Results 111 to 120 of about 23,794,745 (244)

A note on Michelacci and Zaffaroni, long memory, and time series of economic growth [PDF]

long memory, economic ...
B. Verspagen, G. Silverberg
core  

Forecasting Realized Volatility Using A Nonnegative Semiparametric Model [PDF]

This paper introduces a parsimonious and yet flexible nonnegative semiparametric model to forecast financial volatility. The new model extends the linear nonnegative autoregressive model of Barndorff-Nielsen & Shephard (2001) and Nielsen & Shephard (2003)
Anders ERIKSSON, Daniel PREVE, Jun YU
core   +3 more sources

Addressing non-stationarity with stochastic trend in the context of limited time series data: An experimental survey in healthcare analytics

Applied Computer Science
Stationarity is a fundamental assumption in time series modeling that underlies reliable statistical inference and forecasting. Time series data can be found in many domains, including industry, engineering, finance, economics, epidemiology, and health ...
Apollinaire BATOURE BAMANA, Yannick SOKDOU BILA LAMOU, David Jaures FOTSA-MBOGNE, Mahdi SHAFIEE KAMALABAD   +3 more
doaj   +1 more source

Time Analysis of an Emergent Infection Spread Among Healthcare Workers: Lessons Learned from Early Wave of SARS-CoV-2. [PDF]

Int J Gen Med, 2022
Leme PAF, Jalalizadeh M, Giacomelli da Costa C, Buosi K, Dal Col LSB, Dionato FAV, Gon LM, Yadollahvandmiandoab R, Reis LO.   +8 more
europepmc   +1 more source

Forecasting commodity prices: empirical evidence using deep learning tools. [PDF]

Ann Oper Res, 2023
Ben Ameur H, Boubaker S, Ftiti Z, Louhichi W, Tissaoui K.   +4 more
europepmc   +1 more source

Testing and Estimating Persistence in Canadian Unemployment. [PDF]

A vital implication of unemployment persistence applies to the Bank of Canada's disinflation policies since it adversely influences unemployment and considerably lengthens recessions.
Curtis J. Eberwein, Jagdish Handa, Ossama Mikhail   +2 more
core  

A Hybrid Approach Combining the Lie Method and Long Short-Term Memory (LSTM) Network for Predicting the Bitcoin Return

Fractal and Fractional
This paper introduces hybrid models designed to analyze daily and weekly bitcoin return spanning the periods from 18 July 2010 to 28 December 2023 for daily data, and from 18 July 2010 to 24 December 2023 for weekly data. Firstly, the fractal and chaotic
Melike Bildirici, Yasemen Ucan, Ramazan Tekercioglu   +2 more
doaj   +1 more source

Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For? [PDF]

Comput Brain Behav, 2023
Perquin MN, van Vugt MK, Hedge C, Bompas A.   +3 more
europepmc   +1 more source

Assessing the Impact of Market Microstructure Noise and Random Jumps on the Relative Forecasting Performance of Option-Implied and Returns-Based Volatility [PDF]

This paper presents a comprehensive empirical evaluation of option-implied and returns-based forecasts of volatility, in which new developments related to the impact on measured volatility of market microstructure noise and random jumps are explicitly ...
Andrew Reidy, Gael M. Martin, Jill Wright   +2 more
core  

Long Memory Persistence in the Factor of Implied Volatility Dynamics [PDF]

The volatility implied by observed market prices as a function of the strike and time to maturity form an Implied Volatility Surface (IV S). Practical applications require reducing the dimension and characterize its dynamics through a small number of ...
Julius Mungo, Wolfgang Härdle
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