Thursday, December 31, 2009

New Year's Eve - Final Session of the Year

Well, it was a good final session of the year for me and a good start to the new year. It was a nice slow and steady climb, just how I like it. I called a few bluffs and made a few hands to slowly built my stack up. I never got involved with any large hands and before you knew it my stack was over $555. Nicole was running hot! and just kept felting everyone with her rags. Luckily, I was able to stay out of her way and she paid me off 3 out of 4 times we played together.

My New Year's Resolution is to Gamble less and play like a machine. This doesn't not mean no more Poker. It just means to avoid taking to many chances and long shots without proper pot odds. Many people equate Poker to gambling, but for me it's not gambling how I play. I like to say, I play with a slight edge ("only the nuts..") and like most casino table games, in the long run, I cant lose, because mathematically I am always ahead I will stay ahead in the long run.

Here are some stats and charts for my 2009 year in review:

Here is a chart by month. I managed to have just one losing month in November and the rest were profitable. My monthly average is right at $600/month. The way I see it, I make just enough to pay my rent or pay for my girl friend expenses.. I made a bit less in 2009 compared to 2008. My average in 2008 was $692/month, but I played more in 2008 when I lost my primary job for 2 months.

Here is a Cumulative Chart with each session mapped out. In total, I played 87 sessions in 2009. This compares to 108 sessions in 2008. That is about 1 in 4 days playing poker or about 24% of the days in 2009 playing the game. My average winning per session is about $82.64 which is better then my 2008 stat of $76.94 per session. As you can see I don't win all the time, but its a slow and steady rise like a stock. It doesn't always go up, but in the long run it is trending up and I ended the year at my 12 month high of $7,190! My 2008 winnings were $8309, but I played 21 more days during my unemployment in 2008.

Here is a chart by location. In total, I played at 20 different locations. 13 of those locations were profitable and 7 locations were deposits for me, but nothing larger then $895.

Poker Game Robbery




AUSTIN (KXAN) - Catered food, high-profile players and thousands of dollars on the table set the scene for an armed robbery in Southwest Austin.

Sources said gunmen broke into a high-stakes poker game around 11 p.m. Dec. 9. Wearing masks, they entered the apartment, assaulted some of the players and then took off with more than $20,000 in cash.

APD confirms there was an aggravated robbery at the apartment that night involving two suspects and the investigation is still open.

"From what I understand, investigators are at a stalemate," said Commander Chris Noble with APD's organized crime division. "The victim is not being cooperative."

But, Mike Lavigne, the Texas State Director for the Poker Players Alliance , blames antiquated laws for the robbers' success and the unsolved crimes.

"A lot of times people don't even call the cops if these places get busted by a thief because it's not legal for them to be necessarily running that room in the first place," Lavigne said.

Poker becomes illegal in Texas when the House makes a cut. In the case of these underground games, poker hosts can pocket hundreds of thousands of dollars a year for putting together the events. The nights usually involve catered food, free massages and, in some cases, extra security.

"It's not seen as a crime in most parts of the world," said Lavigne. "It just happens to be the leftovers from some old laws in Texas. It's not clear what's legal or illegal in our state right now."

Participating in an illegal poker game is a Class A misdemeanor. But, even with the minor criminal penalty, police said players and homeowners are reluctant to report an attack or a robbery.

"There's no incentive, if you will, for the victim to cooperate with the police," said Noble.

Cooperating with police involves identifying the players, which will then lead to an investigation - minor questioning, at the very least. And, that will likely kill a house's customer base.

"These players don't consider themselves criminals," said Lavigne. "They just want to be able to play with their friends in an environment without being hassled."

Tim Kelly, who founded the Austin Poker Alliance , is another avid fan of the game. Kelly, however, only participates in legal games and often sets up several tables at his own house.

"We'll fill up the place," Kelly said. "But, it's secure. When they come into the house there is a set time when registration is basically over and you're not really going to get into the house unless you break in."

Kelly adds that many of the players are licensed to carry concealed handguns.

"If they do break in, the criminals are risking their lives," said Kelly.

Kelly agrees that poker laws should be loosened in Texas, but said defying the laws in place now is too great a risk.

"I won't affiliate with it simply because of the danger that you're asking about," he said, referring to games where the house gets a cut. "I won't have anything to do with it."

There were similar robberies of poker games in Houston and Dallas in the last month. In both cases, the robbers were caught.

"You don't know what you're walking into until you walk in," said Lavigne. "You know, the fact of the matter is, eventually someone is going to come through that door with a gun - whether it's a cop or a robber."

In the case of the Gaines Ranch Apartments, APD said there are still no suspects in custody and they are working on getting more information from the victim.

Wednesday, December 30, 2009

Hit and Run Session

Had a quick session at the Mobile. Had not played there in six months. I had a bad session the night before. I built my stack to $600 and then donked it all off. I hit two pair with 89 suited and could let it go when I guy kept pushing with the nut straight with J10! The flop was 789...

My 2nd round in the big blind I look down at pocket Queens. The action before had one guy under the gun raise to $10. Another guy re-raise to $20. Mike calls and a 4th guy, maniac, calls the $20 and so I re-raise to $100. The guy under the gun folds, he said he had pocket 99s. The 2nd guy goes all-in for $113 with AK. Mike calls and a maniac calls suggesting pot odds. The pot is now over $400 with 3 all-ins. The flop was 9 high and I take it down. My re-raise pushed out the only hand that would have beat me... Now 3 guys have been busted out and my stack is up to over $500.

Shortly later two more people cash out and the game ends as we are 3 handed. I was kinda glad to take the money and run. Anytime you can win over $300 in less then one hour you better take it! I was on a bit of a heater hitting pocket 10s and Jacks, all with-in this first hour of play and they all held up.

Thursday, December 24, 2009

Shreveport Poker Rooms

Went to Shreveport, LA for the holidays. Also took a little tour of East TX. I manged to get a speeding ticket in tiny city of Rusk, TX. I was clocked going 52 in a 35 zone. The highway changed from 70 to 35 within the city limits and I was in the process of slowing down when the cop pegged me. Hopefully, I can explain to the judge and get a warning. I didnt even pass the 35mph sign when he pegged me.

Anyways, there are plenty of Casinos in Shreveport but none in Texas. The only Casinos that host a real poker room are Eldorado Resort and Harrah's Horseshoe in Bossier City, just across the river.

During this trip I only played at Eldorado's. My last trip to Shreveport was in August and played at Horseshoe. I lost $90 back then. I heard the game was better at Eldorado's so I focused my efforts there. The trip was a success and I made $575 total.

My first night I managed to play like a donkie early and lose $200. I rebuy for another $200 and get my stack back down to $60. I triple the $60 to $180 with pocket kings and 2 callers pre-flop. I win a few more small hands to build my stack to back to around $220. Then I hit pocket Aces under the gun. I raise to $20 and get 2 callers. A guy in late position re-raise me to $100 and I push all-in for my $220. Everyone else folds and he calls with pocket Kings! I win the race and doubled up to over $475! Im back "in the Black" and in the profit zone just like that...

My 2nd night was Christmas night and it was off to the races from the start! I cracked a set of kings with J9. Then cracked pocket Aces with J9 suited again to the same guy. The guy kept slow playing this big pairs and I kept cracking them my rags. He told me that I should never fold J9. He had Aces again later on in the evening and I cracked them with 57 suited. I chased a flush and hit, on the river. It was just one of those nights where the rags were hitting.

My last big hand was pocket Queens. I made a big re-raise pre-flop and got two callers. The flop was J103♠. I bet $75 on the flop and get one old guy calling me. The turn is an 8and I bet $100. He smooth calls me. The river is a 9and I push all-in for my remaining $100 with my straight. He calls and shows 2-pair 810! Damm that was lucky for me...



Monday, December 21, 2009

Gifts for Me..

If you need gift ideas for a typical guy, then here are some ideas. Most guys like gadgets so here are a few that I personally found this year for myself.. They are for the guy that has it all.. Click on any of the pics to take you to a store where you can buy it..

This is currently the best Bluetooth headset on the market today. It even beat out last year's Jawbone headset and is a bit cheaper.


This little gadget uses LEDs to lite up and charges wirelessly by induction. Pretty cool in an emergency.

This $10 device will sound up a small room.


This is a device that allows you to use your car's radio to connect your cell phones speakers for a wireless setup.

This convenient organizer allows you to recharge all your gadgets in one place. For the someone that has a phone, headset and mp3 player it is very handy.. It's also allot cheaper then the Powermat.

This cool device will wirelessly transmit your pics from your camera to your PC or the Internet. You can actually get a free one if you upgrade your storage space with with
Google.

Sunday, December 6, 2009

Biggest One Day Session All Year!

Friday night was my biggest night at Poker all year! I cashed out $900 even and netted $700. I looked back and I haven't made that much in one night, all year long! The amazing part is that I'm not to sure how it all happen. I did log all the big hands on twitter, but looking back it's hard to remember the big pots! I will check my logs now and try to recall the exact amounts.

The night started out slow for me and I didn't win a hand for 2.5hrs. I remember getting my stack down to around $120. I had lots of small pocket pairs early on and could not play most of them to a big raise. I finally got 2 black Aces and doubled up thru Nicole after 3.5hrs of play. At 4.5 hrs into the session I double up again playing A8 and hitting 2 pair. I only had about $220 in front of me, so basically I got back my blinds and then some...


After 5hrs of waiting, I finally hit my first set of 444s. It was a 7-way pot and the flop was 42K. A new guy bets out $35 and Nicole calls. I re-raise to $100 and both call. The turn is a 7 and they both check to me and I push all in for about $120. The new guy calls and Nicole folds. He shows AK and I take down the $540 pot! The guy said that he would have folded if I had more money. In other words, he was willing to give me $220 with top pair, top kicker... Thanks man, Ill take your money.

About 1:20hr later I get pocket kings and re-raise Nicole's $22 raise. She is now short stack and pushes in for another $75. She had 2♦ 4♦ suited and hits a flush! That knocks my stack down to around $380. Nicole proceeds to give my money away to everyone else at the table. As a side note, Nicole's stack was up over $1500 at one point, but it didn't last long as she literally plays every hand she is dealt and donated it away to everyone.

At 7hrs of play I hit a set of 999s and take down a modest pot of $50. Twenty minutes later I get pocket Kings again and felt Tiger. He had raised $15 and I re-raised him another $35. He calls and the flop is Jack high. Tiger bets $45 and I push him all-in for another $150. He calls and never shows. I assume he had AJ and take his stack. My stack is now at $600.

Ten minutes later I have A♥7♥. I call from the small blind and the flop is 6♥7♠8. Bobby bets out $12 and I call. The turn is a 5 of hearts and I bet out $25. Bobby re-raises be to $45. I smooth call looking for a straight flush. The river is a 2♦ and I decided to trap and check. Bobby bets $50 and and I realize I have a blocker to the straight flush, and push all-in. Bobby instant calls and shows a straight with 7♠4♠. My Ace high flush takes it down! Now my stack is around $750.

Twenty minutes later (8hrs into my session) I hit a set of 333s. A short stack slowed played and it costed him his entire stack. The flop was 723 and he said he had an over pair. Now I have around $850 in front of me. I play a bit more building my stack over $900 and decided to cash out when I got back to $900. I stuck to my plan and went home very happy with myself...







Wednesday, December 2, 2009

Wild Thanksgiving Poker Session

What happens in Omaha when a short stack flops a flush draw, Billy flops a wrap, Worm flops the nut flush draw and Anthony flops the nuts on the button?  You get one huge pot!

It was a wild session of poker last week.  I decided to give Omaha a try.  Got down $800 first night and made it back Friday night.  Check out this $1100 pot!

video

Monday, November 23, 2009

Black Friday Deals

Here is a listing of some great shopping deals for this Holiday shopping season:






The Laws of Probability Finally Kick In

It's been a tough November for me.  After a record October and six winning sessions in a row, I went on a bad run.  I had 3 losing sessions in a row, for a total loss of $800.  I wasn't playing badly, but had plenty of bad beats and suck outs, when I was way ahead pre-flop.  I think my biggest mistake was not folding when I was knew I was beat.  Folding is the hardest part of the game, especially when there is nothing obvious to be afraid of on the board.

Anyways, it finally broke on Saturday night when I finally started hitting my sets and taking it down!  I did have to fold Aces once after my continuation bet was re-raised $100 by Mr. Cho.  The board was 7J10 and Mr. Cho said he flopped the nuts.  

I had two red Aces again that night and some new guy flopped top set of Queens on me.  Same thing, he came over the top of my continuation bet 3x, but this time I was stubborn and refused to fold my Aces.  Luckily for me the turn was a King of hearts and that slowed him down.  He said he had put me on Kings or Aces.  The turn was a King of heart and he checked, the river was another heart and so I had the nuts.  It was a suck out, but the best hand did win...

At the end of the night I was up over $700.  I cashed out exactly $700 after using up my white chips on some speculative hands.  I had a net profit of $500 for the night and $300 for the weekend.  I will take that win and hopefully the laws of statistics finally start coming around.  I cant lose in the long run since I only play the best hands.  I'm like a Casino, I get my money eventually.. LOL...



Thursday, November 19, 2009

Saturday, November 7, 2009

Giving Some Back.

Well, I managed to lose my stack last night. I should have known that I couldn't win, when the only hands that I won with were rags and all my premium hands didn't hold up. I had 6 straight winning sessions, so it was not to unexpected for me to lose. That is how poker is sometimes. Some days you just cant win.

I started out fast building my stack up quickly. I had my roommates Jonathan and Rachel playing at another table last night too. I overheard them talking about King-6 and how it was someone's favorite hand. Well, I'm in the big blind and what do you know I have King 6. Well the flop was K108. The turn was a 6 and river a 6, I just boated. Nicole was in the hand with me and paid me off. Now I am up about $70.

Black Aces Cracked: Not five minutes later and I look down at two black Aces. I'm in middle position and raise $20. A Latino guy calls and Nicole calls. The flop is 8810, both of the callers check to me and I bet $50. Both callers now call again. The turn is a Jack. Both players check again, so I think for a moment and check. The river is another Jack and the Latino goes all in for around $90. Nicole folds and I think for a minute. What the heck does this guy have? I know he is a tight player. So I fold my Aces. He shows quad 8888s and asked me if I had Queens, I flip over my Aces! I'm happy I loss the minimum (which was $70 my winnings with K6..), but that was a sick hand!

20 minutes later I get a small blind special, 10-4 suited. It was a limped pot and I turned the flush. One guy had top set and Nicole hit a straight on the river to pay me off. That made my stack back up to around $270 again.

The Bad laid down, but right move: Blair comes to play at our table and she has around $100. He plays pretty tight so I try to respect her bets. Well she is in early position and goes all-in for $100. Mr. Cho thinks for a while and calls. I look down at pocket Jacks, think for a while and fold em. Everyone else folds. I figure I could only beat pocket 10s and with Mr. Cho in there with maybe a big Ace, I cant beat 2 hands. Well, Blair had pocket 10s and Mr. Cho also had Jacks! Blair hit her set on the flop and takes down the entire pot. I guess I made the right move in the long run, but it was sick. I should have known at this time my good hands just weren't going to hold up.

Small blind special bust : So I have 56 in the small blind and everyone limps in. The flop is 347, rainbow, I just flopped the nuts! I bet $8 into the $8 pot. I get 2 callers. The turn is a 5 and I bet $20 to see where Im at. Ed calls and a new guy re-raises to $60. I call $40 more. The river is a King and I check and Ed checks. The guy bets $100. I hope he only has a 6 for a chop and I call. He says, "the nuts..," shows 68 and I lose about $170. The moral to the story is to protect your hand dont let those gut shots, draw out on you, even if you happen to flop the nuts!

I am down to around $70 and add-on for $100. I get pocket Jacks again and raise to $20. Nicole calls and the flop is 689. I bet out $35 and she calls. The turn is an 8, Nicole checks and I bet $50. The river is an Ace and also makes the flush. Nicole pushes me all-in and I fold. She shows 78, she hit trip 888s on me.

Busting out: I have only $47 left. I look down at pocket 88s and call a $7 raise. Someone bumps to $40 and we get 4 callers, so I call. The flop is 457 and Nicole bets out $50. I call with my over pair and remaining $7. Nicole shows 57 and I go home a loser for the night....

Saturday, October 31, 2009

In the Big Apple


In the New York City this weekend. While I grew up in the Rochester area of New York State, I never been to the Big Apple (it's about a 6hr drive from the folks...) NYC city truly lives up to its reputation. It is the most densely populated city in the United States. People are everywhere and the buildings are built one after another with no space in between. The number of people walking around in the streets is amazing. You just have to wonder where they all came from and where they are going to.

I am staying in New Jersey, just off Manhattan Island. I take a bus under the Lincoln Tunnel and get dropped off at the Port Authority. From there you can walk around to many of the popular sites or take a subway ride to anywhere you like.

I spent my first day checking out the tourist areas around Times Square and the Empire State building. In the evening, I found a poker game in midtown Manhattan one block away from the Empire State building. I found the game on K9poker.com it is run by a Korean guy named Jay.

We played a bit shorthanded (5-6 players). The guys playing were all gamblers and very loose. I managed to win about $70 for about 4hrs of play and ended up being the only player to win, besides maybe house.



The house had a few strange rules for there Poker game. First they required anyone leaving to announce at least one hour ahead of time. Also, they had a rule which I wasn't to sure about. Basically it said "No tight players.." and they reminded me of this rule a number of times. They seem to be kidding, but I'm not sure. Well, I played my normal game and that is "tight is right!"

Bad Beat or Stacked Deck?: I was wondering about there 1st rule and being the suspicious guy that I am, I was looking out for funny business. The host of the game, Jay, proceeded to dump about $500 within the first 2 hours and he picked seat#1. Then in one hand he got all his money back. The hand seem very odd to me. Jay basically flopped a set and turned a boat. The odd part was that the two other players were also in it had huge hands. One guy had a nut flush and the other guy hit top trips.

This kind of setup does happen and it has happen to me, but generally not with 3 people in the hand. Two weeks ago I hit a a full house with someone hitting trips, but never with someone else also hitting a nut flush. I am thinking that maybe it was a stacked deck? Here is the hands and the board. Do you think it was a setup? or just bad luck for the two players?







Free Broadway Shows music | Cell phone ringtones at EZ-Tracks.com

Sunday, October 25, 2009

A $1K month!


This month I just hit over $1000 in winnings. Its been 7 months since I did that and that was during my trip to Michigan where they forgot how I played. I have only had 2 other months where I was able to make over $1000 in one month. My average winnings per month, over the last 13 months is $718/month!

I decided to play Saturday night. Normally, if I make my $200/night goal on Friday night, I skip Saturday, but I just felt like playing. I am going to NYC this weekend, so I needed a little extra cash and I wont be playing this weekend. It is also expensive in the Big Apple, so some extra cash would be good.

Saturday night did not disappoint. I started taking down some small pots and slowly built up my stack. I only bought in for $150, thinking I didn't want to lose any more then that. My first big had was A♦A. I raise to $35 and everyone folds, except Nicole. The flop is J♥10 5. Nicole checks and I push all in for $120. Nicole thinks for a while and finally calls. She shows like 86. I look for a moment trying to see what I need to dodge and it's runner runner straight draw? Anyways, she does not hit anything and I take it down. Maybe she thought he had a flush draw?

I patiently wait for my next hand which comes about 1 hour later. I have pocket rockets again, AA! I haven't seen Aces in at least the last 2 sessions, so I knew I was over due. The table is really lose and I am in early position. Nicole calls a straddle for $5, so I raise to $40. German is right next to me and folds pocket 10s, almost with no hesitation. Mike, A.K.A. "Well Dressed," ponders his move. Mike has been gambling all night and looks like he wants to make a move. He finally pushes all-in $251 and says, "he wants to see Anthony gamble!.." Everyone else folds and I look at him, and say, "you really want to mess with me?" It's hard for me to gamble when I hold the nuts! If you are playing cards with me, then you are gambling... I call and show my Aces. Mike has AK suited... The board is all rags, 9 high, and I take down the $500 pot!

This all happens within about 3 hrs and now my stack is over $700. This is way better then average for me. I continue to play some and donk off a few chips. I finally leave a bit past midnight, cashing out $640.


Saturday, October 24, 2009

Along Comes the Good with the Bad.

It was another solid night of poker for me.  This time I finally hit some hands and hit some big pots.  Last week my biggest starting hand was pocket 99s.  This session I hit plenty of pocket pairs, but none of my big pairs made much money or held up, in the beginning.  I wasn't hitting any sets for 5 hours.  Then finally they came.  But along with the big hands, comes the bad beats....

My first set of 77 got me paid with a board of 107Q, the turn was another Queen and river a 3.  The other guy had AQ and just smooth called all my bets to the river, he was afraid that I had what I had and he was right.  To bad he just couldn't fold it..  

This put him on tilt and he wanted to make his money back from me.  I took another $200 from him when I had pocket QQ and he called me down to the river again.  It was a rag flop and he was on some kind of straight draw.  

Finally he cracked me when I hit a set of 99s.  The flop was 79J. Nicole bets $12 on the flop.  I re-raise to $25.  Mevlin and button guy smooth call.  The turn is 3.  Nicole goes all in for $53 so I just smooth call.  Melvin calls and the dealer pushes all-in for $211 more.  I put him on the straight, but have to call.  Melvin folds and the river is an 8, no paired board.  The button guy shows the nuts 10-8...

At that point I still had close to $500 in front of me.  I didn't realize it, but I had my stack up to over $700.  When the rush comes, sometimes you forget how you got there..  I continue to play some and win some of my losses back.  I finally leave cashing out $575 for the session.


Wednesday, October 21, 2009

Recipe for Disaster: The Formula That Killed Wall Street


A year ago, it was hardly unthinkable that a math wizard like David X. Li might someday earn a Nobel Prize. After all, financial economists—even Wall Street quants—have received the Nobel in economics before, and Li's work on measuring risk has had more impact, more quickly, than previous Nobel Prize-winning contributions to the field. Today, though, as dazed bankers, politicians, regulators, and investors survey the wreckage of the biggest financial meltdown since the Great Depression, Li is probably thankful he still has a job in finance at all. Not that his achievement should be dismissed. He took a notoriously tough nut—determining correlation, or how seemingly disparate events are related—and cracked it wide open with a simple and elegant mathematical formula, one that would become ubiquitous in finance worldwide.

For five years, Li's formula, known as a Gaussian copula function, looked like an unambiguously positive breakthrough, a piece of financial technology that allowed hugely complex risks to be modeled with more ease and accuracy than ever before. With his brilliant spark of mathematical legerdemain, Li made it possible for traders to sell vast quantities of new securities, expanding financial markets to unimaginable levels.

His method was adopted by everybody from bond investors and Wall Street banks to ratings agencies and regulators. And it became so deeply entrenched—and was making people so much money—that warnings about its limitations were largely ignored.

Then the model fell apart. Cracks started appearing early on, when financial markets began behaving in ways that users of Li's formula hadn't expected. The cracks became full-fledged canyons in 2008—when ruptures in the financial system's foundation swallowed up trillions of dollars and put the survival of the global banking system in serious peril.

David X. Li, it's safe to say, won't be getting that Nobel anytime soon. One result of the collapse has been the end of financial economics as something to be celebrated rather than feared. And Li's Gaussian copula formula will go down in history as instrumental in causing the unfathomable losses that brought the world financial system to its knees.

How could one formula pack such a devastating punch? The answer lies in the bond market, the multitrillion-dollar system that allows pension funds, insurance companies, and hedge funds to lend trillions of dollars to companies, countries, and home buyers.

A bond, of course, is just an IOU, a promise to pay back money with interest by certain dates. If a company—say, IBM—borrows money by issuing a bond, investors will look very closely over its accounts to make sure it has the wherewithal to repay them. The higher the perceived risk—and there's always some risk—the higher the interest rate the bond must carry.

Bond investors are very comfortable with the concept of probability. If there's a 1 percent chance of default but they get an extra two percentage points in interest, they're ahead of the game overall—like a casino, which is happy to lose big sums every so often in return for profits most of the time.

Bond investors also invest in pools of hundreds or even thousands of mortgages. The potential sums involved are staggering: Americans now owe more than $11 trillion on their homes. But mortgage pools are messier than most bonds. There's no guaranteed interest rate, since the amount of money homeowners collectively pay back every month is a function of how many have refinanced and how many have defaulted. There's certainly no fixed maturity date: Money shows up in irregular chunks as people pay down their mortgages at unpredictable times—for instance, when they decide to sell their house. And most problematic, there's no easy way to assign a single probability to the chance of default.

Wall Street solved many of these problems through a process called tranching, which divides a pool and allows for the creation of safe bonds with a risk-free triple-A credit rating. Investors in the first tranche, or slice, are first in line to be paid off. Those next in line might get only a double-A credit rating on their tranche of bonds but will be able to charge a higher interest rate for bearing the slightly higher chance of default. And so on.

The reason that ratings agencies and investors felt so safe with the triple-A tranches was that they believed there was no way hundreds of homeowners would all default on their loans at the same time. One person might lose his job, another might fall ill. But those are individual calamities that don't affect the mortgage pool much as a whole: Everybody else is still making their payments on time.

But not all calamities are individual, and tranching still hadn't solved all the problems of mortgage-pool risk. Some things, like falling house prices, affect a large number of people at once. If home values in your neighborhood decline and you lose some of your equity, there's a good chance your neighbors will lose theirs as well. If, as a result, you default on your mortgage, there's a higher probability they will default, too. That's called correlation—the degree to which one variable moves in line with another—and measuring it is an important part of determining how risky mortgage bonds are.

Investors like risk, as long as they can price it. What they hate is uncertainty—not knowing how big the risk is. As a result, bond investors and mortgage lenders desperately want to be able to measure, model, and price correlation. Before quantitative models came along, the only time investors were comfortable putting their money in mortgage pools was when there was no risk whatsoever—in other words, when the bonds were guaranteed implicitly by the federal government through Fannie Mae or Freddie Mac.

Yet during the '90s, as global markets expanded, there were trillions of new dollars waiting to be put to use lending to borrowers around the world—not just mortgage seekers but also corporations and car buyers and anybody running a balance on their credit card—if only investors could put a number on the correlations between them. The problem is excruciatingly hard, especially when you're talking about thousands of moving parts. Whoever solved it would earn the eternal gratitude of Wall Street and quite possibly the attention of the Nobel committee as well.

To understand the mathematics of correlation better, consider something simple, like a kid in an elementary school: Let's call her Alice. The probability that her parents will get divorced this year is about 5 percent, the risk of her getting head lice is about 5 percent, the chance of her seeing a teacher slip on a banana peel is about 5 percent, and the likelihood of her winning the class spelling bee is about 5 percent. If investors were trading securities based on the chances of those things happening only to Alice, they would all trade at more or less the same price.

But something important happens when we start looking at two kids rather than one—not just Alice but also the girl she sits next to, Britney. If Britney's parents get divorced, what are the chances that Alice's parents will get divorced, too? Still about 5 percent: The correlation there is close to zero. But if Britney gets head lice, the chance that Alice will get head lice is much higher, about 50 percent—which means the correlation is probably up in the 0.5 range. If Britney sees a teacher slip on a banana peel, what is the chance that Alice will see it, too? Very high indeed, since they sit next to each other: It could be as much as 95 percent, which means the correlation is close to 1. And if Britney wins the class spelling bee, the chance of Alice winning it is zero, which means the correlation is negative: -1.

If investors were trading securities based on the chances of these things happening to both Alice andBritney, the prices would be all over the place, because the correlations vary so much.

But it's a very inexact science. Just measuring those initial 5 percent probabilities involves collecting lots of disparate data points and subjecting them to all manner of statistical and error analysis. Trying to assess the conditional probabilities—the chance that Alice will get head lice if Britney gets head lice—is an order of magnitude harder, since those data points are much rarer. As a result of the scarcity of historical data, the errors there are likely to be much greater.

In the world of mortgages, it's harder still. What is the chance that any given home will decline in value? You can look at the past history of housing prices to give you an idea, but surely the nation's macroeconomic situation also plays an important role. And what is the chance that if a home in one state falls in value, a similar home in another state will fall in value as well?

Enter Li, a star mathematician who grew up in rural China in the 1960s. He excelled in school and eventually got a master's degree in economics from Nankai University before leaving the country to get an MBA from Laval University in Quebec. That was followed by two more degrees: a master's in actuarial science and a PhD in statistics, both from Ontario's University of Waterloo. In 1997 he landed at Canadian Imperial Bank of Commerce, where his financial career began in earnest; he later moved to Barclays Capital and by 2004 was charged with rebuilding its quantitative analytics team.

Li's trajectory is typical of the quant era, which began in the mid-1980s. Academia could never compete with the enormous salaries that banks and hedge funds were offering. At the same time, legions of math and physics PhDs were required to create, price, and arbitrage Wall Street's ever more complex investment structures.

In 2000, while working at JPMorgan Chase, Li published a paper in The Journal of Fixed Incometitled "On Default Correlation: A Copula Function Approach." (In statistics, a copula is used to couple the behavior of two or more variables.) Using some relatively simple math—by Wall Street standards, anyway—Li came up with an ingenious way to model default correlation without even looking at historical default data. Instead, he used market data about the prices of instruments known as credit default swaps.

If you're an investor, you have a choice these days: You can either lend directly to borrowers or sell investors credit default swaps, insurance against those same borrowers defaulting. Either way, you get a regular income stream—interest payments or insurance payments—and either way, if the borrower defaults, you lose a lot of money. The returns on both strategies are nearly identical, but because an unlimited number of credit default swaps can be sold against each borrower, the supply of swaps isn't constrained the way the supply of bonds is, so the CDS market managed to grow extremely rapidly. Though credit default swaps were relatively new when Li's paper came out, they soon became a bigger and more liquid market than the bonds on which they were based.

When the price of a credit default swap goes up, that indicates that default risk has risen. Li's breakthrough was that instead of waiting to assemble enough historical data about actual defaults, which are rare in the real world, he used historical prices from the CDS market. It's hard to build a historical model to predict Alice's or Britney's behavior, but anybody could see whether the price of credit default swaps on Britney tended to move in the same direction as that on Alice. If it did, then there was a strong correlation between Alice's and Britney's default risks, as priced by the market. Li wrote a model that used price rather than real-world default data as a shortcut (making an implicit assumption that financial markets in general, and CDS markets in particular, can price default risk correctly).

It was a brilliant simplification of an intractable problem. And Li didn't just radically dumb down the difficulty of working out correlations; he decided not to even bother trying to map and calculate all the nearly infinite relationships between the various loans that made up a pool. What happens when the number of pool members increases or when you mix negative correlations with positive ones? Never mind all that, he said. The only thing that matters is the final correlation number—one clean, simple, all-sufficient figure that sums up everything.

The effect on the securitization market was electric. Armed with Li's formula, Wall Street's quants saw a new world of possibilities. And the first thing they did was start creating a huge number of brand-new triple-A securities. Using Li's copula approach meant that ratings agencies like Moody's—or anybody wanting to model the risk of a tranche—no longer needed to puzzle over the underlying securities. All they needed was that correlation number, and out would come a rating telling them how safe or risky the tranche was.

As a result, just about anything could be bundled and turned into a triple-A bond—corporate bonds, bank loans, mortgage-backed securities, whatever you liked. The consequent pools were often known as collateralized debt obligations, or CDOs. You could tranche that pool and create a triple-A security even if none of the components were themselves triple-A. You could even take lower-rated tranches of other CDOs, put them in a pool, and tranche them—an instrument known as a CDO-squared, which at that point was so far removed from any actual underlying bond or loan or mortgage that no one really had a clue what it included. But it didn't matter. All you needed was Li's copula function.

The CDS and CDO markets grew together, feeding on each other. At the end of 2001, there was $920 billion in credit default swaps outstanding. By the end of 2007, that number had skyrocketed to more than $62 trillion. The CDO market, which stood at $275 billion in 2000, grew to $4.7 trillion by 2006.

At the heart of it all was Li's formula. When you talk to market participants, they use words likebeautiful, simple, and, most commonly, tractable. It could be applied anywhere, for anything, and was quickly adopted not only by banks packaging new bonds but also by traders and hedge funds dreaming up complex trades between those bonds.

"The corporate CDO world relied almost exclusively on this copula-based correlation model," saysDarrell Duffie, a Stanford University finance professor who served on Moody's Academic Advisory Research Committee. The Gaussian copula soon became such a universally accepted part of the world's financial vocabulary that brokers started quoting prices for bond tranches based on their correlations. "Correlation trading has spread through the psyche of the financial markets like a highly infectious thought virus," wrote derivatives guru Janet Tavakoli in 2006.

The damage was foreseeable and, in fact, foreseen. In 1998, before Li had even invented his copula function, Paul Wilmott wrote that "the correlations between financial quantities are notoriously unstable." Wilmott, a quantitative-finance consultant and lecturer, argued that no theory should be built on such unpredictable parameters. And he wasn't alone. During the boom years, everybody could reel off reasons why the Gaussian copula function wasn't perfect. Li's approach made no allowance for unpredictability: It assumed that correlation was a constant rather than something mercurial. Investment banks would regularly phone Stanford's Duffie and ask him to come in and talk to them about exactly what Li's copula was. Every time, he would warn them that it was not suitable for use in risk management or valuation.

In hindsight, ignoring those warnings looks foolhardy. But at the time, it was easy. Banks dismissed them, partly because the managers empowered to apply the brakes didn't understand the arguments between various arms of the quant universe. Besides, they were making too much money to stop.

In finance, you can never reduce risk outright; you can only try to set up a market in which people who don't want risk sell it to those who do. But in the CDO market, people used the Gaussian copula model to convince themselves they didn't have any risk at all, when in fact they just didn't have any risk 99 percent of the time. The other 1 percent of the time they blew up. Those explosions may have been rare, but they could destroy all previous gains, and then some.

Li's copula function was used to price hundreds of billions of dollars' worth of CDOs filled with mortgages. And because the copula function used CDS prices to calculate correlation, it was forced to confine itself to looking at the period of time when those credit default swaps had been in existence: less than a decade, a period when house prices soared. Naturally, default correlations were very low in those years. But when the mortgage boom ended abruptly and home values started falling across the country, correlations soared.

Bankers securitizing mortgages knew that their models were highly sensitive to house-price appreciation. If it ever turned negative on a national scale, a lot of bonds that had been rated triple-A, or risk-free, by copula-powered computer models would blow up. But no one was willing to stop the creation of CDOs, and the big investment banks happily kept on building more, drawing their correlation data from a period when real estate only went up.

"Everyone was pinning their hopes on house prices continuing to rise," says Kai Gilkes of the credit research firm CreditSights, who spent 10 years working at ratings agencies. "When they stopped rising, pretty much everyone was caught on the wrong side, because the sensitivity to house prices was huge. And there was just no getting around it. Why didn't rating agencies build in some cushion for this sensitivity to a house-price-depreciation scenario? Because if they had, they would have never rated a single mortgage-backed CDO."

Bankers should have noted that very small changes in their underlying assumptions could result in very large changes in the correlation number. They also should have noticed that the results they were seeing were much less volatile than they should have been—which implied that the risk was being moved elsewhere. Where had the risk gone?

They didn't know, or didn't ask. One reason was that the outputs came from "black box" computer models and were hard to subject to a commonsense smell test. Another was that the quants, who should have been more aware of the copula's weaknesses, weren't the ones making the big asset-allocation decisions. Their managers, who made the actual calls, lacked the math skills to understand what the models were doing or how they worked. They could, however, understand something as simple as a single correlation number. That was the problem.

"The relationship between two assets can never be captured by a single scalar quantity," Wilmott says. For instance, consider the share prices of two sneaker manufacturers: When the market for sneakers is growing, both companies do well and the correlation between them is high. But when one company gets a lot of celebrity endorsements and starts stealing market share from the other, the stock prices diverge and the correlation between them turns negative. And when the nation morphs into a land of flip-flop-wearing couch potatoes, both companies decline and the correlation becomes positive again. It's impossible to sum up such a history in one correlation number, but CDOs were invariably sold on the premise that correlation was more of a constant than a variable.

No one knew all of this better than David X. Li: "Very few people understand the essence of the model," he told The Wall Street Journal way back in fall 2005.

"Li can't be blamed," says Gilkes of CreditSights. After all, he just invented the model. Instead, we should blame the bankers who misinterpreted it. And even then, the real danger was created not because any given trader adopted it but because every trader did. In financial markets, everybody doing the same thing is the classic recipe for a bubble and inevitable bust.

Nassim Nicholas Taleb, hedge fund manager and author of The Black Swan, is particularly harsh when it comes to the copula. "People got very excited about the Gaussian copula because of its mathematical elegance, but the thing never worked," he says. "Co-association between securities is not measurable using correlation," because past history can never prepare you for that one day when everything goes south. "Anything that relies on correlation is charlatanism."

Li has been notably absent from the current debate over the causes of the crash. In fact, he is no longer even in the US. Last year, he moved to Beijing to head up the risk-management department of China International Capital Corporation. In a recent conversation, he seemed reluctant to discuss his paper and said he couldn't talk without permission from the PR department. In response to a subsequent request, CICC's press office sent an email saying that Li was no longer doing the kind of work he did in his previous job and, therefore, would not be speaking to the media.

In the world of finance, too many quants see only the numbers before them and forget about the concrete reality the figures are supposed to represent. They think they can model just a few years' worth of data and come up with probabilities for things that may happen only once every 10,000 years. Then people invest on the basis of those probabilities, without stopping to wonder whether the numbers make any sense at all.

As Li himself said of his own model: "The most dangerous part is when people believe everything coming out of it."

Here's what killed your 401(k) David X. Li's Gaussian copula function as first published in 2000. Investors exploited it as a quick—and fatally flawed—way to assess risk. A shorter version appears on this month's cover of Wired.

Probability

Specifically, this is a joint default probability—the likelihood that any two members of the pool (A and B) will both default. It's what investors are looking for, and the rest of the formula provides the answer.

Survival times

The amount of time between now and when A and B can be expected to default. Li took the idea from a concept in actuarial science that charts what happens to someone's life expectancy when their spouse dies.

Equality

A dangerously precise concept, since it leaves no room for error. Clean equations help both quants and their managers forget that the real world contains a surprising amount of uncertainty, fuzziness, and precariousness.

Copula

This couples (hence the Latinate term copula) the individual probabilities associated with A and B to come up with a single number. Errors here massively increase the risk of the whole equation blowing up.

Distribution functions

The probabilities of how long A and B are likely to survive. Since these are not certainties, they can be dangerous: Small miscalculations may leave you facing much more risk than the formula indicates.

Gamma

The all-powerful correlation parameter, which reduces correlation to a single constant—something that should be highly improbable, if not impossible. This is the magic number that made Li's copula function irresistible.

Felix Salmon (felix@felixsalmon.com) writes the Market Movers financial blog at Portfolio.com.