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.
Trading strategy uses Hoeffding's Inequality to predict financial regime change.
Modular pipeline improves stock portfolio prediction robustness under regime changes.
Study identifies change points in piecewise constant reward functions with fixed exploration budget.
This study examines how ChiNext IPOs' initial returns are influenced by regulation regime changes.
Study shows registration regime improves IPO pricing efficiency in China.
Paper optimizes change-point detection using learned distributions from training sequences.
The rBergomi model is improved with a regime switching change of measure to match market VIX smiles.
Unified framework detects change-points and estimates parameters in nonlinear systems with regime switching.
In this paper, we study the modeling and the classification of functional data presenting regime changes over time. We propose a new model-based functional mixture discriminant analysis approach based on a specific hidden process regression model that governs the regime changes over time. Our approach is particularly a…
Bayesian method detects change points in time series data.
Model predicts risk-adjusted returns across various financial markets.
Financial markets change their behaviours abruptly. The mean, variance and correlation patterns of stocks can vary dramatically, triggered by fundamental changes in macroeconomic variables, policies or regulations. A trader needs to adapt her trading style to make the best out of the different phases in the stock marke…
ProteuS generates synthetic financial data with regime changes for testing drift detection.
The paper improves energy contract pricing models by incorporating jumps and varying parameters.
New method clusters financial time series into volatility regimes.
Statistical approaches for Functional Data Analysis concern the paradigm for which the individuals are functions or curves rather than finite dimensional vectors. In this paper, we particularly focus on the modeling and the classification of functional data which are temporal curves presenting regime changes over time.…
RegimeFolio optimizes portfolios by adapting to changing market regimes.
Bayesian VAR and Elliptical Black-Litterman models improve portfolio optimization during regime changes and heavy-tailed returns.
Paper proposes BOCPD for real-time order flow and market impact prediction.
We introduce a novel geometry-oriented methodology, based on the emerging tools of topological data analysis, into the change point detection framework. The key rationale is that change points are likely to be associated with changes in geometry behind the data generating process. While the applications of topological …
This paper presents the construction of a particle filter, which incorporates elements inspired by genetic algorithms, in order to achieve accelerated adaptation of the estimated posterior distribution to changes in model parameters. Specifically, the filter is designed for the situation where the subsequent data in on…
A new jump diffusion regime-switching model is introduced, which allows for linking jumps in asset prices with regime changes. We prove the existence and uniqueness of the solution to the risk-sensitive asset management criterion maximisation problem in this setting. We provide an ODE for the optimal value function, wh…
Study improves S&P 500 volatility forecasting through regime-switching methods.
This paper introduces a novel model-based clustering approach for clustering time series which present changes in regime. It consists of a mixture of polynomial regressions governed by hidden Markov chains. The underlying hidden process for each cluster activates successively several polynomial regimes during time. The…
A major impact of globalization has been the information flow across the financial markets rendering them vulnerable to financial contagion. Research has focused on network analysis techniques to understand the extent and nature of such information flow. It is now an established fact that a stock market crash in one co…
Framework models multiscale dynamics with Bayesian learning for regime changes.
Mixture model-based clustering, usually applied to multidimensional data, has become a popular approach in many data analysis problems, both for its good statistical properties and for the simplicity of implementation of the Expectation-Maximization (EM) algorithm. Within the context of a railway application, this pape…
The paper develops methods to accurately locate change points in high-dimensional mean shift models.
Modeling regime shifts in co-evolving time series with interactions and time-dependency.
The present paper aims at locating the breakings of the integration process of an international system observed during about 50 years in the 19th century. A historical study could link them to special events, which operated as exogenous shocks on this process. The indicator of integration used is the spread between the…
This paper improves risk control for financial markets by calibrating VaR forecasts using conformal methods.
Model for dynamic relational data with regime changes.
We have developed a statistical technique to test the model assumption of binary regime switching extension of the geometric Brownian motion (GBM) model by proposing a new discriminating statistics. Given a time series data, we have identified an admissible class of the regime switching candidate models for the statist…
The paper extends MS models with TVTP to U.S. Treasury yields, finding reliable regime dynamics but challenging TVTP identification.
This paper considers the optimal portfolio selection problem in a dynamic multi-period stochastic framework with regime switching. The risk preferences are of exponential (CARA) type with an absolute coefficient of risk aversion which changes with the regime. The market model is incomplete and there are two risky asset…
Algorithm detects changes online using expert tracking.
New framework for regression trees with multivariate response and dynamic mean vectors.
The private car license plates issued in Shanghai are bestowed the title of "the most expensive sheet iron all over the world", more expensive than gold. A citizen has to bid in an monthly auction to obtain a license plate for his new private car. We perform statistical analysis to investigate the influence of the mini…
The article detects market regimes from covariance matrices using VLSTAR and clustering models.
Improves decision complexity in hybrid environments.
BRPC online Bayesian calibration handles gradual and abrupt system changes.
In this paper, we consider the optimal dividend problem for a company. We describe the surplus process of the company by a diffusion model with regime switching. The aim of the company is to choose a dividend policy to maximize the expected total discounted payments until ruin. In this article, we consider a hybrid div…
A new method for pricing European options in changing market conditions.
A new approach is presented to describe the change in the statistics of the log return distribution of financial data as a function of the timescale. To this purpose a measure is introduced, which quantifies the distance of a considered distribution to a reference distribution. The existence of a small timescale regime…
Paper addresses uncertainty in model generalization under regime shifts.
Patients with epilepsy can manifest short, sub-clinical epileptic "bursts" in addition to full-blown clinical seizures. We believe the relationship between these two classes of events---something not previously studied quantitatively---could yield important insights into the nature and intrinsic dynamics of seizures. A…
We consider option pricing in a regime-switching diffusion market. As the market is incomplete, there is no unique price for a derivative. We apply the good-deal pricing bounds idea to obtain ranges for the price of a derivative. As an illustration, we calculate the good-deal pricing bounds for a European call option a…
We analyze waiting times for price changes in a foreign currency exchange rate. Recent empirical studies of high frequency financial data support that trades in financial markets do not follow a Poisson process and the waiting times between trades are not exponentially distributed. Here we show that our data is well ap…