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Collectible LEGO sets have an 11% annual yield. They’re a better investment than stocks, gold, or art

The 2007 Millennium Falcon LEGO set initially sold for $400 on the primary market, then fetched as much as $15,000 in auctions seven years later. Credit: LEGO.

With cryptocurrencies having one of the most impressive bull runs in the history of financial assets, it’s easy to see why people are no longer impressed by traditional investments. However, if you’re not the kind of person that can handle the heart-racing, wild volatility of the crypto market, you may be interested in another unusual way of investing that can be both highly profitable and not that all that risky. That would be collecting toys, believe it or not.

According to a study published this week in the journal Research in International Business and Finance, some rare toys like retired LEGO sets can grow in value at a rate as high as 11% per year. That’s much faster than gold, stocks, and bonds — the go-to financial instruments preferred by retail and institutional investors for decades.

Collectible toys are in the same investment class as rare wines, vintage cars, jewelry, art, and antiques. Collectibles are items that are worth far more than their original sale price and are considered alternative investments—vehicles that don’t fall into any other category like stocks, bonds, cash, or real estate.

Most wealthy people are aware of the importance of diversifying their portfolios by adding collectibles to their baskets. About 10% of their net worth is comprised of works of art, jewelry, and other collectibles whose value tends to rise in time, providing a cushion during periods when the stock market crashes.

But while traditional collectibles have been widely studied by economists, toy collectibles like discontinued model cars and Barbie dolls have been largely ignored.

For their new study, researchers at the Higher School of Economics at the University of Moscow analyzed the prices of 2,322 LEGO sets that were first released between 1987 and 2015. They compared the primary sales price to those from online auctions of unopened sets.

In just two to three years after a LEGO set is retired, the secondary market prices typically start growing, although there was a great deal of variation ranging from -50% to +600% annually. That’s because the value of the sets depends on numerous factors, the best indicators for swing trading being the number of sets of the edition and the interest in special editions such as those dedicated to iconic films, books, or historic events.

The medium-sized sets saw the least returns, while very large and, conversely, very small sets grew the fastest. Smaller LEGO sets tend to have unique parts or figurines that never show up in other releases, while very big sets tend to be produced in small quantities and are more attractive to adults.

Concerning thematic sets, some of the most expensive were those dedicated to the Millennium Falcon, Cafe on the Corner, Taja Mahal, Death Star II, and the Imperial Star Destroyer.

For instance, the Financial Times reports that the largest set the Danish toymaker ever produced — a version of the Star Wars Millenium Falcon, which consisted of nearly 6,000 pieces — was released in 2007 at a price of around $400. In 2014, an unopened set sold at an auction in Las Vegas for $15,000. This particular sale marks the world’s most expensive Lego set, so it’s definitely an outlier, but elsewhere similar unopened sets regularly fetch $6,000.

Keeping the set unopened and in pristine condition is key to having a collectible toy item that grows in value with time. Once opened, collectible toys decline in value automatically by at least 25%, Gerben van IJken, toy expert, Lego valuer and auctioneer for the site Catawiki.

The prices of LEGO collectibles on secondary markets were not tied to the stock market, making them a good store of value and hedging against market swings. Artworks and antiques play a similar role, but the entry barrier of a collectible LEGO set is usually lower. On the other hand, LEGO sets are only worthwhile as an investment vehicle when playing the long game. You have to hold a set for at least three years after the set is discontinued in order to experience a positive yield. An initial transactional cost is also higher than in stocks or bonds due to factors like delivery and storage.

“Investors in LEGO generate high returns from reselling unpacked sets, particularly rare ones, which were produced in limited editions or a long time ago. Sets produced 20-30 years ago make LEGO fans nostalgic, and prices for them go through the roof. But despite the high profitability of LEGO sets on the secondary market in general, not all sets are equally successful, and one must be a real LEGO fan to sort out the market nuances and see the investment potential in a particular set,” said Victoria Dobrynskaya, study co-author and Associate Professor at the Faculty of Economic Sciences at Moscow University.

Researchers develop a new way to tackle fake news — and it’s aimed at the stock market

Fake news is written to confuse and manipulate public opinion. As such, its intent is always to deceive. But the outcome of twisting facts is, arguably, most evident in financial markets, where there’s always money to be made by shifting people’s trust. Share price, after all, is as much a product of demand as they are of fiscal matters.

Researchers at the University of Göttingen, University of Frankfurt, and the Jožef Stefan Institute in Ljubljana, Slovenia, have developed a new framework that, they hope, will help us identify such content. Since malevolent actors can tailor content to appear genuine, through avoiding incriminating terms, for example, the team focused on other aspects of the text.

No swindlin’

“Here we look at other aspects of the text that makes up the message, such as the comprehensibility of the language and the mood that the text conveys,” says Professor Jan Muntermann from the University of Göttingen, co-author of the paper describing the approach.

The authors used machine learning for the task. This algorithm was tasked with creating analytical models that can be applied to identify suspicious messages on material based on characteristics other than the wording. In very broad lines, it operates similarly to spam filters.

However, there are important differences. For example, today’s spam filters can be appeased by removing incriminating words, so there is a constant back and forth between fraudsters and the systems meant to keep them at bay. To counteract this, the team tested an approach that involves using several overlapping detection models to increase the system’s accuracy (its ability to tell apart fake news from valid information) and robustness (its ability to see through attempts to hide fake news). They explain that even if flagged words are removed from a piece of text, the algorithm can still identify it as fake news based on other linguistic features.

“This puts scammers into a dilemma. They can only avoid detection if they change the mood of the text so that it is negative, for instance,” explains Dr Michael Siering. “But then they would miss their target of inducing investors to buy certain stocks.”

The main intended purpose of this system is to identify attempts to manipulate the corporate news ecosystem in order to influence stock prices — which can lead to major monetary losses for a lot of people. The authors envision a system where their approach can be used as a type of market watchdog, which would flag such attempts at market manipulation and lead to a temporary suspension in the trading of affected stocks. Alternatively, it could potentially become a source of evidence for criminal prosecutions in the future.

Either way, the implementation of such a system would go a long way towards improving public and corporate confidence in the stock market. Normally this wouldn’t really be relevant news for us here, but seeing as retail (i.e. us common Joes and Janes) now comprises an estimated 10% of stock trading, by volume, in the US, I’m certain at least some of you partake as well.

It would be extremely interesting to see how such a system would impact the evolution of the “meme stocks” we’ve seen recently. Although the largest of these undeniably enjoyed major grassroots support, there were definitely a lot of pieces trying to sway public opinion both for and against them. Would a system such as that detailed here help boost retail confidence in meme stocks, in paricular? Or would it stifle their growth by stifling hype around them? Given that the framework is already trialed and the results published, I think it’s a safe bet to say that we’re going to find out in the future.