Research
On-device research index

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.

168,742 papers · 148 categories

Trend · papers per month

3468102136 · May 202619922001200920172026
48 results for Trump family

Study examines Trump's crypto influence on markets, revealing conflicts and vulnerabilities.

problem Presidential power and cryptocurrency markets during Trump's second term.
method Mixed-methods approach combining quantitative and qualitative data.
result Political-linked digital assets became a distinct class with systemic vulnerabilities.

Study examines how Trump tariffs and COVID-19 affected financial market efficiency.

problem Impact of geopolitical and systemic shocks on financial market efficiency.
method Multifractal detrended fluctuation analysis applied to financial asset returns.
result Trump tariffs had moderate but observable effects on market efficiency, while COVID-19 induced substantial changes.

Policy shifts between Trump and Biden impact ESG investments, creating volatility.

problem Dramatic policy shifts between Trump and Biden administrations affect ESG investments.
method Analyzes contrasting policies of Trump and Biden administrations and their impacts on ESG investments.
result Policy changes significantly influence ESG investments, leading to volatility and portfolio reassessment.

Analyzes how Trump's tweets impact global stock markets.

problem Understanding the financial impact of presidential tweets on stock markets.
method Examined tweets from Donald Trump's presidency, collected from The Guardian and Bloomberg, and analyzed their effect on equity indices.
result Identified tweets that significantly influenced stock market indices.

During times of extreme market turmoil, it is acknowledged that there is a tendency towards "flight to safety". A strong (weak) safe haven is defined as an asset that has a significant positive (negative) return in periods where another asset is in distress, while hedge has to be negatively correlated (uncorrelated) on…

2017-03-01abs ↗pdf ↗

We present PROPS, a lightweight transfer learning mechanism for sequential data. PROPS learns probabilistic perturbations around the predictions of one or more arbitrarily complex, pre-trained black box models (such as recurrent neural networks). The technique pins the black-box prediction functions to "source nodes" o…

2019-03-05abs ↗pdf ↗

We discuss the local and global problems for the equivalence of geometric structures of an arbitrary order and, in later sections, attention is given to what really matters, namely the equivalence with respect to transformations belonging to a given pseudo-group of transformations. We first give attention to general pr…

2014-12-29abs ↗pdf ↗

Donald Trump was lagging behind in nearly all opinion polls leading up to the 2016 US presidential election, but he surprisingly won the election. This raises the following important questions: 1) why most opinion polls were not accurate in 2016? and 2) how to improve the accuracies of opinion polls? In this paper, we …

2018-12-31abs ↗pdf ↗

This article presents a preliminary approach towards characterizing political fake news on Twitter through the analysis of their meta-data. In particular, we focus on more than 1.5M tweets collected on the day of the election of Donald Trump as 45th president of the United States of America. We use the meta-data embedd…

2017-12-16abs ↗pdf ↗

Dynamic Time Warping improves regression accuracy on spectroscopy data.

problem Improving regression accuracy on spectroscopy data with DTW when data is across multiple wavelengths.
method Illustrated DTW's effectiveness on spectroscopy time-series data, showing its benefits in improving regression accuracy when only a single wavelength is considered. DTW combined with k-Nearest Neighbour reveals similarities and differences at the time-series level.
result DTW improves regression accuracy on spectroscopy data, especially when considering a single wavelength.

Much significant research has been done to investigate various facets of the link between Bitcoin price and its fundamental sources. This study goes beyond by looking into least to most influential factors-across the fundamental, macroeconomic, financial, speculative and technical determinants as well as the 2016 event…

2017-07-05abs ↗pdf ↗

Study examines market response to concentrated policy communication using entropy measures.

problem Characterizing market response under concentrated policy communication.
method Jointly examines dispersion and information complexity (entropy) using sliding window cumulative entropy.
result Entropy captures both market volatility and narrative constraints, signaling coherent policy-driven moves.

In the paper we formulate and derive the family blowup formula of family Seiberg-Witten invariants. The formula has been used in the enumerative application of counting singular curves on algebraic surfaces. We first give a topological derivation of the formula by using family index theorem. Then we define the algebrai…

2003-05-20abs ↗pdf ↗

Squared families are a new model class derived from linear transformations, offering convenient properties and universal approximation.

problem Developing a new class of probability models that are easier to handle and have useful properties.
method Introducing squared families as families of probability densities obtained by squaring a linear transformation of a statistic, and showing their properties and applications.
result Squared families have convenient properties and can approximate target densities well.

Smooth families of biholomorphisms between strongly pseudoconvex domains are shown to be smooth.

problem Smoothness of families of biholomorphisms between strongly pseudoconvex domains.
method Riemannian geometry of Bergman metrics and smoothness of families of isometries.
result Smoothness of families of biholomorphisms between strongly pseudoconvex domains.

Computes Seiberg-Witten invariants for Kähler families of 4-manifolds.

problem Computing invariants for families of Kähler 4-manifolds.
method Generalized Seiberg-Witten invariants for smooth families of 4-manifolds with Kähler structures.
result Computed invariants for specific Kähler families in terms of characteristic classes.

We investigate families of Legendrian submanifolds of 1-jet spaces by developing and applying a theory of families of generating family homologies. This theory allows us to detect an infinite family of loops of Legendrian n-spheres embedded in the standard contact (2n+1)-space (for n>1) that are contractible in the smo…

2013-11-03abs ↗pdf ↗

Study families of flat connections with nilpotent Higgs fields, showing similar monodromy to regular Higgs bundles.

problem Investigate Cimes\mathbb{C}^ imes-families of flat connections with nilpotent Higgs fields.
method Analyze families of flat connections including real twistor lines and conformal limits, deducing monodromy similarities.
result Traces of holonomies are asymptotically exponential in rational powers of the parameter of the family.

Tangential families are 1-parameter families of rays emanating tangentially from smooth curves. We classify tangential family germs up to Left-Right equivalence: we prove that there are two infinite series and four sporadic simple singularities of tangential family germs (in addition to two stable singularities). We gi…

2004-09-06abs ↗pdf ↗

We consider the local analytic behavior for a family of holomorphic differentials on a family of degenerating annuli. Three results and discussion are presented. The first is the normal families Lemma 1. The second is an isomorphism of sheaves, formula (3), giving a direct description of families of regular kk-differe…

2011-08-16abs ↗pdf ↗

Consider two families of closed oriented curves in a d-manifold. At each point of intersecction of a curve of one family with a curve of the other family, form a new closed curve by going around the first curve and then going around the second. Typically, an i-dimensional family and a j-dimensional family will produce …

1999-11-21abs ↗pdf ↗

Paper introduces kernel deformed exponential families for sparse continuous attention.

problem Creating efficient attention mechanisms for sparse data.
method Developed kernel deformed exponential families, theoretically and experimentally.
result Kernel deformed exponential families can attend to multiple compact regions of data.

After defining reduced minimum braid word and criteria for a braid family representative, different braid family representatives are derived, and a correspondence between them and families of knots and links given in Conway notation is established.

2005-04-23abs ↗pdf ↗

Study algebraic relations of Vassiliev invariants for families of knots.

problem Understanding algebraic structure of Vassiliev invariants for knot families.
method Analyzing algebraic relations and generating sets of Vassiliev invariants in 3D Chern-Simons theory.
result For 1-parametric knot families, Vassiliev invariants are finitely generated. For more parameters, there can be an infinite number of generators.

Constructs non-abelian G2-instantons on ALC members of B7 family.

problem Constructing non-abelian G2-instantons on ALC members of B7 family.
method Using co-homogeneity one symmetries, classify and describe the solutions as perturbations of abelian instantons.
result Find a one-parameter family of instantons with polynomial decay.

The paper introduces structured variational families to improve scalability in black-box variational inference.

problem Scalability issues in black-box variational inference, especially for large datasets and hierarchical models.
method Developed structured variational families that achieve better iteration complexity of O(N) compared to full-rank families.
result Structured variational families can achieve better scaling with respect to dataset size N, improving iteration complexity from O(N^2) to O(N).

In this paper, we study the analogue of the Shafarevich conjecture for polarized Calabi-Yau varieties. We use variations of Hodge structures and Higgs bundles to establish a criterion for the {\it rigidity} of families. We then apply the criterion to obtain that some important and typical families of Calabi-Yau varieti…

2003-08-05abs ↗pdf ↗

Exponential family distributions are highly useful in machine learning since their calculation can be performed efficiently through natural parameters. The exponential family has recently been extended to the t-exponential family, which contains Student-t distributions as family members and thus allows us to handle noi…

2017-05-25abs ↗pdf ↗

In this paper, we first prove a local family version of the Atiyah-Bott-Segal-Singer Lefschetz fixed point formula, then we extend the famous Witten's rigidity Theorems to the family case. Several family vanishing theorems for elliptic genera are also proved.

1999-10-08abs ↗pdf ↗

The classical H surfaces of H. A. Schwarz form a 1-parameter family of triply periodic minimal surfaces (TPMS) that are usually described as close relatives to his more famous P surface. However, a crucial distinction between these surfaces is that the P surface belongs to a 5-dimensional smooth family of embedded TPMS…

2018-07-26abs ↗pdf ↗

Geometric equation defines canonical metrics on vector bundle families.

problem Finding canonical metrics on families of holomorphic vector bundles.
method Introducing a geometric partial differential equation for families of holomorphic vector bundles.
result Construction of Hermite--Einstein metrics in adiabatic classes on product manifolds and proof of the existence of a unique solution for the Dirichlet problem.

In LM, we proved a family version of the famous Witten rigidity theorems and several family vanishing theorems for elliptic genera. In this paper, we gerenalize our theorems LM in two directions. First we establish a family rigidity theorem for the Dirac operator on loop space twisted by general positive energy loop gr…

1999-11-05abs ↗pdf ↗

We study the problem of recovering the subspace spanned by the first kk principal components of dd-dimensional data under the streaming setting, with a memory bound of O(kd)O(kd). Two families of algorithms are known for this problem. The first family is based on the framework of stochastic gradient descent. Nevertheles…

2015-06-04abs ↗pdf ↗