Sunday, July 6, 2008

Financial intelligence makes you wealthy

Chennai: Does money make you rich? The answer is ‘No,’ declares Robert T. Kiyosaki in ‘Increase Your Financial IQ’ (www.landmarkonthenet.com). He bemoans how millions of people go to work every day, work for money, make more money, but fail to become richer.

Rather than the asset, it is the information relative to the asset that ultimately makes a person rich or poor, Kiyosaki decodes. “It is not the real estate, stocks, mutual funds, businesses, or money that makes a person rich. It is information, knowledge, wisdom, and know-how, a.k.a. financial intelligence, that makes one wealthy.”

To explain this, he narrates an example, about a friend who, as a golfing fanatic, spends thousands of dollars a year on new clubs and every new golf gadget that comes to market. “The problem is, he will not spend a dime on golf lessons. Hence his golf game remains the same, even though he has the latest and greatest in golf equipment,” Kiyosaki writes. “If he invested his money in golf lessons and used last year’s clubs, he might be a much better golfer.”

The same nutty phenomenon occurs in the game of money, he frets. “Billions of people invest their hard-earned money in assets such as stocks and real estate, but invest almost nothing in information. Hence their financial scores remain about the same.”

A compulsory read you need to invest in.

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Academic incursion

For a long time, the transparency and integrity of American financial markets have served as magnets attracting global financial flows. Alas, much of that trust has now been squandered and will be even more sorely tested in the years ahead, rues Charles R. Morris in ‘The Trillion Dollar Meltdown’ (www.publicaffairsbooks.com).

“To restore credibility, American officials and financial leaders must forthrightly admit the scale of the problem and proceed to purge the absurd valuations, the phony triple-A ratings, the inflated balance sheets, and the hidden liabilities that are marbled through financial balance sheets,” reads the prescription. The cost of not doing so can be far greater than a one-time trillion-dollar asset writedown, he cautions.

A chapter titled ‘bubble land’ recounts that, before the dotcom bust, the decade from the late 1980s to the late 1990s saw three other boom-and-bust cycles. “There was a big crash in residential mortgages in 1994 and two big trading-based crises – the 1987 stock market crash and the 1998 Long-Term Capital Management crisis.”

All three episodes, says Morris, arose from fundamentally new investment technologies, enabled by breakthroughs in desk-top computing and by an influx of mathematics PhDs to Wall Street.

“The new ‘quants’ could carve up and reassemble old-fashioned asset classes so they were custom-fit to investor needs. Large-volume computerised trading could exploit tiny changes in stock prices or interest rates. Very broad new classes of complex, structured investment instruments revolutionised wholesale banking.”

Eerily, though, all the new technologies and strategies harboured dangerous flaws that tended to reveal themselves only at points of great stress, the author observes. He is of the view that bigger, better, even more far-reaching versions of these strategies have now, in 2008, placed the entire global economy at risk.

Alarming addition to the shelves of the finance avid.

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Mastering modelling

With organisations now holding more data and requiring simple analysis tools at lower levels, spreadsheet techniques have to be a core managerial skill, says Alastair L. Day in ‘Mastering Financial Modelling in Microsoft Excel’ (www.pearsoned.co.in).

Stating that financial modelling can be applied to a multitude of tasks, ranging from simple sheets to add up expenses to sophisticated risk assessment for projects, Day tries to bridge the gap between academic inputs (that usually provide little guidance in applying Excel to finance problems), and the typical software books (that show how to insert a chart or format a cell but provide little guidance on model development).

“By constructing models, managers should understand better: how individual variables ‘flex’; how to discover new variables which should be included in the calculations; how to isolate key variables for further testing; and how to avoid costly mistakes by testing scenarios and potential cases.”

Recommended for a hands-on study.

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