Diamond Cables To Issue Bonus Shares

Diamond Cables Ltd has informed BSE that a meeting of the Board of Directors of the Company will be held on March 06, 2009, inter alia, to consider the issue of the Bonus Shares.

US Current financial crisis vs. Japan's 1990's crisis

US Current Financial Crisis versus Japan's 1990s Crisis

 

While explaining his Financial Stability Plan, president Obama pointed to the dangerous consequences of not acting in a timely manner giving what happened in Japan in the 1990s, "where they did not act boldly and swiftly enough, and as a consequence they suffered what was called the "lost decade" where essentially for the entire '90s they did not see any significant economic growth." Treasury Secretary Tim Geithner also pointed that the current Plan is guided by the lessons of financial crisis throughout history mentioning that Japan crisis in the 90s lasted longer and caused greater damage because government applied the brakes too early, and the US current Administration cannot make that mistake.

 

The comparison between the current crisis and Japan's 90s crisis is fairly true in terms of the origins as both were initiated by wide spreading of reckless lending on the assumption that real estate prices would continue to go up, while it sharply reversed down triggering the financial market turmoil. Also the Japanese authorities took a long time until 1998 to begin cleaning up and recapitalizing its banking sector's assets.

 

However, a major difference in the initiation of the crises is that in Japan, corporate borrowing soared before the burst against the collateral of rising shares and commercial property prices, while in the US crisis, residential debt that much of the complicated mixture of debt products originated from has been the cause of the problem. Cleaning the balance sheet of the corporate sector is much easier than cleaning the balance sheet of the household sector, that's beside the difficulty of justifying using taxpayers money to bail out homeowners who bought mortgages they could not afford. Actually, not only the origin of debt is different, but also the size of debt. In Japan, the size of debt during the crisis reached 52% of the GDP (10% of the GDP for household), while it reached 294% of the GDP in US, almost 100% of the GDP belongs to the household sector. Additionally, the size of banks' holdings of troubled assets (in absolute terms), reached to $910 billion in Japan, or 35% of the GDP, while it amounted in US to $5.7 trillion or 40% of the GDP (according to Goldman Sacks estimates). The US banks forced to write down securitized products promptly due to mark-to-market accounting, while Japanese banks in 90s were allowed to take time to dispose their nonperforming loans since their lending assets were largely not tradable. The IMF recently estimated the size of write downs in US by $2.2 trillion.

 

Finally, as much as the nature of the economy is different (though macroeconomic indicators are not) between US and Japan in terms of debt and saving ratios, the scope of the crisis creates different implications. Japan's 90's crisis was an internal one, and through exports Japan could pass the economic recession as global demand remained solid. The current crisis started in US but spread globally, demand for good and services and capital availability thinned worldwide, which needs demand to be motivated from inside US. The US started earlier in its efforts to overcome the crisis. The last $787 billion Financial Stability Plan takes most of the above facts into account, it allocates large sums to boost demand through government expenditures, and it allocates other part of the fund to clean the balance sheet of the banking sector. It also attempts to improve the affordability of mortgages by providing access to low-cost   refinancing and provide incentives for loan modification for mortgages already owned or guaranteed by Freddie Mac or Fannie Mae. The majority of subprime mortgages were not of this type, thus, the most in need mortgage debtors do not qualify.

Why u must invest in gold now?

For centuries gold has been the ultimate cushion.

 

A way to safeguard your investments against the dangers of stocks price falls, fluctuating rate changes, inflation, rising/falling real estate prices, natural calamities, wars and more.

 

If ever there was a more testing time for gold to prove its mettle, it is now: during a global recession.

 

The million dollar question today is: will gold retain its sheen in the year 2009, the year of reckoning? Nearly everyone has been breaking their heads trying to figure out the safest investment avenue this year.

 

In India the stock markets are low, interest rates have come down and elections are round the corner. Is gold the obvious investment destination in such a scenario?

 

What moves gold prices

Let us first try and understand the factors affecting gold prices before we decide whether we should invest in it.

 

Tightening of gold supply

Gold mining is decreasing and the demand for gold is increasing. Gold supply has decreased by almost 40 per cent as the cost of mining, legal formalities and geographical problems have increased which has led to a fall in gold mining. Economics have taught us that lesser the supply, greater the demand and in turn greater the increase in price.

 

Inflation and interest rates

Gold has always been considered a good hedge against inflation. Rising inflation rates typically appreciates gold prices. It has an inverse relationship with interest rates. As gold is pegged to the US dollar, US interest rates affect gold prices. Whenever interest rates fall, gold prices increase. Lowering interest rates increases gold prices as gold becomes a better investment option vis-à-vis debt products that earn lower interest. Gold loses its shine in a rising interest rate scenario.

 

Currency fluctuation

As gold is pegged to the US dollar, it has an inverse relationship with the dollar. Right now with US being in great financial turmoil, the dollar has weakened against many other currencies. Dollar is expected to weaken further and prices of gold are expected to rise further. Dollar is a de-facto currency of exchange around the world. But now with US on the brink of depression, gold is substituted as a safe haven for investments. Though dollar seems to be getting stronger, it may be a temporary effect and very soon it can head southwards once again, in turn making gold an attractive and safe investment.

 

Geo-political concerns

Whenever there is geo-political strife, investors around the world rush to prevent erosion of their investments and gold as a safe haven attracts one and all. For example after 9/11 terror strike in the United States the demand for gold had increased. With the recent events like tension between India-Pakistan, Israeli strikes over Gaza, the ongoing war in Iraq, the tension between US and Iran coupled with recession have investors scrambling for gold.

 

Central bank demand

With the dollar losing its value, central banks of most of the developed countries have started to increase their share of gold. This explains the increasing market demand for gold.

 

Weakness in financial markets

General rule of thumb in the market is that gold is always attractive when all other investments are unattractive. Why is this? As gold is negatively co-related to stocks, bonds, and real estate, gold is considered to be a safe haven and hence during any crises, investors would like to sell off what they would term as risky investments and be invest the funds in gold.

 

Why you should invest in gold

You might be wondering why gold is termed as safe haven. Gold is the most liquid asset in the world. If you wish to sell a gold bar or gold coin of 99.9 purity or 99.5 purity anywhere in the world, you will get its due worth without the risk attached to other investments like exchange rate risk.

While investing in gold the first question you must ask yourself is whether you should buy at these levels or wait for a while for the prices to come down even further?

 

As for the future of gold in 2009 and further to come 2009 may see gold touching $1,000 or more an ounce and then again settling in the range of $800 to $900 as banks from around the world would sell their gold stocks once it ouches $1,000. But gold will stay bullish till the time the current financial crisis prevails.

 

Financial crisis or no financial crisis, investing 5 percent of your portfolio in gold is always advisable. Gold is a good form of investment for diversification. Remember one thing, just like any other investments; space out your investments in gold. Do not buy at one go; be it gold bars, gold coins, or units on gold exchange traded funds (ETFs). Invest regularly and diligently.

 

Jewellery or gold bars?

Here are a few options that an investor in gold can consider.

 

Jewellery

As an investment avenue, gold jewellery is a BIG NO. Investing in jewellery is not investment as jewellery is generally not made from 24 carat gold; it is generally made from 22 carat or 18 carat gold since 24-carat gold is brittle and cannot be set to beautiful designs of jewellery as being brittle it can break easily.

 

The main drawback here is that you have to pay for the making charges. If and when you want to liquidate the money invested in jewellery, your making charges are cut and you end up getting less than what you had invested.

 

Gold bars or coins

YES.

Investment in gold should be either in gold coins or bars. Remember to buy government-certified gold coins or bars and preferably the purity level should be 99.9 as they are easy to sell. Also, be sure of the place from where you are buying the coins. But preferably from banks.

 

Gold exchange traded funds

This is the latest buzz. It is like buying gold but in indirect form. You invest money in a gold fund, which in turn invests your money in the physical form of gold. These funds are open during the new fund offer and for buying or selling them they are listed on the stock exchanges.

 

When you want to redeem the units, you can go to the fund house and get them converted to either physical gold bars or cash. This form of investment is good for people who have storage problem like no bank lockers and also for spacing out your investment in gold. This way you can take advantage of gold price volatility.

 

Also, wealth tax does not come into picture if you invest through ETFs.

 

There are other forms of investments in gold like derivatives, spread betting, certificates and others. But for retail investors gold ETFs or physical gold bars and coins are the best forms of investment.

 

The only drawback of investing in gold is that it is a sterile investment: it neither pays any dividend nor interest.

Danske Bank: This Looks Like A Meltdown

Market update

. it looks like a meltdown

 

Overnight the sell-off in Central and Eastern European markets accelerated further after Moody

.s announced that it may downgrade Swedish and Austrian banks with exposure to Central and Eastern Europe. This move will further exacerbate concerns over the state of CEE economies and markets.

 

The region

.s large imbalances and significant currency mismatch has long been a problem for us and there is no doubt that the CEE countries can expect a very sharp drop in economic activity. Despite already depreciating substantially, we see no reason why the sell-off of CEE currencies should cease soon absent substantial intervention from the EU and/or the ECB to support markets.

 

We think it unlikely that local authorities will be able to muster sufficient resources to curb the sell-off in CEE currencies in the present environment. To us this looks like a market meltdown on the same scale as occurred during the Asian crisis of 1997. No currency in the region will be unaffected by this.

 

Doubtless the markets have decided that the CEE region is the subprime area of Europe and now everybody is running for the door. In addition, it is not just regional currencies that are under pressure. Stock markets are also being sold off with yields and rates beginning to rise significantly. Furthermore, Credit Default Swaps have risen dramatically across the region during the last couple of weeks.

 

Macro economic implications

. sharp drop in GDP in all CEE countries

 

Continuing aggressive

.deleveraging. of CEE economies due to Western European banks tightening their credit policies in the region and the serious outflow of capital from it effectively represents a .sudden stop. to the funding of large current account deficits in the area.

 

Foreign direct investment in the region is also likely to plummet.

 

The reversal of both portfolio flows and FDI will undoubtedly have a serious negative impact on regional investments. Furthermore, with many households and corporations highly exposed to FX loans (especially in Swiss francs) debt servicing costs are rising dramatically. This is likely to have a substantial negative effect on private consumption, especially in Poland, Hungary and Romania.

 

In our view GDP growth is like to be negative in

all CEE countries this year. In those countries .least. affected by the crisis (i.e. Poland, the Czech Republic, Slovakia and Slovenia) GDP is like to drop at least 2-5%, while those countries worst affected (i.e. the Baltic States, Bulgaria, Romania and Ukraine) are likely to face double digit declines in GDP. In other words, in terms of expected output lost in the region this is as bad as or even worse than the Asian crisis of 1997-98.

LIC ups stake in ICICI Bank to 9.38% - Business Line

LIC ups stake in ICICI Bank to 9.38% - Business Line

http://www.thehindubusinessline.com/businessline/blnus/05241260.htm

 

MUMBAI: Life Insurance Corporation of India has hiked its stake to 9.38 per cent in the country's largest private sector lender, ICICI Bank, after purchasing shares worth Rs 145.62 crore through open market transaction.

In a disclosure on the Bombay Stock Exchange, ICICI Bank said LIC has purchased over 2.27 crore shares for Rs 145.62 crore, representing 2.04 per cent stake. Before the purchase, LIC held 7.34 per cent stake, while now it has over 10.44 crore shares repr esenting 9.38 per cent stake in the bank.

Shares of ICICI Bank were trading at Rs 232.90, down 3.59 per cent on the BSE on Tuesday. - PTI

Recipe for Disaster: The Formula That Killed Wall Street

Recipe for Disaster: The Formula That Killed Wall Street

By Felix Salmon

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 and Britney, 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 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."

Pension funds must go to Nifty-50 stocks: Panel

The Economic Times - Pension funds must go to Nifty-50 stocks: Panel
18 Feb 2009, 0730 hrs IST, TNN

http://economictimes.indiatimes.com/articleshow/4147011.cms?prtpage=1

NEW DELHI: The expert committee constituted by the Pension Fund Regulatory and Development Authority (PFRDA) on Tuesday recommended three investment choices for subscribers of the New Pension System (NPS), while seeking to invest through a standardised Nifty-50 stock portfolio. The NPS is to be launched from April 1.

The committee, chaired by HDFC chief Deepak Parekh, handed over its report to PFRDA chairman D Swarup. The pension fund regulator had earlier shortlisted six fund managers in addition to LIC, SBI and UTI, who will have the mandate to invest upto 50% of an individual's pension fund in equities.

The Nifty-50 stocks would include almost all the top 50 stocks of the BSE, Parekh said, while giving details of the fund investment guidelines. The committee has mooted a thirdparty evaluation of the equities and other investment instruments to be opted by fund managers . The three different investment options under E, G and C category range from highrisk equities to low risk central government securities and a moderate return option under corporate and state government bonds.

Anyone can join the NPS with a proposed minimum investment of Rs 6,000 annually. The minimum investment rule is, however, yet to be formalised. The fund collection would be made using the network of 23 entities selected by PFRDA.
Swarup said the new pension fund would be used as a long-term investment instrument, and, in fact, this may create a long-term debt market for a period ranging between 15-30 years.

Taking lessons from some of the global pension funds which lost all their reserves in the meltdown, it has been proposed that risk to equities factor is reduced to a maximum of 10% towards the retirement age of an employee.At the time of superannuation, the employee receives 60% of the total amount earned through investments and the rest 40% is deposited with an insurance fund manager of the beneficiary's choice from where he receives a monthly pension.

Those who do not make a choice will be assigned auto choice where investment will be made in a life-cycle fund, that is, at the lowest entry age a subscriber's fund will be invested in pre-determined portfolio.

Time right to build well-balanced portfolio: Puneet Nanda (ICICI Prudential Life Insurance CIO)

Economic Times - Time right to build well-balanced portfolio: Puneet Nanda
24 Feb 2009, 1329 hrs IST, Shailesh Menon, ET Bureau

http://economictimes.indiatimes.com/articleshow/4182153.cms?prtpage=1

MUMBAI: "Unlike a lot of people who believe there is further downside, I don't think the market will breach the (lower) levels it reached last

October. Thanks to good liquidity, I expect buying to start in some time. I feel the Sensex would range between 8000 and 11,000 in the coming months," said ICICI Prudential Life Insurance CIO Puneet Nanda.

According to Mr Nanda, the March quarter "could be similar or worse" than the third quarter. "But all that has been factored in by the market. Lower interest rates and fallen commodity prices will catch up the economy towards the second half of current year," he added.

Mr Nanda is of the opinion that more than fourth quarter results, it will be election and global markets that will have bearing on where the Indian market is headed.

"People are clearly expecting a fractured mandate this time round. If the newly-elected government is headed by either of the two national political parties, there shouldn't be anything for India Inc. to worry about. Only a highly-fragmented coalition can scare corporate India and markets," Mr Nanda opined.

According to Mr Nanda, investors should be buying equity shares at this point of time. "Now is the time to build a well-balanced portfolio," he added.

Among sectors, Mr Nanda likes banks and financial services institutions. "Every bank today is virtually below its book value. Contrary to popular perception, almost all Indian banks are well-capitalised; their NPA ratios are at pretty comfortable levels," he said.

Mr Nanda also had good things to say about two-wheeler auto companies and four wheeler manufacturers that make entry-level cars. "Two wheelers should benefit from upbeat rural consumption story. Companies with entry-level cars are likely to do well once demand gather steam. Lower financing cost and reduced input costs coupled with fallen fuel charges will help growth in actual demand for cars and two-wheelers," added Mr Nanda.

With respect to infrastructure companies, Mr Nanda advises investors to pick companies that get government orders. "Infrastructure companies that are largely dependent on corporate capex are in trouble," warns Mr Nanda.

According to Mr Nanda, real estate, fundamentally, has a very positive outlook over the long term, say 10 to 20 years. "Clearly there is demand for real estate; the problem is too much expectation-build-up around the sector. We've not invested in real estate companies for the simple reason that they are not very transparent; we did not like their valuations as well," Mr Nanda added.

According to Mr Nanda, insurance sector has been net buyer in the equities market for quite some time now. "Insurance companies have invested (in to stocks) close to a billion dollar in January. The trend of investing into equities will continue, thanks to healthy inflows through renewal premium," he added.

Speaking of investment strategies adopted by insurance companies, Mr Nanda said: "We do not essentially go for flavours of the day. We are not investing for short-term quick returns; we're aiming at long-term out performance. We're not passive investors, but we do not punt in market either. On the fixed income side, we are risk-averse about credit risk in investments. We only invest in highly-rated securities or Government papers. This may be compromising of returns, but we're fine doing that."

AIG in talks with U.S. government, sees $60 billion loss: source

NEW YORK (Reuters) - American International Group Inc, rescued twice last year by the U.S. government, is asking for more aid and bracing for a fourth-quarter loss of roughly $60 billion, a source familiar with the matter said. It would be the biggest loss in a quarter in corporate history.

The $60 billion would exceed Time Warner's $54 billion single-quarter loss in 2002 and dwarf the $24.5 billion loss AIG posted in the third quarter, when the government increased its rescue package for the insurer to about $150 billion.

By contrast, two analysts polled by Reuters Estimates have forecast on average a net loss of $5.46 billion.

The latest round of talks with the government include the possibility of additional funds for the insurer and trading debt for equity, another source said on Monday.

The situation is fluid and other options are being discussed, this second source said, adding that it was unclear where the talks would lead.

AIG may look to convert preferred shares held by the government into common stock, Bloomberg reported, citing an unnamed source.

The discussions are going on as U.S. financial authorities try to put out other fires, as well. Citigroup Inc, whose stock has been pounded by fears that the government may seize the bank and wipe out shareholders, is also in talks to give the government a larger stake, a person familiar with the matter told Reuters.

CNBC, which first reported AIG's discussions, said the losses to be announced next Monday were due to writedowns on commercial real estate and other assets. It said the insurer's board will meet next Sunday to work out an agreement with the government.

In case they do not reach a deal, AIG's lawyers at Weil, Gotshal & Manges LLP were preparing for the possibility of bankruptcy, CNBC said.

But the first source told Reuters that while AIG has retained Weil Gotshal, the insurer has no plans to file for bankruptcy.

"Is it likely that $60 billion more of capital has been destroyed? Or is it likely that they are just accounting for that which already happened?" said Thomas Russo, a partner at Gardner, Russo & Gardner, which manages more than $2 billion. "I suspect it's more of the latter than the former."

AIG said in a statement it had not yet reported results and would provide an update when it does so in the near future.

"We continue to work with the U.S. government to evaluate potential new alternatives for addressing AIG's financial challenges," AIG said.

U.S. Treasury officials declined to comment. Weil could not be reached immediately for comment.

AIG shares closed down 1 cent at 53 cents on the New York Stock Exchange on Monday.

AIG was first rescued in September after bad mortgage bets left it on the verge of collapse. The government stepped in with $85 billion in bailout financing, as thecredit crisis peaked with Lehman Brothers Holdings Inc filing for bankruptcy and Merrill Lynch agreeing to be bought by Bank of America Corp.

The rescue swelled in November as AIG posted its then-largest ever loss, hurt by writedowns on assets linked to subprime mortgages and capital losses. The Federal Reserve and U.S. Treasury stepped in with even more money to buy mortgage assets that had left AIG deeply in the red, and eased the terms of its loan repayment.

AIG has said it plans to sell all assets except its U.S. property and casualty business, foreign general insurance, and an ownership interest in some foreign life operations, as it looks to raise money to pay back the government.

Although AIG has announced some sales, it is trying to sell assets at a time when buyers are often dealing with their own problems and credit for acquisitions is scarce. The insurer's ongoing troubles are likely making things harder.

"The seller is in a rather perilous position," Russo said. "And buyers typically appreciate the amount of leverage they have."

(Additional reporting by Chris Kaufman and Euan rocha; Editing by Richard Chang, Jeffrey Benkoe, Tim Dobbyn, Gary Hill)

http://www.reuters.com/article/newsOne/idUSTRE51M6LT20090224?pageNumber=1&virtualBrandChannel=0

DLF slashes prices in Bangalore

DLF slashes prices in Bangalore

Pooja Sarkar / DNA

DLF, the country's largest real estate player according to market capitalisation, has re-launched its Bannerghatta Road project in Bangalore with a revised price tag of Rs 2,100 per sq ft from Rs 2,775 a sq ft earlier. The specifications have changed, too. The homes will now be 1,085-1,820 sq ft in size, down from the minimum size of 1,310 sq ft planned earlier. The project was first launched in October last year and DLF sold about 50% of the total 440 flats, said an analyst report. The developer will compensate its existing customers who paid a higher price by adjusting the outstanding amount against future payments. Earlier, the cost of a 1,310-sq ft flat was Rs 36.35 lakh. Now, this cost has come down to Rs 27.51 lakh, a fall of Rs 8.84 lakh. A DLF spokesperson said, "We have launched our Bangalore project in 4 categories, where the base price ranges between Rs 1,800 and Rs 2,100 per sq ft." This relaunch comes close on the heels of DLF's Hyderabad project launch at Rs 1,850 per sq ft last month, which received a fairly good response after a dismal December quarter. JP Morgan analysts Saurabh Kumar and Gunjan Prithyani, in a February 2 report, wrote, "Mid-income housing performance was most disappointing as the company booked just 77 units in the last two months against almost 400 units per month over the last two quarters. Expected rate correction and reducing unit prices may trigger a volume recovery at the earliest by second half of FY10." Analysts, however, said developers who have already launched their projects would find it hard to compete with DLF's prices. The real estate firm's price cuts are to the extent of 40%, much more than what others are offering. This could hit competitors' sales as they are offering a minimum size of 1,445 sq ft with a base price of Rs 2,500 per sq ft. DLF's rivals in Bangalore include the Prestige group and L&T Properties. Ravi Ramu, director at another competitor Puravankara Projects Ltd, said, "We are selling projects at about Rs 2,750 per sq ft. We cannot go lower than this." Analysts warn that sticking to their pricing could cost developers volumes and hurt their topline. Sobha Developers, another major real estate player in the IT city, is offering a paltry 8% discount on its ready projects.

25-Feb-09 mcx settlement prices

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