Ancient DNA sheds light on the genetic origins of early Iron Age Philistines

The ancient Mediterranean port city of Ashkelon, identified as “}Philistine{”} during the Iron Age, underwent a marked cultural change between the Late Bronze and the early Iron Age. It has been long debated whether this change was driven by a substantial movement of people, possibly linked to a larger migration of the so-called {“}Sea Peoples.{” Here, we report genome-wide data of 10 Bronze and Iron Age individuals from Ashkelon. We find that the early Iron Age population was genetically distinct due to a European-related admixture. This genetic signal is no longer detectible in the later Iron Age population. Our results support that a migration event occurred during the Bronze to Iron Age transition in Ashkelon but did not leave a long-lasting genetic signature

New statistic for financial return distributions: power-law or exponential?

We introduce a new statistical tool (the TP-statistic and TE-statistic) designed specifically to compare the behavior of the sample tail of distributions with power-law and exponential tails as a function of the lower threshold u. One important property of these statistics is that they converge to zero for power laws or for exponentials correspondingly, regardless of the value of the exponent or of the form parameter. This is particularly useful for testing the structure of a distribution (power law or not, exponential or not) independently of the possibility of quantifying the values of the parameters. We apply these statistics to the distribution of returns of one century of daily data for the Dow Jones Industrial Average and over one year of 5-minutes data of the Nasdaq Composite index. Our analysis confirms previous works showing the tendency for the tails to resemble more and more a power law for the highest quantiles but we can detect clear deviations that suggest that the structure of the tails of the distributions of returns is more complex than usually assumed; it is clearly more complex that just a power law.Comment: 20 pages (pdf) with 12 figure

Monte Carlo simulation of uncoupled continuous-time random walks yielding a stochastic solution of the space-time fractional diffusion equation

We present a numerical method for the Monte Carlo simulation of uncoupled continuous-time random walks with a Levy alpha-stable distribution of jumps in space and a Mittag-Leffler distribution of waiting times, and apply it to the stochastic solution of the Cauchy problem for a partial differential equation with fractional derivatives both in space and in time. The one-parameter Mittag-Leffler function is the natural survival probability leading to time-fractional diffusion equations. Transformation methods for Mittag-Leffler random variables were found later than the well-known transformation method by Chambers, Mallows, and Stuck for Levy alpha-stable random variables and so far have not received as much attention; nor have they been used together with the latter in spite of their mathematical relationship due to the geometric stability of the Mittag-Leffler distribution. Combining the two methods, we obtain an accurate approximation of space- and time-fractional diffusion processes almost as easy and fast to compute as for standard diffusion processes.Comment: 7 pages, 5 figures, 1 table. Presented at the Conference on Computing in Economics and Finance in Montreal, 14-16 June 2007; at the conference "Modelling anomalous diffusion and relaxation" in Jerusalem, 23-28 March 2008; et

Bootstrapping Smooth Functions of Slope Parameters and Innovation Variances in VAR(∞) Models *

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/101814/1/1468-2354.t01-1-00016.pd

Massive migration from the steppe is a source for Indo-European languages in Europe

We generated genome-wide data from 69 Europeans who lived between 8,000-3,000 years ago by enriching ancient DNA libraries for a target set of almost four hundred thousand polymorphisms. Enrichment of these positions decreases the sequencing required for genome-wide ancient DNA analysis by a median of around 250-fold, allowing us to study an order of magnitude more individuals than previous studies and to obtain new insights about the past. We show that the populations of western and far eastern Europe followed opposite trajectories between 8,000-5,000 years ago. At the beginning of the Neolithic period in Europe, ~8,000-7,000 years ago, closely related groups of early farmers appeared in Germany, Hungary, and Spain, different from indigenous hunter-gatherers, whereas Russia was inhabited by a distinctive population of hunter-gatherers with high affinity to a ~24,000 year old Siberian6 . By ~6,000-5,000 years ago, a resurgence of hunter-gatherer ancestry had occurred throughout much of Europe, but in Russia, the Yamnaya steppe herders of this time were descended not only from the preceding eastern European hunter-gatherers, but from a population of Near Eastern ancestry. Western and Eastern Europe came into contact ~4,500 years ago, as the Late Neolithic Corded Ware people from Germany traced ~3/4 of their ancestry to the Yamnaya, documenting a massive migration into the heartland of Europe from its eastern periphery. This steppe ancestry persisted in all sampled central Europeans until at least ~3,000 years ago, and is ubiquitous in present-day Europeans. These results provide support for the theory of a steppe origin of at least some of the Indo-European languages of Europe

A new approach to bad news effects on volatilit y: the multiple-sign-volume sensitive regime EGARCH model (MSV-EGARCH)

In this paper, using daily data for six major international stock market indexes and a modified EGARCH specification, the links between stock market returns, volatility and trading volume are investigated in a new nonlinear conditional variance framework with multiple regimes and volume eff ects. Volatility forecast comparisons, using the Harvey-Newbold test for multiple forecasts encompassing, seem to demonstrate that the MSV- EGARCH complex threshold structure is able to correctly fit GARCH- type dynamics of the series under study and dominates competing standard asymmetric models in several of the considered stock indexes.info:eu-repo/semantics/publishedVersio

Stone Age Yersinia pestis genomes shed light on the early evolution, diversity, and ecology of plague

The bacterial pathogenYersinia pestisgave rise to devastating outbreaks throughouthuman history, and ancient DNA evidence has shown it afflicted human populations asfar back as the Neolithic.Y. pestisgenomes recovered from the Eurasian Late Neolithic/Early Bronze Age (LNBA) period have uncovered key evolutionary steps that led to itsemergence from aYersinia pseudotuberculosis-like progenitor; however, the number ofreconstructed LNBA genomes are too few to explore its diversity during this criticalperiod of development. Here, we present 17Y. pestisgenomes dating to 5,000 to 2,500y BP from a wide geographic expanse across Eurasia. This increased dataset enabled usto explore correlations between temporal, geographical, and genetic distance. Ourresults suggest a nonflea-adapted and potentially extinct single lineage that persistedover millennia without significant parallel diversification, accompanied by rapid dis-persal across continents throughout this period, a trend not observed in other pathogensfor which ancient genomes are available. A stepwise pattern of gene loss provides fur-ther clues on its early evolution and potential adaptation. We also discover the presenceof theflea-adapted form ofY. pestisin Bronze Age Iberia, previously only identified inin the Caucasus and the Volga regions, suggesting a much wider geographic spread ofthis form ofY. pestis. Together, these data reveal the dynamic nature of plague’s forma-tive years in terms of its early evolution and ecology