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.
VOLARE provides standardized realized volatility measures from financial data.
Paper tackles MLR prediction error without assuming realizable models.
New offline RL method works with limited data and function approximators.
This paper tackles the challenge presented by small-data to the task of Bayesian inference. A novel methodology, based on manifold learning and manifold sampling, is proposed for solving this computational statistics problem under the following assumptions: 1) neither the prior model nor the likelihood function are Gau…
New algorithm SELECT minimizes satisficing regret in bandits.
Breaks the hardness conjecture for batch RL with a novel tournament-based approach.
New algorithm learns efficiently with a simple 'yes/no' oracle.
Study shows offline RL with partial coverage and weak function classes is possible.
This paper explores conformal prediction in the learning under privileged information (LUPI) paradigm. We use the SVM+ realization of LUPI in an inductive conformal predictor, and apply it to the MNIST benchmark dataset and three datasets in drug discovery. The results show that using privileged information produces va…
HAR model outperforms ML in stock forecasting with correct fitting schemes.
This paper proposes a new RV prediction model using neural distributional transformation and co-training.
PLoM learns stochastic solutions to PDEs with limited data.
We investigate active learning by pairwise similarity over the leaves of trees originating from hierarchical clustering procedures. In the realizable setting, we provide a full characterization of the number of queries needed to achieve perfect reconstruction of the tree cut. In the non-realizable setting, we rely on k…
We review the dynamics of the returns of Leveraged Exchange Traded Funds (LETFs) and propose a new measure of realized volatility: Shortfall from Maximum Convexity. We show that SMC has a more intuitive interpretation and provides more statistical information compared to the traditionally used sample standard deviation…
Criterion for realizing groups on Enriques manifolds.
Calculating similarities between objects defined by many heterogeneous data modalities is an important challenge in many multimedia applications. We use a multi-modal topic model as a basis for defining such a similarity between objects. We propose to compare the resulting similarities from different model realizations…
Bayesian realized EGARCH models improve tail risk forecasting.
The realized GARCH framework is extended to incorporate the two-sided Weibull distribution, for the purpose of volatility and tail risk forecasting in a financial time series. Further, the realized range, as a competitor for realized variance or daily returns, is employed in the realized GARCH framework. Further, sub-s…
A method to select validation data from a dataset using statistical criteria.
We study realizations of Lie algebras by vector fields. A correspondence between classification of transitive local realizations and classification of subalgebras is generalized to the case of regular local realizations. A reasonable classification problem for general realizations is rigorously formulated and an algori…
A new model framework called Realized Conditional Autoregressive Expectile (Realized-CARE) is proposed, through incorporating a measurement equation into the conventional CARE model, in a manner analogous to the Realized-GARCH model. Competing realized measures (e.g. Realized Variance and Realized Range) are employed a…
The paper examines circle graphs of Gauss diagrams and finds counterexamples to previous descriptions.
Machine learning has the potential to assist many communities in using the large datasets that are becoming more and more available. Unfortunately, much of that potential is not being realized because it would require sharing data in a way that compromises privacy. In order to overcome this hurdle, several methods have…
A universal LSTM model outperforms asset-specific models in forecasting stock volatilities.
Incorrect parity-based descriptions of realizable Gauss diagrams found, but bipartite graphs provide a valid approach.
The abstract discusses convergent realizations of Lie subalgebras in control theory.
Study tests rough fractional volatility model across different time scales, revealing new volatility patterns.
We give a characterization of conformal classes realizing a compact manifold's Yamabe invariant. This characterization is the analogue of an observation of Nadirashvili for metrics realizing the maximal first eigenvalue, and of Fraser and Schoen for metrics realizing the maximal first Steklov eigenvalue.
New bandit algorithm works without realizability assumption.
Realized moments of higher order computed from intraday returns are introduced in recent years. The literature indicates that realized skewness is an important factor in explaining future asset returns. However, the literature mainly focuses on the whole market and on the monthly or weekly scale. In this paper, we cond…
Study examines asymmetry impacts on Japanese stock market volatility modeling and forecasting.
We study Legendrian and transverse realizations of the negative torus knots in all contact structures on the -sphere. We give a complete classification of the strongly non-loose transverse realizations and the strongly non-loose Legendrian realizations with the Thurston-Bennequin invariant smaller than …
A new model forecasts financial risks using multiple realized measures.
Solves asymptotic -realization problem for curves.
We study distributions of realized variance (squared realized volatility) and squared implied volatility, as represented by VIX and VXO indices. We find that Generalized Beta distribution provide the best fits. These fits are much more accurate for realized variance than for squared VIX and VXO -- possibly another indi…
The paper addresses rigid alignment of noisy patches, providing a polynomial time algorithm and convergence conditions.
This paper considers the power of deep neural networks (deep nets for short) in realizing data features. Based on refined covering number estimates, we find that, to realize some complex data features, deep nets can improve the performances of shallow neural networks (shallow nets for short) without requiring additiona…
We undertake a systematic comparison between implied volatility, as represented by VIX (new methodology) and VXO (old methodology), and realized volatility. We compare visually and statistically distributions of realized and implied variance (volatility squared) and study the distribution of their ratio. We find that t…
Study algebraic obstructions to knot-like complex realizability.
We analyze realized volatilities constructed using high-frequency stock data on the Tokyo Stock Exchange. In order to avoid non-trading hours issue in volatility calculations we define two realized volatilities calculated separately in the two trading sessions of the Tokyo Stock Exchange, i.e. morning and afternoon ses…
Study compares adaptive vs fixed query learning methods.
We introduce a stochastic contextual bandit model where at each time step the environment chooses a distribution over a context set and samples the context from this distribution. The learner observes only the context distribution while the exact context realization remains hidden. This allows for a broad range of appl…
Researchers solve Nielsen Realization problems for K3 surfaces in various categories.
Investigates conditions for GKM fiber bundles and realizability of fiber bundles of GKM graphs.
Bayesian framework forecasts financial tail risks using realized volatility and nonlinear thresholds.
We introduce the notion of partial presimplicial set and construct its geometric realization. We show that any semiadequate diagram yields a partial presimplicial set leading to a geometric realization of the almost-extreme Khovanov homology of the diagram. We give a concrete formula for the homotopy type of this geome…
Groups of homotopy equivalences of graphs help realize compact subgroups.
Dehn twists on K3-type 4-manifolds are not homotopy coherently Nielsen realizable.