cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3625996
title: Self-supervised retinal thickness prediction enables deep learning from unlabeled data to boost classification of diabetic retinopathy

description: <strong>This data repository contains the OCT images and binary annotations for segmentation of retinal tissue using deep learning. To use, please refer to the Github repository </strong>https://github.com/theislab/DeepRT. <strong>#######</strong> <strong>Access to large, annotated samples represents a considerable challenge for training accurate deep-learning models in medical imaging. While current leading-edge transfer learning from pre-trained models can help with cases lacking data, it limits design choices, and generally results in the use of unnecessarily large models. We propose a novel, self-supervised training scheme for obtaining high-quality, pre-trained networks from unlabeled, cross-modal medical imaging data, which will allow for creating accurate and efficient models. We demonstrate this by accurately predicting optical coherence tomography (OCT)-based retinal thickness measurements from simple infrared (IR) fundus images. Subsequently, learned representations outperformed advanced classifiers on a separate diabetic retinopathy classification task in a scenario of scarce training data. Our cross-modal, three-staged scheme effectively replaced 26,343 diabetic retinopathy annotations with 1,009 semantic segmentations on OCT and reached the same classification accuracy using only 25% of fundus images, without any drawbacks, since OCT is not required for predictions. We expect this concept will also apply to other multimodal clinical data-imaging, health records, and genomics data, and be applicable to corresponding sample-starved learning problems.</strong> <strong>#######</strong>
DOI: 10.25387/g3.9172619
title: Supplemental Materials for Bhatta et al. 2020

description: File S1 contains supplementary Tables S1-S6 and Figures S1-S6. Table S1 contains basic summary statistics with BLUEs, standard error, minimum, maximum, coefficient of variation, broad sense heritability, and proportion of variance component for genotype by environment and genotypic effect for agronomic and malting quality traits evaluated across multiple locations and years. Table S2 contains an analysis of variance with mean squares for agronomic and malting quality traits. Table S3 contains genomic predictive ability for un-phenotyped environments using MT-CV1 and MT-CV2 models. Table S4-S6 contains predictive ability for agronomic and malting quality traits using MT-CV1 and MT-CV2 models. Figure S1 shows a principal component analysis of all individuals. Figure S2 contains a distribution of the 6,482 single nucleotide polymorphisms (SNPs) across the seven chromosomes of barley in 145 double haploid lines. Figures S3-S6 contain Pearson’s correlation among environments (locations-years) for grain yield, number of grains per square meter, grain plumpness, and thousand grain weight, respectively. File S2 contains the BLUEs for the agronomic traits (grain yield, plumpness, thousand grain weight, and number of grains per square meter) from individual experiments (EELE15, EELE16, EEMAC15, EEMAC16, EEMAC17, MOSA15, MOSA16, MUSA15, and MUSA16), experiments across locations (EELE, EEMAC, MOSA, and MUSA), years (2015, 2016, and 2017), and all experiments combined (ALL). File S3 contains the BLUEs for the malting quality traits (beta-glucan content, malt extract, protein content, and soluble nitrogen) from the experiments conducted in 2015 in three locations (EELE, EEMAC, and MOSA) and for the combined experiments (ALL15). <br><br>
DOI: 10.25387/g3.9172619.v1
title: Supplemental Materials for Bhatta et al. 2020

description: File S1 contains supplementary Tables S1-S6 and Figures S1-S6. Table S1 contains basic summary statistics with BLUEs, standard error, minimum, maximum, coefficient of variation, broad sense heritability, and proportion of variance component for genotype by environment and genotypic effect for agronomic and malting quality traits evaluated across multiple locations and years. Table S2 contains an analysis of variance with mean squares for agronomic and malting quality traits. Table S3 contains genomic predictive ability for un-phenotyped environments using MT-CV1 and MT-CV2 models. Table S4-S6 contains predictive ability for agronomic and malting quality traits using MT-CV1 and MT-CV2 models. Figure S1 shows a principal component analysis of all individuals. Figure S2 contains a distribution of the 6,482 single nucleotide polymorphisms (SNPs) across the seven chromosomes of barley in 145 double haploid lines. Figures S3-S6 contain Pearson’s correlation among environments (locations-years) for grain yield, number of grains per square meter, grain plumpness, and thousand grain weight, respectively. File S2 contains the BLUEs for the agronomic traits (grain yield, plumpness, thousand grain weight, and number of grains per square meter) from individual experiments (EELE15, EELE16, EEMAC15, EEMAC16, EEMAC17, MOSA15, MOSA16, MUSA15, and MUSA16), experiments across locations (EELE, EEMAC, MOSA, and MUSA), years (2015, 2016, and 2017), and all experiments combined (ALL). File S3 contains the BLUEs for the malting quality traits (beta-glucan content, malt extract, protein content, and soluble nitrogen) from the experiments conducted in 2015 in three locations (EELE, EEMAC, and MOSA) and for the combined experiments (ALL15). <br><br>
DOI: 10.34725/dvn/mn9nrd/3dw8oh
title: 3.Product.tab

description: Raw data for the Product form in Western Ghats.
DOI: 10.34725/dvn/mn9nrd/5axiaq
title: 2.Forest form.7z
DOI: 10.34725/dvn/mn9nrd/cd1e50
title: 2.Product form.7z
DOI: 10.34725/dvn/mn9nrd/htbehp
title: SL_Settlement_Form.pdf
DOI: 10.34725/dvn/mn9nrd/ifbnqs
title: Forest_Form.pdf
DOI: 10.34725/dvn/mn9nrd/jhlkxp
title: 2.Forest form.7z
DOI: 10.34725/dvn/mn9nrd/o2rgqy
title: Association form.7z
DOI: 10.34725/dvn/mn9nrd/usn2yh
title: 3.Settlement-1.tab

description: Raw data for the Settlement form in Western Ghats.
DOI: 10.34725/dvn/mn9nrd/vzb64w
title: 2.Agroforestry systems.7z
DOI: 10.34725/dvn/mn9nrd/5zdbxx
title: Product form.7z
DOI: 10.34725/dvn/mn9nrd/9frlfn
title: Association form.7z
DOI: 10.34725/dvn/mn9nrd/on78yu
title: SL_Product_Form_R.pdf
DOI: 10.34725/dvn/mn9nrd/pklvim
title: 3.Association.tab

description: Raw data for the Association form in Western Ghats.
DOI: 10.34725/dvn/mn9nrd/pmvnzw
title: Disclaimer.pdf
DOI: 10.34725/dvn/mn9nrd/q55eoj
title: 0.Disclaimer.pdf
DOI: 10.34725/dvn/mn9nrd/rloe4h
title: 1.SL_Settlement_Form.pdf
DOI: 10.34725/dvn/mn9nrd/v2uvfu
title: 1.Forest_Form.pdf
DOI: 10.5281/zenodo.3605620
title: Global Dataset of Ecohydrological Parameters Inferred from Satellite Observations

description: This dataset contains global maps of (1) ecohydrological parameters for a theoretical model of the probability distribution of soil saturation;<br> (2) convergence, uncertainty and goodness-of-fit diagnostics; and<br> (3) soil water stress and uptake indexes, associated with analysis in: Bassiouni, M., S.P. Good, C.J. Still, and C.W. Higgins (2020), Plant water uptake thresholds inferred from satellite soil moisture. Geophysical Research Letters. https://doi.org/10.1029/2020GL087077 All variable descriptions and units are included in the .nc metadata. Code associated with this dataset are publicly available:<br> Probabilistic Inference of Ecohydrological Parameters (PIEP): http://doi.org/10.5281/zenodo.1257718.<br> Data Management for Global PIEP: http://doi.org/10.5281/zenodo.3235820 <strong>Abstract</strong><br> Empirical functions are widely used in hydrological, agricultural, and earth system models to parameterize plant water uptake. We infer soil water potentials at which uptake is downregulated from its maximum rate and at which uptake is zero, in biomes with &lt; 60% woody vegetation at 36-km grid resolution. We estimate thresholds through Bayesian inference using a stochastic water balance framework to construct theoretical soil moisture probability distributions consistent with satellite surface soil moisture. The global median Nash–Sutcliffe efficiency between empirical soil moisture distributions derived from satellite soil moisture observations and best-fit theoretical distributions using inferred parameters is 0.8. Spatially variable thresholds capture location-specific vegetation and climate characteristics and can be connected to biome-level water uptake strategies.
DOI: 10.5281/zenodo.3626075
title: Snow depth map and land cover map from satellite photogrammetry (Pleiades) in Tuolumne, California.

description: <strong>snow_depth_20170501_pleiades.tif</strong> Snow depth from the difference of digital elevation models (DEMs) calculated from Pléiades images. The snow-on DEMs were acquired on 2017-05-01. The snow-off DEMs were acquired on 2017-08-08 and 2017-08-13. <strong>land_cover_20170813-08_pleiades.tif land_cover_20170501_pleiades.tif</strong> Land cover calculated from multi-spectral Pléiades images acquired on 2017-05-01 (snow-on) and 2017-08-08 and -13 (snow-off). Classes are snow (1), forest (2), bare rock/low vegetation (3), lake (4).
DOI: 10.34725/dvn/mn9nrd/1yovmq
title: Association form.7z
DOI: 10.34725/dvn/mn9nrd/3a2fqr
title: 1.Association_Form_A.pdf
DOI: 10.34725/dvn/mn9nrd/b56d6l
title: 3.Settlement.tab

description: Raw data for the Settlement form in Western Ghats.
DOI: 10.34725/dvn/mn9nrd/buhyzb
title: Agroforestry systems.7z
DOI: 10.34725/dvn/mn9nrd/epjgag
title: 2.Product form.7z
DOI: 10.34725/dvn/mn9nrd/mp0r8i
title: 1.SL_Settlement_Form.pdf
DOI: 10.34725/dvn/mn9nrd/p7ih4s
title: Settlement form.7z
DOI: 10.34725/dvn/mn9nrd/skxnpx
title: Product.tab

description: Raw data for the Product form in Western Ghats.
DOI: 10.34725/dvn/mn9nrd/ucqcis
title: Disclaimer.pdf
DOI: 10.34725/dvn/mn9nrd/viko1o
title: 3.Product.tab

description: Raw data for the Product form in Western Ghats.
DOI: 10.5281/zenodo.3625174
title: UBL000035549 - Ordonnantien, Instructien, Reglementen, ... van Burgemeesters en Raad der Stad Groningen, van 1655 tot 1732, Volume 2

description: Titel: <em> </em><em>Ordonnantien, Instructien, Reglementen, ... van Burgemeesters en Raad der Stad Groningen, van 1655 tot 1732</em><em>, Volume 2</em> Publisher: Cornelis Barlinckhof Place: Groningen Year: 1681 Used version: The copy we used for the transcriptions is held at Leiden University Library and digitised by the KB National Library of the Netherlands. Link digitised version of the book: https://books.google.nl/books?id=PxMV-YdPnfcC (Main) Language: Dutch. Province: Groningen (city) Font: Gothic. Model used: Dutch_Gothic_Print. Version of Transkribus used: v.1.9.1. Other info: Abbyy FineReader v.11 has been used. Link model: For more information on the HTR-model used, please visit: https://lab.kb.nl/dataset/entangled-histories-ordinances-low-countries. Transcription conventions: The abbreviations have been written out into full words. The hyphens at the end of a line have been kept (when there). If you are in need of the original scans of the documents, please contact dataservices@kb.nl. This transcription is part of the dataset created with the ‘Entangled Histories’-project. PI: dr. C.A. Romein;<br> Scientific Programmer: S.F. Veldhoen, MSc;<br> Project Manager: drs. M. de Gruijter.
DOI: 10.5281/zenodo.3626074
title: Snow depth map and land cover map from satellite photogrammetry (Pleiades) in Tuolumne, California.

description: <strong>snow_depth_20170501_pleiades.tif</strong> Snow depth from the difference of digital elevation models (DEMs) calculated from Pléiades images. The snow-on DEMs were acquired on 2017-05-01. The snow-off DEMs were acquired on 2017-08-08 and 2017-08-13. <strong>land_cover_20170813-08_pleiades.tif land_cover_20170501_pleiades.tif</strong> Land cover calculated from multi-spectral Pléiades images acquired on 2017-05-01 (snow-on) and 2017-08-08 and -13 (snow-off). Classes are snow (1), forest (2), bare rock/low vegetation (3), lake (4).
DOI: 10.34725/dvn/mn9nrd/dmok2g
title: Agroforestry systems.7z
DOI: 10.34725/dvn/mn9nrd/gkptxa
title: Settlement.tab

description: Raw data for the Settlement form in Western Ghats.
DOI: 10.34725/dvn/mn9nrd/h7nyur
title: 0.Disclaimer.pdf
DOI: 10.34725/dvn/mn9nrd/tm4fz4
title: 3.Association.tab

description: Raw data for the Association form in Western Ghats.
DOI: 10.34725/dvn/mn9nrd/trchyx
title: 2.Association form.7z
DOI: 10.34725/dvn/mn9nrd/y1mp42
title: SL_Settlement_Form.pdf
DOI: 10.34725/dvn/mn9nrd/zpkhxp
title: 3.Forest.tab

description: Raw data for the Forest form in Western Ghats.
DOI: 10.3886/e113940v1-21935
title: Replication data for: Pricing in the Market for Anticancer Drugs

description: In 2011, Bristol-Myers Squibb set the price of its newly approved melanoma drug ipilimumab— brand name Yervoy—at $120,000 for a course of therapy. The drug was associated with an incremental increase in life expectancy of four months. Drugs like ipilimumab have fueled the perception that the launch prices of new anticancer drugs and other drugs in the so-called "specialty" pharmaceutical market have been increasing over time and that increases are unrelated to the magnitude of the expected health benefits. In this paper, we discuss the unique features of the market for anticancer drugs and assess trends in the launch prices for 58 anticancer drugs approved between 1995 and 2013 in the United States. We restrict attention to anticancer drugs because the use of median survival time as a primary outcome measure provides a common, objective scale for quantifying the incremental benefit of new products. We find that the average launch price of anticancer drugs, adjusted for inflation and health benefits, increased by 10 percent annually—or an average of $8,500 per year—from 1995 to 2013. We argue that the institutional features of the market for anticancer drugs enable manufacturers to set the prices of new products at or slightly above the prices of existing therapies, giving rise to an upward trend in launch prices. Government-mandated price discounts for certain classes of buyers may have also contributed to launch price increases as firms sought to offset the growth in the discount segment by setting higher prices for the remainder of the market.
DOI: 10.5281/zenodo.3625173
title: UBL000035549 - Ordonnantien, Instructien, Reglementen, ... van Burgemeesters en Raad der Stad Groningen, van 1655 tot 1732, Volume 2

description: Titel: <em> </em><em>Ordonnantien, Instructien, Reglementen, ... van Burgemeesters en Raad der Stad Groningen, van 1655 tot 1732</em><em>, Volume 2</em> Publisher: Cornelis Barlinckhof Place: Groningen Year: 1681 Used version: The copy we used for the transcriptions is held at Leiden University Library and digitised by the KB National Library of the Netherlands. Link digitised version of the book: https://books.google.nl/books?id=PxMV-YdPnfcC (Main) Language: Dutch. Province: Groningen (city) Font: Gothic. Model used: Dutch_Gothic_Print. Version of Transkribus used: v.1.9.1. Other info: Abbyy FineReader v.11 has been used. Link model: For more information on the HTR-model used, please visit: https://lab.kb.nl/dataset/entangled-histories-ordinances-low-countries. Transcription conventions: The abbreviations have been written out into full words. The hyphens at the end of a line have been kept (when there). If you are in need of the original scans of the documents, please contact dataservices@kb.nl. This transcription is part of the dataset created with the ‘Entangled Histories’-project. PI: dr. C.A. Romein;<br> Scientific Programmer: S.F. Veldhoen, MSc;<br> Project Manager: drs. M. de Gruijter.
DOI: 10.5281/zenodo.3625783
title: PubMed IDs from CENTRAL for the year 2016 - for RCT filter paper

description: PubMed IDs from CENTRAL for the year 2016 - for RCT filter paper
DOI: 10.5281/zenodo.3625784
title: PubMed IDs from CENTRAL for the year 2016 - for RCT filter paper

description: PubMed IDs from CENTRAL for the year 2016 - for RCT filter paper
DOI: 10.5281/zenodo.3625991
title: Pre-computed features used for evaluating MS-TCN

description: I3D features for 50Salads, GTEA and the Breakfast datasets that are used for evaluation in "Abu Farha and Gall, MS-TCN: Multi-Stage Temporal Convolutional Network for ActionSegmentation, CVPR 2019 "
DOI: 10.5281/zenodo.3625992
title: Pre-computed features used for evaluating MS-TCN

description: I3D features for 50Salads, GTEA and the Breakfast datasets that are used for evaluation in "Abu Farha and Gall, MS-TCN: Multi-Stage Temporal Convolutional Network for ActionSegmentation, CVPR 2019 "
DOI: 10.34725/dvn/mn9nrd/7vbaie
title: 1.Forest_Form.pdf
DOI: 10.34725/dvn/mn9nrd/bomoxt
title: 3.Product.tab

description: Raw data for the Product form in Western Ghats.
DOI: 10.34725/dvn/mn9nrd/dwjr0r
title: Forest_Form.pdf
DOI: 10.34725/dvn/mn9nrd/fnpxdx
title: Product form.7z
DOI: 10.34725/dvn/mn9nrd/ftlbqi
title: Disclaimer.pdf
DOI: 10.34725/dvn/mn9nrd/iyiuli
title: Product form.7z
DOI: 10.34725/dvn/mn9nrd/juad8u
title: 1.Association_Form_A.pdf
DOI: 10.34725/dvn/mn9nrd/mzz3wf
title: SL_Settlement_Form.pdf
DOI: 10.34725/dvn/mn9nrd/uvzhxo
title: Association_Form_A.pdf
DOI: 10.34725/dvn/mn9nrd/e22b7b
title: 2.Forest form.7z
DOI: 10.34725/dvn/mn9nrd/hsolkz
title: 1.SL_Product_Form_R.pdf
DOI: 10.34725/dvn/mn9nrd/jcum3q
title: 3.Association.tab

description: Raw data for the Association form in Western Ghats.
DOI: 10.34725/dvn/mn9nrd/npsuai
title: 2.Settlement form.7z
DOI: 10.34725/dvn/mn9nrd/qqmdop
title: 1.SL_Product_Form_R.pdf
DOI: 10.34725/dvn/mn9nrd/wqffrz
title: 2.Settlement form.7z
DOI: 10.34725/dvn/mn9nrd/xaaom1
title: 2.Association form.7z
DOI: 10.34725/dvn/mn9nrd/yw5sbg
title: Settlement form.7z
DOI: 10.34725/dvn/mn9nrd/znpztx
title: 3.Settlement.tab

description: Raw data for the Settlement form in Western Ghats.
DOI: 10.5066/p9s4mob6
title: Geospatial datasets for estimating depth to the top of the Dakota Sandstone, Ute Mountain Ute Reservation, Colorado, 2017

description: Geospatial datasets were developed to estimate the depth to the top of the Dakota Sandstone in feet below land surface datum within the Ute Mountain Ute Reservation in Colorado. This study was completed by the U.S. Geological Survey (USGS) in cooperation with the Ute Mountain Ute Tribe. One dataset was created for the contours showing the altitude (in feet) of the top of the Dakota Sandstone (shapefile Kd_talt_hand), and a second dataset was created for polygons representing the outcrops of the Dakota Sandstone (shapefile Dakota_outcrop_poly). These two datasets were used in combination with USGS digital elevation models (DEM) to create a dataset for the depth of the top of the Dakota Sandstone below the land surface contoured at a 100-foot interval (shapefile kd_depth_ci100). The kd_depth_ci100 dataset was used to generate a figure showing the generalized depth to the top of the Dakota Sandstone in feet below land surface in Bauch and Arnold (2019). Bauch, N.J., and Arnold, L.R., 2019, Hydrogeologic characterization, groundwater chemistry, and vulnerability assessment, Ute Mountain Ute Reservation, Colorado and Utah: U.S. Geological Survey Science Investigations Report 2019-5122, https://doi.org/10.3133/sir20195122, in press.
DOI: 10.34725/dvn/mn9nrd/0e9tqp
title: Forest.tab

description: Raw data for the Forest form in Western Ghats.
DOI: 10.34725/dvn/mn9nrd/3jd2h1
title: 2.Settlement form.7z
DOI: 10.34725/dvn/mn9nrd/evncnh
title: Forest form.7z
DOI: 10.34725/dvn/mn9nrd/fzyq96
title: 3.Product.tab

description: Raw data for the Product form in Western Ghats.
DOI: 10.34725/dvn/mn9nrd/hvjmys
title: 2.Agroforestry systems.7z
DOI: 10.34725/dvn/mn9nrd/nc5jlm
title: 2.Settlement form.7z
DOI: 10.34725/dvn/mn9nrd/oqo0ec
title: Product form.7z
DOI: 10.34725/dvn/mn9nrd/th3fqv
title: Association_Form_A.pdf
DOI: 10.17632/tb38t5f2gr.1
title: "Data on Cytoprotective and Anti-inflammatory activities of seagrass Halophila beccarii"

description: The seagrass collected from marine sediments was extracted with aqueous and organic solvents, bioactive metabolites were identified and the anti-inflammatory activity of seagrass extract was analyzed using LPS-stimulated RAW 264.7 as in vitro model. Seagrass extract was found to be non-toxic and showed potential activity against pro-inflammatory markers such as COX-2 and NO2
DOI: 10.34725/dvn/mn9nrd/dg9ime
title: 2.Agroforestry systems.7z
DOI: 10.34725/dvn/mn9nrd/dgxo73
title: Agroforestry systems.7z
DOI: 10.34725/dvn/mn9nrd/eygmxv
title: Forest_Form.pdf
DOI: 10.34725/dvn/mn9nrd/f2owwg
title: 1.Association_Form_A.pdf
DOI: 10.34725/dvn/mn9nrd/gurtrt
title: 0.Disclaimer.pdf
DOI: 10.34725/dvn/mn9nrd/nsqszs
title: Settlement form.7z
DOI: 10.34725/dvn/mn9nrd/x5nfee
title: 1.Forest_Form.pdf
DOI: 10.34725/dvn/mn9nrd/z6lcwq
title: 2.Association form.7z
DOI: 10.34725/dvn/mn9nrd/zdex3d
title: Forest form.7z
DOI: 10.17632/76knkx3fzv.2
title: ReCAN Data - Reverse engineering of Controller Area Networks

description: Abstract --------- This article details the methodology and the approach used to extract and decode the data obtained from the Controller Area Network (CAN) buses in three personal vehicles and four commercial trucks. The dataset is composed of two complementary parts, namely the raw data and the decoded ones. Along with the description of the data, this article also reports both hardware and software requirements to firstly extract the data from the vehicles and secondly decode the binary data frames to obtain the actual sensors' data. Finally, necessary code snippets have been described in pseudo-code and will be publicly available in a code repository. Preliminary results suggest that motivated enough actors may intercept, interact and recognize the vehicle data with consumer-grade technology, ultimately refuting, once-again, the security-through-obscurity paradigm used by automotive manufacturer as main defensive countermeasure. Keywords ---------- Automotive; Controller Area Network (CAN); Reverse Engineering; Dataset Type of data ------------- - RAW: CSV files with timestamp, CANline, ECU identifier, binary data - Decoded: CSV files with timestamp, CANline, ECU identifier, variable, value How data where acquired ---------------------------- Controller Area Network (CAN) buses have been accessed using a standard CAN connector and a CANtact board. The CAN Utils library, publicly available in the Linux Kernel, has been used to intercept the network traffic of the vehicle. Sensors data have been decoded using state-of-the-art algorithm. Source code for each step of the analysis is publicly available in the repository, as specified below. Parameters: - Cars: 500k baudrate, connected o the OBD-II port of each vehicle. - Trucks: 500k baudrate, connected both to the OBD-II port and to a second wire into a second CAN bus. Source code ------------- - Repository: ReCAN Source - Reverse engineering of Controller Area Networks - Provider: Github - Identification number: 10.5281/zenodo.3625715 - URL: https://github.com/Cyberdefence-Lab-Murcia/ReCAN Acknowledgments -------------------- This study was founded by a predoctoral grant from the Spanish National Cybersecurity Institute (INCIBE) within the program "Ayudas para la Excelencia de los Equipos de Investigación Avanzada en Ciberseguridad" ("Grants for the Excellence of Advanced Cybersecurity Research Teams"), with code INCIBEI-2015-27353; a predoctoral travel grant within the program "Ayudas para estancias en el estranjero de alumnos de doctorado en las líneas de actuación de Campus Mare Nostrum" ("Grants for stays abroad of Ph.D. students within the lines of action of Campus Mare Nostrum'').
DOI: 10.17632/7mym92twyp.1
title: Variance premia in developed and emerging equity markets

description: The variance premia of developed markets (as proxied by MSCI EAFE Index), emerging markets (as proxied by MSCI Emerging Markets Index) and the US market (as proxied by S&P500 index). We define the Variance Risk Premium (VRP) as the difference between the ex-post realized return variation and the ex-ante risk-neutral expectation of the future return variation, as proxied by the respective implied volatility index.