Convolutional Neural Networks predict forex trends from charts.
problem Predicting forex trends from trading charts.
method Pre-process data, train CNN, evaluate model performance.
result Trades strategies can be automatically generated.
Deep CNN model uses stock bar charts for trading, outperforming Buy and Hold.
problem Predicting stock prices using 2D bar charts instead of time series data.
method 2D Convolutional Neural Network (CNN) trained on bar chart images of 30-day windows.
result Model outperformed Buy and Hold strategy, especially in trendless markets.
In this paper we try to design the necessary calculation needed for backtesting trading systems when only candle chart data are available. We lay particular emphasis on situations which are not or not uniquely decidable and give possible strategies to handle such situations.
Trading strategies improved by classifying financial time-series images.
problem Improving financial trading strategies using image classification.
method Created a dataset of financial time-series images, labeled them, and trained machine learning models.
result Machine learning models trained on image data outperformed traditional time-series analysis.
We propose a new indicator for technical analysis. The indicator emphasizes maximums and minimums in price series with inherent smoothing and has a potential to be useful in both mechanical trading rules and chart pattern analysis.
FinVision uses LLM agents to predict stock markets by processing various financial data types.
problem Challenges in integrating diverse financial data for accurate stock market prediction.
method Multi-agent framework with LLMs specialized in different financial data types and a reflection module.
result The reflection module enhances decision-making capabilities for financial trading.
MountainLion uses LLMs to interpret financial data and generate investment strategies.
problem Challenges in integrating heterogeneous data for financial trading.
method Multi-modal LLM-based agents that process textual and visual data.
result Improves returns and investor confidence through interpretable investment framework.
No minimal charts with exactly seven white vertices found.
problem Finding minimal charts with specific vertex counts.
method Investigating charts representing embedded surfaces in 4-space.
result No minimal chart with exactly seven white vertices exists.
This paper studies minimal charts of a specific type to understand embedded surfaces in 4-space.
problem Investigating minimal charts of a specific type to understand embedded surfaces in 4-space.
method Analyzing charts of type (5,2) to find a minimal chart.
result Identified a minimal chart of type (5,2) representing an embedded surface in 4-space.
In this paper, we give definitions of three kinds of minimal charts, and we investigate properties of minimal charts and establish fundamental theorems characterizing minimal charts. To classify charts with two or three crossings we use the fundamental theorems. In the future paper, we give an numeration of the charts …
No minimal chart of type (7) exists.
problem Characterizing minimal charts of specific types.
method Analyzing charts based on edge labels and white vertex counts.
result There is no minimal chart of type (7).
No minimal chart of type (4,3) exists in 4-space.
problem Existence of minimal charts of specific type in 4-space.
method Investigation of charts and their properties in 4-space.
result No minimal chart of type (4,3) exists.
Paper classifies surface-links using charts with specific properties.
problem Classifying surface-links with specific charts.
method Using quandle colorings to differentiate charts representing different surface-links.
result Charts in the second class represent different surface-links.
The paper studies 4-charts with three crossings and their equivalence to a specific knot.
problem Investigating the structure and equivalence of 4-charts with three crossings.
method Examining charts as oriented labeled graphs in a disk, focusing on acyclic components and equivalence through label-orientation-reflection.
result Any linear minimal 4-chart with three crossings is equivalent to a 2-twist spun trefoil knot.
No minimal chart of type (2,3,2) exists.
problem Characterizing minimal charts of specific types.
method Analyzing charts with given edge label constraints.
result No minimal chart of type (2,3,2) exists.
No minimal chart of type (3,2,2) exists.
problem Characterizing minimal charts of specific types.
method Analyzing charts of type (3,2,2) and proving non-existence.
result There is no minimal chart of type (3,2,2).
Minimal charts of specific type contain unique subgraphs.
problem Characterizing minimal charts of type (m;2,3,2). method Analyzing the structure of charts and their subgraphs.
result Each of Γm+1 and Γm+2 contains one of three specific subgraphs. Simplifies surface-knots using chart moves involving black vertices.
problem Simplifying branched covering surface-knots.
method Chart moves involving black vertices to simplify surface-knots.
result Properties of simplified branched covering surface-knots with branch points.
In this paper, we shall show a condition for that a chart is C-move equivalent to the product of two charts, the union of two charts Γ∗ and Γ∗∗ which are contained in disks D∗ and D∗∗ with D∗∩D∗∗=∅.
Simplifies surface-knots by adding 1-handles with chart loops.
problem Complexity of branched covering surface-knots.
method Adding 1-handles with chart loops to simplify charts.
result Properties of simplified charts are investigated.
This paper studies the structure of a specific neighborhood in minimal 2-crossing charts.
problem Understanding the structure of a minimal 2-crossing chart with specific neighborhoods.
method Analyzes the neighborhoods of Γα∪Γβ and proposes a normal form for 2-crossing minimal n-charts. result Proposes a normal form for 2-crossing minimal n-charts. Support Vector Data Description (SVDD) is a machine learning technique used for single class classification and outlier detection. SVDD based K-chart was first introduced by Sun and Tsung for monitoring multivariate processes when underlying distribution of process parameters or quality characteristics depart from Norm…
Study integrates deep learning with financial data for improved trading strategies.
problem Enhancing predictive performance in algorithmic trading and portfolio optimization.
method Developed embedding techniques to treat limit order book snapshots as image-based input channels.
result Achieved state-of-the-art performance in high-frequency trading algorithms.
A method to fix radius distortion in generative models on curved spaces.
problem Distortion in geodesic radius measurements across different charts on Riemannian manifolds.
method Radial Compensation (RC) adjusts the tangent-space base distribution to match the geodesic radius law, improving model stability and interpretability.
result RC ensures that the model's geodesic radius matches the intended distribution, improving numerical stability and curvature interpretation.
Paper improves channel charting using autoencoders with spatial constraints.
problem Improving logical positioning of UEs using channel-state information.
method Representation-constrained autoencoders to enhance channel charts.
result Improved quality of learned channel charts for UE positioning.
Study uses CNN and LSTM to recognize stock chart patterns.
problem Recognizing stock chart patterns for trading.
method Used CNN and LSTM neural networks on historical stock data.
result Obtained accuracies for recognizing two common chart patterns.
Enhances trading signals using image analysis and weighted moving averages.
problem Improving price trend trading strategies in financial markets.
method Image-induced importance weights applied to weighted moving averages of trading signals.
result Significant enhancement of price trend trading signals with improved portfolio selection.
Let Γ be a chart. For each label m, we denote by Γm the "subgraph" of Γ consisting of all the edges of label m and their vertices. Let Γ be a minimal chart of type (m;3,3). That is, a minimal chart Γ has six white vertices, and both of Γm∩Γm+1 and Γm+1∩Γm+2 consist of three white ve…
A 2-dimensional braid over an oriented surface-knot F is presented by a graph called a chart on a surface diagram of F. We consider 2-dimensional braids obtained by an addition of 1-handles equipped with chart loops. We introduce moves of 1-handles with chart loops, called 1-handle moves, and we investigate how muc…
Dance Dance Revolution (DDR) is a popular rhythm-based video game. Players perform steps on a dance platform in synchronization with music as directed by on-screen step charts. While many step charts are available in standardized packs, players may grow tired of existing charts, or wish to dance to a song for which no …
New surfaces in 4-ball constructed from knits, described by charts.
problem Constructing surfaces in 4-ball from knits.
method Introducing knitted surfaces, describing them with BMW charts.
result Every compact surface in 4-ball is ambiently isotopic to a knitted surface.
Chart autoencoders learn latent features preserving manifold topology and geometry, with robust denoising capabilities.
problem Learning low-dimensional latent features of high-dimensional data sampled near a manifold.
method Chart autoencoders encode data into latent features on charts, preserving manifold topology and geometry.
result Chart autoencoders achieve a squared generalization error of n−d+22log4n under proper network architectures. Chart descriptions are a graphic method to describe monodromy representations of various topological objects. Here we introduce a chart description for hyperelliptic Lefschetz fibrations, and show that any hyperelliptic Lefschetz fibration can be stabilized by fiber-sum with certain basic Lefschetz fibrations.
We investigate minimal charts with loops, a simple closed curve consisting of edges of label m containing exactly one white vertex. We shall show that there does not exist any loop in a minimal chart with exactly seven white vertices in this paper.
CC charts radio geometry for user localization.
problem Locating users in radio environments.
method Unsupervised learning from passive CSI.
result Extracts channel features for spatial comparison.
Agent Trading Arena trains LLMs in real-time financial markets to improve numerical reasoning.
problem Limited real-world training for LLMs in financial markets.
method Virtual zero-sum stock market with competitive multi-agent trading.
result LLMs perform better with chart-based visualizations and a reflection module.
Introduces Hurewicz fibrations for embedding maps of orbifold charts.
problem No specific problem stated; focuses on new concept definition.
method Defines E-fibration embedding and studies its properties.
result Introduces and studies properties of E-fibration embedding.
Deep learning predicts stock market trends using candlestick charts.
problem Predicting stock market prices with multiple influencing factors.
method Used Deep Convolutional Neural Networks and candlestick charts.
result 92.2% and 92.1% accuracy for Taiwan and Indonesian stock markets.
Chart descriptions are a graphic method to describe monodromy representations of various topological objects. Here we introduce a chart description for genus-two Lefschetz fibrations, and show that any genus-two Lefschetz fibration can be stabilized by fiber-sum with certain basic Lefschetz fibrations.
We give a combinatorial description of closed curves on oriented surfaces in terms of certain permutations, called charts. We describe automorphisms of curves in terms of charts and compute the total number of curves counted with appropriate weights. We also discuss relations between curves, Grothendieck dessins d'enfa…
Unified Siamese network for wireless positioning and channel charting.
problem Wireless positioning and channel charting using CSI.
method Unified Siamese neural network architecture for both supervised and unsupervised learning.
result Siamese networks achieve similar or better performance than existing methods.
The paper proves uniform Temple charts and applies them to null distance metrics.
problem Proving the existence of uniform Temple charts and their applications to null distance metrics.
method Constructing uniform Temple charts and estimating gradients of optical functions; applying these charts to study spacetime metrics.
result Proves (N,d^τ) is a rectifiable metric space and applies a Lorentzian isometry theorem. Introduces orbifolds from charts and various topological perspectives.
problem No specific problem stated; introduces new mathematical objects.
method Charts and classical topological perspectives.
result Orbifolds defined and properties from Algebraic, Differential, and Riemannian Geometries.
This is the first step of the two steps to enumerate the minimal charts with two crossings. For a label m of a chart Γ we denote by Γm the union of all the edges of label m and their vertices. For a minimal chart Γ with exactly two crossings, we can show that the two crossings are contained in Γα∩Γβ f…
In this paper, we find a holomorphic Darboux chart around any immersed noncompact holomorphic Legendrian curve in a complex contact manifold (X,ξ). By using such a chart, we show that every holomorphic Legendrian immersion R→X from an open Riemann surface can be approximated on relatively compact subsets by holo…
Continuing the study of bounded geometry for Riemannian foliations, begun by Sanguiao, we introduce a chart-free definition of this concept. Our main theorem states that it is equivalent to a condition involving certain normal foliation charts. For this type of charts, it is also shown that the derivatives of the chang…
A new control chart detects shifts in binary data streams quickly and reliably.
problem Early detection of small shifts in multiple binary data streams.
method Cumulative Standardized Binomial EWMA (CSB-EWMA) chart with exact variance derivation.
result Adaptive control limits ensure robust detection across different data distributions.
FinAgent tackles financial trading with multimodal data and advanced AI.
problem Challenges in handling multimodal financial data and limited generalizability.
method Multimodal foundational agent with tool augmentation, dual-level reflection, and diversified memory retrieval.
result Significantly outperforms state-of-the-art baselines in financial trading tasks.