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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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4488132176 · Jun 202019922001200920172026
48 results for instantaneous power

This paper is concerned with the estimation of the volatility process in a stochastic volatility model of the following form: dXt=atdt+σtdWtdX_t=a_tdt+σ_tdW_t, where XX denotes the log-price and σσ is a càdlàg semi-martingale. In the spirit of a series of recent works on the estimation of the cumulated volatility, we here focus …

2008-12-18abs ↗pdf ↗

New model for pricing volatility derivatives considering rough volatility and jumps.

problem Modeling instantaneous volatility with rough volatility and jumps.
method Generalized fractional Ornstein-Uhlenbeck process with Lévy subordinator and sinusoidal-composite Lévy process.
result Pricing-hedging formulae for power-type derivatives on average forward variance are derived.

We prove uniqueness of instantaneously complete Ricci flows on surfaces. We do not require any bounds of any form on the curvature or its growth at infinity, nor on the metric or its growth (other than that implied by instantaneous completeness). Coupled with earlier work, particularly [23, 11], this completes the well…

2013-05-08abs ↗pdf ↗

We study a robust portfolio optimization problem under model uncertainty for an investor with logarithmic or power utility. The uncertainty is specified by a set of possible Lévy triplets; that is, possible instantaneous drift, volatility and jump characteristics of the price process. We show that an optimal investment…

2015-02-20abs ↗pdf ↗

New framework IDOL identifies latent causal processes with instantaneous relations from time series data.

problem Identifying latent causal processes with instantaneous relations from time series data.
method Sparse influence constraint and variational inference architecture with sparsity regularization.
result Our method can identify latent causal processes with instantaneous relations.

This paper studies the concept of instantaneous arbitrage in continuous time and its relation to the instantaneous CAPM. Absence of instantaneous arbitrage is equivalent to the existence of a trading strategy which satisfies the CAPM beta pricing relation in place of the market. Thus the difference between the arbitrag…

2019-01-16abs ↗pdf ↗

iCITRIS learns causal variables from interactive systems with instantaneous effects.

problem Identifying causal variables from temporal sequences with instantaneous effects.
method iCITRIS method for causal representation learning that handles instantaneous effects in intervened temporal sequences.
result iCITRIS accurately identifies causal variables and their causal graph from three interactive system datasets.

The Ricci flow preserves product structures with instantaneous curvature bounds.

problem Preserving product structures under Ricci flow with curvature constraints.
method Proving a constant ε exists such that if a solution splits as a product at time 0 and has bounded curvature, it splits for all time.
result A constant ε exists depending on dimension such that if a solution splits as a product at time 0 and has curvature bounded by ε/t, it splits for all time.

Paper introduces REED for noncoherent OTA-FL, reducing latency without phase alignment.

problem Noncoherent OTA-FL requires signed model updates without phase alignment.
method Introduces REED for continuous signed aggregation using resource-element energy difference.
result Exact variance laws for REED and chip-diverse extension in Rayleigh fading.

This paper presents a novel one-factor stochastic volatility model where the instantaneous volatility of the asset log-return is a diffusion with a quadratic drift and a linear dispersion function. The instantaneous volatility mean reverts around a constant level, with a speed of mean reversion that is affine in the in…

2019-08-20abs ↗pdf ↗

Study cryptocurrency price dynamics using adaptive EMD and spectral analysis.

problem Analyze the time-varying volatility of cryptocurrency prices.
method Adaptive complementary ensemble empirical mode decomposition (ACE-EMD) and Hilbert spectral analysis.
result Reveal the properties of various timescales in cryptocurrency price dynamics.

We study hedging and pricing of unattainable contingent claims in a non-Markovian regime-switching financial model. Our financial market consists of a bank account and a risky asset whose dynamics are driven by a Brownian motion and a multivariate counting process with stochastic intensities. The interest rate, drift, …

2013-03-17abs ↗pdf ↗

Working on different aspects of algorithmic trading we empirically discovered a new market invariant. It links together the volatility of the instrument with its traded volume, the average spread and the volume in the order book. The invariant has been tested on different markets and different asset classes. In all cas…

2019-08-07abs ↗pdf ↗

Collective behaviours taking place in financial markets reveal strongly correlated states especially during a crisis period. A natural hypothesis is that trend reversals are also driven by mutual influences between the different stock exchanges. Using a maximum entropy approach, we find coordinated behaviour during tre…

2013-10-30abs ↗pdf ↗

Study optimal execution in a transient price impact model with multiple traders.

problem Optimal execution among multiple traders with transient price impact.
method Analyzed NN-player optimal execution games in an Obizhaeva--Wang model with and without regularization. Derived equilibrium solutions and explained their behavior.
result Existence of equilibrium restored with a specific time-dependent cost on block trades, and equilibrium is tractable.

Paper shows geometric frequency and Lagrange derivative equivalence for electric and fluid systems.

problem Understanding and classifying system operating conditions based on electric quantity waveform distortions.
method Demonstrates equivalence between geometric frequency and Lagrange derivative through numerical examples.
result Identifies components of Lagrange derivative that relate to geometric frequency and waveform distortions.

Estimates chirp signal frequencies using probabilistic models.

problem Estimating instantaneous frequencies of chirp signals when true forms are unknown.
method Non-linear Gaussian processes and stochastic filters/smothers for posterior estimation.
result The method outperforms state-of-the-art methods on synthetic and real-world datasets.

A new principle minimizes residual and introduces momentum to improve PDE solution dynamics.

problem Ill-conditioning in Dirac-Frenkel residual minimization leads to non-unique parameter dynamics.
method Introduces a history variable (momentum) to select better-conditioned parameter velocities, preserving residual minimization while promoting smooth parameter evolutions.
result The approach leads to increased robustness in singular and near-singular PDE solution regimes.

New model identifies regimes in non-stationary data.

problem Identifying latent regimes in non-stationary systems with instantaneous effects.
method Identifiable Markov Switching Models with exponential family noise.
result Established identifiability of latent regimes and causal structures.

Unified framework for optimal liquidation with small market impact and semimartingale strategies.

problem Optimal liquidation under small market impact and portfolio liquidation.
method Semimartingale strategies and convergence results for BSDEs with singular terminal conditions.
result Unified framework for embedding two common liquidation models and microscopic foundation for semimartingale strategies.

To convert standard Brownian motion ZZ into a positive process, Geometric Brownian motion (GBM) eβZt,β>0e^{βZ_t}, β>0 is widely used. We generalize this positive process by introducing an asymmetry parameter α0 α\geq 0 which describes the instantaneous volatility whenever the process reaches a new low. For our new process, …

2018-09-06abs ↗pdf ↗

The ARCH process (R. F. Engle, 1982) constitutes a paradigmatic generator of stochastic time series with time-dependent variance like it appears on a wide broad of systems besides economics in which ARCH was born. Although the ARCH process captures the so-called "volatility clustering" and the asymptotic power-law prob…

2007-05-23abs ↗pdf ↗

We explore the effect of past market movements on the instantaneous correlations between assets within the futures market. Quantifying this effect is of interest to estimate and manage the risk associated to portfolios of futures in a non-stationary context. We apply and extend a previously reported method called the P…

2019-12-27abs ↗pdf ↗

HHT feature generation enhances financial time series forecasting.

problem Forecasting nonstationary financial time series.
method CEEMD and HHT for decomposition, machine learning integration.
result HHT-enhanced models outperform traditional models in forecasting.

We study the Yamabe flow on a Riemannian manifold of dimension m3m\geq3 minus a closed submanifold of dimension nn and prove that there exists an instantaneously complete solution if and only if n>m22n>\frac{m-2}{2}. In the remaining cases 0nm220\leq n\leq\frac{m-2}{2} including the borderline case, we show that the removab…

2019-07-03abs ↗pdf ↗

Study shows gaps in Bitcoin order book are linked to returns but only in the short term.

problem Understanding the relationship between gaps and returns in Bitcoin order books.
method Examined the dynamics of gaps and returns in a Bitcoin order book without considering long-term causation.
result The causal relationship between gaps and returns is limited to instantaneous causation.

This paper introduces a new metric, ULI, for RL that ensures both cumulative and instantaneous performance.

problem High-stakes applications require RL algorithms to avoid playing bad policies.
method Introduces uniform last-iterate (ULI) guarantee, a stronger metric capturing both cumulative and instantaneous performance.
result ULI directly implies near-optimal cumulative performance across various metrics, but not the other way around.

Causal inference uses observations to infer the causal structure of the data generating system. We study a class of functional models that we call Time Series Models with Independent Noise (TiMINo). These models require independent residual time series, whereas traditional methods like Granger causality exploit the var…

2012-07-21abs ↗pdf ↗

We propose a stochastic process for stock movements that, with just one source of Brownian noise, has an instantaneous volatility that rises from a type of statistical feedback across many time scales. This results in a stationary non-Gaussian process which captures many features observed in time series of real stock r…

2004-12-20abs ↗pdf ↗

Study optimal liquidation strategies on Uniswap v2/v3 considering price impact.

problem Optimal liquidation of large positions on Uniswap v2/v3 under transient price impact.
method Dynamic programming and numerical approximation for Uniswap v3, closed-form solutions for v2.
result Obtained optimal strategies for both Uniswap v2 and v3, showing how liquidity profile influences them.