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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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295988117 · May 202619922001200920182026
48 results for homogeneous returns

A homogeneously saturated equation for the time development of the price of a financial asset is presented and investigated for the pricing of European call options using noise that is distributed as a Student's t-distribution. In the limit that the saturation parameter of the equation equals zero, the standard model o…

2013-01-24abs ↗pdf ↗

Stock correlations is crucial to asset pricing, investor decision-making, and financial risk regulations. However, microscopic explanation based on agent-based modeling is still lacking. We here propose a model derived from minority game for modeling stock correlations, in which an agent's expected return for one stock…

2018-03-06abs ↗pdf ↗

We study the high frequency price dynamics of traded stocks by a model of returns using a semi-Markov approach. More precisely we assume that the intraday return are described by a discrete time homogeneous semi-Markov process and the overnight returns are modeled by a Markov chain. Based on this assumptions we derived…

2011-03-31abs ↗pdf ↗

The paper analyzes elicitability of return risk measures and their scoring functions.

problem Elicitability of return risk measures and their scoring functions.
method Dual representation results for convex and geometrically convex return risk measures, axiomatic characterizations of Orlicz premia, and construction of strictly consistent scoring functions.
result Orlicz premia are the only elicitable return risk measures under different sets of conditions.

The paper explores how AI trading agents' similar information representation can cause financial market instability.

problem Systemic instability in AI-dominated financial markets due to similar information representation.
method Structural multi-agent market model with two-layer decision architecture for AI agents.
result Representation homogeneity can lead to systemic instability in financial markets.

Extends return risk measures to multiple assets, proving properties and comparing different risk models.

problem Evaluating risk in financial markets with multiple assets.
method Develops multi-asset return risk measures (MARRMs), analyzes their properties, and compares them with other risk models.
result Proves that a positively homogeneous MARRM is quasi-convex if and only if it is convex, and provides conditions to avoid inconsistent risk evaluations.

The paper studies how expert opinions improve stock return predictions in a market with a hidden drift.

problem Improving stock return predictions in a market with a hidden Gaussian drift.
method Uses Kalman filter techniques to estimate the hidden drift from noisy expert opinions and stock returns.
result The Kalman filter estimates of the drift converge to the hidden drift as the frequency of expert opinions increases.

We test the price momentum effect in the Korean stock markets under the momentum universe shrinkage to subuniverses of the KOSPI 200. Performance of the momentum strategy is not homogeneous with respect to change of the momentum universe. It is found that some submarkets generate the higher momentum returns than other …

2012-11-28abs ↗pdf ↗

We study the high frequency price dynamics of traded stocks by a model of returns using a semi-Markov approach. More precisely we assume that the intraday returns are described by a discrete time homogeneous semi-Markov which depends also on a memory index. The index is introduced to take into account periods of high a…

2011-09-20abs ↗pdf ↗

We consider the tail probabilities of stock returns for a general class of stochastic volatility models. In these models, the stochastic differential equation for volatility is autonomous, time-homogeneous and dependent on only a finite number of dimensional parameters. Three bounds on the high-volatility limits of the…

2018-09-22abs ↗pdf ↗

The study uses Bayesian Hidden Markov Models to predict cryptocurrency returns.

problem Predicting the volatility and trends of cryptocurrencies.
method Bayesian Hidden Markov Models with four states to capture different return characteristics.
result The NHHM model with four states outperforms other models in predicting cryptocurrency returns.

Bayesian VAR and Elliptical Black-Litterman models improve portfolio optimization during regime changes and heavy-tailed returns.

problem Portfolio optimization under market regime changes and heavy-tailed returns.
method BAVAR-BLED algorithm combining BAVAR and Black-Litterman models with Elliptical Distributions.
result Significant outperformance of state-of-the-art methods in Sharpe, Sortino ratios, and total returns.

This paper gives a brief overview on the nonparametric techniques that are useful for financial econometric problems. The problems include estimation and inferences of instantaneous returns and volatility functions of time-homogeneous and time-dependent diffusion processes, and estimation of transition densities and st…

2004-11-01abs ↗pdf ↗

New risk metric for RL in finance considers time splits of returns.

problem Optimizing financial decisions with a balance between return and risk.
method Developed a new risk metric for reinforcement learning that allows for flexible target levels of rewards over time.
result Proposed risk metric optimizes for arbitrary time splits of returns, improving upon classical risk measures.

Researchers analyze optimal investment strategies for a collectivised pension fund with identical investors.

problem Optimizing investment strategies for a collectivised pension fund with identical investors.
method Analytical computation of optimal investment-consumption strategies for a fund of n identical investors with Epstein-Zin preferences.
result Constant consumption strategy is suboptimal for infinite collectives, suggesting annuities and defined benefit investments are suboptimal.

The paper optimizes portfolios in a market with hidden drift and random expert opinions.

problem Optimizing portfolios in a market with hidden Gaussian drift and random expert signals.
method Modeling the hidden drift using Kalman filters and solving the utility maximization problem with dynamic programming.
result Derivation of optimal portfolio weights and utility maximization under the given market conditions.

Study Nash equilibrium in market with relative wealth concerns under partial information and heterogeneous priors.

problem Analyzing Nash equilibrium in a market with unobservable return rates and heterogeneous priors.
method Established a Nash equilibrium through a separation result and martingale argument. Used fully-coupled linear FBSDEs and deep neural networks for numerical computation.
result Investment strategies under relative wealth concerns exhibit a herd effect, with accurate prior estimators leading the market.

This paper compares stationarity in Bitcoin and S&P500 price indices.

problem Comparing stationarity in cryptocurrency and traditional stock market indices.
method Wide sense stationarity defined; Wiener-Khinchin Theorem applied; stationarity achieved through detrending and normalization of price returns.
result S&P500 price return achieves stationarity for 28 years with specific normalization windows, while Bitcoin's stationarity varies by segment and volatility.

We study tick-by-tick financial returns belonging to the FTSE MIB index of the Italian Stock Exchange (Borsa Italiana). We can confirm previously detected non-stationarities. However, scaling properties reported in the previous literature for other high-frequency financial data are only approximately valid. As a conseq…

2012-12-03abs ↗pdf ↗

We consider the optimal investment problem when the traded asset may default, causing a jump in its price. For an investor with constant absolute risk aversion, we compute indifference prices for defaultable bonds, as well as a price for dynamic protection against default. For the latter problem, our work complements S…

2017-02-28abs ↗pdf ↗

Study reduces emissions in portfolios with error-prone emissions data.

problem Portfolio optimization with firm-level emissions intensities measured inaccurately.
method Introduced a scope-specific penalty operator to rescale asset payoffs based on revenue-normalized emissions intensity.
result Reduces average Scope~1 emissions intensity by roughly 92% while maintaining similar Sharpe ratios.

We give a complete algorithm and source code for constructing what we refer to as heterotic risk models (for equities), which combine: i) granularity of an industry classification; ii) diagonality of the principal component factor covariance matrix for any sub-cluster of stocks; and iii) dramatic reduction of the facto…

2015-08-20abs ↗pdf ↗

Unified framework for estimating high-dimensional conditional factor models.

problem Estimating high-dimensional conditional latent factor models with practical limitations.
method Constrained nuclear norm regularization and cross-validation for parameter selection.
result Imposing homogeneity improves model predictability, with new method outperforming alternatives.

BRACE addresses noncompliance in bandits, offering methods for recommendation and treatment policies.

problem Noncompliance in bandit problems complicates learning objectives and treatment effects.
method BRACE formalizes objective-choice, identifies direct-control regimes, and proposes a phase-doubling algorithm for IV inversion.
result BRACE delivers valid policy values and structural uncertainty, even under weak identification and homogeneity failure.

New framework optimizes portfolio diversification beyond mean-variance.

problem Optimizing portfolio diversification beyond classical methods.
method Introduces portfolio dimensionality, connects diversification to non-Gaussian returns, and develops global optimization algorithms.
result Maximizing portfolio dimensionality leads to highly non-trivial optimization problems with multiple local optima.

Recently, it is shown that each regular homogeneous Finsler space MM admits at least one homogeneous geodesic through any point oMo\in M. The purpose of this article is to study the existence of homogeneous geodesics on singular homogeneous (α,β)(α,β)-spaces, specially, homogeneous Kropina spaces. We show that any homoge…

2017-10-06abs ↗pdf ↗

In this paper, we study homogeneous geodesics in homogeneous Finsler spaces. We first give a simple criterion that characterizes geodesic vectors. We show that the geodesics on a Lie group, relative to a bi-invariant Finsler metric, are the cosets of the one-parameter subgroups. The existence of infinitely many homogen…

2007-06-24abs ↗pdf ↗

A new model for S&P 500 and VIX options pricing and calibration.

problem Calibrating and pricing S&P 500 and VIX options with a 4-factor path-dependent volatility model.
method Pathwise neural network approximation of VIX, leveraging Markovianity of the 4-factor model.
result The model accurately fits S&P 500 implied volatilities and reproduces VIX option smiles.

We prove that the Penrose limit of a spacetime along a homogeneous geodesic is a homogeneous plane wave spacetime and that the Penrose limit of a reductive homogeneous spacetime along a homogeneous geodesic is a Cahen--Wallach space. We then consider several homogenous examples to show that these results are indeed sha…

2004-05-26abs ↗pdf ↗

The study verifies a conjecture about homogeneous quotients of manifolds with positive curvature.

problem Verifying the Homogeneity Conjecture for manifolds with positive curvature.
method Examining globally homogeneous Riemannian quotients of homogeneous manifolds, focusing on those admitting a positive curvature metric.
result Further evidence supports the Homogeneity Conjecture for certain manifolds with positive curvature.

In this article we study homogeneous warped product Einstein metrics and its connections with homogeneous Ricci solitons. We show that homogeneous (λ,n+m)(λ,n+m)-Einstein manifolds (which are the bases of homogeneous warped product Einstein metrics) are one-dimensional extensions of algebraic solitons. This answers a questi…

2014-03-19abs ↗pdf ↗