gambling

Why Not to Invest in Futures Funds

readingbyeugene Leave a comment

If you or your family has investments in so-called futures funds, you might want to pull out your money out of them immediately. David Evans, writing in Bloomberg, has a big piece on how these futures funds have been a complete cash drain on those who unwisely chose to invest in them. While traditional hedge funds charge a 2 and 20 fee (2% fees, 20% of profits), these futures funds charge as as much as 9 percent in total fees each year (which is astronomical):

Investors who kept their money in Spectrum Technical for that decade, however, reaped none of those returns — not one penny. Every bit of those profits — and more — was consumed by $498.7 million in commissions, expenses and fees paid to fund managers and Morgan Stanley.

After all of that was deducted, investors ended up losing $8.3 million over 10 years. Had those Morgan Stanley investors placed their money instead in a low-fee index mutual fund, such as Vanguard Group Inc.’s 500 Index Fund, they would have reaped a net cumulative return of 96 percent in the same period.

The “powerful argument” for managed futures turned out to be good for brokers and fund managers but not so good for investors.

In the $337 billion managed-futures market, return-robbing fees like those are common. According to data filed with the U.S. Securities and Exchange Commission and compiled by Bloomberg, 89 percent of the $11.51 billion of gains in 63 managed-futures funds went to fees, commissions and expenses during the decade from Jan. 1, 2003, to Dec. 31, 2012.

Fees: $1.5 Billion

The funds held $13.65 billion of investor money at the end of last year, according to SEC filings. Twenty-nine of those funds left investors with losses.

What’s more, it seems many of these futures funds escape transparency:

Like hedge funds, managed-futures funds haven’t been required to file with the SEC as a matter of course. However, an SEC rule has mandated that any partnership with more than 500 investors and $10 million in assets — even a hedge fund — must file quarterly and annual reports.

The SEC has no category listing managed-futures funds, as it does for mutual funds or corporate filings. Bloomberg Markets culled through thousands of filings in several categories, including one called “SIC 6221 Unknown,” to identify 63 managed-futures funds that reported to the SEC.

Even sophisticated investors should stay away from these managed funds.

Little Bastard: The Computer Poker Machine

readingbyeugene Leave a comment

A fascinating piece in New York Times Magazine on the advancement of artificial intelligence in how machines play poker:

The machines, called Texas Hold ‘Em Heads Up Poker, play the limit version of the popular game so well that they can be counted on to beat poker-playing customers of most any skill level. Gamblers might win a given hand out of sheer luck, but over an extended period, as the impact of luck evens out, they must overcome carefully trained neural nets that self-learned to play aggressively and unpredictably with the expertise of a skilled professional. Later this month, a new souped-up version of the game, endorsed by Phil Hellmuth, who has won more World Series of Poker tournaments than anyone, will have its debut at the Global Gaming Expo in Las Vegas. The machines will then be rolled out into casinos around the world.

They will be placed alongside the pure numbers-crunchers, indifferent to the gambler. But poker is a game of skill and intuition, of bluffs and traps. The familiar adage is that in poker, you play the player, not the cards. This machine does that, responding to opponents’ moves and pursuing optimal strategies. But to compete at the highest levels and beat the best human players, the approach must be impeccable. Gregg Giuffria, whose company, G2 Game Design, developed Texas Hold ‘Em Heads Up Poker, was testing a prototype of the program in his Las Vegas office when he thought he detected a flaw. When he played passively until a hand’s very last card was dealt and then suddenly made a bet, the program folded rather than match his bet and risk losing more money. “I called in all my employees and told them that there’s a problem,” he says. The software seemed to play in an easily exploitable pattern. “Then I played 200 more hands, and he never did anything like that again. That was the point when we nicknamed him Little Bastard.”

Read the rest here.

On Gambler’s Fallacy in Blackjack

readingbyeugene Leave a comment

Jonathan Adler has penned an excellent guest post on Felix Salmon’s blog regarding the gambler’s fallacy when playing blackjack:

Blackjack is a game where it is easy to fall prey to the gambler’s fallacy. As a player, if you receive several losing hands in a row it is easy to think that you’re “due” for a winning hand. However since each hand is essentially an independent event (and I’ll get back to this later), the number of losses you have had in a row doesn’t change chance of you getting a win on your next hand. Even if you get a run of bad hands in a row, your next hand is still just about as likely to lose as the previous one, similar to the situation with flipping a coin.

Adler then recounts the story of hedge fund manager Michael Geismar and how he was able to work with a different gambling strategy:

Lawrence Delevingne’s story on Michael Geismar’s time in Vegas is a great anecdote showing that people in charge of billions of dollars on Wall Street don’t understand the idea of shifting risk. After hearing Ben Mizrech speak, Geismar was seen using a betting strategy to try and improve his winnings at the blackjack table. After every winning hand, he would increase his bet by $1,000. After a losing hand he would lower his bet. The article doesn’t say by how much, but let’s assume after losing a hand he would reset his bet to $1,000.

This betting strategy has the opposite effect the one described before; instead of having a single win wipe out previous losses, a single loss will wipe out much of the earlier winnings. On most sequences of hands Geismar would lose money, but occasionally he will have an unlikely winning streak and make a very large amount. Instead of shifting the downside risk to the tail events, Geismar shifted the upside risk to tail events. Over time this betting strategy is expected to lose Geismar money, just like all other betting strategies. But Geismar fell victim to the gambler’s fallacy: he thought that a run of winnings changed the chance of getting another winning hand.

The takeaway is this: any kind of gambling strategy that you devise will not work against the house in the long run. Card counting can give you an edge, but it’s extremely difficult to put into practice.

I myself have been prone to devise gambling strategies when playing blackjack, and reading Adler’s post serves as affirmation that doing so doesn’t work. That interlude of Geismar’s lucky streak is just a major deviation, a long tail event.

The Man Who Broke Atlantic City

readingbyeugene Leave a comment

Don Johnson won almost $6 million playing blackjack in one night, single-handedly obliterating the monthly revenue of Atlantic City’s Tropicana casino. Not long before that, he’d taken the Borgata for $5 million and Caesars for $4 million. But Don Johnson isn’t a card counter. So how did he do it?

Turns out, he is one of those sophisticated (high roller) gamblers who can negotiate with casinos, as explained in this story in The Atlantic:

Sophisticated gamblers won’t play by the standard rules. They negotiate. Because the casino values high rollers more than the average customer, it is willing to lessen its edge for them. It does this primarily by offering discounts, or “loss rebates.” When a casino offers a discount of, say, 10 percent, that means if the player loses $100,000 at the blackjack table, he has to pay only $90,000. Beyond the usual high-roller perks, the casino might also sweeten the deal by staking the player a significant amount up front, offering thousands of dollars in free chips, just to get the ball rolling. But even in that scenario, Johnson won’t play. By his reckoning, a few thousand in free chips plus a standard 10 percent discount just means that the casino is going to end up with slightly less of the player’s money after a few hours of play. The player still loses.

But two years ago, Johnson says, the casinos started getting desperate. With their table-game revenues tanking and the number of whales diminishing, casino marketers began to compete more aggressively for the big spenders. After all, one high roller who has a bad night can determine whether a casino’s table games finish a month in the red or in the black. Inside the casinos, this heightened the natural tension between the marketers, who are always pushing to sweeten the discounts, and the gaming managers, who want to maximize the house’s statistical edge. But month after month of declining revenues strengthened the marketers’ position. By late 2010, the discounts at some of the strapped Atlantic City casinos began creeping upward, as high as 20 percent.

The house has advantage, over long term, with typical gamblers who wager from a few to a few hundred dollars per hand. But when you have elite status and can negotiate with casinos to give you discounts on losses, you can turn the odds in your favor. And that’s what Don Johnson did…

Last question: is Don Johnson the most famous blackjack player in the world? That’s what the article attests.

On Shuffling and Randomness

readingbyeugene Leave a comment

From this fascinating piece in The Wall Street Journal, we learn about the randomness (or lack thereof) when shuffling cards:

The standard way to mix a deck of playing cards—the one used everywhere from casinos to rec rooms—is what is known as a riffle (or “dovetail”) shuffle. You begin by splitting the deck into two roughly equal stacks. Then you flick the cards with your thumbs off the bottoms of the piles in alternating fashion, interleaving the two stacks.

For games like blackjack or poker to be truly fair, the order of the cards must be completely random when the game begins. Otherwise a skilled cheat can exploit the lack of randomness to gain an advantage over other players.

How many riffle shuffles does it take to adequately mix a deck of 52 playing cards?

As it turns out, you have to shuffle seven times before a deck becomes truly scrambled. Not only that, the cards become mixed in a highly unusual way: The amount of randomness in the deck does not increase smoothly. The first few shuffles do little to disturb the original order, and even after six shuffles, you can still pick out distinctly non-random patches.

But right around the seventh shuffle something remarkable happens. Shuffling hits its tipping point, and the cards rapidly decay into chaos.

The seven-shuffles finding applies to messy, imperfect riffle shuffles. The deck might not be divided exactly in half, for instance, or the cards might be riffled together in a haphazard way. Far from undesirable, a little sloppiness is actually the key to a random shuffle.

A perfect (or “faro”) shuffle, meanwhile, wherein the deck is split precisely in half and the two halves are zippered together in perfect alternation, isn’t random at all. In fact, it’s completely predictable. Eight perfect shuffles will return a 52-card deck to its original order, with every card cycling back to its starting position.

And this doesn’t just work for 52 cards. A deck of any size will eventually return to its starting order after a finite sequence of faro shuffles, although the number of faros required isn’t always eight—and doesn’t increase linearly. If you have 104 cards, for instance, it takes 51 faros to restore the deck. For a thousand cards, it takes 36.

These findings are among the many fascinating results explored in Magical Mathematics, a dazzling tour of math-based magic tricks. The authors, Persi Diaconis and Ron Graham, are distinguished mathematicians with high-powered academic pedigrees. Both are also accomplished magicians who have taught courses on mathematical magic at Harvard and Stanford.

I’ve put the book on my to-read list.