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April 30, 2005

Techno for Credit: musie145

Update 2006 May: Electro 145 Techno class notes.

Why does relatively obscure electronic music seem to
appeal to mainstream advertisers? How does the music
communicate to an audience unaware of who the artist
style might be, or even unaware that they are listening
to music? Why would electronic music make for the
"sonic wallpaper" of choice?

Is there anything radically different between the mashup
aesthetic and previous sample-based styles? In what ways
does the mashup emerge from pre-existing practices?
What distinguishes a mashup from a remix? How do
mashups derive their affective force? Is irony a necessary
dimension of a mashup's power?


In the mid-1990s, the advent of the term electronica marked a mainstream arrival of sorts for electronic music. But long before marketing teams and MTV fastened on the concept, electronic music had become integral to musical experience in the mainstream and on the margins. From the tape-splicing and studio-craft that are now part and parcel of popular music production to the increasingly central and creative role played by DJs in the transmission and performance of music, electronic music—i.e., music produced, performed, and mediated via electronic technologies—has suffered from an absence in the public conversation at the same time that it has enjoyed a certain ubiquity.

Required Texts:

* Peter Shapiro and Iara Lee, ed. Modulations: A History of
Electronic Music
. Caipirinha Productions: 2000.

* Cox and Warner, eds. Audio Culture: Readings in Modern Music.
Continuum: 2004.

* Simon Reynolds. Generation Ecstasy: Into the World of Techno
and Rave Culture
. Routledge: 1999.

When discussion does turn to electronic music and its various
subjects, the discourse reveals a range of assumptions about
technology and musicianship, ownership and community, social change
and cultural continuity, to name a few. This course aims to illuminate
the many ways that electronic technologies have shaped popular music
production and consumption over the last fifty years, shaping selves
(and often others) in the process.

Beginning with the European and American avant-garde, this course will
trace the development of electronic music through Kingston Dub,
Chicago House, Detroit Techno, Bronx Hip-hop, British Rave, Rio Funk
and Global Trance, among others. Analysis/appreciation of musical
style and the relationship to particular technologies—aided by
creative workshops and "production projects"—will accompany an
examination of the music in its social and cultural contexts with an
attention to popular and scholarly representations. Overarching themes
will include: the dynamics of global circulation and local creation;
the production of identities—racial, ethnic, class-based,
counter-cultural, etc.—via electronic music; questions of musical
meaning/value and cultural propriety in post-colonial circumstances
(e.g., notions of authenticity, appropriation, dominance/resistance);
the phenomenological aspects of listening and dancing.

Six times over the course of the semester, using FL Studio
music-making software (or the software/hardware of one's choice) and
drawing from the lecture-demonstrations, the listening selections, and
the stylistic templates and samples provided, students will create
tracks in the musical styles we study.

Useful References:

* Ishkur.com – good overview of various substyles, with listening examples
(and rather opinionated commentary).
* JahSonic.com – lots of hyperlinks and informed commentary.
* Allmusic.com – browse by genre for overview of various styles, with links
to specific artists.

All for credit at musie145.

April 29, 2005

Decision Science News / Dan Goldstein

Decision Science News by Dan Goldstein and Kevin Flora
about the decision sciences including but not limited to Psychology,
Economics, Business, Medicine, and Law, but
mostly marketing.

Also on Wilmott.

April 28, 2005

Statistical Modeling, Causal Inference / MLM

Statistical Modeling, Causal Inference, and Social Science (MLM)
Andrew Gelman and Samantha Cook at Columbia.

Urban Review STL

Excelent Urban Review STL architrectural review of Saint Louis, MO
housing and commercial real estate.

April 27, 2005

XLISP-Stat estimates Generalised Estimating Equations

XLISP-Stat tools for building Generalised Estimating Equation models
offers an introduction to GEE models.

Much of the brain trust of XLISP Stat has moved on to r.

Generalised Estimating Equations models, proposed by Liang and Zeger
in 1986, are probably the simplest method for analysing data collected
in groups where observations within a group may be correlated but
observations in separate groups are independent. A complete
description of the method is given in their two 1986 papers. The basic
principle of the method is a generalisation of the fact that weighted
least squares analyses give unbiased parameter estimates no matter
what weights are used. Generalised linear models, such as logistic
regression, have similar robustness properties, giving asymptotically
correct parameter estimates even when the data are correlated. This
means that it is possible to estimate regression parameters using any
convenient or plausible assumptions about the true correlation between
observations and get the right answer even when the assumptions are
not correct.

It is only necessary to use a ``model-robust'' or ``agnostic''
estimate of the standard errors. It would be unreasonable to expect
this freedom of choice to be without cost and it turns out that there
is a moderate gain in efficiency resulting from choosing a working
correlation structure close to the true one.

Useful references include the two original papers (Zeger & Liang 1986,
Liang & Zeger 1986) and two recent books: Diggle, Liang & Zeger (1993)
and Fahrmeir & Tutz (1995). As far as I know the most elementary
treatment anywhere in the literature is still Zeger & Liang (1986).

Section 2 gives an overview of the theory and use of Generalised
Estimating Equations. Section 3 describes how to use the Lisp-Stat
code, including diagnostics. Finally there is a brief discussion of
missing data handling and of other software for fitting GEE models.
Appendix A describes some aspects of the implementation, including the
global variables (Table 5) that control many program options.

April 26, 2005

Residential Mortgage Termination and Severity, De Franco

Modeling Residential Mortgage Termination and Severity
Using Loan Level Data

Three essays on modeling residential mortgages.

Chapter 1 presents and estimates a new model of loss given
default using a new dataset of prime and subprime mortgages. The
model combines option theory proxies with information on the loan
contract and the cash flow position of the borrower. The results
suggest that severity on subprime and adjustable rate mortgages are
similar to losses on fixed rate prime loans, but that investor owned
properties have significantly higher losses than owner occupied
houses. The results also suggest systemic overappraisals on refinanced
loans.

Chapter 2 uses option pricing methodology to value the prepayment and
default options associated with a residential mortgage, if house
prices are mean reverting.

Numerical solutions compare the results from the mean reverting house
price model to the results from a model where house prices follow a
geometric Brownian motion process.

The main contributions are:

(1) the value of the implicit rent (service flow) is derived as a
function of the house price process instead of assumed to be constant,
as in prior research;

(2) the mean reverting model has additional factors that may help
forecast mortgage termination; and

(3) the house price process is shown to have a significant effect on
the value of a mortgage over a wide range of parameter values.

Chapter 3 presents a modeling framework for residential mortgages that
has separate models for each loan payment status (Current, 30 Days
Late, 60 Days Late, 90+ Days Late, in Foreclosure, in REO, or Paid
Off). It is shown that several classes of traditional mortgage
prepayment and default models are restricted forms of this model, and
that the restrictions are rejected empirically.

Dissertation by Ralph DeFranco (U.C. Berkeley) 1994 [PDF]

April 25, 2005

Housing after boom

Housing after the boom explained by angry bear:

Expectation is for slowly declining prices in much of the
United States and significantly lower transaction volumes
nationwide.

April 24, 2005

Option-Theoretic Prepayment Model for Mortgages: Fabozzi , Kalotay and Yang

A new approach for modeling the prepayments of a mortgage pool
shows how to value mortgage pools and agency mortgage-backed
securities. A notion of refinancing efficiency describes the
full spectrum of refinancing behavior.

The approach has two distinguishing features:

(1) The primary focus is on understanding the market value of a
mortgage, in contrast with standard models that strive (often
unsuccessfully) to predict future cash flows, and

(2) we use two separate yield curves, one for discounting mortgage
cash flows and the other for MBS cash flows.

An Option-Theoretic Prepayment Model for Mortgages and Mortgage-
Backed Securities

To appear in International Journal of Theoretical and Applied Finance
Dec 2004, jrg 7, nr 8, december 2004, pages 949-978.
[PDF]

April 23, 2005

Google: branding, beyond adwords

Google is trusting the advertiser’s motivation to target ads to
relevant sites, but Google has never before trusted the advertiser to
make that judgment. The AdWords method has always been to
automatically sever the connection between any underperforming ad and
its keywords, curtailing the appearance of that ad. Google’s
technology was the sole arbiter of relevance, and that relevance was
determined by clickthrough rate. Now, placing ads on
advertiser-determined sites, with payment by the impression, ad
performance is no longer a viable concept. Accordingly, any advertiser
with the loony idea that motor oil will sell on an environmental
activism site can outbid competitors and place that ad. And Google’s
reputation for relevance gets poured into the ground.

[via weblogsinc's google]

April 22, 2005

The High Cost of Free Parking

Free parking isn't really free. In fact, the average parking space
costs more than the average car. Initially, developers pay for the
required parking, but soon tenants do, and then their customers, and
so on, until the cost of parking has diffused throughout the economy.
When we shop, eat in a restaurant, or see a movie, we pay for parking
indirectly because its cost is included in the price of everything
from hamburgers to housing. The total subsidy for parking is
staggering, about the size of the Medicare or national defense
budgets. But free parking has other costs: It distorts transportation
choices, warps urban form, and degrades the environment.

It doesn't have to be this way. In The High Cost of Free Parking,
Donald Shoup proposes new ways for cities to regulate parking, namely,
charge fair market prices for curb parking, use the resulting revenue
to pay for services in the neighborhoods that generate it, and remove
zoning requirements for off-street parking. Such measures, according
to the Yale-trained economist and UCLA planning professor, will make
parking easier and driving less necessary.


The High Cost of Free Parking
by Donald C. Shoup.

Update: 15 % of parking should be empty spaces.

April 21, 2005

VIX: trade implied volatility

One of the most interesting ways to trade implied volatility (long)
is to buy forward starting out of the money calls on S&P500. At some
shops you can get decent pricing and better deal than the vol swap
market offers.

Since the option is forward starting it does not have any time decay
until the strike is set at a "strike date". At strike date the option
turns into a regular european call, which you can sell or dynamically
manage.

This strategy works like a call on volatility in the sense that vega
is convex. The skew and liquidity is a risk factor so I wouldn't got
that far out of the money.

Marketwatch quotes the VIX.

April 20, 2005

Calculated Risk

Calculated Risk offers nicely illustrated economics.

There has been a significant increase in mortgage brokers. There
has been a similar increase in residential building trades, appraisers,
home inspectors and other housing related occupations. The
impact of a housing slowdown on employment will be significant.

What will the end of the refinance boom and the housing boom
do to the mortgage industry ?

calculatedrisk.blogspot.com moved to www.calculatedriskblog.com.

April 19, 2005

r graphics, Paul Murrell

R Graphics by Paul Murrell

Update 2005 Sept 03: R Graphics is shipping !

A book on the core graphics facilities of the R language and
environment for statistical computing and graphics (to be published
by Chapman & Hall/CRC in August 2005). Preview now.

April 18, 2005

Trade the VIX

Can you trade the VIX ?

Chart: VIX vs SPY ?

CBOE micro site on the vix.

CBOE Volatility Index® (VIX®) is a key measure of market expectations
of near-term volatility conveyed by S&P 500 stock index option prices.
Since its introduction in 1993, VIX has been considered by many to be
the world's premier barometer of investor sentiment and market
volatility.

April 17, 2005

Sell your car online

Field report:

Your odds are much better when placing an online ad for your used
MINI, in the main "outlets" such as Cars.com and Autotrader.com. A
dedicated MINI website for this purpose could not always be a successful
thing because buyers out there interested in MINIs (mainly, classics are
a more confined market)are also shopping for other vehicles as well.

I sold my '04 MCS in Cars.com, just 6 days after placing the ad
with 12 photos. The buyer of the car is a local resident, so you never
know who may show interest in your car.

April 16, 2005

housepricecrash.co.uk

housepricecrash.co.uk expert opines on the UK estate market.
Also tabulates industry index data.

See also Vancouver Housing Market and The Housing Bubble.

April 15, 2005

Motorist News

Motorist news covers sppeding tickets, enforcement,
traffic calming and road imrprovements from a motorist's
point of view.

April 14, 2005

thehousingbubble

thehousingbubble, not to be confused with housingbubble track
over financed, over mortgaged real estate.

April 13, 2005

Vancouver housing market

Vancouver housing market.
Somewhere between curbed and housing bubble.

Noticed and awarded.

April 12, 2005

Germans poke their eyes out and see America

Red states, blue states, as seen from Germany.

[medienkritik]

April 11, 2005

Bibamus: left democrat but fair

Bibamus' economic punditry is left democrat partisan but fair. A notch less shrill than
Economist's View.

April 10, 2005

Craig's List and Google Maps

Craig's List and Google Maps merge, and the result is good.

See for rent and for sale listings plotted on a map,
pins colourized to show availability of pictures,
drill down the matches to a feature set or price band.

April 9, 2005

Santa Barbara bubble, dismissed

A Santa Barbara real estate tout dismisses claims of a
real estate bubble.

April 8, 2005

Economist's View / Mark Thoma

Economistsview offers leftist hardcore partisan commentary, often Oregon-centric, posing as economic analysis. (archives).


Update 2006 May: value added.
Update 2005 October: Offers pointers to academic papers and Fed speeches.

Update 2010 Jan:
at CBS MoneyWatch. They named it named Maximum Utility 1,

April 7, 2005

VW Jetta

2005 VW Jetta

[via Autoblog]

April 6, 2005

Housing Bubble Bust

Housing Bubble Bust is San Francisco-centric and frequently updates
its headlines.
Also a good list of links (at page bottom).

April 5, 2005

Housing bubble bloggers

housingbubble, moderately frequent. not to be confused with
thehousingbubble. Both track home of those who over finance,
over mortgage their real estate.

April 4, 2005

Subaru Impreza WRX STi

Subaru Impreza WRX STi

[imprezawrxsti]

April 3, 2005

Dynamist housing bubble

Dynamist Virginia Postrel looked at rent to own costs and
saw a SoCal
housing bubble.

April 2, 2005

date simulation

Want a list of week-ending dates simulated, starting
at 2005 March 28 and ending at 2005 Nov 21.

Find magic number 16515 by trial and error,
or a SAS date function.

Find magic nbumber 250 by trial and error,
or a SAS date function.

data plan;
datebase = 16515;
do i = 1 to 250 by 7;
datex = datebase + i;
week = round (1+i/7);
output;
end;
format datex mmddyy10.;
run;
proc print data = plan; var datex week; run;

More SAS date dox.

Obs datex week

1 03/21/2005 1
2 03/28/2005 2
3 04/04/2005 3
4 04/11/2005 4
5 04/18/2005 5
6 04/25/2005 6
7 05/02/2005 7
8 05/09/2005 8
9 05/16/2005 9
10 05/23/2005 10
11 05/30/2005 11
12 06/06/2005 12
13 06/13/2005 13
14 06/20/2005 14
15 06/27/2005 15
16 07/04/2005 16
17 07/11/2005 17
18 07/18/2005 18
19 07/25/2005 19
20 08/01/2005 20
21 08/08/2005 21
22 08/15/2005 22
23 08/22/2005 23
24 08/29/2005 24
25 09/05/2005 25
26 09/12/2005 26
27 09/19/2005 27
28 09/26/2005 28
29 10/03/2005 29
30 10/10/2005 30
31 10/17/2005 31
32 10/24/2005 32
33 10/31/2005 33
34 11/07/2005 34
35 11/14/2005 35
36 11/21/2005 36

April 1, 2005

Busy Busy Busy

busybusybusy is a great leftish summary the
day's talking heads' punditry.