3,350 research outputs found
Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances
We propose a new class of models specifically tailored for spatio-temporal
data analysis. To this end, we generalize the spatial autoregressive model with
autoregressive and heteroskedastic disturbances, i.e. SARAR(1,1), by exploiting
the recent advancements in Score Driven (SD) models typically used in time
series econometrics. In particular, we allow for time-varying spatial
autoregressive coefficients as well as time-varying regressor coefficients and
cross-sectional standard deviations. We report an extensive Monte Carlo
simulation study in order to investigate the finite sample properties of the
Maximum Likelihood estimator for the new class of models as well as its
flexibility in explaining several dynamic spatial dependence processes. The new
proposed class of models are found to be economically preferred by rational
investors through an application in portfolio optimization.Comment: 33 pages, 5 figure
The period change of the Cepheid Polaris suggests enhanced mass loss
Polaris is one of the most observed stars in the night sky, with recorded
observations spanning more than 200 years. From these observations, one can
study the real-time evolution of Polaris via the secular rate of change of the
pulsation period. However, the measurements of the rate of period change do not
agree with predictions from state-of-the-art stellar evolution models. We show
that this may imply that Polaris is currently losing mass at a rate of yr based on the difference between modeled and
observed rates of period change, consistent with pulsation-enhanced Cepheid
mass loss. A relation between the rate of period change and mass loss has
important implications for understanding stellar evolution and pulsation, and
provides insight into the current Cepheid mass discrepancy.Comment: 5 pages, 4 figures, compiled using emulateapj, Accepted for
publication in ApJ Letters. Fixed correction in titl
Factor-mimicking portfolios for climate risk
We propose and implement a procedure to optimally hedge climate change risk. First, we construct climate risk indices through textual analysis of newspapers. Second, we present a new approach to compute factor-mimicking portfolios to build climate risk hedge portfolios. The new mimicking portfolio approach is much more efficient than traditional sorting or maximum correlation approaches by taking into account new methodologies of estimating large-dimensional covariance matrices in short samples. In an extensive empirical out-of-sample performance test, we demonstrate the superior all-around performance delivering markedly higher and statistically significant alphas and betas with the climate risk indices
Fokker-Planck equation of distributions of financial returns and power laws
Our purpose is to relate the Fokker-Planck formalism proposed by [Friedrich
et al., Phys. Rev. Lett. 84, 5224 (2000)] for the distribution of stock market
returns to the empirically well-established power law distribution with an
exponent in the range 3-5. We show how to use Friedrich et al.'s formalism to
predict that the distribution of returns is indeed asymptotically a power law
with an exponent mu that can be determined from the Kramers-Moyal coefficients
determined by Friedrich et al. However, with their values determined for the
U.S. dollar-German mark exchange rates, the exponent mu predicted from their
theory is found around 12, in disagreement with the often-quoted value between
3 and 5. This could be explained by the fact that the large asymptotic value of
12 does not apply to real data that lie still far from the stationary state of
the Fokker-Planck description. Another possibility is that power laws are
inadequate. The mechanism for the power law is based on the presence of
multiplicative noise across time-scales, which is different from the
multiplicative noise at fixed time-scales implicit in the ARCH models developed
in the Finance literature.Comment: 11 pages, in press in Physica
A Quest for Justice in Cuzco, Peru:Race and Evidence in the Case of Mercedes Ccorimanya Lavilla
The life of Mercedes Ccorimanya Lavilla renders a telling portrait of the pursuit of justice in Cuzco, Peru, revealing how courts of law can be key sites in the production and negotiation of racial and gender taxonomies. Mercedes (who was gang-raped as a young woman) illustrates the near-heroic efforts necessary to mount and pursue rape charges in Peruvian courts, where rape victims largely manage the construction of evidence in lieu of the state. In the following article, I reconstruct the social circumstances and legal institutional setting surrounding the rape trial of Mercedes Ccorimanya Lavilla through the use of historical and ethnographic materials. In arguing that race mutually defines women's sexuality in rural Peru, I show how (in order to achieve a conviction) Mercedes had to develop a strategy in which she instrumentally employed the languages of race to distance herself from her own indigeneity, as well as that of her alleged attackers
Large dynamic covariance matrices: Enhancements based on intraday data
Multivariate GARCH models do not perform well in large dimensions due to the so-called curse of dimensionality. The recent DCC-NL model of Engle et al. (2019) is able to overcome this curse via nonlinear shrinkage estimation of the unconditional correlation matrix. In this paper, we show how performance can be increased further by using open/high/low/close (OHLC) price data instead of simply using daily returns. A key innovation, for the improved modeling of not only dynamic variances but also of dynamic correlations, is the concept of a regularized return, obtained from a volatility proxy in conjunction with a smoothed sign of the observed return
Revisiting the Simplicity Constraints and Coherent Intertwiners
In the context of loop quantum gravity and spinfoam models, the simplicity
constraints are essential in that they allow to write general relativity as a
constrained topological BF theory. In this work, we apply the recently
developed U(N) framework for SU(2) intertwiners to the issue of imposing the
simplicity constraints to spin network states. More particularly, we focus on
solving them on individual intertwiners in the 4d Euclidean theory. We review
the standard way of solving the simplicity constraints using coherent
intertwiners and we explain how these fit within the U(N) framework. Then we
show how these constraints can be written as a closed u(N) algebra and we
propose a set of U(N) coherent states that solves all the simplicity
constraints weakly for an arbitrary Immirzi parameter.Comment: 28 page
Colored Group Field Theory
Group field theories are higher dimensional generalizations of matrix models.
Their Feynman graphs are fat and in addition to vertices, edges and faces, they
also contain higher dimensional cells, called bubbles. In this paper, we
propose a new, fermionic Group Field Theory, posessing a color symmetry, and
take the first steps in a systematic study of the topological properties of its
graphs. Unlike its bosonic counterpart, the bubbles of the Feynman graphs of
this theory are well defined and readily identified. We prove that this graphs
are combinatorial cellular complexes. We define and study the cellular homology
of this graphs. Furthermore we define a homotopy transformation appropriate to
this graphs. Finally, the amplitude of the Feynman graphs is shown to be
related to the fundamental group of the cellular complex
Transaction fees and optimal rebalancing in the growth-optimal portfolio
The growth-optimal portfolio optimization strategy pioneered by Kelly is
based on constant portfolio rebalancing which makes it sensitive to transaction
fees. We examine the effect of fees on an example of a risky asset with a
binary return distribution and show that the fees may give rise to an optimal
period of portfolio rebalancing. The optimal period is found analytically in
the case of lognormal returns. This result is consequently generalized and
numerically verified for broad return distributions and returns generated by a
GARCH process. Finally we study the case when investment is rebalanced only
partially and show that this strategy can improve the investment long-term
growth rate more than optimization of the rebalancing period.Comment: 17 pages, 7 figure
Flipped spinfoam vertex and loop gravity
We introduce a vertex amplitude for 4d loop quantum gravity. We derive it
from a conventional quantization of a Regge discretization of euclidean general
relativity. This yields a spinfoam sum that corrects some difficulties of the
Barrett-Crane theory. The second class simplicity constraints are imposed
weakly, and not strongly as in Barrett-Crane theory. Thanks to a flip in the
quantum algebra, the boundary states turn out to match those of SO(3) loop
quantum gravity -- the two can be identified as eigenstates of the same
physical quantities -- providing a solution to the problem of connecting the
covariant SO(4) spinfoam formalism with the canonical SO(3) spin-network one.
The vertex amplitude is SO(3) and SO(4)-covariant. It rectifies the triviality
of the intertwiner dependence of the Barrett-Crane vertex, which is responsible
for its failure to yield the correct propagator tensorial structure. The
construction provides also an independent derivation of the kinematics of loop
quantum gravity and of the result that geometry is quantized.Comment: 37 pages, 4 figure
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