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Uncertainty plays an important role in the global economy. In this paper, the economic policy uncertainty (EPU) indices of the United States and China are selected as the proxy variable corresponding to the uncertainty of national economic…

Statistical Finance · Quantitative Finance 2020-07-28 Peng-Fei Dai , Xiong Xiong , Wei-Xing Zhou

Economic Policy Uncertainty (EPU) represents the uncertainty realized by the investors during economic policy alterations. EPU is a critical indicator in economic studies to predict future investments, the unemployment rate, and recessions.…

Computers and Society · Computer Science 2023-08-22 Fatemeh Kaveh-Yazdy , Sajjad Zarifzadeh

Economic Policy Uncertainty (EPU) is a critical indicator in economic studies, while it can be used to forecast a recession. Under higher levels of uncertainty, firms' owners cut their investment, which leads to a longer post-recession…

Computation and Language · Computer Science 2021-05-12 Fatemeh Kaveh-Yazdy , Sajjad Zarifzadeh

This paper constructs internationally consistent measures of macroeconomic uncertainty. Our econometric framework extracts uncertainty from revisions in data obtained from standardized national accounts. Applying our model to post-WWII…

Econometrics · Economics 2021-01-01 Andreas Dibiasi , Samad Sarferaz

China has experienced an outstanding economic expansion during the past decades, however, literature on non-monetary metrics that reveal the status of China's regional economic development are still lacking. In this paper, we fill this gap…

Economics · Quantitative Finance 2017-12-19 Jian Gao , Tao Zhou

We define a Hidden Markov Model (HMM) in which each hidden state has time-dependent $\textit{activity levels}$ that drive transitions and emissions, and show how to estimate its parameters. Our construction is motivated by the problem of…

Machine Learning · Statistics 2015-07-28 David A. Meyer , Asif Shakeel

Time series subject to change in regime have attracted much interest in domains such as econometry, finance or meteorology. For discrete-valued regimes, some models such as the popular Hidden Markov Chain (HMC) describe time series whose…

Machine Learning · Computer Science 2021-02-26 Fatoumata Dama , Christine Sinoquet

This study investigates the relationship between the market volatility of the iShares Asia 50 ETF (AIA) and economic and market sentiment indicators from the United States, China, and globally during periods of economic uncertainty.…

Econometrics · Economics 2025-07-23 Bahram Adrangi , Arjun Chatrath , Saman Hatamerad , Kambiz Raffiee

Land use land cover changes (LULCC) are generally modeled using multi-scale spatio-temporal variables. Recently, Markov Chain (MC) has been used to model LULCC. However, the model is derived from the proportion of LULCC observed over a…

Applications · Statistics 2020-07-02 Piyush Yadav , Shamsuddin Ladha , Shailesh Deshpande , Edward Curry

The Economic Policy Uncertainty index had gained considerable traction with both academics and policy practitioners. Here, we analyse news feed data to construct a simple, general measure of uncertainty in the United States using a highly…

Econometrics · Economics 2020-06-12 Rickard Nyman , Paul Ormerod

In its semi-strong form, the Efficient Market Hypothesis (EMH) implies that technical analysis will not reveal any hidden statistical trends via intermarket data analysis. If technical analysis on intermarket data reveals trends which can…

Statistical Finance · Quantitative Finance 2022-12-22 N'yoma Diamond , Grant Perkins

This paper evaluates the dynamic response of economic activity to shocks in uncertainty as percieved by agents.The study focuses on the comparison between the perception of economic uncertainty by manufacturers and consumers.Since…

Applications · Statistics 2020-12-02 Oscar Claveria

Price movements of stock market are not totally random. In fact, what drives the financial market and what pattern financial time series follows have long been the interest that attracts economists, mathematicians and most recently computer…

Statistical Finance · Quantitative Finance 2013-11-20 G. Kavitha , A. Udhayakumar , D. Nagarajan

The Economic Complexity Index (ECI; Hidalgo & Hausmann, 2009) measures the complexity of national economies in terms of product groups. Analogously to ECI, a Patent Complexity Index (PatCI) can be developed on the basis of a matrix of…

Economics · Quantitative Finance 2019-12-18 Inga Ivanova , Oivind Strand , Duncan Kushnir , Loet Leydesdorff

Hidden Markov models (HMMs) have been extensively used in the univariate and multivariate literature. However, there has been an increased interest in the analysis of matrix-variate data over the recent years. In this manuscript we…

Methodology · Statistics 2021-07-16 Salvatore D. Tomarchio , Antonio Punzo , Antonello Maruotti

Utilization of non-linear tools to characterize the state of development of the electricity markets in Italy and Greece. This is equivalent to testing the Efficient Market Hypothesis on these markets. The tools include a variety of…

The COVID-19 pandemic has caused more than 8 million confirmed cases and 500,000 death to date. In response to this emergency, many countries have introduced a series of social-distancing measures including lockdowns and businesses'…

General Economics · Economics 2020-07-08 Carlo Fezzi , Valeria Fanghella

Security-Constrained Unit Commitment (SCUC) is one of the most significant problems in secure and optimal operation of modern electricity markets. New sources of uncertainties such as wind speed volatility and price-sensitive loads impose…

Optimization and Control · Mathematics 2017-01-25 Mahdi Mehrtash , Mahdi Raoofat , Mohammad Mohammadi , Mohammad Hossein Zakernejad

This paper explores the application of Hidden Markov Models (HMM) and Long Short-Term Memory (LSTM) neural networks for economic forecasting, focusing on predicting CPI inflation rates. The study explores a new approach that integrates…

Machine Learning · Computer Science 2025-01-07 Guhan Sivakumar

The electricity industry is heavily implementing smart grid technologies to improve reliability, availability, security, and efficiency. This implementation needs technological advancements, the development of standards and regulations, as…

Machine Learning · Computer Science 2022-10-21 Ankitha Nandipura Prasanna , Priscila Grecov , Angela Dieyu Weng , Christoph Bergmeir
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