### bully pulpit

On George W. Bush: *He does not take the bully pulpit and use it effectively.
But when the chips are down, he does the right thing.*

James C. Dobson, Focus on the Family.

« November 2004 | Main | January 2005 »

On George W. Bush: *He does not take the bully pulpit and use it effectively.
But when the chips are down, he does the right thing.*

James C. Dobson, Focus on the Family.

Probably the biggest eye-catcher is iShares FTSE/Xinhua China 25

Index Fund (FXI) — the first ETF investing solely in China

available to U.S. investors. Launched earlier this month,

the ETF tracks the 25 largest and most liquid Chinese stocks.

Of course, there's increasing talk of China's red-hot economy

cooling, but few expect the growth spigot to be shut entirely.

The China 25 Index Fund's expense ratio of 0.74% is higher

than that of most ETFs, but it's substantially lower than the

average China-region mutual fund's expense ratio of 2.37%,

according to Lipper. ETFs, by nature, carry lower expense ratios

than their mutual-fund counterparts. [1]

Standard and Poors index tracker.

Vanguard REIT Vipers VNQ 0.18% 6,200 Vanguard Industrials Vipers VIS 0.28% 1,100 Vanguard Energy Vipers VDE 0.28% 400 Vanguard Telecommunication Services Vipers VOX 0.28% 100 SPDR O-Strip ETF OOO 0.36% 92,000 Vanguard Small-Cap Vipers VB 0.18% 6,400 Vanguard Small-Cap Growth Vipers VBK 0.22% 52,200 Vanguard Consumer Discretionary Vipers VCR 0.28% 1,900 Vanguard Financials Vipers VFH 0.28% 2,400 Vanguard Mid-Cap Vipers VO 0.18% 1,100 Vanguard Health Care Vipers VHT 0.28% 13,400 Vanguard Information Technology Vipers VGT 0.28% 3,800 Vanguard Utilities Vipers VPU 0.28% 2,700 Vanguard Large-Cap Vipers VV 0.12% 13,500 Vanguard Small-Cap Value Vipers VBR 0.22% 9,400 Vanguard Materials Vipers VAW 0.28% 5,300 Vanguard Consumer Staples Vipers VDC 0.28% 200 Vanguard Growth Vipers VUG 0.15% 292,100 Vanguard Value Vipers VTV 0.15% 471,200 iShares S&P 1500 Index Fund ISI 0.20% 26,600 iShares FTSE/Xinhua China 25 Index Fund FXI 0.74% 158,400 iShares Morningstar Large Core Index Fund JKD 0.20% 3,400 iShares Morningstar Large Growth Index Fund JKE 0.25% 11,900 iShares Morningstar Large Value Index Fund JKF 0.25% 1,200 iShares Morningstar Mid Core Index Fund JKG 0.25% 2,300 iShares Morningstar Mid Growth Index Fund JKH 0.30% 4,000 iShares Morningstar Mid Value Index Fund JKI 0.30% 3,900 iShares Morningstar Small Core Index Fund JKJ 0.25% 1,900 iShares Morningstar Small Growth Index Fund JKK 0.30% 1,500 iShares Morningstar Small Value Index Fund JKL 0.30% 2,200 iShares NYSE 100 Index Fund NY 0.20% 5,200 iShares NYSE Composite Index Fund NYC 0.25% 1,000

Harris Yong's (snow driving) and car and tire reviews.

Pics index, and Dragon drive review, and cupholder movie.

Rick Aster's SAS info aka *programming secrets*:

Professional SAS Programming Shortcuts and Professional SAS Programming Logic.

FX FXStreet Foreign Exchange Currency news on trading and trends.

The VIX takes the weighted average of implied volatility for the

Standard and Poor's 100 Index (OEX calls and puts) and measures the

volatility of the market. A low VIX indicates trader confidence. A

high Vix the opposite. Dividing the S&P 500 by the Vix (ratio) gives

the confidence level in relation to the market. The higher the ratio

the higher the confidence.

VIX, the ticker symbol for the Chicago Board Options Exchange (CBOE)

Volatility Index and represents the implied volatility on the S&P 100

(OEX) option. This volatility is meant to be forward looking and is

calculated from both calls and puts that are near-the-money. The VIX

is a popular and widely used measure of market risk.

Investopedia says,

Introduced by the CBOE in 1993, VIX is a weighted measure of the

volatility for eight OEX put and call options. The eight puts and

calls are weighted according to the time remaining and the degree to

which they are in- or out-of-the-money. The result forms a composite

hypothetical option that is at-the-money and has 30 days to

expiration. VIX represents the implied volatility for this

hypothetical at-the-money OEX option. Typically, VIX has an inverse

relationship to the market, which means that a rising stock market is

viewed as less risky and a declining stock market more risky. The

higher the perceived risk is in stocks, the higher the implied

volatility and the more expensive the associated options, especially

puts. Hence, implied volatility is not about the size of the price

swings, but rather the implied risk associated with the stock market.

When the market declines, the demand for puts usually increases.

Increased demand means higher put prices and higher implied

volatilities.

SAS Proc Tabulate FAQ [ucla]

with a few axamples.

Use SAS to generate nice looking statistical report documents.

Excel (XLS) file

ods html file = "c:\temp\data.xls";

proc print data =new;run;

ods html close;

Web(HTML) file

ods html file = "body.html";

proc print data =new;run;

ods html close;

More at SAS ODS intro [PDF]

comp.soft-sys.sas SAS newsgroup at googlegroups.

Hands on statistical computing howto.

Weblogsinc's SAS blog is more about business than statistics.

Update: 2006 Dec 01:This SAS Weblog is no loger active, but archives are on line.

Demoted to blogroll4.

Update 2005 Jan 15: Welcome Weblogsinc SAS blog readers.

There are more Coruscation SAS blog items.

Overlawyered chronicles the excesses of litigation, lawsuits,

and regulation. By Walter Olson, intellectual guru of tort reform,

and Ted Frank.

The ethics sections includes an even handed look at pro bono work.

Good to know, even if you don't need a lawyer.

How much do you need to know to pass the CFA ? Here is some

advice for Chartered Financial Analyst aspirants.

They do not mean - **have a general idea or sense of the material**

or **be able to pick the concept out of a lineup based on your
initial impression or cued recall**.

They do mean **Very quickly, relative to similar concepts and
formulas, distingush and differentiate the key concepts, recall
the special exceptions or impacts that the concept had on other
concepts, be able to calculate forward and back into or out of
the relevant formula, and finally (the test taking part) be able
to quickly pick out the imbedded error or limiting factor in each
the accompanying 'wrong' answers among the choices presented so
that you can pick that which is least or most likely to conform
to the issue or question presented.**

See also CFA, FRM communities.

[via analystforum]

Listen live to CBC Radio One Vancouver.

MedCalc has good list of basic statisitical features.

# Stepwise Multiple regression

# Stepwise Logistic regression

# Paired and unpaired t-tests

# Rank sum tests: Wilcoxon test (paired data), Mann-Whitney U test (unpaired data)

# Variance ratio test (F-test)

# One-way analysis of variance (ANOVA) with Student-Newman-Keuls (SNK) test for pairwise comparison of subgroups

# Two-way analysis of variance

# Kruskal-Wallis test

# Frequencies table, crosstabulation analysis, Chi-square test, Chi-square test for trend

# Tests on 2x2 tables: Fisher's exact test, McNemar test

# Frequencies bar charts

# Kaplan-Meier survival curve, logrank test for comparison of survival curves, hazard ratio, logrank test for trend

# Cox proportional-hazards regression

# Meta-analysis: odds ratio (random effects or fixed effects model - Mantel-Heinszel method); summary effects for continuous outcomes; Forest plot

# Reference interval (normal range)

# Analysis of Serial measurements with group comparison

# Bland & Altman plot for method comparison (bias plot) - repeatability

Sage advice from the avuncular Donald Rumsfeld:

"Intellectual capital is the least fungible kind."

"Most people spend their time on the 'urgent'

rather than on the 'important.' "

"When you initiate new activities, find things you

are currently doing that you can discontinue--whether

reports, activities, etc. It works, but you must force

yourself to do it. Always keep in mind your

'teeth-to-tail ratio'."

See also Jack Welsh's five questions for leaders.

Post exam gossip is taken to a new level when people around the

world share a common exam, and share it on web forums. Let the

CFA candidates second guess until exam results are posted.

Re: Odds of passing FRM with 7 days of studying Author: mustill Date: Tuesday, November 16 @ 8:07 pm

Hi folks!

This is summarized from some of the questions posted by Student and

other fellow 2003 candidates on the FRM 2003 exam. I do not warrant

the accuracy of these questions as posted. Maybe those who passed 2003

exam may want to provide some inputs?

(a) Which option is very interest path dependent?

Candidates speculated between barrier and binary option.

(b) Which option has an unlimited upside?

Candidates guessed Asian option.

(c) Is it appropriate to sell deep in the money put option?

(d) Geometric Brownian Motion. Which is normally and lognormally

distributed?

(i) S

(ii) ds

(iii) ds/s

(e) If you have a stock and options position with delta neutral and

positive gamma, how do you hedge it?

(f) Company A with netting agreement with Company B. A owes B $1m

after netting. Without netting agreement with Company B, B owes A

$10m. What is A's exposure to B?

(g) Candidates said there is a question on calculating tracking

error.

(h) A company files for bankruptcy. Which bonds trade at higher

price? Bond with higher or lower coupon? Assuming duration is not the

same but same seniority and term. I

(i) Which bond has a "reasonably strong ability" to pay?

The 2 main choices are AA and A.

(j) Say a fund is managed by 2 person only. Which of the following

matter most? Assuming no asset.

(i) Asset under management

(ii) Risk control/ system reporting system

(iii) Investment style

(k) Which of the following is not a derivative?

(i) CBOE weather derivative

(ii) REITS

(l) Firm A has economic capital in addition to regulatory capital

while firm B does not have economic capital. Is A as good as B?

(m) I think there is a question posted by candidates on a Price yield

curve for a callable

bond asking candidate to mark out where convexity is 0.

(n) There is a question asking candidates on SPAN ( Std Portfolio

Analysis Network)?

(o) Which one has more time value premium?

(i)ATM call

(ii) Out of the money call

(iii) ITM call

(p) If Y=ln(x). If Y is normally distributed with mean of 0, what is

the mean of X?

I guess if most of you can answer the above questions, I am sure you

would have no problem this Saturday.

All the best. Remember to have a break after the exam. I am sure most

of you are fellow CFA candidates who are in Level 3 or had just passed

the Level 3 exam. All of you deserve a break after 2 major exams in a

year.

Christmas is coming. HAve fun!

From analystforum.

See also CFA mastery.

More USA-Canada maps from the post-election era.

.

from Canada is an ally in the War on Terror.

from BluePrint magazine.

Hedgefund.net has hedgefund news. See also

Hedge-Fund Manager vs Investment Bankers in the

New York Wiki and Hedge Week.

Dominant Score Cutoff Strategies

The purpose of this research is to develop new results for

(1) the equivalence of statistical, business and economic

dominance in risk scoring,

(2) dominant risk scoring strategies in the presence of

non-dominant scores, and

(3) the effect of Bayesian score combination on dominant

risk scoring strategies.

One can show that there is ROC dominance if and only if there

is dominance of expected profits or efficient frontiers that

involve different business measures such as profit/volume

tradeoffs. If there is no such dominance, an intersection of

the ROC curves for two different scores nevertheless yields

a dominant strategy for use of the different scorecards and

the cutoffs. Finally, we show that a Bayesian combination of

the two scores leads to a dominant ROC curve with a single

dominant strategy.

*.

SAS tip: How do I obtain percentiles not automatically calculated?

proc univariate data=hsb noprint;

var write;

output out=percentiles1 pctlpts=33 45 80 to 90 by 2 pctlpre=P;

run;

proc print data=percentiles1;run;

Nodular sclerosing Hodgkin's disease, a lymphoma chronicles the

diagnosis and treatments of this cancer.

Kevin Drum is Political Animal, the in-house blogger of

The Washington Monthly and something of a clearinghouse

for smart liberals.

Update Dec 2008: Moved to Mother Jones. as Kevin Drum.

Salford CART allows one to choose from several ways of combining

separate CART trees into a single predictive engine. The

trees are combined by either averaging their outputs for

regression or by using an unweighted plurality voting scheme

for classification. The current version of CART offers two

combination methods: Bootstrap aggregation and ARCing. Each

generates a set of trees by resampling (with replacement)

from the original training data.

The sports economist by Skip Sauer covers stadium economics,

player-league bargaining, and more.

S-PLUS Predictive Modeling and Computational Finance

event with abstracts.

Nov 2004 Finance Event Proceedings for LossCalc II: Dynamic Prediction of LGD.

Greg Gupton, Moody's KMV

We describe LossCalc(tm) version 2.0, the Moody's KMV model to predict

loss given default (LGD). LGD is of natural interest to lenders and

investors wishing to estimate future credit losses. LossCalc is a

robust and validated model of LGD for loans and bonds globally.

LossCalc is a statistical model that incorporates information at all levels:

collateral, instrument, firm, industry, country, and the macroeconomy

to predict LGD. Also, and what may be more interesting than merely

having a powerful predictive model, is to see and understand the

underlying drivers of default recovery/loss that we show.

Predictive Modeling for Property & Casualty Pricing Decisions

Jeremy Stanley, Ernst & Young

This presentation focuses on the application of predictive modeling

methodologies to pricing decisions for property & casualty insurance

lines. Predicting the probability of an insured having one or more

claims in a policy period is a key ingredient to determining the price

a carrier will charge. This presentation will compare and contrast

three types of models applied to this problem: generalized linear

models (GLMs), generalized additive models (GAMs) and neural networks.

GAMs allow for non-linearity in the additive terms and limited types

of specified interactions, requiring an intensive modeling effort to

determine the appropriate model structure. GAMs benefit from fast

model fitting performance, robust measures of in-sample error (such as

the Akaike Information Criterion) and can be easily translated into a

multiplicative rating plan. Neural networks, through the control of

the number of optimization iterations, the size of the hidden layer,

and the use of a weight decay parameter, allow for the near-automatic

selection of model architecture, simultaneously encompassing

interaction terms and complex non-linearities. The predictions of

neural networks are difficult to visualize in high dimensions or with

more than two continuous factors, and are not easily translated into a

multiplicative rating plan. Model performance will be compared in

S-PLUS via cross-validation and bootstrap methods, and visualized with

the use of ROC curves and lift charts. Model structure will be

visualized with S-PLUS Trellis Plots, leading to insights that can

improve the selected model structure.

Microsoft's MSN Spaces allow users to create personal Web logs.

Check out Mightily Redacted.

PROC CAPABILITY is a component of SAS/QC (Quality Control). The

features described below are now available in PROC UNIVARIATE (part of base SAS).

# Histograms and comparative histograms. Optionally, these can be

superimposed with fitted probability density curves for various

distributions and kernel density estimates.

# Cumulative distribution function plots (cdf plots). Optionally,

these can be superimposed with specification limits and probability

distribution curves for various distributions.

# Quantile-quantile plots (Q-Q plots), probability plots, and

probability-probability plots (P-P plots). These plots facilitate the

comparison of a data distribution with various theoretical

distributions.

# Goodness-of-fit tests for a variety of distributions including the

normal.

# Statistical intervals (prediction, tolerance, and confidence

intervals) for a normal population.

# The ability to inset summary statistics and capability indices in

plots produced on a graphics device.

Paul Dickman has some good SAS tips for statistical programming

and handling datasets and simple graphics.

Economy Professor provides a glossary of some well known terms, theories, and economists.