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Moving average separation [PDF]
ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing, 2003 A real symmetric polynomial Q(z) can be factored into the product A(z)A(z/sup -1/) if Q(z) is nonnegative on the unit circle. The authors pose a constrained minimization problem that results in the correct factorization in this case and gives an approximation to Q(z) if Q(z) does not satisfy the nonnegativity condition. >
C.T. Mullis, G. Feyh
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MOVING AVERAGES AND PRICE DYNAMICS
International Journal of Theoretical and Applied Finance, 2002We introduce a stochastic price model where, together with a random component, a moving average of logarithmic prices contributes to the price formation. The future price is linearly influenced by the difference between the moving average and the current price, together with a noise component. Our model is tested against financial datasets, showing an
Baviera R +3 more
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Market Timing With Moving Averages
International Review of Finance, 2012AbstractI present evidence that a moving average (MA) trading strategy has a greater average return and skewness as well as a lower variance compared to buying and holding the underlying asset using monthly returns of value‐weighted US decile portfolios sorted by market size, book‐to‐market, and momentum, and seven international markets as well as 18 ...
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The moving averages demystified
Physica A: Statistical Mechanics and its Applications, 1999A common method in technical analysis is the construction of moving averages along time series of stock prices. We show that they present a practical interest for physicists, and raise new questions on fundamental ground. Indeed, self-ane signals characterized by a dened roughness exponent H can be investigated through moving averages.
P. Boveroux +2 more
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Canadian Journal of Mathematics, 1993
AbstractLet ℝ denote the real line. Let {Tt}tєℝ be a measure preserving ergodic flow on a non atomic finite measure space (X, ℱ, μ). A nonnegative function φ on ℝ is called a weight function if ∫ℝ φ(t)dt = 1. Consider the weighted ergodic averagesof a function f X —> ℝ, where {θk} is a sequence of weight functions. Some sufficient and some necessary
Y. Déniel, Mustafa A. Akcoglu
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AbstractLet ℝ denote the real line. Let {Tt}tєℝ be a measure preserving ergodic flow on a non atomic finite measure space (X, ℱ, μ). A nonnegative function φ on ℝ is called a weight function if ∫ℝ φ(t)dt = 1. Consider the weighted ergodic averagesof a function f X —> ℝ, where {θk} is a sequence of weight functions. Some sufficient and some necessary
Y. Déniel, Mustafa A. Akcoglu
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2019
This chapter deals with time series trends based on moving average formulas. A special case, in which the trend values are calculated with the exponential smoothing formula, is discussed with more detail.
Miguel Ángel Canela +2 more
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This chapter deals with time series trends based on moving average formulas. A special case, in which the trend values are calculated with the exponential smoothing formula, is discussed with more detail.
Miguel Ángel Canela +2 more
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On prediction of moving-average processes
Advances in Applied Probability, 1980Let {X n } be a discrete-time stationary moving-average process having the representation where the real-valued process (Y n ) has a well-defined entropy and spectrum. Let ∊∗2 k denote the smallest mean-squared error of any estimate of X n based on observations of X n–1 , X n–2 , …, X n–k , and let ∊∗2 klin , be the corresponding least mean-squared ...
D. Slepian, L. A. Shepp, A. D. Wyner
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The Review of Economics and Statistics, 1929
THE use of the moving average has become widespread because of the simplicity of its application in the computation of the trend of statistical time series. This method, however, has two essential disadvantages, which make it applicable only in a limited degree.
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THE use of the moving average has become widespread because of the simplicity of its application in the computation of the trend of statistical time series. This method, however, has two essential disadvantages, which make it applicable only in a limited degree.
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2021
It is very common for market data series to be smoothed, as smoothing reduces volatility, and allows traders to eliminate the bumpy movements. The two most common smoothing indicators are: Simple Moving Average (SMA) and Exponential Moving Average (EMA).
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It is very common for market data series to be smoothed, as smoothing reduces volatility, and allows traders to eliminate the bumpy movements. The two most common smoothing indicators are: Simple Moving Average (SMA) and Exponential Moving Average (EMA).
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2017
This chapter presents a brief motivation for using moving averages for trend detection, how moving averages are computed, and their two key properties: the average lag (delay) time and smoothness. The most important thing to understand right from the start is that there is a direct relationship between the average lag time and smoothness of a moving ...
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This chapter presents a brief motivation for using moving averages for trend detection, how moving averages are computed, and their two key properties: the average lag (delay) time and smoothness. The most important thing to understand right from the start is that there is a direct relationship between the average lag time and smoothness of a moving ...
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