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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.

168,657 papers · 148 categories

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3469103137 · May 202619922001200920172026
48 results for Sharp move

We investigate the behaviour of Rasmussen's invariant ss under the sharp operation on knots and obtain a lower bound for the sharp unknotting number. This bound leads us to an interesting move that transforms arbitrary knots into non-alternating knots.

2006-02-06abs ↗pdf ↗

Dynamic trading strategies, in the spirit of trend-following or mean-reversion, represent an only partly understood but lucrative and pervasive area of modern finance. Assuming Gaussian returns and Gaussian dynamic weights or signals, (e.g., linear filters of past returns, such as simple moving averages, exponential we…

2019-05-31abs ↗pdf ↗

The Margulis constant for Kleinian groups is the smallest constant cc such that for each discrete group GG and each point xx in the upper half space H3{\bold H}^3, the group generated by the elements in GG which move xx less than distance c is elementary. We take a first step towards determining this constant by p…

1995-04-07abs ↗pdf ↗

DASH improves ensemble generalizability by encouraging diverse, flat loss landscapes.

problem Improving generalization and robustness of deep ensembles.
method DASH promotes diversity and flatness in deep ensembles by encouraging base learners to move towards low-loss regions of minimal sharpness.
result DASH improves ensemble generalizability, as demonstrated by extensive empirical evidence.

We present a detailed study of the performance of a trading rule that uses moving average of past returns to predict future returns on stock indexes. Our main goal is to link performance and the stochastic process of the traded asset. Our study reports short, medium and long term effects by looking at the Sharpe ratio …

2019-06-29abs ↗pdf ↗

A new method corrects bias in machine learning for trading by filtering out non-executable prices.

problem Contaminated data from price limits causes misleading performance metrics in trading models.
method Mask-first design with tradability filters, GPU optimization, and penalized losses.
result The system achieves Sharpe ratios of 1.63 on real data, significantly outperforming existing methods.

This paper improves bounds on how many Delta-moves are needed to trivialize a link.

problem Counting the minimum number of Delta-moves to make a link homotopy trivial.
method Classification of link homotopy and extremal graph theory.
result Quadratic and cubic upper bounds on the homotopy trivializing numbers of links.

Sharp analysis of power iteration for tensor PCA, improving convergence and stopping criteria.

problem Analyzing the power iteration algorithm for tensor PCA to improve convergence and stopping criteria.
method Sharp bounds on the number of iterations, revealing a smaller algorithmic threshold, proposing a stopping criterion.
result Sharp bounds on the number of iterations required for power method to converge, revealing a smaller algorithmic threshold than previously conjectured.

The asymptotic behavior of the heat kernel of a Riemannian manifold gives rise to the classical concepts of parabolicity, stochastic completeness (or conservative property) and Feller property (or C0C^{0}-diffusion property). Both parabolicity and stochastic completeness have been the subject of a systematic study whic…

2010-10-08abs ↗pdf ↗

Let MM be an nn-vertex combinatorial triangulation of a $\ZZ_2$-homology dd-sphere. In this paper we prove that if nd+8n \leq d + 8 then MM must be a combinatorial sphere. Further, if n=d+9n = d + 9 and MM is not a combinatorial sphere then MM can not admit any proper bistellar move. Existence of a 12-vertex triangula…

2005-06-27abs ↗pdf ↗

Improved trading strategy using deep learning and changepoint detection for market changes.

problem Traditional momentum strategies struggle with rapid market changes, especially after trend reversals.
method Inserted an online changepoint detection module into a Deep Momentum Network (DMN) pipeline.
result Improvement in Sharpe ratio by one-third over 1995-2020 period, especially beneficial in nonstationary periods.

The World Trade Web (WTW) is a weighted network whose nodes correspond to countries with edge weights reflecting the value of imports and/or exports between countries. In this paper we introduce to this macroeconomic system the notion of extinction analysis, a technique often used in the analysis of ecosystems, for the…

2011-04-22abs ↗pdf ↗

A new method uses deep learning to efficiently solve complex physics equations in high dimensions.

problem Efficiently solving high-dimensional time-dependent PDEs with dynamic solutions.
method Deep adaptive sampling framework for PINNs extended to spacetime domains using normalizing flows.
result The method effectively identifies and tracks high-residual regions in both space and time.

We study the emergence of instabilities in a stylized model of a financial market, when different market actors calculate prices according to different (local) market measures. We derive typical properties for ensembles of large random markets using techniques borrowed from statistical mechanics of disordered systems. …

2012-07-02abs ↗pdf ↗

Behavior cloning training instabilities amplified by SGD noise over long horizons.

problem Training instabilities in behavior cloning with deep neural networks.
method Empirical dissection of minibatch SGD updates and their effects on long-horizon rewards.
result Exponential moving average (EMA) of iterates effectively mitigates gradient variance amplification (GVA).

It is well known that any two diagrams representing the same oriented link are related by a finite sequence of Reidemeister moves O1, O2 and O3. Depending on orientations of fragments involved in the moves, one may distinguish 4 different versions of each of the O1 and O2 moves, and 8 versions of the O3 move. We introd…

2009-08-21abs ↗pdf ↗

In this paper, we introduce an equivalence relation on the set of local moves and classify local moves, called the extended STST-moves, up to the equivalence. Moreover, by inducing a binary relation on the set of equivalence classes of local moves, we show that an extended STST-move realizes the crossing change or the …

2016-04-26abs ↗pdf ↗

Minimal sets of moves for isotopic knots and trivalent graphs identified.

problem Identifying minimal sets of moves for isotopic knots and trivalent graphs.
method Provided and proved the existence of minimal generating sets of oriented Reidemeister moves for isotopic knots and spatial trivalent graphs.
result Twelve minimal generating sets of oriented Reidemeister moves for isotopic knots and ten for spatial trivalent graphs identified.

The H(n)-move simplifies virtual and welded knots and links.

problem Tackling the unknotting of virtual and welded links.
method Extending the H(n)-move to virtual and welded links and showing their equivalence to Reidemeister moves.
result Virtualization and forbidden move can be realized by a finite sequence of generalized Reidemeister moves and H(n)-moves.

We prove that the classical set of moves for standard spines of 3-manifolds (i.e. the MP-move and the V-move) does not suffice to relate to each other any two standard skeleta of a 3-manifold with marked boundary. We also describe a condition on the 3-manifold with marked boundary that tells whether the generalised set…

2008-04-04abs ↗pdf ↗

Large learning rates cause parameter instability, leading to better generalization.

problem Understanding why deep neural networks perform well despite operating outside the traditional stability regime.
method Analyzing the effect of large learning rates on the orientation of Hessian eigenvectors and parameter exploration.
result Large learning rates induce parameter instability, leading to better generalization through exploration of flatter regions of the loss landscape.

Study proposes adaptive RL for dynamic portfolio optimization.

problem Traditional portfolio optimization models fail to adapt to regime shifts.
method Regime-aware reinforcement learning framework with hybrid observations and constrained reward functions.
result Transformer PPO achieves highest risk-adjusted returns, while LSTM variants offer a good balance.

New methods for delta-moves on algebraically split links identified.

problem Understanding delta-moves on algebraically split links.
method Introducing self and mixed delta-moves, proving equivalence, and calculating delta-splitting numbers.
result Two links are mixed delta-equivalent if they have the same pairwise linking number and components.

We start a systematic analysis of links up to 5-move equivalence. Our motivation is to develop tools which later can be used to study skein modules based on the skein relation being deformation of a 5-move (in an analogous way as the Kauffman skein module is a deformation of a 2-move, i.e. a crossing change). Our main …

2007-12-06abs ↗pdf ↗

Link concordance equals homotopy for high-dimensional spheres.

problem Understanding when immersions of high-dimensional spheres are homotopically trivial.
method Developed stratified Morse theory for generic immersions, using gradient-like vector fields and Cerf theory.
result Every link of high-dimensional spheres is homotopically trivial, resolving a long-standing conjecture.

The ΞΞ-move is a local move generated by forbidden moves in virtual knot theory. This move was introduced by Taniguchi and the second author, who showed that it characterizes the odd writhe of virtual knots, which is a fundamental invariant defined by Kauffman. In this paper, we extend this result by classifying 22-c…

2020-02-19abs ↗pdf ↗