It's always good to have a hindsight view right?? Also do note that investments will go up and down. It is impossible/close to impossible to not be having a loss when the whole market is going down. Note also that GIC is investing for the long term and not day/short term.

Yeah right. When it goes up, it's all due to their great vision and we have to pay them lots of monies and everyone has to bow low to them for their wonderful leadership. When it goes down, well, investment goes up and down and they invest for the long term and so we still have to pay them lots of monies and bow low for their wonderful leadership. Heads they win tails you lose.

It's amazing the kind of shit that Singaporeans will swallow so long as it's from their PAP government. If Bernie Madoff tried his scam in Singapore, not only will he not ever be exposed, the fools here will probably be so grateful to him and make him Minister Mentor and his son the Prime Minister and let his company rule the country.

MR LEE AND THE CONFLICT OF INTEREST

Monday, 16 February 2009
Singapore Democrats

Mr Lee Kuan Yew's appointments as an international advisor to corporations such as JP Morgan, Total, DaimlerChrysler (now defunct) and Citigroup have gone largely unnoticed by most in Singapore, until now that is. Especially noteworthy for obvious reasons is Mr Lee's role in Citigroup. On 5 Sep 06, the American banking giant purred:

“Minister Mentor Lee is a modern-day visionary and a unique statesman who is respected world-wide, and it is a privilege for Citigroup to benefit from his understanding, insights and experience. I am honored that Minister Mentor Lee has chosen to be a special advisor to Citigroup and look forward to having the opportunity to work closely with him as we pursue our international growth strategy.”

Few Singaporeans really cared when the announcement was made. How can anyone take issue with such an accolade especially one coming from the world's biggest bank? In fact, then DPM Lee Hsien Loong lauded his father's appointment in Parliament in 2000 when he pointed out that Lee Sr's roles in these corporations would help to promote Singapore globally.

Mr Lee holds the position of Minister Mentor now as he did in 2006 when he was appointed Citi's advisor. This much is clear. What is ambiguous is whether Mr Lee holds the Citi portfolio in his official capacity as Minister Mentor representing Singapore or whether he does so in his personal capacity as a citizen, albeit a prominent one.

There is no mention of Mr Lee's role in Citi in his profile shown in the Singapore Government's website which leads one to think that these extra-ministerial appointments are a private matter.

But Citi's 2006 press release (and JP Morgan's website) trumpets the fact that Mr Lee is the Minister Mentor of the Republic of Singapore and makes no qualifications that he is serving in a private capacity.

The ambiguity raises the following questions as naturally and necessarily as the day follows night:

* Does Mr Lee receive remuneration or compensation monetarily or otherwise from these positions that he holds? If so, how much? Does Mr Lee get to keep the income?
* In return, what is expected of Mr Lee in terms of the time he spends attending to the business of these corporations?
* What kinds of information is expected from Mr Lee as an advisor and what sort is provided? Is the cabinet fully informed of the discussions that Mr Lee is involved in with these companies?
* Do our ministers also hold such appointments in companies, foreign or domestic? If yes, which ones and in what capacities? If no, why not, since MM Lee does?

What is more disturbing, if that's actually possible, is that these questions have never been asked of the PAP Government in any meaningful manner. Ministers, MPs, state journalists, etc have this uncanny ability to not notice the hyperactive, rainbow-coloured gorilla jumping up and down, screaming and poking them in the eyes right in the middle of the living room.

Maybe the reticence is because it didn't cross anyone's mind that there is actually something called conflict of interest. Be that as it may, that was then and this is now. The now is when we learn that in January 2008 the GIC, chaired by Mr Lee, had poured into Citigroup S$10 billion of our funds.

It transpired that GIC made the investment after it received an “invitation” from Citi to invest in its equity. GIC dove in because, according to its deputy chairman Dr Tony Tan (who, by the way also controls all the Singaporean newspapers as chairman of the SPH), it was “well within the risk limits which we had prescribed for the finance sector.”

Not only were the risks reasonable, Dr Tan assessed, Citi was a "sound bank..temporarily facing significant problems. But their franchises are strong".

Nine months after Dr Tan made the endorsement Citigroup announced that it was on the verge of bankruptcy and needed bail-out money from the US Government. It received US$25 billion – the biggest bailout in history. In November, it came back for more and got another US$20 billion. The bank was staring into the abyss with a potential loss of US$306 billion in toxic assets.

If the US Government had not stepped in, and there is every possibility that the bailout could still fail, Citi would have collapsed and our $10 billion would be no more. (If it's any comfort, our money spread much good cheer among the many millionaire executives of the bank.)

How can a sound bank with strong franchises collapse in just nine months? Did everyone at GIC skip class the day the teacher went through the chapter on Citi's troubles?

More important, did Citi seek its special advisor's advice before it approached the GIC for funds? If it did, what was the advise given? When the GIC received the invitation from Citi, what went into the decision to go ahead with the investment? Did Mr Lee's position in one organisation affect the decision made in the other?

The conflict of interest is too jarring to even contemplate.

Now consider this: When former Senator Hillary Clinton's name was put up for the post of US Secretary of State, there were concerns that she could be influenced by big donors who gave to her husband's presidential foundation. As a result former president Bill Clinton suspended day-to-day responsibilities at the foundation, revealed the identities of all his donors and the amounts they gave, and promised to clear future donations with the White House. And he's not even the one holding office.

But, of course, this is Singapore. Conflict of interest is defined a little different here.

Incredible as it may seem the GIC still refuses to explain its decisions or open up its books for scrutiny or even tell Singaporeans how much it has lost in its investments. Obviously, the Government is a little shy about revealing such information. The question is: Should the people be shy about demanding it?

GIC is a large cooperation operating billions of dollars, naturally, there must be confidentially so that it's operation strategy is not exposed to competitors.

Point is how to safe guard our CPF money from lost and who is monitoring it? Is it a group or just some employee making financial decisions?

The standard of singapore medical clinics is very good now. But of course everyone is entitled to their own opinion.

Here is an interesting take on the global financial meltdown:
http://video.google.com/videoplay?docid=6076118677860424204
Sounds more credible than any of those explanations given so far by the big boys.

The nation’s largest banks are so close to collapse and the world economy is coming unglued so rapidly, a major Wall Street meltdown is now imminent.

Specifically, it’s now increasingly likely that virtually all of our forecasts of recent months could come to pass in a very short period of time, including …

* Stock market crash: A swift plunge in stocks to about 5000 on the Dow, 500 on the S&P 500 and 900 on the Nasdaq … or lower. (For our reasons, see “Stocks to fall AT LEAST another 40%!“)

* Corporate bankruptcies: A chain reaction of Chapter 11 filings or federal takeovers, including not only General Motors and Chrysler, but also Ann Taylor, Best Buy, Jet Blue, Macy’s, Saks Fifth Avenue, Sears, Toys “R” Us, U.S. Airways and even giants like Ford or General Electric.

* Megabank failures: Bankruptcies or nationalization not only of Citigroup and Bank of America, but also JPMorgan Chase and HSBC. (See my January issue, “Megabanks Could Fail Despite Federal Aid.”)

* Nationwide epidemic of small and medium-sized bank failures: Outright FDIC takeovers, with little prospect of nationalization. (I’ll give you a link to our free guide with a more extensive list in a moment.)

* Insurance failures: State takeovers of companies like Ambac Assurance, Bankers Life and Casualty, Conseco, FGIC, Medical Liability Mutual, Mortgage Guaranty Insurance, Nuclear Electric Insurance, PMI Mortgage, Standard Life of Indiana and many others. (Our free guide also contains a more extensive list of insurers.)

* Cities and states: An epidemic of defaults by thousands of cities, states and other issuers of tax-exempt municipal bonds.

* Stock market shutdowns: Trading halts on major, big-cap stocks … plus on-again, off-again exchange shutdowns, making it increasingly difficult for investors to liquidate their holdings at any price.

* Credit market deep freeze: A virtual shutdown in all debt markets except U.S. Treasuries. An avalanche of selling — and virtually no buyers — for corporate bonds, commercial paper, asset-backed securities, municipal bonds and all forms of bank loans.

* Government bond collapse: A steep decline in the price of medium-and long-term government securities, as the U.S. Treasury bids aggressively for scarce funds to finance a ballooning budget deficit.

Shocking? Perhaps. Avoidable? No.

Nor am I alone in anticipating this rapid unraveling of the economy and financial markets. This past Friday, at a Columbia University dinner reported by Reuters …

* George Soros said the financial system has effectively disintegrated, with the turbulence more severe than during the Great Depression and with the decline comparable to the fall of the Soviet Union, while …

* Paul Volcker said he could not remember any time, even in the Great Depression, when things went down so fast and quite so uniformly around the world.

Both recognize that we’re in a new era of chaos. What’s the landmark event that separates us from the past era of relative stability?

According to Soros, it’s precisely the same event we forecast in 2007 and the same event we have repeatedly highlighted here in Money and Markets: The bankruptcy of Lehman Brothers. (See “Dangerously Close to a Money Panic,” December 3, 2007 and “Closer to a Financial Meltdown,” March 17, 2008.)

That was the final straw that punctured the already imploding bubble. And it was the first major domino that set off the chain reaction of events now careening out of control: The collapse of consumer credit markets … surging unemployment … and now, a new set of even larger financial failures looming.

The Raging Debate Right Now Is How To Prevent
A Banking Collapse: To Nationalize Or Not To
Nationalize. But It’s A Moot Point.

Based on the analysis we presented here in August 2008 (”The Next Big Failures“) …

Based on the frank recognition of the catastrophe by Soros and Volcker on Friday …

And based on the trillions in government bailout funds already spent, lent or guaranteed (”The Obama Stimulus: Truth and Consequences“) …

The fact is that the banking collapse has already occurred!

So the relevant question is not “How can we prevent it?” Instead, it’s “How can you protect yourself from the inevitable fallout?”

Washington and Wall Street, however, are either too cowered or too confused to give you the answers you need.

They won’t tell you which banks are the most likely to fail or which ones are the most likely to survive.

They won’t offer you alternative safe havens for your money.

They won’t even guide you to publicly available information provided by the U.S. Treasury Department itself.

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 Income titled "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 like beautiful, 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," says Darrell 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."