Dumpling Shopper: Launch Your Own Grocery Delivery Business

Grocery delivery startup Dumpling is taking on Instacart and Shipt — and the whole gig economy — by offering grocery delivery drivers an entirely new moneymaking model.

Thanks to a surge in demand as a result of the pandemic, grocery delivery apps are more popular than ever. Since last March, Instacart and Shipt have hired more than half a million gig workers to shop and deliver food to customers who’d rather stay at home and order online.

Those hordes of gig workers, who are independent contractors, rely on grocery delivery to supplement their earnings or make up their income entirely. While this arrangement is a welcome and fast form of cash for some folks, others are finding that the income from Instacart and Shipt is unsustainable.

That’s where Dumpling comes in: capitalizing on the growing trend of grocery delivery as well as the rising concerns of delivery workers who want more control over their income by allowing them to choose who to work with and how much to charge.

Here’s a look at one of the newest grocery delivery apps on the block, and how you could use it to launch your own grocery delivery business.

Dumpling founders pose for a photograph against a red brick wall.
Tom Schoelhammer, left, Joel Shapiro and Nate D’Anna are the founders of Dumpling. Photo courtesy of Dumpling

What Is Dumpling?

Dumpling is a grocery delivery service founded in 2017 by Tom Schoelhammer, Nate D’Anna and Joel Shapiro, who all left corporate tech jobs to try their hands as entrepreneurs.

On the customer side, Dumpling operates much like other grocery shopping apps: You download the app, select a nearby grocery store, choose what items you want to buy, place your order and voila, a nearby personal shopper will deliver the items to your doorstep.

Where Dumpling differentiates itself is in how it’s used by delivery workers. It is essentially a suite of software and coaching services for those looking to launch their own small grocery-delivery business.

Pro Tip

As a shopper for Dumpling, you’re considered a small business owner, not a gig worker.

According to the company, more than 2,000 small business owners from all 50 states use Dumpling to deliver groceries locally.

Dumpling markets itself aggressively as a “personal, ethical and local” alternative to Instacart and Shipt, which rely on an army of gig workers to do the shopping.

Since its launch and especially during the pandemic, Dumpling and its co-founders have become increasingly outspoken about the downsides of the gig economy.

“What can we do to help more people gain greater control, autonomy, and flexibility over the way they work?” Dumpling’s website states. “When we set out to find an answer, we didn’t know we’d eventually be taking on the gig economy.”

But does the company provide a meaningful alternative?

How It Works for Dumpling Shoppers (aka Business Owners)

As a grocery shopper for Dumpling, you’ll have more autonomy than with typical gig apps.

In a training video for new Dumpling shoppers, Bree Crawford, director of coaching at Dumpling, contrasts the company with other shopping gigs.

“As a prior Instacart shopper, I have a pretty good idea of some of the questions you’re going to run into,” she said. “With Instacart, we’re used to just sitting around waiting for batches, and it’s just stupid.”

With Dumpling, you can choose who you want to deliver to, set how much you want to charge per delivery, select the stores where you want to shop, schedule deliveries in advance and more.

But that autonomy comes at a cost.

Dumpling Shopper Fees

To start your shopping business, you need to pay a one-time fee, currently $19.99, for an activation kit. The activation kit includes:

  • A Dumpling business credit card that you’ll use for your orders.
  • Access to a personal shopper website hosted by Dumpling.
  • 100 business cards.
  • Access to the “Boss” version of the Dumpling app, which you’ll need to connect with clients.

“The Dumpling credit card works as a micro loan to business owners. When the client places an order, the credit card is funded for the business owner to shop and pay for the order,” Shapiro told The Penny Hoarder. “This system allows Dumpling business owners to shop all orders without fronting any funds themselves.”

The company also offers Pro and Tycoon monthly membership plans for business owners, which give you access to better credit-card and business-profile perks. Pro costs $49 per month, and Tycoon costs $99 per month. A standard plan is free.

You can expect the activation process to take about a week.

In addition to the activation fees, you pay two fees per grocery order: a credit card processing fee and a “platform” fee. The credit card fees are tiered based on your membership category.

Under the standard plan, you pay 3.9% of the order total, including gratuity, plus 30 cents. If you’re Pro, you pay 3.2% plus 30 cents. Tycoons pay 2.8% plus 30 cents. The platform fee is a flat 5% of the cost of groceries sans delivery and gratuity for all membership levels.

For example, if you have a $100 grocery order, plus your delivery charge of $10 (which you can customize) and a $20 tip, here’s how your earnings would break down under the free standard plan.

  • Gross order earnings: $30 ($10 order charge plus $20 tip).
  • Credit card processing fee: $5.26 (3.9% of $135 plus 30 cents).
  • Platform fee: $5.00 (5% of $100 worth of groceries).
  • Net order earnings: $19.74.

According to Shapiro, the average earnings per order are $40, “which is significantly higher than traditional gig work platforms for grocery delivery.”

Previously, you could set a fixed minimum gratuity percentage up front for every order, but Dumpling recently removed that feature, according to app store reviews.

To prevent tip baiting, a practice where some Instacart customers lure shoppers in with big tips up front only to zero them out after the order, Dumpling does not allow your customers to reduce their tips after the delivery. They can only increase it.

The trick is to find the right delivery charge. Too high, and you risk driving your customers to Instacart, Shipt or another Dumpling deliverer. Too low, and those fees eat away at your tip.

Free Coaching

Once you set up your Dumpling account and receive your activation kit, you’re eligible for free coaching. The initial coaching session is a basic onboarding call in which a Dumpling coach will show you the ropes.

After that, you can receive additional coaching free of charge. The program includes three calls with one of Dumpling’s staff coaches, “all of whom have backgrounds in grocery delivery gig work and run successful businesses on Dumpling themselves,” Shapiro said.

The coaching program can start at any time so long as your account is active, with each session spaced out “a few weeks apart.”

Coaches can help you with a range of things like utilizing your business website, app functionality and marketing tips. Between sessions, coaches can help with smaller questions, too.

After the three coaching sessions, you may be able to get more assistance if needed.

“Dumpling business owners never have to pay money to access this program,” Shapiro said. “However the coaches do ask for their undivided attention and that they continue putting in the effort on their own business to remain in the program.”

Finding Your Own Customers

Perhaps the most notable difference between Dumpling and other grocery shopping gig apps is that, as a business owner, you’re responsible for finding your own customers.

There are several ways to connect with them, and Dumpling does assist you with this, but the process is not automatic.

For example, with Shipt or Instacart, you log on and wait for an order to pop up on your app. Then you can choose to accept or decline, knowing little to nothing about the customer. Or it’s possible that an order will be claimed by competing shoppers in your area before you have a chance to act.

At Dumpling, you’ll need to interact much more with customers — with the ultimate goal of scheduling them on a recurring basis. And the initial order could take some leg work.

Since Dumpling is a relatively new company with fewer customers than competitor grocery delivery apps, you may find yourself giving a sales pitch: first to explain what Dumpling is, and second, to convince the customer to schedule you for grocery orders through the app.

Customers may also find you through a ZIP code search function on the Dumpling website and app or directly from your personal Dumpling business site. But that’s assuming that one of your neighbors is already familiar with the company.

Dumpling is not for every gig worker. It takes a certain amount of risk tolerance. Given the activation and processing fees, there is a chance you could go in the red on some orders, and there’s no guarantee that you’ll get any orders in the first place.

What Dumpling does offer you is more autonomy and control over your grocery-delivery enterprise — something many gig workers, whose earnings are based on ever-changing algorithms, are craving.

Adam Hardy is a former staff writer at The Penny Hoarder.



Source: thepennyhoarder.com

Everything to Consider Before You Sell Pokemon Cards

The resurgence of Pokemon has young adults rummaging through their closets in hopes of finding their old collection of trading cards. 

And, if they’re lucky, a rare card that could make them a fortune.

The 1997 Japanese anime-turned-trading-card-game-turned-video-game series holds a special place in the hearts of ‘90s kids, who cherished the furry creatures with elemental powers that could be traded and battled and hoarded for years to come. 

For Scott Pratte, a Pokemon enthusiast and card-trading expert, the hobby never dimmed. Pratte collects and sells some of the most treasured Pokemon cards in the world.

“I’ve done 7-figure deals,” Pratte says. “That’s just one deal, not even my lifetime” earnings.

Due to nondisclosure agreements, he can’t say exactly which cards have made him the most money, but he says that his trophy cards, aka the rarest Pokemon cards on the market, easily rake in upwards of $1 million.

Only a select few people hold these trophy cards, usually those who won Pokemon tournaments in the early 2000s and were awarded ultra limited edition cards. But there are a fair amount of more common Pokemon cards that could sell for hundreds or even thousands of dollars.

Pokemon Cards Worth Selling

The two biggest value factors to consider about old Pokemon cards are their rarity and condition.

In terms of rarity, “base-set” cards are where the money is for most collectors, and these cards are the most traded ones in the hobby. Set cards are “any card you can pull from a pack” bought from the store, says Pratte. The base set comprises the original 102 cards printed in 1999 and includes classic Pokemon like Pikachu, Blastoise, Charizard and Venusaur.

A complete first-edition base set in mint condition sold for $100,000 in December 2017. If you have a base-set card in your collection, there are a few visual indicators of its worth.

A graphic compares rare and common Pokemon cards
Illustration by Chris Zuppa and Adam Hardy
  1. Holographic cards: These are the most discernable at first glance. The background of the Pokemon illustration is shiny and reflective — not the whole card, only the picture of the monster. They’re typically referred to as “holo” cards, and only 16 of the original 102 are holo.

  2. First-edition cards: Directly next to the left corner of the illustration appears the “edition 1” logo. These cards were bought up shortly after initial release and remain some of the rarest and most sought-after cards.

  3. Shadowless cards: This version is almost identical to the first-edition prints but exclude the first-edition logo. If you don’t have a newer card for comparison, this is particularly hard to notice: the illustration box appears 2D. On newer cards, the picture box has a shadow along the right border to give it a 3D appearance.

  4. Unlimited cards: These cards are still old and rare, but they do not include the first-edition symbol and have an added shadow behind the illustration to give the picture box a 3D effect. To check if your card is part of the base set, look at the bottom right corner of the picture box. If you do not see one of the many later-added set symbols, then you have a base-set, Unlimited card.

The second important factor in a card’s value is the condition. If you do happen to have a first-edition, holographic base-set Charizard, you’re not guaranteed thousands of dollars. The price it fetches depends on how well the card has been taken care of.

If you have a card that you expect is worth more than $100, Pratte recommends getting it graded by Professional Sports Authenticator (PSA). 

Despite its name, the PSA grades all kinds of trading cards, including non-sports cards like Pokemon. PSA’s 10-point grading scale is accepted as the industry standard, and the company also publishes price guides to help determine a card’s worth. According to its current valuations, first-edition cards in perfect condition are valued at a minimum of $40. Those aren’t rarer, holographic cards either. A first-edition holo in mint condition can rake in between $1,000 and $24,000.

So why Pratte’s $100 limit? Well, the number isn’t a hard-and-fast rule, but the card-grading services offered by PSA will cost $20 or more per card, meaning a lower-value card doesn’t always merit the cost to get it authenticated.

“It’s a process,” says PSA spokesperson Terry Melia. “But it’s something that could reap big rewards in the end.”

In addition to grading the condition of the card, PSA ensures the card isn’t a forgery by using high-powered lights and magnifying equipment to check for tampering.

“There are a lot of forgeries and bogus merchandise out there,” says Melia.

Especially so online.

Where to Sell Pokemon Cards

After you’ve done some homework — checking the type of card, estimating its value and sending it in for authentication, if needed — you’re finally ready to sell.

“The main marketplace is for sure going to be eBay,” Pratte says. “Even if you’re someone who just stumbled upon your childhood collection, it’s really easy to take a couple of pictures [and] make a decent listing.”

The PSA’s grading system and authentication make selling online much easier. This process allays fears that the card is a fake and curbs arguments over its true condition. Each authenticated card comes in a protective case with the grade and barcode clearly visible at the top.

As Pokemon re-enters mainstream culture with the release of new video games and movies, expect to see an uptick in buying and selling activity of old cards. But interest doesn’t pick up overnight.

“It’s not binary in that sense,” Pratte says.

Instead, it’s a more gradual process where each new Pokemon-related release reminds twenty- and thirty-somethings of their childhood: the crinkling sound of ripping open a new pack of cards followed by a strong whiff of ink as they shuffle through the set, hoping to find something rare.

Pratte offers this caution about getting rich overnight: “Be realistic.”

“If you put in little or no effort back in the day,” he says, “you probably don’t have the homerun card.”

But as you rummage through your collection, remember that there’s no rush to purge now. Spend some time with your cards. See if they’re valuable. Consider getting them authenticated. Then decide if they’re worth selling. 

After two decades, Pokemon — and its card-collecting hobbyists — aren’t going anywhere anytime soon.

Adam Hardy is a former staff writer at The Penny Hoarder. 

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Source: thepennyhoarder.com

How the Knack Tutoring App Became a Booming Startup

Samyr Qureshi and his friend Dennis Hansen turned an idea they had in their early 20s into an app that matches college students with student tutors on campus. The app, Knack, turned into a start-up that landed them on the 2020 Forbes 30 under 30 list, which highlights the country’s top innovators.

Knack is now used on more than 24 college campuses around the country. It became even more in demand as students went online during the pandemic and is being used for K-12 education as well.

“COVID definitely accelerated the need for campuses to provide this sort of service,” Qureshi said recently in an interview.

Initially students paid for their tutors, who set their own price, and Knack took a 2.9 percent cut. But as the app spread to more than 60 college campuses, leaders at a few universities were so impressed with the help students were gaining through Knack, they wanted to make it accessible to everyone at no charge.

The colleges started paying Knack an annual fee and paying tutors an average of $15 an hour. Having fewer big payors proved better than taking a cut from thousands of individual tutors. So, the company changed its business model. Most students at all partnered campuses are using the platform for free.

As it has grown, Knack is now valued at 20 times more than at its 2015 founding.

Qureshi, 28, knows about the benefits of tutoring from both sides of the desk. He attended St. Petersburg College in Florida and entered the University of Florida with 73 credits. He excelled, worked as tutor himself and landed jobs at Apple, then Gartner, Inc. after graduating.

While at Gartner, a leading information and technology research company, he learned from his mother that he had actually struggled with learning as a young child. English was his second language since he moved to the United States at age 6 from Dubai. She had found tutoring to help her young son.

“When she told me this, it helped me understand the value and benefit of one-to-one tutoring,” Qureshi recalled. “At the same time Uber and Airbnb were really taking off.”

He talked with Hansen about how college students should have easier access to tutors. The idea of connecting students who needed help with students who were successful in the same course was born. They called their project Knack and set about creating an app.

The Knack App founder poses for a portrait against a painting depicting the magic school bus.
Samyr Qureshi, co-founder of Knack app, was reminded of the importance of tutoring after his mother told him the story of hiring a tutor to help him learn English as a second language when he was a child. The Knack app allows student tutors and students needing help with a course to connect easily. Chris Zuppa/The Penny Hoarder

Qureshi quit his job and joined Hansen at UF’s Gator Hatchery, an incubator that offers students workspace, office support, mentors and other resources for startups.

“I was living off of my savings and pretty much poured everything I had into Knack,” he said.

David Soker, who had a master’s degree in electrical and computer engineering and knew how to build apps, joined the team. He’s also a co-founder and now Chief Technology Officer at Knack.

“We intentionally put our team together to have engineers,” Qureshi said. Paying an outside company to build the app would have easily cost six figures.

They launched the beta version of Knack in late 2015. Students using it at UF and the University of Central Florida in Orlando proved the founders’ belief that there was a high demand for student-to-student tutoring. The users also offered critiques and tips for making the app better.

In 2016, Knack won first place and $25,000 cash in UF’s Big Idea Business Plan Competition. It was time to really launch the business and move out of the Gator Hatchery. They won a few grants and got investments from friends and family. These efforts plus the $25,000 prize gave them about $75,000 when they started Knack in office space in downtown Tampa. Qureshi worked part-time delivering cookies and some of the other co-founders had full-time jobs while also working at their startup.

They ran digital ads and started marketing the app to students on numerous campuses to recruit tutors and clients. The most effective way to do this was to hire campus ambassadors to represent Knack at college events around the country and gather small groups to learn about it.

“We recruited them cold from job postings and interviewed them then hired them,” Qureshi said. “We gave them $300 to $500 a month and a list of tactics that we had tested at UF: ‘Go buy pizza and entice some students to come hear about it.’”

An Indian woman with long brown curly hair poses for a portrait in front of a sign that says grow together. She's a tutor who found tutoring jobs on Knack, a mobile app.
Sonia Duraimurugan is an MBA student at the University of South Florida who used the Knack app to make money as a tutor. Chris Zuppa/The Penny Hoarder

At the same time, they were expanding the app, they were finding more people to invest in the company.

“The (Big Idea) contest put us a bit on the map,” Qureshi said. “There were really great judges who said we should come out to San Francisco and meet some folks.” They did, and secured some West Coast investors.

In Tampa, Qureshi joined a downtown business incubator he found by searching Google. A mentor in the incubator invested in the company and connected him to Jeff Vinik, owner of the Tampa Bay Lightning NHL hockey team. Vinik has also headed successful investments funds and is a philanthropist who has given millions of dollars to education. He invested in the company as did others.

“We initially raised about $1 million in capital from the Tampa Bay area,” Qureshi said.

His advice to college students or recent grads who have an idea that could turn into an app or a business, is to “go for it.”

“We were pretty naive and that gave us some pause. I was a pre-law student so I didn’t have any business experience. The majority of our team did not study business,” he said. “We learned a lot from mentors. We were srappy, scraping up dollars where we could.”

Katherine Snow Smith is a freelance editor and reporter in St. Petersburg, Fla., and author of Rules for the Southern Rulebreaker: Missteps & Lessons Learned.

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Source: thepennyhoarder.com

19 Purchases That Buyers Almost Always Regret

a shopper regrets a purchase
Prostock-studio / Shutterstock.com

There are certain purchases that buyers tend to regret.

No, that doesn’t mean everyone: There are plenty of happy boat and hot tub owners out there, and surely more than a few people count their timeshare property as a true delight.

But when faced with one of the potential purchases listed here, it’s a good idea to take a breath and think seriously about whether to buy it.

1. DVDs

Dragon Images / Shutterstock.com

Movie-watching has moved online, with streaming and downloadable films that are easier to manage and watch than ever. You can buy or rent movies on demand from streaming services like Redbox or Amazon’s Prime Video.

What’s for sure is, you don’t have storage space for hundreds of DVDs. You’re not Blockbuster Video, and besides, look what happened to them.

2. Extended warranty

Extended Warranty
rawpixel.com / Shutterstock.com

You’ve bought the product, but the sales pitch isn’t over: Now your clerk is gunning to sell you an extended warranty, just in case the brand-new product falls apart.

Research the product you’re buying. Extended warranties can be complicated. We explain the ins and outs in “Should I Buy an Extended Car Warranty?” and “Are Extended Warranties Worth It?”

Whatever you do, first check whether you have coverage through other sources, such as a manufacturer’s warranty or through your credit card. You may not even need to fork out for extra coverage.

3. Boats

Motorboat
freevideophotoagency / Shutterstock.com

There’s an old saying: The two best days of owning a boat are the day you buy it and the day you sell it.

Owning a boat is a lot of work. If you live on a lake and have plenty of room for it, and are willing to spend the money needed to keep afloat, then ship ahoy! But most of us can get by with an occasional boat rental, or wait until our friend Gilligan invites us over for a sail.

For more options, check out “4 Ways to Go Boating Without Buying a Boat.”

4. Timeshare

Virginia Beach, Virginia
JoMo333 / Shutterstock.com

Timeshares, which give you a partial share of ownership in a vacation property, are probably one of the most stereotypically regretted purchases — and for good reason.

You may love vacations, but do you always want to vacation in the exact same spot? Yes, you can exchange your timeshare with others, but booking a hotel or resort is more flexible.

Those are a few reasons why Money Talks News founder Stacy Johnson says, “I’d chop off my own foot with a dull ax before buying a timeshare.”

5. An extravagant wedding

Wedding couple
Cedric Carter / Shutterstock.com

A wedding lasts one day, and then it’s all photos and memories.

You’ll be just as legally married in a $100 gown as in a $5,000 one, and you’ll have a lot more money left over. You can pull off a wedding elegantly without going into debt in the process.

Learn how: “Your Own Royal Wedding: 20 Classy Ways to Save on the Big Day.”

6. Pricey engagement ring

Diamond ring
Vladimir Sazonov / Shutterstock.com

And speaking of weddings, consider whether a whopping diamond ring is really the best way to tie the knot.

Modern jewelers offer more price-conscious alternatives that are just as lovely. Your hard-earned dollars can bring more satisfaction if they’re used for a down payment on a home. So, consider lab-grown diamonds — not only are they cheaper, they’re more environmentally friendly.

7. Desktop computer

NicoElNino / Shutterstock.com

Desktop computers once were an amazing innovation, but few people need that kind of computing power these days. A tablet or laptop gives you the flexibility to move your home office around and travel with your computer if you wish.

Think different, a la Apple’s motto. And when it comes to home computing, don’t think big — think small.

8. Giant tent or other expensive camping gear

dezy / Shutterstock.com

For hardcore campers, owning a nuclear-fueled camp stove, a three-bedroom tent, an enormous inflatable mattress or a kit specifically made for roasting s’mores might make sense.

But for those of us who camp maybe only once every year or two, a small tent and standard sleeping bag work just as well. And you can always just toast marshmallows on sticks, which are still free.

9. Camcorder

StockKK / Shutterstock.com

Most of us carry smartphones these days, and their video capabilities keep getting better and better. Hauling around a camcorder, storing it and getting the videos off of it is a chore few of us need.

10. Home printer

Using a printer to print out documents
FabrikaSimf / Shutterstock.com

Even those who run a home business are finding fewer and fewer opportunities to use gigantic printers, since so many documents can be filled out, signed, sent and received electronically.

Printers take up a ton of space and require replacement ink cartridges that can cost as much as a new printer.

Those in major cities who need a printer for a one-time use can make the occasional trek to the public library or local business offering printing services.

11. Pedometer

Andrew Haddon / Shutterstock.com

Counting steps to keep yourself moving is trendy again, but it’s not pedometers that brought it back. Instead, it’s wrist-worn fitness trackers and smartphones and smartwatches.

You have to plan to wear a pedometer. With a smartphone or smartwatch, you can track your steps almost without thinking.

12. Home exercise equipment

Sladic / Shutterstock.com

There likely have been days when you wished you didn’t have to make the trek to the gym to work out. At those times, buying exercise equipment seems like a no-brainer.

But the equipment is huge and bulky, and storing it takes up precious space in your home. Did we mention that it’s also seriously expensive?

13. Single-purpose kitchen gadgets

Woman making fruit juice with a juicer
ABO PHOTOGRAPHY / Shutterstock.com

Some kitchen appliances make solid sense: Coffeemakers and toasters earn their keep every day. But appliances that are super-specific and can perform only one rarely needed task? They’re rarely worth the money.

Will you really use a juicer, a bread maker, a hot-dogger, a food dehydrator? Maybe once or twice, but it is unlikely to earn the space it takes up on your kitchen counter.

14. Pools and hot tubs

kurhan / Shutterstock.com

Sure, some people swim every day. And some of us can’t imagine gloomy winters without a hot tub.

But for many people, there’s only a short period of time when a pool or hot tub is used enough to earn its keep. After that, it becomes a huge bowl of water that needs to constantly be cared for and cleaned.

15. Piano

Skumer / Shutterstock.com

If you’re on Facebook, head to the online shopping section to see how many people are desperately trying to give away pianos for free. Few things take up more space and are more difficult to move than a piano.

If you truly have a junior Beethoven in your house, you may genuinely need a piano. But if your kid hasn’t even learned where middle C is, you can start with a borrowed portable keyboard and see if music lessons hit the right note.

16. Fine china

Kondor83 / Shutterstock.com

Once, fine china was on every couple’s wedding registry and was broken out regularly for dinner parties and family holidays. Ours is a more casual world now, for good or for ill. Few engaged couples want 12 place settings of Royal Doulton china.

If china appeals to you, check with the older generations in your family. They may be happy to give you theirs.

17. Collectibles

Toy Collection
Tinxi / Shutterstock.com

Face facts: Beanie Babies that were the rage in the 1990s are never going to make you rich.

The same goes for most collectibles, from Franklin Mint collector plates to Department 56 Snow Village buildings.

If it makes you happy to buy a spoon or shot glass from each country or state you visit, have your fun. But don’t collect with the expectation that you’ll make money from the collection one day.

18. Baby gadgets

Africa Studio / Shutterstock.com

New moms and dads don’t need half of the things on many baby registries. Diapers and clothes, sure. Burp cloths and bassinets? Go for it. But a diaper wipe warmer?

If you’re giving a present to a new parent, consider a gift card.

19. Giant desserts

Man eating giant sundae
Todd Castor / Shutterstock.com

Many restaurants have one on the menu — the giant, jumbo, lollapalooza, monster-sized dessert. But eat one, and you’ll quickly regret it.

Unless you have a soccer team or hungry family to help you eat the giant treat, skip it.

Disclosure: The information you read here is always objective. However, we sometimes receive compensation when you click links within our stories.

Source: moneytalksnews.com

How to Turn an Idea Into an App

The CEO of Knack does work on his laptop at the office's headquarters. A light up Knack signs is hung on the wall behind him.

Samyr Qureshi is CEO of Knack, an app that connects college students with tutors at more than 60 college campuses across the United States. Qureshi co-founded the app in 2015 with Dennis Hansen and David Soker. Qureshi was photographed at the company’s headquarters in Tampa, Fla, on February 2, 2020. Chris Zuppa/The Penny Hoarder

Samyr Qureshi and his college friend Dennis Hansen had an idea for an app that would match students with student tutors on the same college campus. That was 2015. Six years later their company, Knack, has secured more than $1 million in equity investments and is worth 20 times more than when it started. It also landed Qureshi, CEO, and Hansen, Chief Product Officer, on the 2020 Forbes 30 under 30 list, which highlights the country’s top innovators.

The steps they took to make Knack a reality offer a game plan for anyone with a viable idea and the drive to turn an idea into an app.

1. Find a Need and a Solution

Qureshi was tutored as a young child and then was a tutor himself in college. He and Hansen knew tutors helped with academic success, but realized it wasn’t always easy to find one. Through research they learned the “near peer” concept was successful. The more recently someone has taken a class and learned a concept, the more effective they are at helping someone else understand it. They decided to create an app that would match students at the same campus, one needing help in a course and another who has had recent success taking the same course.

2. Do your Homework

Airbnb and Uber were taking off so Qureshi and Hansen learned all they could about how these apps got started and why they were a success. They also researched how people were finding tutors on Craigslist, Wyzant and other resources, and what was working and what wasn’t. They decided what they wanted their app to offer and researched what it would take to create it.

3. Build a Team with the Variety of Talent Needed

The friends asked David Soker, who had a master’s in electrical and computer engineering and knew how to build apps, to join their team. He’s also a co-founder and now Chief Technology Officer at Knack.

“We intentionally put our team together to have engineers,” Qureshi said. Paying an outside company to build the app would have easily cost six figures.

This is a portrait of a woman who finds tutoring gigs through the Knack app. She has long curly dark hair. Behind her is a painting of the magic school bus.
Sonia Duraimurugan is an MBA student at the University of South Florida who used the Knack app to make money as a tutor. Before using Knack, she relied on food banks for groceries. “I was literally strapped for money,” she said. The app provided a way for her to earn as much as $12 per hour. Chris Zuppa/The Penny Hoarder

4. Take Advantage of University Incubators

Qureshi and Hansen, both graduates of the University of Florida, secured a spot at UF’s Gator Hatchery, an incubator that offers students workspace, office support, mentors and other resources for startups. There are hundreds of University Business Incubators (UBIs) across the country at schools of all sizes. Some offer grants or stipends to help support students financially while they create their business or product. Others have relationships with banks that provide special loans to entrepreneurs. Most UBIs are adept at creating networking opportunities for students to gain access to potential funders, often alumni. They also have media relations teams that get publicity for students and their endeavors.

5. Get Feedback

Whether it’s a product, service or app, testing a beta version with a wide audience (beyond your mom and next-door neighbor) is essential for understanding what works and what doesn’t. Knack launched a beta version at the University of Florida and the University of Central Florida to work out the kinks.

6. Enter Contests, Apply for Grants and Raise Equity

UBIs keep students informed about competitions and grant applications. But even if you aren’t in a UBI, there are many competitions for entrepreneurs and college students launching an idea as well as grant opportunities. In 2016, Knack won first place and $25,000 cash in UF’s Big Idea Business Plan Competition. That led to more interest from investors. A few family members wanted to invest in the company to help it get off the ground. The Knack co-founders sold them shares in the business in exchange for equity. They priced their stock by comparing their company to the market value of similar existing startups.

7. Get Your App in Front of Users

To reach an audience of users and tutors, they ran digital ads and marketed the app to students on numerous college campuses. One of the most effective marketing tools was creating a network of ambassadors on college campuses to represent Knack

“We recruited them cold from job postings, interviewed them and hired them,” Qureshi said. “We gave them $300 to $500 a month and a list of tactics that we had tested at UF: ‘Go buy pizza and entice some students to hear about it.’”

8. Have a Side Gig or Full-Time Job

Qureshi, who had been working professionally about two years, quit his job and lived off of his savings after joining the UF business incubator to create Knack. Later, when the company moved to Tampa, he worked for a cookie delivery business on the side to make ends meet.

Final Advice: Go For It

Qureshi’s advice to college students or recent grads who have an idea that could turn into an app is to “go for it.”

“We were pretty naive and that gave us some pause. I was a pre-law student so I didn’t have any business experience. The majority of our team did not study business,” he said. “We learned a lot from mentors. We were srappy, scraping up dollars where we could.”

Katherine Snow Smith is a freelance editor and reporter in St. Petersburg, Fla., and author of Rules for the Southern Rulebreaker: Missteps & Lessons Learned.

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Source: thepennyhoarder.com

Ergodicity: The Coolest Idea You’ve Never Heard Of – The Best Interest

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Surely that’s a typo…ergodicity!? No, it’s right! Ergodicity is a powerful concept in economic theory, investing, and personal finance.

Even if the name seems wild to you, the idea is simple—stick with me while I explain it. And then we’ll apply ergodicity to retirement planning and investing ideas.

By the end of this article, you’re going to be seeing ergodic systems and non-ergodic systems all over your life!

Ergodic, Non-Ergodic, and Russian Roulette

Ergodicity compares the time average of a system against the expected value of that system. Let’s explain those two terms: time average and expected value.

The time average asks, “If we did something a million, billion, trillion times…what would we expect the results to look like?” It needs to be a sufficiently long random sample.

The expected value asks, “By simply averaging probabilities, where would we expect the result to be?”

At first blush, you might think, “Those two are the same thing…right?” Right! Or, at least you’d be right if the system in question is ergodic.

I flip a coin a billion times, and I end up with a time average of 50/50 heads and tails. Alternatively, I could just use their known probabilities and surmise the expected value of 50/50.

In this case, the time average and the expected value are the same. Therefore, the system—coin flipping—is ergodic.

But let’s contrast coin flips against Russian Roulette. The expected value of Russian Roulette is optimistic. ~83% success and ~17% failure. But what happens if one “plays” a million times? Ahh! I think you’d agree that the time average of Russian Roulette is 100% failure.

When one fails in Russian Roulette, it is a devastating failure. To only look at the expected value of the system is too simple. The expected value is far different than the time average. Thus, Russian Roulette is non-ergodic.

Ergodicity –> Over and Over, Big & Small

Ergodicity rears its head in two circumstances. First, ergodicity matters when we do things over and over and over. And second, ergodicity matters when certain outcomes are meaningful while other outcomes are insignificant.

To further explain ergodicity, imagine this bet:

I have a 100-sided die.

I’ll roll the die and you pick a number. If it lands on any other number than your number, then you win $1000.

But if it lands on your number, then Mike Tyson punches you in the face and takes your money.

What a deal! You call 99 of your friends and you all come to take this bet. Sure enough, one of your friends loses. But the rest of you win a combined $99,000 and agree to pay for his medical bills (which may or may not be covered by the $99K…which is another crazy blog post waiting to happen).

The “ensemble average” is that you won! One individual loss doesn’t change that.

But would that result be the same if you had played 100 times by yourself? No! In that scenario, there’s a 63% chance that you’d eventually lose the roll, lose your money, and get punched in the face.

The expected value (you and all your friends) is different than the time average (you doing it 100x). This is not an ergodic process.

Revisiting Ergodicity & Coin Flips

We concluded earlier that coin flips are ergodic. The expected value of a single coin flip equals the time average results of many coin flips.

But let’s change the rules a bit. Imagine I promised you a 40% positive return on heads but a 30% loss on tails. You start with $100,000. Would you take this bet?

Again, let’s call up 100 of your friends. You each take the bet.

We can predict that half of you will end up with $140K (40% return) and half end up with $70K (a 30% loss). On average, you each have $105K. As a group, you’ll end up 5% higher than you started.

Sure enough, we can run this simulation a million times and that’s exactly what we see. Both the mean and median results of these simulation show a 5% profit. Taking the bet was smart.

But what if you took the bet 100 times? Same result?

Same for You?

To start, let’s look at two common snippets in the sequence of returns: one win followed by one loss, and one loss followed by one win.

Win then loss

Loss then win

(You mathematicians will see the commutative property at play. The order of this multiplication didn’t matter.)

This result completely shifts our mindset.

When two people share a win/loss, then end up with $140K+$70K = $210K, or $105K each. They gain $5K. But when one person sequentially suffers a win/loss, she ends up with $98K, or a $2K loss.

What happens if you take this bet 100 times in a row? On average, you are going to lose money. Let’s look at a 50/50 heads/tails split.

Group 50/50:

That’s a 5% profit.

You 50/50:

That’s a 64% loss

But you might “spike” a certain run where you get more heads than tails. What happens if the group gets 60 heads and 40 tails? What happens if you get 60 heads and 40 tails?

Group 60/40:

You 60/40:

That’s…a big profit. $37.3 million.

I simulated the “you get 100 flips” case 100,000 times. As expected, the median result is a 64% loss. But the best result of the 100K simulations turns your $100K bet into $950 million dollars (68 heads, 32 tails).

This bet is non-ergodic. The expected value (100 friends scenario) is completely different than the time average (you 100x bets scenario).

But it’s also interesting that the distribution in the expected value case is tight (low risk, low reward) while the distribution in the time average case is extremely wide (high risk, potentially high reward).

EV is a profit, while time average is a loss. EV is low variance, while time average is high variance.

In case you can’t tell, ergodicity economics and subsequent economic theory is a serious field. There are big conversations taking place and serious money to be made (or lost).

But let’s focus a little closer to home: ergodicity and retirement.

Ergodicity and Retirement

In retirement planning, probability of success is often used as a figure of merit. I’ve used it here on the blog.

For example, the famous Trinity Study and 4% Rule cite a “95% chance of success,” where success is equivalent to “not running out of money before you die.”

Die with money? Success! Die without money? Failure! This is an expected value metric—for 95% of all people, the 4% rule would have worked.

But a few problems in this thinking immediately arise and ergodicity is to blame.

Problem 1: Equal and Opposite?

The 5% of retirement fail cases are painful. Very painful. I would argue that the pain of failure in retirement is greater than the joy of success.

This is reminiscent of loss aversion, or the “tendency to prefer avoiding losses to acquiring equivalent gains.” The keyword in loss aversion is “equivalent.” People would rather avoid a $100 parking ticket than win a $100 lotto ticket. Those are equivalent. And yes, loss aversion is irrational.

But is failing in retirement equivalent-and-opposite to succeeding in retirement? I’d argue no. Failing in retirement is akin to a Russian Roulette loss. Devastating! And succeeding in retirement is a Russian Roulette win. It’s “expected.”

Problem 2: Expected Value & Risk Sharing

Let’s assume we all follow the 4% rule. And true to historical form, let’s assume that 95% of us have successful retirements, but 5% of us “fail” and run out of money.

In the previous examples—100 friends and Mike Tyson, or 100 friends and the 40% win/30% loss coin flip—we assumed that the group would share the risk and share the reward.

This guaranteed that we’d see profits, but eliminated our chance to win $950 million. This guaranteed that even if we did get face-punched by Mike Tyson, our winning friends would still help us out.

But in retirement planning, people do not share risk. The 95% winners have no obligation to bail out the 5% losers. This changes the game. This isn’t traditional ergodicity.

Instead, we’re all in the game by ourselves (like the time average participant), but only have one shot to get it right (lest our retirement plan fail). From the ergodicity point of view, it’s a conundrum. It’s like playing Russian Roulette with a 20-chamber gun (5% failure = 1 chance in 20).

How do potential retirees react to this change in the rules?

For starters, many real retirement plans are couched with so much conservatism that the retiree ends up with more money when they die than when they retired. Put another way—their investment gains outpace their ability to spend.

And we know that money is time. Therefore, we can conclude that many people work for years more than they need to. They’re cursing at spreadsheets when they could be sipping mojitos. Pardon my 2020 vernacular, but this is an abundance of caution.

Is there an ergodic solution to this over-cautious planning?

Does Ergodicity Have a Solution?

What did we learn from Mike Tyson ergodicity example? What did we learn from our coin flipping?

If we share risk, we reduce our potential upside but also eliminate downside.

Imagine that 100 retirees pool a portion of their money together. They all know that 95% of them won’t need to dip into that pool. They also know that their money in the pool is probably going to have worse returns than it would outside of that pool.

However! These 100 retirees also realize that the pool will save 5 of them from failure. And thus, the pool guarantees that their retirement will be successful. Instead of 100% of them worrying about a 5% downside, now none of them need to be concerned.

The purpose of investing is not to simply optimise returns and make yourself rich. The purpose is not to die poor.

William Bernstein

Some of you will know that this “pool” concept already exists. It’s called an annuity.

Annuities?! Jesse, You Son of a B…

Wait, wait, don’t shoot me! Besides, you only have one bullet in those 20 chambers (thank ergodicity)

Real quick: an annuity is a financial product where a customer pays a lump sum upfront in return for a series of payments over the rest of their life. Insurance companies often sell annuities.

Annuities—on average—are losing propositions. Just like my pool above, the average annuitant will suffer via opportunity costs. Their money—on average—is better invested elsewhere.

Insurance protects wealth. It doesn’t build wealth.

Ben Carlson

Never let someone convince you that an insurance product is going to build your wealth. Why? There are only two parties involved—you and the insurance company. If you’re building wealth, then the insurance company is…losing money? No way.

Insurance products are equivalent to average mutual funs with high fees. The high fees drain you like a vampire bat. They make money, and you lose via opportunity costs.

But one thing that annuities get right is that they hedge against downside risk in your retirement planning. The insurance company—i.e. my pool in the example above—collects a loss from most customers in order to provide a vital win to few customers.

This is just like real insurance. Most people pay more in insurance premiums—for their house, their car, their medical life—then they ever see in payouts. But for a vital few, insurance saves them from complete disaster.

Of course, detractors will rightly point out that annuities aren’t always guaranteed. If the insurance company goes belly-up, your state guarantor might only cover a portion of what you’re owed. Yes—that means your risk mitigation technique has risk itself. Riskception.

Annuities aren’t perfect. I don’t plan on buying one. But if the ergodicity of retirement planning has you fretting small chances of failure, annuities are one way to hedge that downside.

Is Robin Hood Ergodic?

Jesse is a boring index fund investor. It’s true.

But not Robin. She day-trades on Robin Hood, often experimenting with exotic trades with high leverage.

We can examine Jesse and Robin using ergodicity.

Jesse is playing the long game. In this simple hypothetical, his yearly returns are +30%, +10%, then -15%. The same three-year cycle keeps repeating. One might look at those three values and think, “Ah. About 8.3% per year, on average.”

Robin thinks daily. She wants money now. In this hypothetical, her daily returns are +60%, +15%, and -50%. The same three-day cycle keeps repeating. Again, one might look at those three values and think, “Ah. About 8.3% per day, on average.”

You might see a problem. We’ve used the arithmetic mean here. The arithmetic mean is useful in finding the expected value, in ergodicity terms. If Person A gains 60%, Person B gains 15%, and Person C loses 50%, their average change is an 8% gain.

But sequencing investment returns—e.g. the ergodicity time average—requires that we use a logarithmic average. So let’s do that below:

[note: exp = the exponential function, ln = the natural log]

Uh oh. Robin’s log average return is negative. And sure enough, if Robin executed this particular day-trading strategy, she would turn her $10,000 into $500 in less than four months. Meanwhile, Jesse is fine with his 6.7% annual return (trust me…he is).

The simple lesson is one that new investors love to scream from the rooftops (and that’s a good thing). Namely, a given portfolio loss requires a larger equivalent gain to return back to even. The arithmetic mean does not capture this fact, while the log mean does.

The larger the loss, the more significant the returning gain needs to be. That’s another ergodicity concept.

E.g. a 1% loss is offset by a 1.01% gain—they’re essentially the same. But a 50% loss—like the one Robin suffers every third day—requires a 100% gain to offset it

Just like we said earlier in the post—big risks matter most, and those large downsides are when we’re likely to see non-ergodic systems.

Everyday Ergodicity

I would argue that a smooth, ergodic personal life is also optimal. Imagine ranking your days on a scale of 1-10. Would you rather have half 10’s and half 4s? Or all dependable 7’s? Or two-thirds 10’s and one-third 1’s?

To each their own. I’d prefer the 7’s. I don’t want half my days to be “bad,” even if the flip side of that coin is that half my days are “perfect.”

Don’t make ‘perfect’ the enemy of good enough.

-Someone at Jesse’ work

Maybe it’s boring. Maybe it’s the same muscle that pushes me towards indexing and away from Gamestop. To each their own. But I’ll take the 7’s.

Ergodicity in Grad School

In grad school, I studied fluid dynamics. See—this is me! Specifically, I worked on reaction-diffusion-advection problems in the University of Rochester Mixing Lab.

Fluid mixing is a terrific example of ergodicity. Take a few seconds to watch the video below. It’s a pretty way to view equilibrium statistic physics. Ergodicity applies to many different dynamical systems, stochastic processes, thermodynamic equilibrium problems, etc. It’s a mechanical engineer’s dream.

Ergodic mixing

If we mix sufficiently, we see that small sub-sections of the fluid are representative of the fluid as a whole. The time average of many mixes is equal to our expected value of a uniform mix. This is ergodicity. This system is ergodic.

If this was butter and sugar—soon to be cookies—we could take any teaspoon of the mixture and draw reasonable assumptions about the mixture as a whole. Mmmmm!

But imagine if we accidentally introduce a dog hair into the mix (not that that’s ever happened in my kitchen). Suddenly, the mix is no longer ergodic.

Why? The expected value of any given cookie is that it will not contain the dog hair. But of course, eat enough of the cookies and you’ll eventually find the hair.

Or put another way, a single teaspoon of the mixture—which will contain either the entire dog hair or no dog hair at all—is no longer representative of the total mixture.

Good Article. Ergo…

Ergo it’s time for the summary.

Ergodicity is a fun concept. Or at least fun for nerds like me. It’s a terrific way to consider risk. It helps us in behavioral economics, personal finance, and real retirement planning.

What do you think? Any cool ergodic or non-ergodic systems in your life?

If you enjoyed this article and want to read more, I’d suggest checking out my Archive or Subscribing to get future articles emailed to your inbox.

This article—just like every other—is supported by readers like you.

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Tagged ergodicity, retirement, risk, statistics

Source: bestinterest.blog

Ergodicity: The Coolest Idea You’ve Never Heard Of

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Share This Post:

Surely that’s a typo…ergodicity!? No, it’s right! Ergodicity is a powerful concept in economic theory, investing, and personal finance.

Even if the name seems wild to you, the idea is simple—stick with me while I explain it. And then we’ll apply ergodicity to retirement planning and investing ideas.

By the end of this article, you’re going to be seeing ergodic systems and non-ergodic systems all over your life!

Ergodic, Non-Ergodic, and Russian Roulette

Ergodicity compares the time average of a system against the expected value of that system. Let’s explain those two terms: time average and expected value.

The time average asks, “If we did something a million, billion, trillion times…what would we expect the results to look like?” It needs to be a sufficiently long random sample.

The expected value asks, “By simply averaging probabilities, where would we expect the result to be?”

At first blush, you might think, “Those two are the same thing…right?” Right! Or, at least you’d be right if the system in question is ergodic.

I flip a coin a billion times, and I end up with a time average of 50/50 heads and tails. Alternatively, I could just use their known probabilities and surmise the expected value of 50/50.

In this case, the time average and the expected value are the same. Therefore, the system—coin flipping—is ergodic.

But let’s contrast coin flips against Russian Roulette. The expected value of Russian Roulette is optimistic. ~83% success and ~17% failure. But what happens if one “plays” a million times? Ahh! I think you’d agree that the time average of Russian Roulette is 100% failure.

When one fails in Russian Roulette, it is a devastating failure. To only look at the expected value of the system is too simple. The expected value is far different than the time average. Thus, Russian Roulette is non-ergodic.

Ergodicity –> Over and Over, Big & Small

Ergodicity rears its head in two circumstances. First, ergodicity matters when we do things over and over and over. And second, ergodicity matters when certain outcomes are meaningful while other outcomes are insignificant.

To further explain ergodicity, imagine this bet:

I have a 100-sided die.

I’ll roll the die and you pick a number. If it lands on any other number than your number, then you win $1000.

But if it lands on your number, then Mike Tyson punches you in the face and takes your money.

What a deal! You call 99 of your friends and you all come to take this bet. Sure enough, one of your friends loses. But the rest of you win a combined $99,000 and agree to pay for his medical bills (which may or may not be covered by the $99K…which is another crazy blog post waiting to happen).

The “ensemble average” is that you won! One individual loss doesn’t change that.

But would that result be the same if you had played 100 times by yourself? No! In that scenario, there’s a 63% chance that you’d eventually lose the roll, lose your money, and get punched in the face.

The expected value (you and all your friends) is different than the time average (you doing it 100x). This is not an ergodic process.

Revisiting Ergodicity & Coin Flips

We concluded earlier that coin flips are ergodic. The expected value of a single coin flip equals the time average results of many coin flips.

But let’s change the rules a bit. Imagine I promised you a 40% positive return on heads but a 30% loss on tails. You start with $100,000. Would you take this bet?

Again, let’s call up 100 of your friends. You each take the bet.

We can predict that half of you will end up with $140K (40% return) and half end up with $70K (a 30% loss). On average, you each have $105K. As a group, you’ll end up 5% higher than you started.

Sure enough, we can run this simulation a million times and that’s exactly what we see. Both the mean and median results of these simulation show a 5% profit. Taking the bet was smart.

But what if you took the bet 100 times? Same result?

Same for You?

To start, let’s look at two common snippets in the sequence of returns: one win followed by one loss, and one loss followed by one win.

Win then loss

Loss then win

(You mathematicians will see the commutative property at play. The order of this multiplication didn’t matter.)

This result completely shifts our mindset.

When two people share a win/loss, then end up with $140K+$70K = $210K, or $105K each. They gain $5K. But when one person sequentially suffers a win/loss, she ends up with $98K, or a $2K loss.

What happens if you take this bet 100 times in a row? On average, you are going to lose money. Let’s look at a 50/50 heads/tails split.

Group 50/50:

That’s a 5% profit.

You 50/50:

That’s a 64% loss

But you might “spike” a certain run where you get more heads than tails. What happens if the group gets 60 heads and 40 tails? What happens if you get 60 heads and 40 tails?

Group 60/40:

You 60/40:

That’s…a big profit. $37.3 million.

I simulated the “you get 100 flips” case 100,000 times. As expected, the median result is a 64% loss. But the best result of the 100K simulations turns your $100K bet into $950 million dollars (68 heads, 32 tails).

This bet is non-ergodic. The expected value (100 friends scenario) is completely different than the time average (you 100x bets scenario).

But it’s also interesting that the distribution in the expected value case is tight (low risk, low reward) while the distribution in the time average case is extremely wide (high risk, potentially high reward).

EV is a profit, while time average is a loss. EV is low variance, while time average is high variance.

In case you can’t tell, ergodicity economics and subsequent economic theory is a serious field. There are big conversations taking place and serious money to be made (or lost).

But let’s focus a little closer to home: ergodicity and retirement.

Ergodicity and Retirement

In retirement planning, probability of success is often used as a figure of merit. I’ve used it here on the blog.

For example, the famous Trinity Study and 4% Rule cite a “95% chance of success,” where success is equivalent to “not running out of money before you die.”

Die with money? Success! Die without money? Failure! This is an expected value metric—for 95% of all people, the 4% rule would have worked.

But a few problems in this thinking immediately arise and ergodicity is to blame.

Problem 1: Equal and Opposite?

The 5% of retirement fail cases are painful. Very painful. I would argue that the pain of failure in retirement is greater than the joy of success.

This is reminiscent of loss aversion, or the “tendency to prefer avoiding losses to acquiring equivalent gains.” The keyword in loss aversion is “equivalent.” People would rather avoid a $100 parking ticket than win a $100 lotto ticket. Those are equivalent. And yes, loss aversion is irrational.

But is failing in retirement equivalent-and-opposite to succeeding in retirement? I’d argue no. Failing in retirement is akin to a Russian Roulette loss. Devastating! And succeeding in retirement is a Russian Roulette win. It’s “expected.”

Problem 2: Expected Value & Risk Sharing

Let’s assume we all follow the 4% rule. And true to historical form, let’s assume that 95% of us have successful retirements, but 5% of us “fail” and run out of money.

In the previous examples—100 friends and Mike Tyson, or 100 friends and the 40% win/30% loss coin flip—we assumed that the group would share the risk and share the reward.

This guaranteed that we’d see profits, but eliminated our chance to win $950 million. This guaranteed that even if we did get face-punched by Mike Tyson, our winning friends would still help us out.

But in retirement planning, people do not share risk. The 95% winners have no obligation to bail out the 5% losers. This changes the game. This isn’t traditional ergodicity.

Instead, we’re all in the game by ourselves (like the time average participant), but only have one shot to get it right (lest our retirement plan fail). From the ergodicity point of view, it’s a conundrum. It’s like playing Russian Roulette with a 20-chamber gun (5% failure = 1 chance in 20).

How do potential retirees react to this change in the rules?

For starters, many real retirement plans are couched with so much conservatism that the retiree ends up with more money when they die than when they retired. Put another way—their investment gains outpace their ability to spend.

And we know that money is time. Therefore, we can conclude that many people work for years more than they need to. They’re cursing at spreadsheets when they could be sipping mojitos. Pardon my 2020 vernacular, but this is an abundance of caution.

Is there an ergodic solution to this over-cautious planning?

Does Ergodicity Have a Solution?

What did we learn from Mike Tyson ergodicity example? What did we learn from our coin flipping?

If we share risk, we reduce our potential upside but also eliminate downside.

Imagine that 100 retirees pool a portion of their money together. They all know that 95% of them won’t need to dip into that pool. They also know that their money in the pool is probably going to have worse returns than it would outside of that pool.

However! These 100 retirees also realize that the pool will save 5 of them from failure. And thus, the pool guarantees that their retirement will be successful. Instead of 100% of them worrying about a 5% downside, now none of them need to be concerned.

The purpose of investing is not to simply optimise returns and make yourself rich. The purpose is not to die poor.

William Bernstein

Some of you will know that this “pool” concept already exists. It’s called an annuity.

Annuities?! Jesse, You Son of a B…

Wait, wait, don’t shoot me! Besides, you only have one bullet in those 20 chambers (thank ergodicity)

Real quick: an annuity is a financial product where a customer pays a lump sum upfront in return for a series of payments over the rest of their life. Insurance companies often sell annuities.

Annuities—on average—are losing propositions. Just like my pool above, the average annuitant will suffer via opportunity costs. Their money—on average—is better invested elsewhere.

Insurance protects wealth. It doesn’t build wealth.

Ben Carlson

Never let someone convince you that an insurance product is going to build your wealth. Why? There are only two parties involved—you and the insurance company. If you’re building wealth, then the insurance company is…losing money? No way.

Insurance products are equivalent to average mutual funs with high fees. The high fees drain you like a vampire bat. They make money, and you lose via opportunity costs.

But one thing that annuities get right is that they hedge against downside risk in your retirement planning. The insurance company—i.e. my pool in the example above—collects a loss from most customers in order to provide a vital win to few customers.

This is just like real insurance. Most people pay more in insurance premiums—for their house, their car, their medical life—then they ever see in payouts. But for a vital few, insurance saves them from complete disaster.

Of course, detractors will rightly point out that annuities aren’t always guaranteed. If the insurance company goes belly-up, your state guarantor might only cover a portion of what you’re owed. Yes—that means your risk mitigation technique has risk itself. Riskception.

Annuities aren’t perfect. I don’t plan on buying one. But if the ergodicity of retirement planning has you fretting small chances of failure, annuities are one way to hedge that downside.

Is Robin Hood Ergodic?

Jesse is a boring index fund investor. It’s true.

But not Robin. She day-trades on Robin Hood, often experimenting with exotic trades with high leverage.

We can examine Jesse and Robin using ergodicity.

Jesse is playing the long game. In this simple hypothetical, his yearly returns are +30%, +10%, then -15%. The same three-year cycle keeps repeating. One might look at those three values and think, “Ah. About 8.3% per year, on average.”

Robin thinks daily. She wants money now. In this hypothetical, her daily returns are +60%, +15%, and -50%. The same three-day cycle keeps repeating. Again, one might look at those three values and think, “Ah. About 8.3% per day, on average.”

You might see a problem. We’ve used the arithmetic mean here. The arithmetic mean is useful in finding the expected value, in ergodicity terms. If Person A gains 60%, Person B gains 15%, and Person C loses 50%, their average change is an 8% gain.

But sequencing investment returns—e.g. the ergodicity time average—requires that we use a logarithmic average. So let’s do that below:

[note: exp = the exponential function, ln = the natural log]

Uh oh. Robin’s log average return is negative. And sure enough, if Robin executed this particular day-trading strategy, she would turn her $10,000 into $500 in less than four months. Meanwhile, Jesse is fine with his 6.7% annual return (trust me…he is).

The simple lesson is one that new investors love to scream from the rooftops (and that’s a good thing). Namely, a given portfolio loss requires a larger equivalent gain to return back to even. The arithmetic mean does not capture this fact, while the log mean does.

The larger the loss, the more significant the returning gain needs to be. That’s another ergodicity concept.

E.g. a 1% loss is offset by a 1.01% gain—they’re essentially the same. But a 50% loss—like the one Robin suffers every third day—requires a 100% gain to offset it

Just like we said earlier in the post—big risks matter most, and those large downsides are when we’re likely to see non-ergodic systems.

Everyday Ergodicity

I would argue that a smooth, ergodic personal life is also optimal. Imagine ranking your days on a scale of 1-10. Would you rather have half 10’s and half 4s? Or all dependable 7’s? Or two-thirds 10’s and one-third 1’s?

To each their own. I’d prefer the 7’s. I don’t want half my days to be “bad,” even if the flip side of that coin is that half my days are “perfect.”

Don’t make ‘perfect’ the enemy of good enough.

-Someone at Jesse’ work

Maybe it’s boring. Maybe it’s the same muscle that pushes me towards indexing and away from Gamestop. To each their own. But I’ll take the 7’s.

Ergodicity in Grad School

In grad school, I studied fluid dynamics. See—this is me! Specifically, I worked on reaction-diffusion-advection problems in the University of Rochester Mixing Lab.

Fluid mixing is a terrific example of ergodicity. Take a few seconds to watch the video below. It’s a pretty way to view equilibrium statistic physics. Ergodicity applies to many different dynamical systems, stochastic processes, thermodynamic equilibrium problems, etc. It’s a mechanical engineer’s dream.

Ergodic mixing

If we mix sufficiently, we see that small sub-sections of the fluid are representative of the fluid as a whole. The time average of many mixes is equal to our expected value of a uniform mix. This is ergodicity. This system is ergodic.

If this was butter and sugar—soon to be cookies—we could take any teaspoon of the mixture and draw reasonable assumptions about the mixture as a whole. Mmmmm!

But imagine if we accidentally introduce a dog hair into the mix (not that that’s ever happened in my kitchen). Suddenly, the mix is no longer ergodic.

Why? The expected value of any given cookie is that it will not contain the dog hair. But of course, eat enough of the cookies and you’ll eventually find the hair.

Or put another way, a single teaspoon of the mixture—which will contain either the entire dog hair or no dog hair at all—is no longer representative of the total mixture.

Good Article. Ergo…

Ergo it’s time for the summary.

Ergodicity is a fun concept. Or at least fun for nerds like me. It’s a terrific way to consider risk. It helps us in behavioral economics, personal finance, and real retirement planning.

What do you think? Any cool ergodic or non-ergodic systems in your life?

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Source: bestinterest.blog