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In January 2020, the Center for Science in the Public Interest (CSPI), The Food Trust, Johns Hopkins Bloomberg School of Public Health, and Healthy Eating Research (HER) met for a Healthy Retail Research Convention in Washington, D.C. Attendees included food industry representatives, researchers, and nonprofit organizations. The objective of the convention was to develop a national healthy retail research agenda by (1) determining the effectiveness of government policies, corporate practices, and in-store pilots in promoting healthy eating; (2) identifying gaps in the healthy food retail literature and generating questions for future research, with an intentional focus on reducing health disparities and improving equity; (3) highlighting best practices for partnering with retailers and food manufacturers on healthy retail research; (4) facilitating relationships between retailers and researchers to implement and evaluate retail interventions; and (5) identifying existing datasets, ongoing work, and new opportunities for retail–research partnerships.

trade promotion --- price --- promotion --- placement --- food and beverage --- food retailer --- grocery --- consumer behavior --- marketing --- chronic disease --- choice architecture --- retail food environment --- food purchasing --- federal nutrition assistance --- COVID-19 --- grocery stores --- restaurants --- dietary intake --- food purchase --- policy --- federal nutrition assistance programs --- beverage tax --- menu labeling --- financial incentives --- health disparities --- food access --- nutrition --- healthier food --- dietary behaviors --- review --- grocery store --- restaurant --- environment --- retail --- food purchasing behavior --- diet quality --- diet disparities --- urban --- rural --- socioeconomic --- income disparities --- consumer packaged goods --- packaged foods --- intersectionality --- race --- ethnicity --- socioeconomic status --- grocery retail --- supermarket --- research agenda --- healthy food retail --- food environment --- online food retail --- conceptual framework --- food choices --- online shopping --- retailer policies --- n/a

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Modern financial management is largely about risk management, which is increasingly data-driven. The problem is how to extract information from the data overload. It is here that advanced statistical and machine learning techniques can help. Accordingly, finance, statistics, and data analytics go hand in hand. The purpose of this book is to bring the state-of-art research in these three areas to the fore and especially research that juxtaposes these three.

Index parameter --- estimation --- wrapped stable --- Hill estimator --- characteristic function-based estimator --- asymptotic --- efficiency --- GARCH model --- HARCH model --- PHARCH model --- Griddy-Gibs --- Euro-Dollar --- safe-haven assets --- gold price --- Swiss Franc exchange rate --- oil price --- generalized Birnbaum–Saunders distributions --- ACD models --- Box-Cox transformation --- high-frequency financial data --- goodness-of-fit --- banking competition --- credit risk --- NPLs --- Theil index --- convergence analysis --- interest rates --- yeld curve --- no-arbitrage --- bonds --- B-splines --- time series --- multifractal processes --- fractal scaling --- heavy tails --- long range dependence --- financial models --- Bitcoin --- capital asset pricing model --- estimation of systematic risk --- tests of mean-variance efficiency --- t-distribution --- generalized method of moments --- multifactor asset pricing model --- Lerner index --- stochastic frontiers --- shrinkage estimator --- seemingly unrelated regression model --- multicollinearity --- ridge regression --- financial incentives --- public service motivation --- job performance --- job satisfaction --- intention to leave