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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.

168,695 papers · 148 categories

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243485728970 · Jun 202019922001200920172026
48 results for Performance Fluctuations

Spectral clustering performance depends on eigenvector fluctuations, shown to be Gaussian.

problem Predicting the performance of spectral clustering.
method General spike random matrix model and rotational invariance of noise.
result Fluctuations of eigenvector entries are Gaussian in large-dimensional regime.

Bayesian models' singular fluctuation is shown to be akin to specific heat, influencing model complexity and generalization.

problem Understanding the thermodynamic interpretation of singular fluctuation in Bayesian models.
method Showed singular fluctuation as the curvature of Bayesian free energy and variance of log-likelihood observable under a Gibbs posterior.
result Singular fluctuation is the statistical analogue of specific heat, controlling model complexity and generalization.

In order to emphasize cross-correlations for fluctuations in major market places, series of up and down spins are built from financial data. Patterns frequencies are measured, and statistical tests performed. Strong cross-correlations are emphasized, proving that market moves are collective behaviors.

2000-01-20abs ↗pdf ↗

Study uses neural networks to predict wall quantities in turbulent flows.

problem Predicting wall quantities in turbulent open channel flows.
method Training convolutional neural networks (FCN) and a proposed R-Net architecture to predict wall-shear-stress and wall pressure.
result R-Net architecture performs better and predicts wall quantities with around 10% error.

The properties of q-dependent cross-correlation matrices of stock market have been analyzed by using the random matrix theory and complex network. The correlation structures of the fluctuations at different magnitudes have unique properties. The cross-correlations among small fluctuations are much stronger than those a…

2017-04-13abs ↗pdf ↗

This paper proposes a framework to predict long-term trends and short-term fluctuations in multivariate time series.

problem Existing prediction methods often ignore the distinction between long-term trends and short-term fluctuations.
method The paper introduces a MTS forecasting framework that uses both original time series and its first difference to capture long-term trends and short-term fluctuations.
result The proposed method improves forecasting performance by using more supervision information.

Study shows cryptocurrency price fluctuations become more similar to national currencies over time.

problem Understanding the volatility and inequality in cryptocurrency prices.
method Calculated inequality measures (Gini, Kolkata indices, QQ factor) for cryptocurrency and national currency price fluctuations over 10 years.
result Cryptocurrency price fluctuations become more similar to national currencies over time.

Cryptocurrency forecasting model considers macro, sentiment, and technical indicators.

problem High price volatility in cryptocurrency markets.
method Dual-prediction mechanism incorporating macroeconomic fluctuations, technical indicators, and individual cryptocurrency price changes.
result The proposed model outperforms ten comparison methods in short-term cryptocurrency forecasting.

In Biology, all motor enzymes operate on the same principle: they trap favourable brownian fluctuations in order to generate directed forces and to move. Whether it is possible or not to copy one such strategy to play the market was the starting point of our investigations. We found the answer is yes. In this paper we …

2007-05-15abs ↗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 perform an extensive empirical analysis of scaling properties of equity returns, suggesting that financial data show time varying multifractal properties. This is obtained by comparing empirical observations of the weighted generalised Hurst exponent (wGHE) with time series simulated via Multifractal Random Walk (MR…

2012-12-13abs ↗pdf ↗

We study the nature of fluctuations in variety of price indices involving companies listed on the New York Stock Exchange. The fluctuations at multiple scales are extracted through the use of wavelets belonging to Daubechies basis. The fact that these basis sets satisfy vanishing moments conditions makes them ideal to …

2012-05-08abs ↗pdf ↗

New spectral functionals for Dirac operators with inner fluctuations computed.

problem Spectral functionals and Dirac operators with inner fluctuations.
method Extension of spectral functionals for Dirac operators with inner fluctuations.
result Computed spectral Einstein functional for Dirac operator with inner fluctuations on even-dimensional spin manifolds.

We propose a new approach for properly analyzing stochastic time series by mapping the dynamics of time series fluctuations onto a suitable nonequilibrium surface-growth problem. In this framework, the fluctuation sampling time interval plays the role of time variable, whereas the physical time is treated as the analog…

2008-08-24abs ↗pdf ↗

This work studies fluctuation in multilayer neural networks using mean field theory.

problem Understanding fluctuation in multilayer neural networks with mean field training.
method Developed a second-order mean field limit to capture fluctuation, demonstrating stability of gradient descent training.
result Gradient descent training in multilayer networks biases towards minimal fluctuation, even after convergence.

We propose a new approach for analyzing price fluctuations in their strongly correlated regime ranging from minutes to months. This is done by employing a self-similarity assumption for the magnitude of coarse-grained price fluctuation or volatility. The existence of a Cramer function, the characteristic function for s…

2001-01-12abs ↗pdf ↗

We analyze daily prices of 29 commodities and 2449 stocks, each over a period of 15\approx 15 years. We find that the price fluctuations for commodities have a significantly broader multifractal spectrum than for stocks. We also propose that multifractal properties of both stocks and commodities can be attributed mainl…

2003-08-01abs ↗pdf ↗

Study identifies contagion in aggregated defaults despite environmental changes.

problem Identify contagion in aggregated default counts with fluctuating probabilities.
method Compare three contagion mechanisms (Davis-Lo, Torri, Vasicek) under i.i.d. and hierarchical specifications.
result Threshold contagion is largely absorbed into environmental heterogeneity, while cumulative contagion leaves a persistent signature.

We address the question of how stock prices respond to changes in demand. We quantify the relations between price change GG over a time interval ΔtΔt and two different measures of demand fluctuations: (a) ΦΦ, defined as the difference between the number of buyer-initiated and seller-initiated trades, and (b) ΩΩ, def…

2001-06-29abs ↗pdf ↗

We perform an analysis of fractal properties of the positive and the negative changes of the German DAX30 index separately using Multifractal Detrended Fluctuation Analysis (MFDFA). By calculating the singularity spectra f(α)f(α) we show that returns of both signs reveal multiscaling. Curiously, these spectra display a s…

2008-03-10abs ↗pdf ↗

Study on price fluctuations in NFT market, showing heavy-tailed distributions and long-range memory.

problem Characterizing price fluctuations in NFT market.
method Analysis of capitalization, floor price, transactions, inter-transaction times, and volume value of NFTs.
result NFT market exhibits heavy-tailed probability distribution functions, well described by stretched exponentials, with long-range memory.

We analyze the fluctuation of the loss from default around its large portfolio limit in a class of reduced-form models of correlated firm-by-firm default timing. We prove a weak convergence result for the fluctuation process and use it for developing a conditionally Gaussian approximation to the loss distribution. Nume…

2013-04-04abs ↗pdf ↗

Deep networks with orthogonal weights show stable fluctuations, improving generalization and training speed.

problem Fluctuations in deep networks with Gaussian weights can impair training, especially in networks with depth comparable to width.
method Analytical and numerical studies of fully-connected networks with orthogonal weight initialization and tanh activations.
result Rectangular networks with orthogonal weights have stable fluctuations independent of network depth, leading to better generalization and training speed.

Derives scaling limits and fluctuations for SGD in high dimensions.

problem Understanding SGD behavior in high-dimensional settings with varying noise levels.
method Interacting particle system approach, treating SGD iterates as such, with covariance structure considered.
result Precise three-step phase transition observed in SGD behavior: ballistic, diffusive, then random.

Study analyzes fluctuations in Mexican financial market index.

problem Understanding intra-day fluctuations in Mexican financial market index.
method Statistical analysis of high frequency tick-to-tick data, temporal aggregation, and comparison of distributions.
result Intra-day fluctuations do not follow alpha-stable distributions, suggesting autocorrelations.

We constructed an analog electrical circuit which generates fluctuations in which probability density function has power law tails. In the circuit fluctuations with an arbitrary exponent of the power law can be obtained by adjusting the resistance. With this low cost circuit the random fluctuations which have the simil…

2001-04-18abs ↗pdf ↗

The financial market and turbulence have been broadly compared on account of the same quantitative methods and several common stylized facts they shared. In this paper, the She-Leveque (SL) hierarchy, proposed to explain the anomalous scaling exponents deviated from Kolmogorov monofractal scaling of the velocity fluctu…

2012-09-19abs ↗pdf ↗

Predicting absolute magnitude of fluctuations of price, even if their sign remains unknown, is important for risk analysis and for option prices. In the present work, we display our predictions about absolute magnitude of daily fluctuations of the Dow Jones Industrials Average (DJIA), utilizing the original theory of c…

2006-02-08abs ↗pdf ↗

Graph-based multi-view model predicts trading volume movement from various sources.

problem Lack of comprehensive understanding of trading volume movement from different sources.
method Graph-based approach incorporating long-term, short-term, and sudden event information.
result Our method outperforms strong baselines by a large margin.

We investigate the large-fluctuation dynamics in financial markets, based on the minute-to-minute and daily data of the Chinese Indices and German DAX. The dynamic relaxation both before and after the large fluctuations is characterized by a power law, and the exponents p±p_\pm usually vary with the strength of the lar…

2013-08-03abs ↗pdf ↗

The paper analyzes fluctuations in ensemble models in high-dimensional settings.

problem Understanding statistical fluctuations in ensemble models in high-dimensional settings.
method Develops a rigorous theory for the study of fluctuations in ensemble of generalised linear models.
result Provides a complete description of the asymptotic joint distribution of the empirical risk minimizer for convex losses in high-dimensional settings.

A new model that combines economic growth rate fluctuations at the microscopic and macroscopic level is presented. At the microscopic level, firms are growing at different rates while also being exposed to idiosyncratic shocks at the firm and sector level. We describe such fluctuations as independent Lévy-stable fluctu…

2017-08-26abs ↗pdf ↗

In this paper, we present own point of view how the unexpected fluctuations of the long-term real interest rate can be explained. We describe a macroeconomic environment by the modification of the fundamental macroeconomic equilibrium model called the IS-LM model. Last but not least, we suggest a possible cooperation b…

2012-11-12abs ↗pdf ↗

The study reveals the hierarchical structure of the international FOREX market using currency fluctuation distribution similarities.

problem Understanding the hierarchical structure of the international FOREX market.
method Using Jensen-Shannon divergence to quantify the similarity between normalized logarithmic return distributions of currencies.
result Clusters of currencies are consistent with the nature of underlying economies but diverge during crises.

We study the cause of large fluctuations in prices in the London Stock Exchange. This is done at the microscopic level of individual events, where an event is the placement or cancellation of an order to buy or sell. We show that price fluctuations caused by individual market orders are essentially independent of the v…

2003-12-30abs ↗pdf ↗