text:
Post-Confusion, 1: Clinton Green, Tarab, Tony Buck & Rik Rue
Monday 14 February 2022
I've been listening to a range of pieces by artists working with degrees of freedom in their approach to composition, from fixed but open structures to pure improvisation. The eclectic sonic materials used render questions of harmonic or other pitch-based organsiation obsolete. Perhaps it's the ultimate expression of Ezra Pound's theory of harmony, that any two sounds can follow one anonther in consonance as long as you get the timing right: the disposition of heterogeneous sounds to create a balanced, unified musical experience is a genre that has slowly defined itself over the last half-century or so. As with the materials, the unifying forces can be left very loose, defying our expectations of associating anarchy with chaos.
The densest, noisiest works all happen to be Australian, produced across a gap of twenty-five years. Maybe there's a pattern that singles out these three albums, or perhaps these piece are just crowding out my mind right now. There appears to be a tradition, as represented by the reissue of Tony Buck & Rik Rue's Come Let Us Build Ourselves A City collaboration from 1996. A double improvisation of Buck on drums and electronic percussion devices, embellished and corrupted by Rue's electronics and samples played through minidisc recorders set to shuffle, the collection of pieces push the density of signals to the brink of noise. Technology allows each musician to be their own Sixties happening in terms of immersion in omni-attentiveness. With such abundance, pacing or restraint in exposition are irrelevant: the energy is unstinting and phrasing can be confrontingly abrupt.
The same qualities can be heard in Tarab's 2018 recording, HOUSEKEEPING, derived from an 8-channel installation. Recordings of found objects, spaces, rehearsals are all swept up in this vast accumulation of otherwise inconsequential odds and ends. The collection may appear indiscriminate but the presentation is far from flat, using the perspectives of time and space over which the piece was shaped to present sounds in sharp relief. If there's a shared tradition here, it's in the use of domestically-oriented material to produce something otherworldly, transcending its innate quotidian attributes to become something more than itself, rather than seeking to relocate artistic experience within the mundane.
That transcended domesticity carries over into the most recent work here, Clinton Green's Here?/Secret, a pair of related lockdown compositions created out of frustration at being unable to access his studio and equipment. The two collages were created from, and on, cassettes, using older material left at home and processed on an old 4-track cassette mixer. The gear at work here is similar to that used by Rik Rue in the 1980s. Green mentions a compositional procedure for choice of tape, tape speed and direction and panning, which yields a combination of sounds disturbingly mismatched to eerie perfection, much in the way of a prolonged chance collision. Once again, the ordinary is repurposed into a hallucinatory melange of sounds beyond conventional comprehension. It taps into a powerful strand of late 20th Century experimental music, going back to Cage's collages from the 1950s, that's occasionally forgotten only to be taken up again a generation later…
Tags: Clinton Green, Rik Rue, Tarab, Tony Buck


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Home Tags Mac
MAC x Puma launches at Six:02
If you're one of the lucky people who are in NYC today you can get your hands on the limited edition MAC Cosmetics x PUMA sneaker, for everyone else they will officially be launching May 17th at all Six:02 locations and on their website.
The collection included three colors based on MAC Cosmetic's best-selling lip shades Lady Danger (coral-red), Sin (deep dark blue red/wine) and Creme D'Nude (pale muted peach beige).
MAC Lipensity is HERE!
The eagle has landed! As in MAC Cosmetics Liptensity Lipstick have finally dropped and are now available for a limited time. Many of you saw their launch party on my snap — or every other beauty editors social media. No one wanted to miss this mega launch for the brand!
Maureen Seaberg, James Gager, Creative Director MAC Cosmetics and Jennifer Balbier, Senior VP Product Development MAC Cosmetics introducing MAC Liptensity to the audience
MAC is always pushing the boundaries of colour and finding new innovation. They aren't afraid to color outside the lines and for this collection they partnered with tetrachromat (that's a new vocab word for me too), Maureen Seaberg — who has the genetic ability to see up to 100 million hues imperceptible to the average naked eye. Let me break this down for you — if we as "normal" people see somewhere around the million shade spectrum, she would see 100 million.
Working with Maureen, M·A·C created, Liptensity, an unprecedented spectrum of 24 shades with extreme, undeniable colour intensity, using their new groundbreaking High-Frequency Tetrachromatic Pigments technology.
I highly recommend them. They go on like balms, and have this rich color that lasts. They are designed to be the same color on all skintones, and for me were incredibly true to shade. What you see on the packaging (which I love by the way) is what I got when I swatch it on my hands and on my lips.
Left to right these are shades: Galaxy Grey, Lobster and Ambrosial. They are easy to apply, and you don't have to build them. It's love at first swipe, packed with gorgeous pigment and they are very lightweight.
Also new from MAC is their Trend Forecast Spring 2017 Collection which features a lip palette, eye palette and two new Studio Eye Gloss shades, Clear as Glass (pictured above), which is like lip gloss for your eyes. They are also introducing the Next Up Neon shade which is a high shine "iodine" yelloworange.
For spring 2017 MAC predicts shades of pale pink to deep berry, which I'm all for. It's a beautiful, very wearable range of lippies. They go on like a gloss meets lipstick, a pretty stain to each shade that isn't intense but still carries it's shade.
The cream eye shadow palette I have to play around with more. It's a whole spectrum of colors from soft cinnamon, pink to bright green, eggplant and denim blue.
Shop the collection at maccosmetics.com
MAC Cosmetics Sample Sale Hits NYC. Shop at 60% off!
Calling all MAC Cosmetics shoppers, their Sample Sale is this week in NYC! Shop the sale from July 19 – 22nd at the Metropolitan Pavilion at 123 West 18th street, on the 4th floor. Details and invite above. All products are 60% off the retail price.
Get their early, you know there's going to be a line! Good luck!
PFW: Backstage Beauty Look at Carven S/S 2016
Backstage at the Carven Spring/Summer 2016 show lead makeup artist Nina Haverkamp for MAC Cosmetics created a "healthy, pure and sporty, no-makeup look". The Carven girl is a very natural girl who knows how to dress and doesn't need anything else to be a complete show stopper.
It's that 'I woke up this morning beautiful and healthy' look we all wish we actually woke up looking like. And while it plays off the 'no makeup makeup' that's been such a big trend for the past season there is a uniqueness to this look in the transparency in the skin and technique.
MAC Announces latest Collaborations
MAC Cosmetics is on a role with their collaborations! While taking over fashion week (they always dominate the backstage beauty scene), the brand announced a collaboration with designer, Jeremy Scott during his New York Fashion Week show. To Coincide with the New York premiere of Jeremy Scott: The People's Designer, Jeremy Scott released his first-ever beauty exclusive. Available only in a special M.A.C red, the color comes enclosed in a Scott-designed tube.
MAC Cosmetics Announces #MACSelena
The internet is a buzz with the announcement of #MACSelena: the multi-product collection inspired by Latin icon, Selena Quintanilla. Back in February, fans of the late singer started a Change.org petition urging MAC Cosmetics to release a limited-edition collection inspired by the singing sensation. 37,772 signatures later, everyone (including us) is freaking out!
MAC Cosmetics launches Mia Moretti Collection at Coachella
One of our favorite parties during Coachella for both myself and Patricia Field was the poolside bash hosted by MAC Cosmetics for the launch of their festival inspired collection with DJ superstar, Mia Moretti. Filled with a beautiful range of peach-tones, pinks to reds, the seven piece collection (plus makeup bag and tote!), consists of two lipsticks, a six shade lipstick palette, and four color creme's which can be used on cheeks, lids and lips. While catching up with the Moretti, she chatted about how much she wanted to create a very wearable collection using colors she would actually wear and could also envision women wanting to carry around in their makeup case.
M·A·C Cosmetics and Proenza Schouler Collaborate for Spring 2014 Collection
Shut the front door! Proenza Schouler is partnering with MAC Cosmetics for a limited edition collection for spring! Launching globally in April 2014, the collection will feature Ombre Face Powders, Lipsticks, Pro Longwear Eye Liners and Lip Pencils, Nail Lacquers, and a 129SE Powder Brush. Inspired by one of Proenza Schouler's past collections, the collaboration packaging will be extremely unique. .
"I have always respected Jack and Lazaro's keen vision and point of view. We've worked together backstage creating beauty looks for their runway shows for many years and it has been fascinating to me watching them evolve. They have a very particular perspective on their makeup look each season. It has been a great experience collaborating with them to bring their beauty vision off the runway to our customers." – James Gager, Creative Director, Senior Vice President, M·A·C Cosmetics
NYC Event: Rock with MAC and Century 21
Attention shoppers…
NYFW: Ruffian Spring/Summer 2013 Runway Show (+ finale video)
For the Spring/Summer 2013 show, Ruffian wanted to explore their love of couture within the context of Williamsburg, Brooklyn where they live. While the word couture didn't come to mind when watching the models walk down the runway, it did make me reminiscent of my years living on Bedford Avenue. Sure, their were hipster elements – skinnies with oversized top, printed pants, skirts and tops, (and all matched with Converse) — but it wasn't contrived or trying to hard. The contrast of the baroque counterbalanced the minimalism, street style, and luxury fabrics that were cut into classic American utilitarian shapes.
I took a video of the finale for you:)
http://www.youtube.com/watch?v=-dTfQUaSlUE&feature=youtu.be
Favorite looks… (I love the relaxed comfort of it all and the styling with Converse}

redpajama_set_name: RedPajamaCommonCrawl


This means that if you take some number a, multiply it by itself p times and subtract a, the result is divisible by p (see modular arithmetic). It is called Fermat's little theorem to differentiate it from Fermat's last theorem. Pierre de Fermat found the theorem around 1636; it appeared in one of his letters, dated October 18 1640 to his confidante Frenicle in the following equivalent form: p divides ap-1 - 1 whenever p is prime and a is coprime to p. The case a = 2 was known to the ancient Chinese.
Fermat explained his theorem without a proof. The first one who gave a proof was Gottfried Wilhelm Leibniz in a manuscipt without a date, where he wrote also that he knew a proof before 1683.
See Proofs of Fermat's little theorem.
A slight generalization of the theorem, which immediately follows from it, is as follows: if p is prime and m and n are positive integers with m ≡ n (mod p-1), then am ≡ an (mod p) for all integers a. In this form, the theorem is used to justify the RSA public key encryption method.
where φ(n) denotes Euler's φ function counting the integers between 1 and n that are coprime to n. This is indeed a generalization, because if n = p is a prime number, then φ(p) = p - 1.
This can be further generalized to Carmichael's theorem, stated here: " class="external">http://mathworld.wolfram.com/CarmichaelsTheorem.html.
If a and p are coprime numbers such that ap-1 - 1 is divisible by p, then p need not be prime. If it is not, then p is called a pseudoprime to base a. A number p that is a pseudoprime to base a for every number a coprime to p is called a Carmichael number.


text:
\section{Introduction}

In neo-classical finance, future securities prices are regarded as
a function of risk and (realisable) present  value. We  compare
{\em arbitrage pricing theory} (APT) risk-factor pricing models
with {\em characteristic based models} (CBM), which offer
alternative causal relationships for returns in a equity markets.

 {\em No-arbitrage} (NA) refers to the
reasonable idea that a (theoretic) riskless portfolio with
possible { positive return}  in the future, must cost something
now. It can be shown to be equivalent to the existence of a
positive linear pricing rule or {\em pricing kernel}
\cite{HK1979,Ross1976} and has been generalised to the concept of
\emph{no-free-lunch-with-vanishing-risk} \cite{DS1994}, in an
overarching valuation framework \cite{AG1994} that has facilitated
the growth of a multi-trillion dollar derivatives market concerned
with pricing future cashflows, risk-sharing and completing
markets.

The general linear factor APT model formulation was introduced by
Ross to explain returns in the simplest possible manner consistent
with the assumption of NA \cite{DR2003, Ross2005}. The
Fama-and-French model followed thereafter, as special case, to
incorporate specific risk premia which were not explained by the
CAPM, namely {\em value} and {\em size}. In particular, Ball, Banz
and Basu \cite{Ball1978,Banz1981, Basu1983}  were amongst the
earliest authors to discuss empirical evidence that
small-capitalised stocks and stocks with low price-to-book values
exhibit higher long-term performance. More than a decade of
literature demonstrating the explanatory power of stock specific
accounting variables followed before Haugen and Baker eventually
crystallised the approach in the literature by describing a
general characteristic based model for equity market returns
\cite{HB1996}. This presented a different paradigm to the
 Fama-and-French time-series factors, which had been constructed to be consistent with a linear regression approach for
explaining risk in both stocks and bonds and which could be combined
with macro-economic variables in the APT framework.

In a comprehensive triple-sort testing framework to separate overlapping effects,  Daniel and Titman
 compared characteristic based models and Fama-and-French APT models
with attention to the same market factor, size and value variables
\cite{DT1997}. They show that the return premia to size and value do not appear to
originate from the covariance of stocks with intrinsic risk factors,
but that cross-sectional price variation seems to be driven directly by
stock characteristics. In particular, they demonstrate
portfolios which have similar characteristics (size and
book-to-market), but significantly different loadings to the Fama-and-French
factors can have similar average returns.

One of the findings in \cite{DT1997}  is that $\alpha$ {\em is
generally non-zero } for both models, contradicting the FF model's
linear requirements. Similar results were obtained in
\cite{G2007}. A possible reconciliation of their findings is that
$\alpha$ and the factor $\beta's$ are nonlinear functions of risk.
Ferson and Harvey \cite{FH1999} used out-of-sample testing to
illustrate the effectiveness of time-varying alpha and beta
APT-type models.

We adopt the predictive form of the models used in \cite{FH1999} for a simplified comparison of {\em conditional} APT
models\footnote{ i.e. with time-varying alpha and beta's} with
corresponding CBM models\footnote{The authors of this report are
not aware of other investigations with this particular innovation
in the literature.} with respect to their abilities to forecast
returns. This avoids the cumbersome triple-sorting as in \cite{DT1997}.
In particular we compare the returns of portfolios whose
weights (loadings) are updated monthly according to out-of-sample
expected parameters and then select stocks with the best expected
returns predicted using (2) and (4) below.

We consider portfolios whose weights (loadings) are updated monthly according to out-of-sample
expected returns according to equations (2) and (4) below.
The comparable APT and CBM implementations are constructed
using stocks listed on the South African Johannesburg Stock
Exchange (JSE)  between 1994 and 2007. We
demonstrate that characteristic-based models have provided higher returns at lower
volatility than risk-based models over a relatively short time
horizons.

Since we restrict our attention to specific sets of information in our comparisons, the out-performance suggests that CBM are more efficient in pricing in those types of information.

Thus, the characteristic approach not only provides a
empirical tool for exposing the phenomenology and structure of a
given market,  is it is also useful for making ex-ante stock
return predictions \cite{HB1996}. This makes the characteristic
approach interesting both practically and theoretically.

We discuss our findings in the context of pricing risk under assumptions of {\em no-arbitrage} and the weaker {\em no-free-lunch-with-vanishing-risk}: In
Section 2 we review the two model types and evolution of ideas, as
motivated by empirical evidence for equity returns.  In Section 3
we review the market context for our investigation and in Section
4  we present the outcomes of our analysis of the risk-return
profiles for portfolios constructed via the different asset price
models. We conclude in Section 5.

\section{Models for equity returns and risk premia}

The idea that NA drives pricing is coupled to the perspective that
risk factors exogenous to the market can move prices and that news
arrives often and randomly and gets priced in instantaneously. In
particular, this theory assumes that prices incorporate the impact
of exogenous factors fully. If this is the case, then endogenous
factors should be computable from the reflection of exogenous
factors in price changes (see for example \cite{Matoti2009,
WG2008}). Notably, APT does not specify its risk factors and
macroeconomic, fundamental or statistical factors may be used,
provided the dependence on these is linear .

Endogenous characteristics (attributes), such as  book-to-price or earnings-per-share, may also be used to
construct portfolios that represent the risk factors used in a
linear pricing rule \cite{Ross1976}.
 Fama and French \cite{FF1992, FF1996} developed a
model to compensate for two such attributes which have been
correlated with returns, namely value (measured via
book-to-price) and size.

The initial idea of characteristic based models was that company
specific characteristics could directly explain most of the
expected return differentials. However, to facilitate consistent pricing of uncertain future cash-flows of different types of securities,  factor mimicking portfolios that
mirror the roles of  characteristics, were devised.  The use of stock characteristics to generate a covariance structure
was a key  innovation in asset pricing \cite{FF1993}, since it allowed
a parsimonious interpretation without the rejection of linear
pricing models and the resulting 3-factor FF risk-based
model became a standard against which others were compared

\subsection{APT risk factor vs.  characteristic based
models}

We describe the two classes of models which are compared in order
to identify how information and risk are reflected in equity
prices.

 For an APT-type
risk factor model, we implement the following to explain and
predict returns:

\begin{eqnarray}
R_{i,t} = \alpha_t^F +\sum_j\beta_{i,j,t} f_{j,t-1} + \epsilon_{i,t}.\label{eqn:risk}
\end{eqnarray}
Here the unexplained component $\epsilon_{i,t}$ relates to the
factor loading (coefficient/weight) of $i$-th stock with respect to
the return on $j$-th price risk factor $f_{j,t}$, at time $t$, and
the risk factors are Fama-and-French model risk factors, derived
from size and value information, which are described in the next
section. The expectation of return at time $t-1$ for time $t$ is:
\begin{eqnarray}
\mathrm{E}_{t-1}[R_{i,t}] = \mathrm{E}_{t-1}[\alpha_t^F] + \sum_k \mathrm{E}_{t-1}[\beta_{i,j,t}] f_{j,t-1} \label{eqn:exprisk}
\end{eqnarray}

 Haugen and Baker discuss characteristic based models (as class of models) for equity market returns  in  \cite{HB1996}.
 In our analysis we implement   the form which they propose:
\begin{eqnarray}
R_{i,t} = \alpha_t^C + \sum_k \delta_{k,t} \theta_{i,k,t-1} + \epsilon_{i,t},\label{eqn:haugen}
\end{eqnarray}
where $\theta_{i,t-1}$ is the $i$-th observable stock characteristic at time $t-1$, such as book-to-price, and the payoffs to the $k$-th characteristic at time $t$ is $\delta_{k,t}$.
The expected return at time $t-1$ for time $t$ is:
\begin{eqnarray}
\mathrm{E}_{t-1}[R_{i,t}] = \mathrm{E}_{t-1}[\alpha_t^C] + \sum_k \mathrm{E}_{t-1}[\delta_{k,t}] \theta_{i,k,t-1} + \epsilon_{i,t}.\label{eqn:exphaugen}
\end{eqnarray}

For the comparison, the characteristic factors incorporated were size (market value) and value (book-to-price) attributes.

We note that the forms used in  Eqn. (\ref{eqn:risk}) -  Eqn.
(\ref{eqn:exphaugen}) should not be confused with general form
considered in the Daniel and Titman \cite{DT1997,DTW2001}, where
the risk model is purely explanatory and has {\em no time-lags}:
\begin{eqnarray} \mathrm{E}_{t-1}[R_{i,t}] = \alpha_t + \sum_k
\delta_{k,t} \theta_{i,k,t-1} + \sum_j \beta_{i,j,t-1}f_{j,t-1}.
\label{eqn:DT} \end{eqnarray} Furthermore, the formulation of Eqn.
(\ref{eqn:DT}) requires additional regressions to estimate
expectations of both prior characteristic and risk factor
loadings.

The forms used in  Eqn. (\ref{eqn:risk}) -  Eqn.
(\ref{eqn:exphaugen}) are consistent with our investigation to
test the ability of stock characteristics to act as predictors in
comparison with analogous risk factors. In particular,  we
consider the ability of the factor mimicking portfolios to predict
future returns (via dynamically changing loadings) rather than the
ability of the loadings themselves to act as predictors
(independent of the factor-mimicking portfolios). This latter
formulation has been explored elsewhere \cite{G2007}.

These equations are well suited for multi-factor regression
analysis with out-of-sample testing using small frequently
reformed data sets for rolling time-frames:  In order to compare
the risk-return profiles of CBM models described in  Eqn.
(\ref{eqn:haugen}) with corresponding risk factor models described
in Eqn. (\ref{eqn:risk}), ex-ante predictions from Eqn.
(\ref{eqn:exprisk})  and Eqn.  (\ref{eqn:exphaugen}) were used to
evaluate the risk-return profiles of the two models out-of-sample
. The expectations: $\mathrm{E}[\alpha_i^F]$,
$\mathrm{E}[\alpha^C]$, $\mathrm{E}[\beta_{i,j}]$ and
$\mathrm{E}[\delta_k]$ were assumed to be slowly varying functions
of time. This allowed us to estimate  $\mathrm{E}[\alpha_i^F]$ and
$\mathrm{E}[\beta_{i,j}]$ using time-series analysis and
$\mathrm{E}[\alpha_t^C]$ and $\mathrm{E}[\delta_{k,t}]$ using
cross-sectional analysis.

\subsubsection{The Fama and French APT model}

 We review  the construction of the three Fama-and-French risk factors
 (FF) which are proxied by {\em factor mimicking portfolios }
 based on  {\em book-to-price}  and {\em size} information. First, six
portfolios are constructed via  the intersection of three
book-to-price categories ($H\equiv$ High, $M\equiv$ Medium and
$L\equiv$ Low)  with two  {\em  size} categories ($B\equiv$ Big
and $S\equiv$ Small). These portfolios are designated $HS, \ MS, \
LS, \ HB, \ MB$, and $ LB$ \cite{FF1992,FF1995,FF1996,DT1997}.
These portfolios  are then used to capture the disentangled {\em
size} and {\em value} effects as factor mimicking portfolios:

\begin{eqnarray}
R_{_{SMB}} &=& \frac{1}{3} \left( {(R_{_{HS}} + R_{_{MS}} + R_{_{LS}}) - (R_{_{HB}} + R_{_{MB}} + R_{_{LB}})} \right), \\ \label{eqn:SMB}
R_{_{HML}} &=& \frac{1}{2} \left( {(R_{_{HB}} + R_{_{HS}}) - (R_{_{LB}} + R_{_{LS}})} \right) \label{eqn:HML}.
\end{eqnarray}

Here the risk factor variation $SMB$ is the excess return for small relative to large capitalized stocks (corrected for value), while the variation of $HML$ is the excess return of high value stocks relative to low value stocks (adjusted for size-effect contributions).

The resulting FF risk factor model for the $i$-th stock takes on the usual explanatory form
\begin{eqnarray}
& & R_{i,t} - R_{_{rfr},t} \\ &=& \alpha_i +
\beta_{i,_{Mkt}}(R_{_{Mkt},t} - R_{_{rfr},t}) + \beta_{i,_{HML}}
R_{_{HML},t} + \beta_{i,_{SMB}} R_{_{SMB},t} + \epsilon_{i,t},
\nonumber \label{eqn:FF}
\end{eqnarray}
where the risk-free rate of return is denoted by $R_{rfr,t}$ at time $t$, the bias is $\alpha$ and the factor loadings are given by the respective $\beta$'s. This is not the same form as the return-prediction mode for APT risk factors  used in Eqn. \ref{eqn:exprisk}. It is the predictive formulation that is investigated here. We note further that  it is the predictive power of the characteristics relative to the factor loadings that is explicitly tested for in  Daniel and Titman \cite{DT1997,DTW2001}, rather than the predictive power of the factor mimicking portfolio's as loaded by the $\beta$'s.

\subsection{Model implications: Arbitrage and linear vs nonlinear pricing kernels}

From a pragmatic point of view it may be that characteristic based
models make better predictions, given the vagaries and noise of
financial markets and financial data, simply because they are
better representations of available measurements.

Calibration to APT risk-factors is rewarded with linearity of the
pricing kernel.  A {\em linear pricing kernel } yields the price
of an asset as a scalar product of
 a representation of future payoffs (including contingent claims)
 with numbers which calibrate how the payoffs impact current asset prices.
 It's equivalence to the reasonable assumptions of NA pricing follows
by translating the NA into concise mathematical assumptions.

In particular, by combining NA with some simplifying assumptions
on the nature of investment returns in a finite (and complete)
state-space, an extremely elegant pricing framework can be derived
from a foundational theorem of early 20$^{th}$ century Hilbert
space theory \cite{Riesz1909}. The Riesz Representation theorem
provides the mathematical foundation for the following key
equivalences in the Fundamental Theorem of Asset Pricing and the
Pricing Representation theorems \cite{CR1976, DR2003}:
\begin{enumerate}
\item the market does not admit arbitrage opportunities
\item there exists a positive linear pricing rule for the relationship between
asset prices and future state-dependent payoffs ,
\item there exists a pricing measure under which risk-neutral discounted securities prices are
martingales
\item there exists of a positive pricing  kernel which provides the connection between positive probabilities of
events occurring and the payoffs of those events.
 \end{enumerate}

A key benefit of this approach is that  it facilitates a relatively simplified methodology to
pricing derivative claims which have nonlinear payoffs.

No-arbitrage has been generalised to more realistic continuous
(infinite-dimensional) and incomplete market settings
\cite{HK1979,HP1981} to the assumption of
no-free-lunch-with-vanishing-risk (NFLVR) \cite{DS1994}. The
latter can be interpreted as the condition whereby
 it is impossible to devise a potentially profitable {\em trading
 strategy}
which never  loses money.

While the failure of NA or NFLVR negates the existence of any
reliable market pricing kernel, the validity of a CBM does not
necessarily imply the existence of any arbitrage opportunities. In
fact it follows from arguments similar to those used in
\cite{DR2003}, that  it is also possible to construct a linear
pricing kernel in the case of a finite dimensional market which
admits a zero-alpha CBM.

In the literature,  stock specific characteristics  have been
interpreted to be {\em non-risk } determinants of asset prices
\cite{BCS1998}. Our view is that the effectiveness of these
variables points to a reality of {\em non-linear pricing
kernels}\footnote{ Giving up linearity of the pricing kernel poses
a further challenges for finance theory. In particular, if it is
possible to construct a NA characteristic based model which offers
more comprehensive and consistent market modelling, then the
result that firms are independent of their financial structure
\cite{MM1958,MM1961} may require reinterpretation.}. For example,
Daniel and Titman find $\alpha \neq 0 $ for both FF and CBM type
models investigated \cite{DT1997}. Such results imply that
$\alpha$ must be a nonlinear function of risk factors for a risk
pricing perspective to be preserved.

Departures from linearity may also be interpreted as manifesting
themselves in the $\beta$ of a factor-pricing model, where for example, the
$\beta$'s may be  functions of the characteristics that underpin the
factors. In this case, the model can remain linear in the
factors, but becomes non-linear in the characteristics in an
auto-regressive manner via factor coefficients \cite{FH1999}.

The notion of a nonlinear pricing kernel is consistent with the more general reflection of information in prices.
Motivated by the same considerations as Ross, Fama and French in their development of the linear APT risk factor approach, Bansal and Viswanathan (1993) and Harvey and Kirby (1995) investigated the theory of nonlinear pricing kernels in \cite{BV1994, HK1995}. Ferson and Harvey showed how to   calibrate the nonlinear (conditional) APT approach in \cite{FH1999}, while Chernov developed a  more general nonparametric calibration of nonlinear kernel models in \cite{Chernov2003}.

From an investors perspective, decisions are rewarded partly as
compensation for taking on the risk, which can be proxied by
appropriately specified factors,  as well as for removing possible
mispricings (arbitrage opportunities) identified by their
investment model.

We note that behavioural economists have not been convinced by the
risk-based explanation of the FF model \cite{LSV1994} and have
suggested, for example, that behavioural biases in the forward
estimation of earnings could explain the value premium found by
Fama and French \cite{FF1992}.  Similar criticism could be
directed to characteristic based models.

Thus, as asset managers \textit{chase alpha} by following almost identical strategies to identify possible
mispricings, the collective impact of their
investment strategies in the same assets can impact price formation.
This would be consistent with the extensive literature emanating
from theorists on the SA market, who have promoted characteristic approaches (\cite{vRR2003a, vRR2003b, vRR2004} and subsequent investigations in that journal).

We also note that the size effect can explained as a portfolio
level phenomena by following arguments given in the stochastic
portfolio theory (SPT) of Fernholz \cite{Fernholz1998, FK2006}.
While the SPT approach does not offer insight into the existence
or nature of pricing kernels, it does expose how capital entering and leaving the market impacts price as a function of cross-border cash-flow risk \cite{WG2007}.

In the next sections we present a period in the SA market for
which characteristic models have offered higher returns for lower
volatility, with the possible interpretation that APT models were
not able to price in as much information available to investors as
CBM.

\section{Data, market context and related investigations}

Our investigation is based on monthly data for stocks listed on the Johannesburg Stock Exchange
(JSE) between 1994 and 2007.

\subsection{Data and market context}

Our data set runs from 31 Jan 1994 to 30 April 2007, complementing
previous studies and including the bull-market post 2003, a period
in which  the market factor made a considerable contribution, as
well as  the peak in a value cycle in mid-2005.

We consider three distinct universes of stocks by using market
value to select the largest 50, 100 and 250 stocks respectively,
each month. The Top 250 stock universe was the largest universe
which could be kept sufficiently constant in stock number for the
study. We regarded this as  the simplest approach to creating a
representatuve universe of JSE as a whole for the out-of-sample
comparison of the APT and CBM models\footnote{Our data treatment
avoids the use of liquidity screens,  used in preceding analysis
of the same \cite{G2007, WG2004, WG2008}}.   In this paper we
report primarily on the Top 250 stock universe since the results
are similar across all universes including, yet surprisingly, the
relatively small Top 50 universe.

Continuous-time model returns (log-returns) were used. The proxy
for the cash asset was the current 3 month NCD (negotiable cash
deposit). This is the closest SA equivalent to US 3-month treasury
bills. South African NCD's are quoted at discount yield (NACQ).
This required that we construct a monthly price index using the
publicly quoted yield time-series for the instruments by computing
the face value and re-balancing monthly.

 Zero-valued prices and returns  were treated as missing
 data in all the sorts and regressions so that the lack
of meaningful numbers would not bias the analysis for  other
stocks and variables where data existed. In particular,  we did
not use interpolation methods, nor did we systematically exclude
data for some stocks due to missing data for others. Infinite
characteristic values were also treated as missing data in all the
sorts and regressions.

The data preprocessing follows Haugen and Baker \cite{HB1996} by
first winsorising the data at 3 standard deviations and then
z-scoring the resulting data. Missing data is excluded at the
level of the algorithms employed, and as such we have avoided
excluding entire data rows if missing data is encountered because
of data sparsity (rather than  the occurrence of non-trading
days).

 A synthetic market weighted index was computed from market values.
The CAPM $\beta$'s were computed relative the synthetic market
index. Such a market index was computed for each of the three
universes and re-balanced monthly. This was useful in that it
ensured that the market index was defined in terms of the same
universe of stocks as the study itself as well as ensuring
meaningful comparison within the 3 stock universes.

We restricted ourselves to a small set of input variables for the
characteristic models: a total return index, historic dividend
yield, price-to-book, volume traded, market value and earnings
yield. The data was sourced from Thomson-DataStream. Although a
more extensive list of characteristics was available  and
commercial applications of such CBM models include forward broker
information\footnote{A typical stable commercial characteristic
based model for the South African market could include most of the
following factors (perhaps less if volatility becomes a concern):
total return, log-size, price, book-to-price, cash-to-price,
dividend yield, earnings yield, 1-year forward earnings yield,
2-year forward earnings yield, 1-year forward earnings growth,
earnings torpedo (change from latest earnings to next consensus
earnings), neglect (negative log of number of analysts covering a
stock), earnings revision, earnings downgrade, earnings upgrade,
broker recommendation (buy, hold, sell), low price, payout ratio,
3-month momentum, 6-month momentum, 9- month momentum, 1-month
momentum (smoothed), currency plays (dummy for USD/ZAR
exposure).}, the intention here is to focus on value and size in
the context of  $HML$ and $SMB$ constructions for the Johannesburg
Stock Exchange.

Two momentum characteristics were also computed using the total
return index. Specifically,  a long-term 12-month momentum, lagged
1 month prior to formation date, and a short-term 3-month momentum
signal, also lagged 1 month prior to formation date, were
computed. The limited length of the data sets and the relative
sparsity of the sort data made momentum signals longer than 2
years impractical.

A unique problem with the South African market is the dominant
effect that dual listed stocks have. Dual listed stocks whose
primary listings were not on the Johannesburg Stock Exchange where
included and the book-to-price and earnings yield of the primary
listed entities where used in the analysis \footnote{This included
dual-listed counters such as Anglo American, BHP-Billiton,
Richmont, SAB-Miller, Old Mutual, Liberty Life and Investec. The
list was constructed using the JSE listed ISIN codes to find the
primary listing exchange and tickers. With this information the
correct primary listing characteristics could be sourced. By using
price ratios in the primary listing's currency  one avoids
additional uncertainties arising when converting the
characteristics, such as earnings and book-value, to local
currencies.}.

\subsection{Related investigations}
There have been several studies relating to characteristic based
models on JSE listed stocks since \cite{FP2000, vRR2003a,
vRR2004}. More recently, we considered the impact of foreign
portfolio investment, as a risk factor for emerging markets
\cite{WG2007}, via the stochastic portfolio theory factorisation
of Fernholz \cite{Fernholz1998}.

In  \cite{FP2000, vRR2003a, vRR2004} the authors argued that the
cross-section of returns on the JSE is explained by
characteristics (attributes) rather than risk factors for
correlated price-to-earnings and size risk factors. Our approach
is different however, since  \cite{vRR2004} constructed the
following: a portfolio $SLL$ or {\em small-less-large}, driven by
the difference  between small and large cap returns,  as a risk
factor capturing the size effect, and a portfolio {\em LLH} or
{\em  low-less-high}, driven by the difference between low and
high value stock returns. Their factors are uncorrected for
possible correlation, which is a key ingredient in the FF risk
factor constructions \cite{FF1996, DT1997}.

Daniel and Titman  recommend the use multi-factor regressions on
triple sorted portfolios\footnote{The use of multi-factor
regressions in the context of triple sorted portfolio intercept
tests was  also presented in \cite{G2007}.} as a step for dealing
with the errors-in-variables problem which portfolio sort based
testing procedures have \cite{DTW2001}.  Understanding  of the
method is important because it provides a key motivation for our
review of the FF model for South African data. We note that
\cite{vRR2004} used single factor regressions in the context of
double sorted portfolios. However, the theoretical context of
their contribution was not that of discriminating between risk and
characteristic-based models but rather that of identifying a more
appropriate form of asset pricing model specification  based on
characteristics (attributes).

The sample studied by Fraser and Page \cite{FP2000} was from 1973
through 1997 and examined financial and industrial stocks with a
focus on price-to-earnings, dividend yield and market value. They
argued that price-to-earnings was the key determinant of the
cross-sectional price differences at that time. The sample studied
by \cite{vRR2003a} ran 1990 through 2000 and also focused on
price-to-earnings and market value. They considered  a more
extensive set of characteristics with commercial applications in
fund management in view. This provided one of the first screens of
characteristics and aligned with their stated objective of finding
a more appropriate asset pricing model for the JSE.

In our investigation,  we recover an apparent {\em value effect}
in three different stock universes, namely the Top 50, Top 100 and
Top 250 stocks, as reformed monthly. The {\em size effect} was
more prominent in  the Top 50  and Top 250 stock universes. Prior
work on the size effect on US common stocks \cite{Banz1981} was
extended to the JSE by Page and Palmer \cite{PP1993}. Similarly,
the effect of price-to-earnings \cite{Basu1983} and price-to-book
\cite{Stattman1980} has been extended to the JSE
\cite{FP2000,vRR2003a}. Various ad hoc investigations on price
premia in the same market are also documented in the literature.

We add to this discussion in the context  that the South African
market has hierarchical aspects: ALSI 40 (largest 40 stocks)
attracts international investors while simultaneously being
important to domestic investors, who also focus on the ALSI
(largest 165 stocks). We promote a nonlinear pricing kernel
perspective to reconcile the findings in favour of direct
characteristic based pricing with no-arbitrage pricing paradigms.

\section{Results and discussion}

\subsection{Risk and return comparisons between model types}

We compare a 3-factor APT model, using our FF factors, and  a CAPM
model with two characteristic based models (CBM), one without
momentum (CBM \#2 in Table \ref{tab:payoffs}) and one with
momentum (CBM \#6 in Table \ref{tab:payoffs}).

For Figure \ref{fig1:riskreturn}, returns for each model were
sorted\footnote{The sorts where carried out using a symmetric
quantiling algorithm that kept the sort symmetric around the
middle quantile for odd numbers of quantiles, and symmetric around
the two middle quantiles for even numbers of quantiles. The
algorithm was also tailored to ignore missing data and cope with
listings, delistings  and illiquid instruments that may have had
no trade or fundamental data available on a given month. This
quantiling algorithm was then used to sort stocks into quintiles.}
into five quintiles, with highest expected returns binned into the
$1^{st}$ quintile. Best fit lines for corresponding realised
returns and realised volatilities were then plotted.

  The CAPM and FF risk models yielded ex-post returns
which were less than those from two CBM, but at higher
volatilities. This is evident in Figure \ref{fig1:riskreturn} for
the Top 250 universe, but holds for all three stock universes
studied and demonstrates that  one could generate higher returns
with lower risk by using CBM and selecting stocks whose returns
fall into the $1^{st}$ quintile. A more rigorous statistical
treatment using the Daniel and Titman \cite{DT1997, DTW2001}
approach was given in \cite{G2007} and is consistent with the
visual results shown here.

 Risks, measured by volatility, vary little across the quintiles
for CAPM and FF models, but are significantly higher in the
$4^{th}$ and $5^{th}$ quintiles for their characteristic based
counterparts. This result is robust across the three different
universes of stocks. We note further that loadings to the market
factors in the APT and CAPM models were higher than the
corresponding market factor loadings in the CBM.

Hence, we claim that CBM have been  effective even in fairly small
concentrated data sets, such as the ALSI 40 universe, as well as
being effective in the larger universes. This demonstrates that
investors have not necessarily rewarded for risk in the sense of
APT or CAPM on the JSE.  These results holds across the Top 250,
Top 100 and Top 50 stock universes, providing a key finding for
JSE for the pre-global crisis period considered and corroborating
the findings of \cite{Haugen1998}.

In \cite{G2007}, which implemented the triple-sort approach of
Daniel and Titman \cite{DT1997} to compare the models, it was
found that generally $\alpha \neq 0$ for the  FF models. Assuming
that the FF factors provided a robust model, this points to
possibility that the stock $\alpha$'s were nonlinear functions of
risk \cite{FH1999}.

\subsection{JSE results for the Fama and French risk factor model}

The cumulative factor returns for the { value} ({\em HML}), size
({\em SMB}) and market (Mkt)  factors are given in Figure
\ref{fig1:HML_SMB} for the Top 250 universe of stocks. The market
factor return was constructed using stock  market capitalisation
values and the factor was re-balanced monthly. The fundamental
factor (market cap data) dates were shifted 1 quarter backward in
time relative to the date the information is documented in the raw
data, since the latter is done with a 1 quarter time lag.
The $\beta$'s were estimated in 6 year rolling windows (72
months).

The study of the Top 250 stock universe uncovered a delayed size
effect. Assessment of  the {\em SMB} factor returns \cite{G2007}
showed a peak 12 months after portfolio formation. By inspection,
there was limited return advantage apparent in the time-series
behaviour of the {\em SMB} factor shown in Figure 1. Nevertheless,
there was still a discernible size-effect.  The value effect is
clearly evident from 1998 through to mid 2005. The importance of
the market factor after 2003 is  visually apparent from the
nominal performance of the factor mimicking portfolio in Figure 1.

\begin{figure}
\includegraphics[width=12cm]{BW_Figure1_WilcoxGebbie.jpg}
\caption{\small The Top 250 {\em HML} (High-Minus-Low)and {\em
SMB} (Small-Minus-Big) factor mimicking portfolios formed from the
6 intersection portfolios as in Eqn's. 5 and Eqn. 6 and reformed
monthly using only the largest 250 stock each month out of 472
stocks listed on the JSE between 31 January 1994 and 30 April 2007
are shown. The {\em HML} (value) factor mimicking portfolio is
given by the solid line, the {\em SMB} (size) factor mimicking
portfolio is given by the dashed line and the market portfolio
{\em Mkt} is given by the dotted line.}\label{fig1:HML_SMB}
\end{figure}

\subsection{Observations for characteristic based models}

Results are summarised for 14 characteristic based models in Table
1 for the 250 stock universe studied. Table entries are the median
characteristic payoffs .

As expected, we find a broad positive loading to book-to-price and
a negative loading to size. This is in agreement with the analysis
using the {\em HML} and {\em SMB} factor loading portfolios. The
value effect increases with increase in universe size, while the
size effect diminishes. This is surprising, since  one would
expect the size effect to be more meaningful in a larger universe
of stocks. When controlling for dividend yield the size effect is
diminished in the Top 50 universe but not significantly diminished
within the Top 100 and Top 250 universes of stocks. The size
effect is also diminished in the presence of momentum.

\normalsize
\begin{table}
\begin{footnotesize}
\begin{tabular}{cccccccccc}
\hline
& \multicolumn{9}{c}{Median Payoffs to Z-scored characteristics [units of\%]}\\
\hline
Model \# & $\alpha$ & $\delta_{_{BVTP}}$ & $\delta_{_{MV}}$ & $\delta_{_{Mkt}}$ & $\delta_{_{MOML}}$ & $\delta_{_{MOMS}}$ & $\delta_{_{EY}}$ & $\delta_{_{DY}}$ & $\delta_{_{VOL}}$ \\
\hline
1 & 1.93 & 0.39 & -0.15 & & & & & & \\
2 & 1.92 & 0.41 & -0.17 & 0.01 & & & & & \\
3 & 1.96 & 0.57 & -0.15 &  & 0.36 & & & & \\
4 & 1.95 & 0.51 & -0.18 & 0.30 & -0.00 & & & & \\
5 & 1.96 & 0.47 & -0.13 & 0.74 & -0.51 & & & & \\
6 & 1.96 & 0.46 & -0.19 & 0.65 & -0.49 & -0.14 & & & \\
7 & 1.99 & 0.49 & -0.15 & 0.57 & -0.54 &  0.12 & & & -0.11 \\
8 & 1.94 & 0.41 & -0.25 & 0.10 & & & & & 0.04\\
9 & 1.75 & 0.44 & -0.06 & 0.60 & -0.52 & 0.43 & -0.19 & & \\
10 & 1.70 & 0.26 & -0.08 & & & & 0.16 & & \\
11 & 1.65 & 0.42 & -0.10 & & 0.49 & -0.52 & 0.26 & 0.13 & \\
12 & 1.85 & 0.36 & -0.20 & & & & & 0.04 & \\
13 & 1.86 & 0.50 & -0.07 & 0.49 & -0.47 & 0.24  & & 0.12 & \\
14 & 1.68 & 0.04 & -0.14 & 0.49 & -0.48 & 0.12 & 0.28 & 0.01 & \\
\hline
\end{tabular}
\end{footnotesize}
  \caption{\small Top 250 stock JSE characteristics based models. The characteristic factors are, from left
to right, the model bias, book-to-price, market value, market
factor, long term momentum, short term momentum, earnings yield,
dividend yield and volume traded. Model \#2 and \#6 are compared
with CAPM and the 3-factor Fama and French APT model in Figures 2
and 3. The dynamics of the payoffs for model \#14 (the medians are
presented here) is shown in Figure 2. }\label{tab:payoffs}
\end{table}
\normalsize

The book-to-price effect is correlated with the earnings yield
(inverse of price-to-earnings), and it is found that the
book-to-price effect can be reduced when controlling for earnings
yield in the presence of size. This apparent multi-collinearity
between book-to-price and earnings yield becomes less effective in
the presence of momentum. This broadly corroborates the identified
ability to substitute book-to-price with price-to-earnings and
size on the JSE \cite{vRR2003a}.

It is also noted the earnings yield and change in volumes traded
provide little additional explanatory power when in the presence
of price-to-book, market value, momentum and a market factor.
Hence, there appears to have been little additional advantage in
using volumes traded, given its  high multi-collinearity with
other factors. The market factor can be substituted with volume
traded.

We do find subtle dependencies on the dividend yield: when
controlling for the loading on the market portfolio one finds that
the effect of the dividend yield changes sign in the Top 50
universe. Long-term momentum is generally positive except when
controlling for the market portfolio. Short term momentum is
negative except when controlling for dividends, earnings and
volumes.

The payoffs to the various characteristics have time dependent
oscillatory dynamics. This is graphically demonstrated in Figure
\ref{fig1:payoff_dynamics} for CBM model \#14 (whose median
payoffs values are in Figure \ref{tab:payoffs} for the full
sample). For example, prior to December 2001 there was a positive
payoff to market value.

This shifted to a negative payoff to market value a year later,
which can be attributed  to the December 2001 crash in the USD/ZAR
exchange rate. Similar pathologies can be seen for almost all the
characteristic payoffs,  demonstrating that price anomalies
associated with payoffs to characteristics were reasonably
short-term.

\begin{figure}
\includegraphics[width=12cm]{BW_Figure2_WilcoxGebbie.jpg}
\caption{\small The Top 250 dynamics of the smoothed payoffs to
the various characteristics used in CBM \#14 from Table
\ref{tab:payoffs} against the change in Tsallis entropy (LOC),
which is a measure of market wide localisation (the more localised
the market the fewer opportunities there are because portfolio
market values are more concentrated on fewer stocks). The dynamic
behaviour of the characteristic payoffs is apparent.
}\label{fig1:payoff_dynamics}
\end{figure}

On a practical note, using an extensive list of characteristics
can lead to data-mining effects. This is particularly important in
a concentrated market such as the JSE. This may arises when
multi-collinearity swamps the model estimation process with noise
effects. It is our view that a model with more than about 10
factors in the SA market will be prone to this flaw.  It is also easy to
select a particular window of data for which the model happens to
work well. This type of error is difficult avoid in a bull market
as almost all the characteristics become coupled to momentum.

We recommend that practitioners opting to use CBM
carry-out tests for randomness in the model outputs in addition to
the usual out-of-sample back-testing. We also recommend scenario
analysis with characteristic shocks to further understand dynamics
under noisy conditions due to the presence of oscillatory cycles
(see Figure \ref{fig1:payoff_dynamics}).

A related concern is that
associated with the liquidity premium. Characteristic based models
constructed with many too factors can result in the identification
of a liquidity premium which cannot be traded.
Finally, we note that equity premia have been shown to include exogenous factors such as currency flows during regional and global crises \cite{WG2007}.

\begin{figure}
\includegraphics[width=12cm, height=5.5cm]{BW_Figure3_WilcoxGebbie_1.jpg}
\includegraphics[width=12cm, height=5.5cm]{BW_Figure3_WilcoxGebbie_2.jpg}
\caption{\small Stocks were quintiled on expected return, with the
highest in the first quintile. The upper graph has the average
annualised returns in the top 250 stock universe for each of the 5
quintiled portfolio's of two characteristic based models and two
risk based models is given. The lower graph depicts the average
volatilities. The first characteristic based model (CBM) uses
market capitalisation, book-to-price and a market factor and
corresponds to CBM \#2 in the Table 1 and is denoted by solid
squares with a thin dashed best fit line. The second CBM is model
\#6 from Table 1, it includes momentum signals and is denoted by
dark circles with a solid line running from the upper left to
lower right. The risk based models (RBM) are the 3-Factor APT
model using the HML, SMB and Mkt factors and CAPM, denoted by
right triangles and a solid dash best fit line and left triangles
and the solid horizontal best fit line respectively. The CBM
models provide realised returns commensurate with the quintile
sorts from highest expected return quintile 1 through to the
lowest expected return quintile 5. As such the CBM model are good
predictors of portfolio wide return commonalities, the RBM models
are not. The lower graph has the volatilities of two risk based
asset pricing models and two characteristic based pricing models
in the top 250 stock universe. The CBM models provide realised
volatilities inversely related to the quintile sorts from highest
expected return quintile 1 through to the lowest expected return
quintile 5. As such the CBM models provide lower volatilities in
quintiles with higher expected returns this is contrary to the RBM
models which expect higher returns with relatively higher
volatilities. }\label{fig1:riskreturn}
\end{figure}

\section{Conclusion}

We have demonstrated that cross-sectional characteristic models have
yielded portfolios with higher excess monthly returns but lower
risk than their risk based factor model counterparts on the JSE between 1994 and 2007.  The outcome is consistent with the Daniel-and-Titman triple sort comparison carried out in \cite{G2007}.
Thus, investors appear to have been rewarded for the self-consistent use of information as
proxied by stock characteristics.

This may  simply have been a reflection of the way information and
risk were priced. In particular, CBM may have priced information
more efficiently if stock specific accounting variables were used
by many investors in that period.  With such models popularised in
academic literature, the price impact of investors using similar
strategies may have influenced price fluctuations in traded
assets.

We have focussed our attention on detecting how size and value
information were reflected in stock prices and of the two models
investigated, the cross-sectional characteristic model was the
better predictor of returns. Extending the pricing kernel further
to incorporate  more prevailing market information, including
other stock characteristics, exchange-traded derivative prices and
credit, liquidity and other risks in an incomplete market, would
more likely confirm a nonlinear price transition kernel.

Characteristic based models are typically nonlinear, but can still
be consistent with assumptions of NFLVR for a market with
non-unique risk-neutral pricing solutions \cite{Chernov2003,
HK1995}.  At the same time, evidence of CBM information pricing
does not imply that a market is free of arbitrage.

In the context of an aggregate influx of capital into the JSE
\cite{WG2007} for the period investigated, this paper highlights
that it was possible to select outperforming portfolios by
incorporating information based on  value and size criteria
directly, as compared to pricing risk information via
Fama-and-French time-series factors. This contributes to the
understanding of how information and risk are priced within a more
general Markovian perspective of  markets.

\section*{Acknowledgements}

The authors thank the participants of the 2008 South African
Finance Association conference, held that the Graduate School of
Business at the University of Cape Town, and participants of the
Summer School on Mathematical Finance held at the African
Institute for Mathematics in February 2008. Criticism from proponents
of strictly linear APT modelling served as motivation for us to reconcile the
evidence for characteristic based pricing.

This research was partially funded by a Carnegie Foundation research grant
administered by the University of the Witwatersrand and an National Research
Foundation NPYY Grant [Number 74223].

redpajama_set_name: RedPajamaArXiv


Great Barrier Reef in Google Maps earlier this year and launching Street View imagery for the Amazon last week, one of the final frontiers we have yet to bring to your favourite computing device has been the Australian outback. One of our top requests from our users is the ability to roam the vast Australian continent. Unfortunately, the remoteness of the outback has posed a challenge for our traditional Street View cars and trikes.
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After announcing tens of thousands of 360-degree panorama pictures of the Great Barrier Reef in Google Maps earlier this year and launching Street View imagery for the Amazon last week, one of the final frontiers we have yet to bring to your favourite computing device has been the Australian outback. One of our top requests from our users is the ability to roam the vast Australian continent. Unfortunately, the remoteness of the outback has posed a challenge for our traditional Street View cars and trikes.


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Home Bulgaria Bulgaria: Defence Minister meets Iraqi, Bosnian, Herzegovinan, and Rwanda counterparts
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Minister Inad further expressed his desire to have and strengthen robust diplomatic ties between the two countries in the sector of the military-technical domain.
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Speaker Bios:
Travor C. Brown is is a Professor of Labour Relations and Human Resources with Memorial University. He has taught at Memorial University, the University of Toronto and University of Ulster. Since joining Memorial University, he has also served as the Associate Dean (Research) and the Director of the Master of Employment Relations program. Much of his research examines issues concerning goal setting and training effectiveness, with special focus on performance management and leadership development. He is currently Associate Editor with Human Resource Development Quarterly.
Paula O'Kane is a senior lecturer in Human Resource Management at the University of Otago in New Zealand. Her research interests sit within the areas of social media in HRM and strategic HRM. She has published articles in Human Resource Management Journal, Personnel Review and Human Resource Development International among others.
Bishakha Mazumdar is Assistant Professor at Shannon School of Business in Cape Breton University. Her primary area of research is re-employment of retirees after retirement (popularly known as bridge employment), performance management and experiential learning. She completed her PhD from Memorial University of Newfoundland.
Martin McCracken is the Research Director at Ulster University Buiness School, UK. His research is focused mainly upon understanding the factors that influence "effective transfer of HRD interventions", "public and voluntary sector change", as well as "Human Resource Management Business Partnering". Since 2010 he has acted as the Editor in Chief of Education and Training (now in its 61styear of publication). Martin has published his work in a number of journals including Work, Employment and Society,Human Resource Management Journal, The International Journal of Human Resource Management and The Journal of Rural Studies.
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When I'm editing a work of fiction, I look for active writing—the life of a novel—on three distinct levels: 1. Voice, 2. Language and, 3. Plot.
Active writing… the antithesis of passive writing. Friends who write and creative writing teachers, editors and agents, publishers and critics and helpful relatives at Thanksgiving dinner—they're always imploring us to "Write active, not passive." So what part of the creative writing process—voice, style or composition—should continually sparkle with activity?
The answer is:Yes, yes and yes. All of the above.
However, breathing life into a novel isn't a singularity. It happens (subliminally or not) on multiple levels during the creation of a novel. I look for the life of a novel on three distinct levels: Voice, Language and Plot. But let's look at voice, first.
Show, don't tell. Meaning… show the reader the gleam of the diamond, the glint of hard steel, the fragrance of new blossoms in the spring—and not simply tell the reader, it's a rock, it's a sword, it was warm.
The statement may be clear and simple—but it's hardly exciting writing. When you allow us to glimpse morsels of your story by using active voice, you're using interpretive sensory details far more illuminating, and pleasing—or horrifying, if that's your intent—to the reader's senses. You're revealing hidden passions or characteristics or secrets that may not otherwise be revealed. You're sifting through the layers of each character, seeking those few gleaming shards that best illustrates the fact that John does indeed hate Mary. You're picking a single carrot out of the stew, and investigating that one morsel in breathtaking detail.
Mary recoiled at her husband's touch. She found his breath cloying, his voice dripping with a sarcastic bitterness that betrayed his disgust with the woman who had once captured his soul.
Or ponder the efficient, yet detached: Joan loved Paul.
Now consider the alternate: She adored the way Paul reached for her hand when they walked together on the beach, or how he touched her face in the moonlight, and whispered her name.
Not once does a writer need to use the words "love" or "hate." Instead, the reader intuits those vibes from the use of richer language. A single tear falling from an eye can be a far more poetic experience than Joan sobbed all day long.
She adored the way Paul reached for her hand….
A pretty basic concept, no? A single, simple sentence evokes an emotion, a bond between Joan and Paul. A confident writer might intuit that no further character development is necessary yet, or else add a line or two more to impart other significant detail about their relationship at the moment. However, lavishing nuance after nuance into another dozen pages would, indeed, complicate the obvious. Once we intuit that Joan indeed loves Paul, it's time to move on. Thus, a writer might begin to scene set, adding details about the endless, palm swept, black-sand beach. Or perhaps it's time to infuse a plot element—introducing that unseen, 18-foot Great White swimming hungrily just beyond the breakers.
She adored Paul because he'd once bought her flowers that had cost twenty dollars at the carnival in Rio, but back then Paul had a part-time job as an undertaker, so he didn't mind spending so much, even though he could have bought roses cheaper down the road at a place called Pepe's, where Paul had once dated a girl named Rita.
Unless any of the above rambling "summary" is later crucial to the plot (or a very specific style choice that's leading somewhere), Paul's former career, the existence of Pepe's or Rita's mention, that information does not belong in the book. And certainly none of it belongs on this beach. If any of the information is later crucial—introduce those elements at the appropriate time. In other words, if we don't meet Rita again for 150 pages, don't mention her in passing now. We certainly won't recall her name! Nor should you expect a reader to carry that baggage for 150 pages. However, if Rita will develop later into a necessary character, give her ample stage-time (if only a few paragraphs), or some specific trait, sufficient for readers to remember her 150 pages hence.
Muse Harbor Publishing's Eileen Workman, Economic Philosopher/Author of "Sacred Economics: The Currency of Life" and former Wall Street Economic Financier/Vice President, shares a hopeful vision for how to create an abundant, harmonious economy that eliminates indebtedness, exploitation and inequality. She will discuss how resurrecting the archetypal energies of The Divine Feminine can help us build a regenerative, sustainable and compassionate society on a global scale.
On February 19th, 2014 at 7 PM PST, controversial political, socio-economic author/blogger Eileen Workman will discuss her book "Sacred Economics"and the rehabilitation of the Divine Feminine here on Voices of The Sacred Feminine Radio, hosted by Karen Tate. Please click on the link above to listen to the show.
Workman and Tate will be discussing the progressive ideas and practical life-tools used to manifest abundance from her book, "Sacred Economics: The Currency of Life" and the return of the Divine Feminine to promote new ways of thinking from the heart for world betterment.
The financial expert and noted economic visionary will provide simple, non-monetary steps that individuals, companies and local governments can take toward building sustainable communities, and peace of mind.
Workman will provide concrete examples of how real-life, self-sustainable, gift-based communities, modeled after natural ecosystems are being created and successfully implemented in cities around the world.
Showing how today's greed has killed many industries, Workman predicts the death of the debt system and explains how these new, gift-based communities are not only here, they are thriving.
In her book, "Sacred Economics: The Currency of Life", available from Amazon, Barnes & Noble, iTunes, and Muse Harbor Publishing, Workman offers a logical analysis of the problems that are undermining the global monetary system. She also maps out steps individuals and governments can take to move beyond our present economic gridlock to create a real sustainable and life-affirming economy.
Workman worked most recently as a First Vice President of Investments with a major international Wall Street firm and draws upon her work experience and extensive research, to present a powerful argument that the outmoded and corrupted vehicle of capitalism cannot sustain us for another generation.
Better to confront our fear, our unknown self, than to run because we're too afraid to ask those questions we've been taught never to ask.
Workman does not blame capitalism for the problems we face. Instead, she questions why society continues to worship the aggressive growth engine that drives our global economy.
Why is debt necessary? How can society overcome greed? Why does poverty exist? Is a moneyless society possible? By carefully deconstructing our shared, often unexamined beliefs around "making the grade" in modern society, Sacred Economics points to an evolutionary opportunity.
Sacred Economics' inspired perspective explains why humans are drawn to the innovation of creative exchange, and how—in the interest of becoming the best we can collectively be—society might direct their attention toward the purposeful design of a more compassionate, cooperative and abundantly flowing economic system.
Ms. Workman, an engaging speaker, financial expert and global economic visionary, can be reached for further Radio, TV, Print and Online interviews or event speaking engagements, by contacting Margaux(at)museharbor(dot)com. Friend Eileen on Facebook to join her blog and conversations on innovative solutions and political/economic philosophies targeting a wide array of current events.
I'm not sure if there's a sage in the world who can teach the secrets of exciting writing. If they can't, I certainly can't either.
I happen to believe that writers, like ball players, concert cellists and chess masters, are born into this world fully equipped with the ability to succeed. Some will never have the chance or the perseverance to fully explore or hone our true talents. Others will spill blood, sweat and tears, but never catch that lucky break. (Sorry, yeah, it's about luck, too.) Sometimes, good writers simply encounter bad timing. Or the wrong agent, or editor, or the wrong publisher. And don't think I haven't lost a sleepless night or two fretting about that last quandary. I have.
She's right. But the biggest tragedy is never knowing. Never trying. The world may indeed be overladen with Studebakers pretending to be Ferraris, but I suspect the world has its fair share of idling Ferraris, glumly assuming they're Studebakers. These are the writers who'll never allow themselves the chance to experience themselves flying balls out down that literary speedway of life. And that's a shame.
As hopeful authors, most of us are capable of crafting and honing our mechanical abilities—we can read creative writing books, we can study language and craft and attend workshops—we're able to eventually intuit a noun from a verb. Because a writer can learn the simple stuff. But you can't learn what can't be taught. You can't learn writing excitement.
When I talk about excitement, I'm talking about a writer's individual style, that unique blend of panache and enthusiasm and articulation. Style can't be bought or taught or handed down, generation to generation. Nobody taught Picasso Cubism. Nobody taught Babe Ruth to hit homers. Nobody taught Einstein to think. They each had it in 'em, all along.
If you have it—and Tom Wolff would call it the right stuff—good for you. Aim for the center field bleachers. If you don't have it, you'll discover that soon enough and move on. Ninety-five percent of wannabe fiction writers move on, and often to even greater endeavors. Ain't no shame in crossing off write a novel from your bucket list, before skiing the Alps or designing a home or discovering cold fusion.
So… do I have advice for those of you attempting to determine your own stylistic prowess? (Does a goose have paté?) I can offer a few suggestions to flint that spark, to perhaps ignite something inside that might never extinguish.
Suggestion #1. New to fiction writing? Overwhelmed by the concept of writing 350 pages end-to-end? Unsure of your own abilities or talent or stamina? Start with smaller bites. Write a short story. Write an idea. Write a slice of life—a simple scene, a simple page with no beginning or no end—with no other agenda than pure enjoyment. Write for yourself. Make yourself smile. If that works… write another page. If you find yourself pouring out your soul, or simply amusing yourself with your own creative genius, perhaps you're onto something. But writing a novel is kinda like giving birth. Give it time. Give it room. If you start pushing too hard at three months you'll only hurt yourself, and the kid'll be thinking WTF, mom?
So…. Rule #3. Always write for yourself. If you find yourself writing for an audience, you'll eventually lose yourself in the crowd. Even if you're successful, sooner or later you'll probably sell your soul. So write to please yourself, first and foremost.
Suggestion #2. Chances are, if you're a writer, you're also a reader. As a reader, what excites you? When I write, I keep a favorite novel on my desk and, most mornings before I begin working, I pick a random page and begin to read. Sometimes I read a few paragraphs, sometimes a few pages. I read until I'm filled with awe and appreciation and amazement that, yeah, that's great stuff. And I can do it too.
By reading snippets, I'm not attempting emulate a writer's style or content—I'm not plagiarizing substance or verbiage—I'm simply trying to jump start my own creative juices by absorbing another writer's creative juices. It's the literary equivalent of a Vulcan Mind-Meld.
Suggestion #4. Keep your voice active. Not passive.
Muse Harbor Publishing's "Awakening Into Perfect Peace" author teaches an easy, proven three-step process to achieving mental peace in his Hummingbird Living School's TeleCourse, over four Wednesdays, February 12th – March 5th. His simple ROAR approach to acceptance and letting go is gaining national popularity as a healer of anxiety, stress and low self-esteem.
On four Wednesdays from February 12 – March 5, 2014, Hummingbird Living School in Santa Fe, New Mexico will host a TeleCourse with Dr. Ralph Huber,popular Communications Expert/Coach and Author of "Awakening Into Perfect Peace: Reflections on Freedom from Suffering." Space is limited and previous courses have sold-out, so listeners are encouraged to register soon by clicking on hummingbirdlivingschool.org.
Ralph Huber is one of the great minds and hearts of our times. 'Awakening Into Perfect Peace' serves as a fertile ground for self-actualization.
Two of Huber's students from a recent workshop said, "I had many significant takeaways including that pain exists but suffering is optional" and "For me, this class gets at the heart of how to live life from peace rather than from anxiety." JB and MH from Santa Fe, New Mexico.
"Awakening" recently launched on 2013's International Day of Peace from Muse Harbor Publishing. It can be found on Amazon.com and museharbor.com.
An engaging, inspirational speaker with practical "inner peace" tools that benefit any reader, listener or viewer, Dr. Huber can be reached for further interviews, including Radio, TV, Print, Online Blogs and event speaking engagements, by contacting Margaux(at)museharbor(dot)com.


Light heartedness, laughing at one's self!
Tears flowing, as I smile, just, for you!
Wash me clean, being human, is challenging me!
I pray to be free!
How, do I bring you back home?
Earth's people, it is time to wake up! The 'Prince' is alive!
Blessed am I, to wake, to the magnificence of such glorious love and beauty!
Now, as an adult, I clearly understand!
That you didn't remind me of that!
Seriousness leading to rigidness, pathway to small mindedness!
Seriousness, up tightness, humourless, imagination vanished, pathway to madness!
Feels like an eternity, as you kiss me, so perfect!
A sinner I am not!
The animal kingdom loves him!
Sharp and cleverly witted, he is!
Not knowing what to do!
High light of my day!
they hand over to me a suspicious fruit.
yet keen as I am, I hurried home with my kit.
then wonder swells over these black slushy balls.
I scuttle across the weeded gardens so bland.
that tumbles across plains; that was what I had.
caught my eyes in the clearing; a green little blot.
so pleasant in texture; so pretty yet unique.
"My child" I called it, ah, so young I was!
Tending it day and night with not a single pause!
Beautifully written! A very simple & heart moving, thought provoking, piece of writing. It is a good teacher! It is a timeless piece that the young & elderly can relate to. A great story/ poem that provokes personal refection. Igniting & connecting one to the spirit of love, devotion, selflessness, commitment & Faith, within. I like how you take the reader on an inner journey NotenSMSK . As we learn about the cycles of life through a young boy who matures into a man of today, who comes to recognise & understand the nature of life, through nature itself. Blessed are we to have trees & nature as our allies & friends! Poems/ stories like this survive the tests of time & live on, for generations to come. I am glad I followed 'latinacrg' (an artist I am watching on dA) to you NortenSMSK.
softcaramelkisses has started a donation pool!
Hello I have now returned back after being away for sometime and I look forward to posting my new poetry and adding more amazing artists work to my art collection.
My personal poetry is my heart and inner voice that now can speak. Poetry assists me in healing within. Poetry helps me to relate with the world and all the people I share this beautiful planet with. My love of artwork also assists me in expressing the different facets of my personality. It speaks of what I have experienced on my lifes journey and who I am as a unique individual.
Thanks for the llama and all the faves!!!


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Life in SpaceMarsShareSubscribe
Here's What's in Lockheed Martin's Mars 2028 Plan
By Rosalie Chan
Filed Under Science, Engineering, Food, NASA, Space Science & Space Travel
In just over a decade, Lockheed Martin will have built a base orbiting Mars. And only a few years later, Mars' surface will have a base camp for astronauts.
On Tuesday at the National Space Club Florida Committee's meeting, Tony Antonelli, Lockheed Martin's chief technologist for civil space exploration and a former NASA space shuttle pilot, spoke about the company's concept for an orbital Mars base by 2028.
The base camp will rely on systems that are already available or in development, and the concept assumes NASA will end International Space Station operations in 2024 and redirect funds to exploration systems.
To get it into space, NASA will leverage the Orion deep space capsule and the Space Launch System, a launch vehicle. This spacecraft orbiting Mars will have Orion capsules on either end, as well as laboratory modules. This six-person mission would last about three years.
On the orbital base, astronauts can search for life, analyze Martian rock and soil samples, study Mars' moons, and find the best place for humans to eventually land. Six astronauts will launch on Orion, which serves as the heart of the Mars base camp ship. Orion will be built with life support, deep space communications, navigation, and Earth re-entry capability.
"Now picture yourself as a scientist or geologist around Mars, and you're able to fly drones, quadcopters and rovers as well," Rob Chambers, Orion spacecraft production lead engineer at Lockheed Martin, tells Inverse. "You can get global exploration in a very short amount of time. You can get access to the entire planet."
By 2033, NASA plans to land humans on Mars, and that's when Lockheed Martin hopes to place a surface base camp on Mars.
"Getting to Mars and landing on Mars are really, really hard," Chambers says. "It's very very difficult, very very challenging, but we've been doing it for decades."
This diagram shows how Lockheed Martin's Mars base camp will work.
Here are some problems Lockheed Martin will need to solve as it prepares to build a base for Mars.
Sustainable Propulsion Technology
For the base, Lockheed Martin plans to use two types of propulsion: solar electric propulsion and chemical propulsion. Solar electric propulsion is highly efficient, as it generates electricity from the sun. The Asteroid Redirect Mission will also utilize solar electric propulsion.
However, just using solar electric propulsion to put supplies into orbit is not enough. While it's highly efficient, using solar electric propulsion alone would take humans three years to get to Mars, Chambers says.
That's why Lockheed Martin will also use chemical propulsion, which includes liquid oxygen and liquid hydrogen fuel. One problem engineers will work on solving is how to keep these fuels cold in orbit, since they can only be liquefied at extremely low temperatures. Spacecraft fueled with liquid hydrogen must be carefully insulated to keep the hydrogen from boiling off.
That being said, chemical propulsion will give the thrust that's needed to get the base into Mars' orbit.
Habitats and Shielding
Inside the Mars base camp, there's a habitat where the crew will live and work.
"They're safely shielded from radiation," Chambers says. "This is where the crew spends most of their waking hours. This is where the high integrity life support is."
Right now, space radiation is a major obstacle preventing humans from taking deep space missions, so this is something Lockheed Martin will have to address. One possible solution is using hydrogen to shield astronauts from galactic cosmic rays.
Humans will also have to shield themselves from solar events. According to Chambers, this problem is easier to address. Engineers plan to build polypropylene (similar to plastic) habitats.
"If there is a solar event, we call out to the crew, and they get into the habitats," Chambers says. "It's like building a fort in your living room and climbing inside there."
In addition, if solar events occur, the crew will wear protective vests.
Deep-Space Communications
The base will use two main forms of communication: radio frequency transmissions and laser communication. With the planned propulsion system, it will provide enough power for radio frequency transmissions.
"Once you're done propelling, you have a really nice power system," Chambers says. "You can pump up the power on RF really high and get good old-fashioned bandwidth."
Laser communication uses flashing lasers to communicate, similar to sailors on two ships flashing lamps at each other. This has previously been tested from the moon to the Earth, and Lockheed Martin plans to use it for the Mars base camp as well.
This is the pillow you'll thank god you have this summer.
However, since Mars is so far away from Earth, there will be obstacles to communication. Literally. For example, as Mars orbits around the sun, it will reach a point where Mars is on one side of the sun, and Earth is on the other. Since the sun is in the way, astronauts on the base camp won't be able to communicate with their friends on Earth for a week.
"For about a week, you won't be able to communicate with the crew because the sun is so noisy from a radio frequency perspective," Chambers says. "That's one of the interesting parts of all this. Can you imagine being 200 million miles away from home and not being able to talk to anyone from home?"
On the orbital space camp, astronauts will eat mostly food with high caloric density that is low in volume and mass. This is because there's only limited space. Astronauts will also grow some food on the base, but they will rely mostly on food they brought aboard.
Once Lockheed Martin builds a base camp on Mars, astronauts can set up larger gardens to grow food like potatoes, sweet potatoes, and strawberries, similar to how Mark Watney from The Martian started his own potato garden.
Scientists from the International Potato Center successfully grew potatoes grown in soil that mimics the Martian earth.
"They can set up larger gardens where you can grow your own food that is both pleasurable and keep you from starving to death," Chambers says.
A Water-Based Economy
Once we start exploring and settling in deep space, the politics will probably be a bit complicated, but astronauts will likely start a water-based economy. After all, we need water to live, and it's versatile for other uses, too — cracking it into oxygen for breathing and burning it for fuel.
"Wherever humans want to go, there's water there," Chambers says. "That's why it's interesting to go there. It really opens up the trade space from a design standpoint.
Scientists believe water can be found on Mars' two moons, Phobos (the large moon) and Deimos (the small moon).
Engineers plan to tap water from Mars' two moons, and having a base in orbit will give astronauts access to these moons. The water used on the base will also be recycled. Right now, engineers are still studying how to recycle water efficiently, especially since it's crucial for survival.
"We believe there's a lot of ice content on those two moons," Chambers says. "If there is, those are orbiting gas stations. If that ice is easy to access, you can drink it, breathe it or use it as rocket fuel."
Media via Lockheed Martin (1, 2), International Potato Center, Flickr / sjrankin
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