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Moving Average Process (moving + average_process)

Distribution by Scientific Domains
Business, Economics, Finance and Accounting60%
Mathematics and Statistics40%

Selected Abstracts

Why Has U.S. Inflation Become Harder to Forecast?

JOURNAL OF MONEY, CREDIT AND BANKING, Issue 2007
JAMES H. STOCK
Phillips curve; trend-cycle model; moving average; great moderation We examine whether the U.S. rate of price inflation has become harder to forecast and, to the extent that it has, what changes in the inflation process have made it so. The main finding is that the univariate inflation process is well described by an unobserved component trend-cycle model with stochastic volatility or, equivalently, an integrated moving average process with time-varying parameters. This model explains a variety of recent univariate inflation forecasting puzzles and begins to explain some multivariate inflation forecasting puzzles as well. [source]

Time series modelling of two millennia of northern hemisphere temperatures: long memory or shifting trends?

JOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 1 2007
Terence C. Mills
Summary., The time series properties of the temperature reconstruction of Moberg and co-workers are analysed. It is found that the record appears to exhibit long memory characteristics that can be modelled by an autoregressive fractionally integrated moving average process that is both stationary and mean reverting, so that forecasts will eventually return to a constant underlying level. Recent research has suggested that long memory and shifts in level and trend may be confused with each other, and fitting models with slowly changing trends is found to remove the evidence of long memory. Discriminating between the two models is difficult, however, and the strikingly different forecasts that are implied by the two models point towards some intriguing research questions concerning the stochastic process driving this temperature reconstruction. [source]

Embedding a Gaussian discrete-time autoregressive moving average process in a Gaussian continuous-time autoregressive moving average process

JOURNAL OF TIME SERIES ANALYSIS, Issue 4 2007
Mituaki Huzii
Abstract., Embedding a discrete-time autoregressive moving average (DARMA) process in a continuous-time ARMA (CARMA) process has been discussed by many authors. These authors have considered the relationship between the autocovariance structures of continuous-time and related discrete-time processes. In this article, we treat the problem from a slightly different point of view. We define embedding in a more rigid way by taking account of the probability structure. We consider Gaussian processes. First we summarize the necessary and sufficient condition for a DARMA process to be able to be embedded in a CARMA process. Secondly, we show a concrete condition such that a DARMA process can be embeddable in a CARMA process. This condition is new and general. Thirdly, we show some special cases including new examples. We show how we can examine embeddability for these special cases. [source]

The valuation of European options when asset returns are autocorrelated

THE JOURNAL OF FUTURES MARKETS, Issue 1 2006
Szu-Lang Liao
This article derives the closed-form formula for a European option on an asset with returns following a continuous-time type of first-order moving average process, which is called an MA(1)-type option. The pricing formula of these options is similar to that of Black and Scholes, except for the total volatility input. Specifically, the total volatility input of MA(1)-type options is the conditional standard deviation of continuous-compounded returns over the option's remaining life, whereas the total volatility input of Black and Scholes is indeed the diffusion coefficient of a geometric Brownian motion times the square root of an option's time to maturity. Based on the result of numerical analyses, the impact of autocorrelation induced by the MA(1)-type process is significant to option values even when the autocorrelation between asset returns is weak. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:85,102, 2006 [source]

UNCERTAINTY AND CONSUMPTION: NEW EVIDENCE IN OECD COUNTRIES

BULLETIN OF ECONOMIC RESEARCH, Issue 3 2010
Mario Menegatti
D91; E21 ABSTRACT This work analyses the empirical evidence about precautionary saving in OECD countries in the period 1955,2000. Unlike the previous literature, we perform the test using a measure of uncertainty allowing for heterogeneity in stochastic processes which generate data for each country and selecting for each economy the autoregressive moving average process which best describes the series. The results obtained support the main conclusion of precautionary saving theory, showing that a greater degree of uncertainty increases saving. A less clear conclusion is obtained with reference to the effect of uncertainty on consumption growth, which does not seem to be strongly supported by the data. [source]