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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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3876113151 · May 202619922001200920172026
48 results for detrending moving average

The detrending moving average (DMA) algorithm is a widely used technique to quantify the long-term correlations of non-stationary time series and the long-range correlations of fractal surfaces, which contains a parameter θθ determining the position of the detrending window. We develop multifractal detrending moving a…

2010-05-06abs ↗pdf ↗

The Hurst exponent HH of long range correlated series can be estimated by means of the Detrending Moving Average (DMA) method. A computational tool defined within the algorithm is the generalized variance σDMA2=1/(Nn)i[y(i)y~n(i)]2 σ_{DMA}^2={1}/{(N-n)}\sum_i [y(i)-\widetilde{y}_n(i)]^2\:, with y~n(i)=1/nky(ik)\widetilde{y}_n(i)= {1}/{n}\sum_{k}y(i-k) the…

2006-08-31abs ↗pdf ↗

A new method for direct determination of multifractal spectrum from moving average analysis.

problem Direct determination of multifractal spectrum from moving average analysis.
method Proposes a new approach based on detrending moving average method (MF-DMA) to directly determine multifractal spectrum.
result Direct determination of multifractal spectrum is possible with less computation cost compared to traditional approach.

New method estimates robust multi-period portfolios using entropy.

problem Lack of general agreement on building robust multi-period portfolios.
method Detrended cluster entropy approach to estimate portfolio weights.
result Portfolio weights are estimated reliably from real-world data at varying time horizons.

There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross-correlations. The multifractal detrended cross-correlation analysis (MF-DCCA) approaches can be used to quantify such cross-correlations, such as the MF-DCCA based on detrend…

2011-03-14abs ↗pdf ↗

We extend our previous study of scaling range properties done for detrended fluctuation analysis (DFA) \cite{former_paper} to other techniques of fluctuation analysis (FA). The new technique called Modified Detrended Moving Average Analysis (MDMA) is introduced and its scaling range properties are examined and compared…

2012-12-20abs ↗pdf ↗

Paper finds significant impact of stock market swings on equity risk premium predictability.

problem Predicting equity risk premium based on stock market behavior changes.
method Introduced Bullish Index and used FDMAA for returns analysis; considered 28 indicators.
result Positive shocks in Bullish Index correlate with strong equity risk premium predictability for up to six months, while negative shocks correlate for up to nine months.

We study finite sample properties of estimators of power-law cross-correlations -- detrended cross-correlation analysis (DCCA), height cross-correlation analysis (HXA) and detrending moving-average cross-correlation analysis (DMCA) -- with a special focus on short-term memory bias as well as power-law coherency. Presen…

2014-09-24abs ↗pdf ↗

We study power-law correlations properties of the Google search queries for Dow Jones Industrial Average (DJIA) component stocks. Examining the daily data of the searched terms with a combination of the rescaled range and rescaled variance tests together with the detrended fluctuation analysis, we show that the searche…

2015-02-01abs ↗pdf ↗

We examine several recently suggested methods for the detection of long-range correlations in data series based on similar ideas as the well-established Detrended Fluctuation Analysis (DFA). In particular, we present a detailed comparison between the regular DFA and two recently suggested methods: the Centered Moving A…

2008-04-25abs ↗pdf ↗

We examine the performance of six estimators of the power-law cross-correlations -- the detrended cross-correlation analysis, the detrending moving-average cross-correlation analysis, the height cross-correlation analysis, the averaged periodogram estimator, the cross-periodogram estimator and the local cross-Whittle e…

2016-02-17abs ↗pdf ↗

We propose a comprehensive treatment of the leverage effect, i.e. the relationship between returns and volatility of a specific asset, focusing on energy commodities futures, namely Brent and WTI crude oils, natural gas and heating oil. After estimating the volatility process without assuming any specific form of its b…

2014-03-01abs ↗pdf ↗

The detrending moving average (DMA) algorithm is one of the best performing methods to quantify the long-term correlations in nonstationary time series. Many long-term correlated time series in real systems contain various trends. We investigate the effects of polynomial trends on the scaling behaviors and the performa…

2015-04-28abs ↗pdf ↗

We perform detrending moving average analysis (DMA) and detrended fluctuation analysis (DFA) of the WTI crude oil futures prices (1983-2012) to investigate its efficiency. We further put forward a strict statistical test in the spirit of bootstrapping to verify the weak-form market efficiency hypothesis by employing th…

2012-11-20abs ↗pdf ↗

In this paper, we show how the sampling properties of the Hurst exponent methods of estimation change with the presence of heavy tails. We run extensive Monte Carlo simulations to find out how rescaled range analysis (R/S), multifractal detrended fluctuation analysis (MF-DFA), detrending moving average (DMA) and genera…

2012-01-23abs ↗pdf ↗

Explains the difference between EMA and moving EMA, focusing on market trend indicators.

problem Understanding the difference between exponential moving average and moving exponential average.
method Explains the mathematical tools and definitions of trend indicators.
result Discusses the properties of the MACD indicator and its use in market trend analysis.

This paper looks into the analysis of the long-range auto-correlations and cross-correlations in bond market. Based on Detrended Moving Average (DMA) method, empirical results present a clear evidence of long-range persistence that exists in one year scale. The degree of long-range correlation related to maturities has…

2016-10-31abs ↗pdf ↗

Study uses multifractal detrended cross-correlation to detect Forex arbitrage opportunities.

problem Detecting arbitrage opportunities in Forex markets.
method Multifractal detrended cross-correlation analysis applied to Forex time series.
result Strong cross-correlations found between exchange rates involved in triangular relations, including AUD and NZD.

This study uses moving average cluster entropy to analyze financial market dynamics.

problem Understanding long-range dependence in financial markets.
method Moving average cluster entropy approach applied to ARFIMA and FBM processes.
result Long-range positive correlation in financial markets is linked to the cluster entropy behavior.

Study finds multifractal cross-correlations between agricultural markets and external uncertainties.

problem Investigating relationships between agricultural spot markets and external uncertainties.
method Multifractal detrending moving-average cross-correlation analysis (MF-X-DMA).
result Maize exhibits intrinsic joint multifractality with all uncertainty proxies.

We discuss martingales, detrending data, and the efficient market hypothesis for stochastic processes x(t) with arbitrary diffusion coefficients D(x,t). Beginning with x-independent drift coefficients R(t) we show that Martingale stochastic processes generate uncorrelated, generally nonstationary increments. Generally,…

2007-01-23abs ↗pdf ↗

Study on cryptocurrency trading patterns using multifractal analysis.

problem Lack of systematic study on temporal structure of cryptocurrency trading.
method Multifractal detrended cross-correlation analysis of price returns, trades, and volume.
result All analyzed quantities exhibit multifractal structure, both univariate and bivariate.

We apply two non-parametric methods to test further the hypothesis that log-periodicity characterizes the detrended price trajectory of large financial indices prior to financial crashes or strong corrections. The analysis using the so-called (H,q)-derivative is applied to seven time series ending with the October 1987…

2002-05-25abs ↗pdf ↗

The possibility that price dynamics is affected by its distance from a moving average has been recently introduced as new statistical tool. The purpose is to identify the tendency of the price dynamics to be attractive or repulsive with respect to its own moving average. We consider a number of tests for various models…

2006-01-12abs ↗pdf ↗

We propose a method for pricing American options whose pay-off depends on the moving average of the underlying asset price. The method uses a finite dimensional approximation of the infinite-dimensional dynamics of the moving average process based on a truncated Laguerre series expansion. The resulting problem is a fin…

2010-11-16abs ↗pdf ↗

The paper analyzes MACD using operator theory.

problem Understanding the mathematical foundation of MACD.
method Developed a functional-analytic framework interpreting MACD as a phase-corrected, smoothed derivative operator.
result MACD is structurally equivalent to a band-pass filter and can be expressed as a finite difference of delayed and doubly averaged signals.

Study uses detrended cross-correlation to analyze cryptocurrency market, revealing robust collective modes and distinguishing interdependencies.

problem Nonstationarity, long-range memory, and heavy-tailed fluctuations obscure traditional correlations in complex systems.
method Constructs detrended correlation matrices using multifractal detrended cross-correlation coefficient ρrρ_r to emphasize different fluctuations.
result Detrending and fluctuation analysis reveal distinct spectral properties from random case, identifying market and sectoral components.

Neural moving average model speeds up state space model inference for time series data.

problem Efficiently scaling approximate Bayesian inference for time series data.
method Proposes a novel generative model (neural moving average model) for latent temporal states in state space models.
result Achieves accurate parameter estimation in a short time for various models.

Paper predicts cryptocurrency bull and bear phases using Bitcoin's moving averages.

problem Determining cryptocurrency bull and bear phases based on Bitcoin performance.
method Employing predictive algorithms to forecast Bitcoin's 50 Day and 200 Day Moving Averages.
result Predicted data from Bitcoin's moving averages helps identify potential bull and bear phases.

Study finds intrinsic multifractality in maize and barley spot markets, but not in wheat and rice.

problem Understanding the complex price behavior of global grain spot markets.
method Utilized multifractal fluctuation analysis (MF-DFA) to investigate intrinsic multifractality.
result Intrinsic multifractality found in maize and barley sub-indices, but not in wheat and rice.

PACE optimizes training for averaged language models, improving performance.

problem How to optimize training for averaged language model iterates.
method Formulated as an optimal-control problem, solved for minimizing error of the average with a penalty on intervention size.
result PACE improves the limiting squared error of the iterate-average estimator by an arbitrarily large factor on some instances.