Results 91 to 100 of about 111,952 (197)
Bitcoin Return Dynamics Volatility and Time Series Forecasting
International Journal of Financial StudiesBitcoin and other cryptocurrency returns show higher volatility than equity, bond, and other asset classes. Increasingly, researchers rely on machine learning techniques to forecast returns, where different machine learning algorithms reduce the ...
Punit Anand, Anand Mohan Sharan
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Maximum Likelihood Estimation of ARMA Model with Error Processes for Replicated Observations [PDF]
In this paper we analyse the repeated time series model where the fundamental component follows a ARMA process. In the model, the error variance as well as the number of repetition are allowed to change over time. It is shown that the model is identified.
Keshab Shrestha +2 more
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The Contribution of Growth and Interest Rate Differentials to the Persistence of Real Exchange Rates. [PDF]
This paper employs a new methodology for measuring the contribution of growth and interest rate differentials to the half-life of deviations from Purchasing Power Parity (PPP).
Dimitrios Malliaropulos +3 more
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Energy Prediction Method for Metro HVAC Systems based on the ARMA Model
Zhileng xuebao, 2019 This paper proposes an energy consumption-prediction method for metro heating, ventilation and air-conditioning (HVAC) systems based on an auto-regressive moving average (ARMA) model using a time-series data analysis.
Huang Ronggeng +6 more
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, 1988 This thesis estimates the frequency response of a network where the only data is the output obtained from an Autoregressive-moving average (ARMA) model driven by a random input. Models of random processes and existing methods for solving ARMA models are examined.
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KALMAN FILTERS AND ARMA MODELS
Ratio Mathematica, 2003 The Kalman filter is the celebrated algorithm giving a recursive solution of the prediction problem for time series. After a quite general formulation of the prediction problem, the contributions of its solution by the great mathematicians Kolmogorov and Wiener are shorthly recalled and it is showed as Kalman filter furnishes the optimal predictor, in ...
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Fruit production forecasting by neuro-fuzzy techniques [PDF]
Neuro-fuzzy techniques are finding a practical application in many fields such as in model identification and forecasting of linear and non-linear systems.
Atsalakis, George S. +1 more
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Bayesian change-point modeling with segmented ARMA model. [PDF]
PLoS One, 2018 Sadia F, Boyd S, Keith JM.
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From Discrete to Continuous: Modeling Volatility of the Istanbul Stock Exchange Market with GARCH and COGARCH [PDF]
The objective of this paper is to model the volatility of Istanbul Stock Exchange market, ISE100 Index by ARMA and GARCH models and then take a step further into the analysis from discrete modeling to continuous modeling.
Unal, Gazanfer, Yildirim, Yavuz
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This paper considers both the least squares and quasi-maximum likelihood estimation for the recently proposed scalable ARMA model, a parametric infinite-order vector AR model, and their asymptotic normality is also established. It makes feasible the inference on this computationally efficient model, especially for economic and financial time series. An
Lin, Yuchang +3 more
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