Bloomberg TV @ 22:00ish, MNL

Janney analyst Guy Lebas on fixed income after B of A tops expectations:

• Monthly home price declines are fluctuating between 1 to half a percent level - this MAY be a good sign.
• Inflation and growth - short end of the YC is growth-sensitive, and long end is sensitive to inflation and inflation expectations. We are seeing a steepening YC.
• Optimistic on short end - inflation is a problem for longer-term bonds. Buy 2-5 years.
• In a quiet release week, what do we look out for? It’s all about the consumer. Look at retail sales figures (ICSC-UBS store sales numbers coming out tomorrow, 22 July 2008, 19:45, MNL).

In other news…

• Paulson: the downturn may continue for some time.
• Business economists surveyed are less pessimistic about the economy for 2H08 than in 1H08.
• Leading Economic Indicators (LEI) are down another month in a row at -0.1%.

An hour with our friends on Bloomberg TV tonight.

22:00ish, MNL

Early in US trading, equities started diving on what looks like a more broad-based selling in financials. GM looking precarious at the deep end.

The nail-biters today? Ben’s speaking, Dubya’s speaking, Hank’s speaking and Chris is speaking. Lots of words to be thrown around within the next few hours.

The IMF (fairly) recently published a brief on Globalization here, which identifies several general principles that “seem to underpin greater prosperity”. These include the following:

• Investment (particularly foreign direct investment);
• The spread of technology;
• Strong institutions;
• Sound macroeconomic policies;
• An educated workforce; and
• Participation in, and integration with, the global economy.

The paper also discusses the implications of more integrated financial markets, citing two main findings of a recent IMF paper on the subject:

1. Countries must do a careful cost-benefit analysis (CBA) before they fully liberalize capital flows; and
2. There are costs associated with being too conservative on opening capital flows.

The policy lesson to be drawn then is that capital account liberalization “should be pursued as part of a broader reform package encompassing a country’s macroeconomic policy framework, domestic financial system, and prudential regulation”.

Big News today (an hour fresh) - US consumer confidence took a spill in June, dropping to 50.4 (well below the consensus 56.5 and lower than May’s 57.2). The news came just as the market digested a record house price tumble in April of 15.3% in 20 of the largest US cities. This has sent the dollar in a tailspin against the majors (even vs. the bearish cable - for now). Oil and gold futures did a distinct Saturday Night Fever move, pointing up in morning trading as dollar hedgers ran for shelter. US stocks fell - they were also buffeted by a cut in UPS earnings forecasts reported yesterday, as well as a continuing upward journey for oil prices.

Equity markets across the globe commiserated with the dollar and US equities on concerns about US consumption expenditure, which accounts for about 70 % of the world’s largest economy’s… economy (Is this right? Calculated from here). The US continues to reign as the export destination champion of the world.

What has the US in store for the rest of the week? The world awaits the FOMC announcement due out on Wednesday the 25th of June (2:15pm, EST - that means 2:15am on the 26th for Manila). The Fed is expected to keep its Funds Rate at 2.00%, but to say hawkish things. Tricky situation as growth hangs in the balance - US durable goods orders for June, as well as May new home sales are also on tap for Wednesday (8:30 and 10:00 EST, respectively - that means opposite time of day for Manila).

On the personal ramble, I’m a little bit frustrated with the Bloomberg website and its frequency of updates. The Reuters website I’ve seen so far are too corp-y (though I haven’t really explored things there just yet). Am also frustrated with the Forex.com charts - but it’s the best I can do now on a Java-based system (not into downloading anything just yet). Good news feeds, though. But confusing calendar. Spoiled by Reuters systems.

Bits

• The European Union has completed its migration from a decentralized payments system to a single shared platform for real-time settlement of large euro payments, TARGET2 ( Trans-European Automated Real-time Gross settlement Express Transfer system). This system harmonizes fund and securities transfers in the EU, reduces settlement risk and lowers transaction costs.
• Moody’s Investor Service accidentally assigned constant proportion debt obligations (CPDOs), papers with high coupons and high ratings, triple-AAA ratings - up to four notches higher than warranted.  They discovered the glitch in early 2007.
• UBS took pressure off its balance sheets by lending Blackrock 75 percent of US$ 15 billion so that the US asset manager could buy distressed assets from the Swiss bank. Doing so effectively took subprime mortgage risk off the bank’s books and replaced it with debt exposure to Blackrock.
• Mitsubishi UFJ Financial Group (MUFG), a Japanese megabank, announced on Tuesday losses of 81 billion yen on subprime-related exposures. Japan’s second-largest bank, Mizuho Financial, reported subprime-related losses of 645 billion yen.
• Vietnam has widened the trading band of the dong from up or down 1 percent to plus or minus 2 percent. Before the increase in March to 1 percent, the dong was trading in a band of plus or minus 0.75 percent.

Pieces

An individual securities trader should mind where the Big Money’s going. He should also:

• Mind supply and demand
• Use volume to identify accumulation and distribution
• Use stop orders to limit losses (5%, 10% loss, what have you)

 A Recipe to Grow Quickly?

A recent report published by the World Bank cites five characteristics in countries that have shown exceptionally high growth for an extended period of time. They are:

• Full exploitation of the world economy (importing good ideas and technology; producing exports that others want)
• Macroeconomic stability
• High rates of saving and investment
• Letting the market allocate resources
• Committed, credible, capable governments

There are ten demonstrable examples of disciplined trading according to Dr. Alexander Elder. A disciplined trader does the following:

1. Keeps accurate records
2. Demonstrates, with only minor and short losses, positive performance greater than 25% return per year
3. Develops a unique trading plan based on his or her own personal techniques
4. Never shares information or listens to advice from others
5. Learns as much as possible about his or her chosen market
6. Constantly grades his or her own adherence to a chosen trading plan
7. Devotes as much time to the markets as possible every trading day
8. Monitors the chosen markets every day even if he or she is not actively trading
9. learns new ideas to improve trading methods, but thoroughly tests them before putting them to work
10. Follows his or her set of rules as though life depended on them.

This is a summary of the ten points outlined in his book, Come into My Trading Room (2002).

United States - Economy at a Glance (BLS)

• GDP Growth (annual and quarterly, %) - US Bureau of Economic Analysis [.xls]
• Inflation (annual, %) - US Bureau of Labor Statistics
• Unemployment (seasonally adjusted, %) - US Bureau of Labor Statistics

 

European Union - Principal European Economic Indicators (Eurostat)

• GDP Growth - Eurostat
• Inflation - Eurostat
• Unemployment - Eurostat (here for longer time series)

Japan - Financial and Economic Statistics Monthly (BOJ)

• GDP Growth - Cabinet Office Japan
• Inflation - Bureau of Statistics, Ministry of Internal Affairs and Communications Japan
• Unemployment - Bureau of Statistics, Ministry of Internal Affairs and Communications Japan

Two tools for extracting trend and cycle components from time-series data are:

• The Hodrick-Prescott filter, which extracts the TREND component from time-series data and leaves the CYCLE, SEASONAL and IRREGULAR components behind
• The Baxter-King method, which extracts the CYCLE component from time-series data and leaves the TREND, SEASONAL and IRREGULAR components behind

For the HP filter, values of lambda depend on the frequency of the data: the more frequent, the higher the lambda:

1. Annual: 100
2. Quarterly: 1600
3. Monthly: 14400

Both methods use centered moving averages (CMAs), so the values at the very beginning and very end of the extracted series will not mean much. The Baxter-King method cuts 3 years’ worth of data from the beginning and end of the extracted series.

A time series is a collection of values over time. You can analyze time series data using two approaches:

1. Time-domain approach: Data occurs discretely at equally-spaced time intervals.
2. Frequency-domain approach: Data is continuous - this uses sine and cosine somehow.

Some non-standard features of time-series data are:

1. Unequally spaced data (missing values)
2. Continuous-time series
3. Aggregation

(!) When you aggregate data, it does not behave in the same way as the original data set!

Time series may be considered to be composed of unobserved components. Statisticians try to decompose time series into their constituent parts through the unobserved components method (UC method).

Time-series data comprises four components:

1. Trend, y(T): Slow variation over the period of years caused by structural factors
2. Cyclical, y(C): Quasi-periodic fluctuation characterized by alternating periods of expansion and contraction
3. Seasonal, y(S): Effect of climactic and institutional events that repeat more or less regularly each year
4. Irregular, y(I): Unforseeable movements related to various events. These can be well-behaved or be extreme values (outliers).

Trend, cyclical and seasonal effects are signals, while irregular effects are noise. Sometimes, trend and cyclical effects cannot be separated, so they are considered one component, y(TC).

Seaonality may be caused by:

1. Calendar effects: Dates of national holidays
2. Institutional factors: Tax periods, bonuses, dividends
3. Weather or climate
4. Expectations

Seasonal adjustment: The isolation of seasonal fluctuations

This is done in a 3-step process:

1. Identification: Test for the presence of seasonality
2. Estimation: Measure the magnitude of seasonal effects
3. Removal: Extraction of seasonal variations from the series

The result is a seasonally adjusted, or deseasonalized series.

The reasons for seasonal adjustment are:

1. To facilitate the interpretation of data without significant loss of information
2. To use seasonally adjusted series in models.

“Seasonal adjustment is done to simplify data so that they may be more easily interpreted by statistically unsophisticated users without a significant loss of information.” (Bell and Hellmer, 1992)

NB: For non-seasonally adjusted data that exhibit seasonality, rates of growth should be compared year-on-year.

From Newly Corporate, 19 Places to Learn Online for Free.