only in universities ‘n’ now Shiller proved otherwise. Da big brokers ‘n’ traders always knew better.  It’s so stupid, it’s—” 

Loop stops. Cocks his head.  Switches to a conciliatory tone. “Okay Don—why doncha explain it to us in simple terms, so’s we understand?”

Don raises himself erect in his chair. “I try. With you, is not so easy.  I give example:  Once upon time, news come out on certain stock.  Investors, they predict it go up.  Everybody buy.  Drive up price.  Stock no longer good value.  Fall again.  Price chart show no logic or reason—what they call Random Walk.”

“Bullshit!” Loop’s thick fist pounds our heavy table and beer sloshes out of my glass.  “Sure they drive up da price.  It’s a determined strategy.  Once that happens, the trade is done, ‘n’ all da smart money is already out with fat gains leavin’ da retail crowd high ‘n’ dry.  Markets move due t’ aggression.  It ain’t some disconnected perfect market.   Real traders profit in real dollars. 

“But now that’s changing too. Da High Freaks—I mean da big brokerage houses—is tradin’ with powerful computer algorithms, in ‘n’ out in miliseconds.  Hell, they make over 70% of the volume ever’where ya look.  They pushed all da floor traders off the edge of the world.  Kaput!  Short term gets killed off by shorter term ‘n’ da universities still say it don’t exist!”

Me: “That’s why you switched to private equity?”

“Yeah, I saw it comin’ years ago.” Loop shows both palms.  “But I still wanna talk about Bob Shiller.

S&P Price Earnings, Div, Int from Irrational Exuberance Shiller

S&P Index Price vs Dividends – from Irrational Exuberance

“Ever’body thinks investors make rational decisions.  Shiller’s a completely different animal.  He takes into account all da crazy stuff goes on. He gave us Behavioral Finance.  He called da internet bubble o’ 2000 right to the month. Then he gave us da Case-Shiller Index ‘n’ called the housing bubble.” 

Loop turns his palms back down.  “Fama never predicted nothin.’   

Loop pauses—for effect I suppose—then goes on: “Shiller says, you can predict asset prices. Fer an economist, dis is big stuff!  How does he do it?  Way too much volatility caused by illogical decisions compared to future cash flow.  Turns out you can measure it.  That shakes up da whole academic world.” 

Home Prices, Irrational Exuberance Shiller

Home prices – from Irrational Exuberance

So this is this the news flash I missed while embroiled in such excellent and enjoyable physical therapy.

Don: “You not correct about Shiller study.  It predict long term only.  To quote famous economist, ‘In long run, we all dead.’”

Loop: “Yeah, Shiller’s model’s limited t’ dividend-paying stocks, so that’s as far as he can go fer now. Maybe someday he gets the resta the story.” 

Our steak is served and we all tuck in. When dinner is done, Lonagan surprises me by paying the bill.

We exit the premises to find Clamps crouched on the pavement, his short, powerful tail wagging vigorously. The dog is happily chewing on an electric green Nike sneaker.  I always thought dogs were color blind.

Loop bends down to inspect the shoe. “Just makin’ sure there ain’t no foot in it.”

READ – THROW THE BUM OUT

 READ SERIES FROM BEGINNING

Sources:

Wikipedia bio on Robert Shiller.

IRRATIONAL EXHUBERANCE – Robert Shiller

The Royal Swedish Academy of Sciences – Prize in Economice 2013

 

Image Credits –Irrational Exuberance—Shiller,  Bio on Wikipedia

Chicago Venture Magazine is a publication of Nathaniel Press www.ChicagoVentureMagazine.com Comments and re-posts in full or in part are welcomed and encouraged if accompanied by attribution and a web link. This is not investment advice. We do not guarantee accuracy. It’s not our fault if you lose money.

.Copyright © 2016 John Jonelis – All Rights Reserved

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UNDERESTIMATING THE COMPETITION

Olga of Kiev Tby Robert Jonelis

Ever face a crisis situation?  Raw panic?  Of course you have.  We’ve all been burned by miscalculation, greed, and shoddy research.  People have been making the same mistakes for quite a long time and a young woman from the 10th Century can teach us a pointed lesson about the importance of accurately sizing up the competition.

Miscalculation

Meet Princess Olga.  She lived in Kiev back in the 900s with her husband Igor, ruler of Kiev, and their young son Svyatoslav.  Igor was leaning on the Drevlians, a neighboring people, for tribute.

The Drevlians decided that killing Igor would be cheaper than paying up, so they assassinated him.  That left Olga, a young widow, as regent for her three-year-old son.

The Drevlians were now dealing with an angry leader that they had badly underestimated.

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Greed

The Drevlian ruler wasn’t satisfied with merely eliminating the payment of tribute.  He could do even better.  If he married Olga, he’d rule Kiev!  After all, she was a poor widow with nobody to protect her or rule her kingdom.  He dispatched a group of important Drevlians to make the pitch to Olga—something along the lines of, “We know you’re single since we killed your husband, how about you marry our leader?”

Olga’s response was not what they were hoping for.  She buried the envoys alive.

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Shoddy Research

Before news got out about the demise of the Drevlian ambassadors of love, Olga sent word to the Drevlian leader that she accepted his proposal.  However, she said, for her people to accept her remarriage, the wisest and most knowledgeable of the Drevlians must come to serve as an honor guard on her perilous journey.

When these men arrived, she burned them to death.

Undeterred by her delayed arrival and still blissfully unaware of events, the Drevlians send a huge contingent to a feast put on by Olga.  A large number of them became exceeding intoxicated.  Her soldiers then attacked the largely helpless drunks.  Several thousand more Drevlians perished.

Pieter_Bruegel_the_Elder_-_The_Dutch_Proverbs 500

Painting by Pieter Bruegal the Elder

The Drevlians finally caught on that Olga was less than happy with them, but by this time she was gathering her army.  Deprived of much of their leadership and a significant chunk of their manpower, things didn’t go well for the Drevlians, and Olga soon besieged their main city.

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Crisis Management

Sensing doom, the Drevlians tried to negotiate peace. Olga responded that all she required would be three live pigeons and three live doves from each Drevlian household as tribute. (Drevlian families commonly kept bird coops on the roofs of their homes).

The night after delivery of the tribute, Olga’s troops tied a piece of string to the leg of each bird, bearing a flaming material.  They released the birds, all of which immediately flew back to their homes.  Every building in the city caught fire at about the same time.

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Panic Mode

The Drevlians fled their flaming fortified city into the arms of Olga’s waiting troops.

The Drevlians underestimated their competition.  This is probably why you don’t hear much about them today.

Ω

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Bob Face 2

Robert Jonelis is a mathematician and history buff who knows how to tell a good story.  He spends his days programming automated machinery in search of the perfect robot.

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This article originally appeared in NEWS FROM HEARTLAND – The Journal of the Heartland Angels.    http://news.heartlandangels.com   Copyright © 2014 John Jonelis

Chicago Venture Magazine is a publication of Nathaniel Press www.ChicagoVentureMagazine.com Comments and re-posts in full or in part are welcomed and encouraged if accompanied by attribution and a web link. This is not investment advice. We do not guarantee accuracy. It’s not our fault if you lose money.

.Copyright © 2015 John Jonelis – All Rights Reserved

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IF WE BUILD IT, THEY WILL COME

BANANASMoises Goldman PhD – Resident Scientist

EDITOR’S NOTE–Everybody’s familiar with the phrase.  But is there a genuine application in industry for IF WE BUILD IT, THEY WILL COME?  Here’s one offered by a highly respected source:

Many in industry believe that logistics is now THE important field of study. Nothing could be further from the truth.

Logistics is simply a natural process that is part of any enterprise. It is inherent in any enterprise trying to minimize cost, maximize profits, or simply optimize its performance. (I am not talking about probabilistic or statistical studies.)

Moises Goldman 2

Let me clarify with an example: When Dole Foods or Chiquita Banana initially found that better fruit was grown in Latin America; they initially went down there, picked the fruit, and brought it back to the U.S. for processing.

Low Hanging FruitUltimately, common-sense logistics influenced their thinking and they moved their processing plants close to the source. This not only made economic sense but also being close to the fruit allowed them to be first in picking the best.

By moving industry to the source, it will remain close the best fruit it can pick. If we break ground close to the source, I am certain that: IF WE BUILD IT, THEY WILL COME.

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GO BACK TO PART 1

Contacts

This article was adapted from a paper for the Institute for Work and the Economy by Moises Goldman PhD. www.workandeconomy.org

Moises Goldman—Moises6@comcast.net

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Chicago Venture Magazine is a publication of Nathaniel Press www.ChicagoVentureMagazine.com Comments and re-posts in full or in part are welcomed and encouraged if accompanied by attribution and a web link . This is not investment advice. We do not guarantee accuracy. It’s not our fault if you lose money.

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Copyright © 2013 Moises Goldman – All Rights Reserved

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CHICAGO’S NEW SOUTH SIDE

Brazil from WikipediaThe City of Broad Shoulders is looking to the south. South of 119th street. South of Springfield. South of Mexico. Way south

They’re looking to Brazil where GDP is 6th worldwide and growing. And consumer confidence?  Up.  Infrastructure investment?  On the rise.  Interest rates?  Decreasing. Unemployment?  Only 5.6%.

And Brazil encourages business growth: An open-door trade policy. Aggressively lower tariffs.  Lower taxes. Their complex regulatory environment is getting easier to navigate.  Not surprisingly, international investment is moving to Brazil.

IERG

IERG

This is the 2nd International Forum of IERG — The Intenational Executives Resouces Group—a one-of-a-kind organization—a not-for-profit group made up of volunteers—senior business executives from around the world whose careers have been enriched by broad experience in the global arena.  And no economic mumbo jumbo at this conference.  Everything’s solid.  Everybody comes away with a better understanding of what it takes to do business in Brazil

Brazil is the world’s 5th largest economy and Illinois’ fifth-largest export market.  In 2011, they bought more than $2.55 billion of our goods and we could do a lot more.  Even our politicians are taking junkets there. 

Think of it as Chicago’s new SOUTH South Side.

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SPEAKERS:

  • The honorable Paulo Camargo, Consulate General of Brazil in Chicago 
  • Ernesto Ramon, former CEO, Dow Chemical in Brazil 
  • Michael Ross, VP & General Manager, Encyclopaedia Britannica
  • Dr. Yara deAndrade
  • Roland Dietz, Chicago Chairperson, IERG

MODERATOR: Bruce Montgomery, Executive Producer, IERG

LOCATION: The Chicago offices of Baker & McKenzie

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Brazil ClubIERG logo.

This summary is adapted from an article by Brazil Club with permission of IERG.  For the full text, go to – http://brazilclubusa.com/blog/chicagos-business-with-brazil-forum-a-success.html

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Brazil Club –  http://brazilclubusa.com/index.php

IERG –  http://iergonline.org/
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GO TO PART 2 – WHERE IS CHINA’S STEVE JOBS?


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Find Chicago Venture Magazine at www.ChicagoVentureMagazine.com Comments and re-posts are welcomed and encouraged. This is not investment advice – do your own due diligence. I cannot guarantee accuracy but I give you my best.

Copyright © 2012 John Jonelis – All Rights Reserved

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