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.
Automated VOC classification using embedded machine learning.
ETFs with 2x and 3x leverage underperformed the S&P 500 index due to compounding and volatility.
In this paper, we study various new Hawkes processes. Specifically, we construct general compound Hawkes processes and investigate their properties in limit order books. With regards to these general compound Hawkes processes, we prove a Law of Large Numbers (LLN) and a Functional Central Limit Theorems (FCLT) for seve…
In this paper we introduce two new Hawkes processes, namely, compound and regime-switching compound Hawkes processes, to model the price processes in limit order books. We prove Law of Large Numbers and Functional Central Limit Theorems (FCLT) for both processes. The two FCLTs are applied to limit order books where we …
In this paper, we study various new Hawkes processes, namely, so-called general compound and regime-switching general compound Hawkes processes to model the price processes in the limit order books. We prove Law of Large Numbers (LLN) and Functional Central Limit Theorems (FCLT) for these processes. The latter two FCLT…
Generates natural product-like compounds using GPT models.
The paper shows robustness of Hilbert space-valued stochastic volatility models to perturbations.
Leveraged ETFs can outperform their targets in certain market conditions, contrary to the volatility drag hypothesis.
This paper analyzes liquidations in DeFi protocols, showing how price volatility can lead to significant losses.
New approach tackles open compound domain adaptation without clear domain labels.
Study short-maturity VIX and European option prices with jumps.
One endeavour of modern physical chemistry is to use bottom-up approaches to design materials and drugs with desired properties. Here we introduce an atomistic structure learning algorithm (ASLA) that utilizes a convolutional neural network to build 2D compounds and layered structures atom by atom. The algorithm takes …
New model prices options with complex market data structures.
Paper defines new topological invariants for DP tangles.
The paper develops a new framework for managing asymmetric volatility.
Researchers prove a new measure for a financial volatility model.
We prove that the perpetual American put option price of level dependent volatility model with compound Poisson jumps is convex and is the classical solution of its associated quasi-variational inequality, that it is except at the stopping boundary and that it is everywhere (i.e. the smooth pasting conditio…
CSLVAE generates large chemical libraries efficiently.
There is an intuitive analogy of an organic chemist's understanding of a compound and a language speaker's understanding of a word. Consequently, it is possible to introduce the basic concepts and analyze potential impacts of linguistic analysis to the world of organic chemistry. In this work, we cast the reaction pred…
Study uses topological signatures to quantify financial market complexity.
Derives a pricing formula for VIX options using a new stochastic volatility model.
The paper predicts cryptocurrency prices using a path-dependent Monte Carlo simulation.
Low-cost sensor fusion for organic substance classification.
PCA reveals a market factor in S&P500 implied volatilities.
The paper develops a Gaussian process model for predicting chemical efficacy.
We fit the volatility fluctuations of the S&P 500 index well by a Chi distribution, and the distribution of log-returns by a corresponding superposition of Gaussian distributions. The Fourier transform of this is, remarkably, of the Tsallis type. An option pricing formula is derived from the same superposition of Black…
SOC theory explains financial volatility and economic shocks.
Improves topic modeling for multi-collection corpora.
Concept Relation Discovery and Innovation Enabling Technology (CORDIET), is a toolbox for gaining new knowledge from unstructured text data. At the core of CORDIET is the C-K theory which captures the essential elements of innovation. The tool uses Formal Concept Analysis (FCA), Emergent Self Organizing Maps (ESOM) and…
The asymptotic behavior of the implied volatility associated with a general call pricing function has been extensively studied in the last decade. The main topics discussed in this paper are Lee's moment formulas for the implied volatility, and Piterbarg's conjecture, describing how the implied volatility behaves in th…
Paper derives Thiele's equation for unit-linked policies in a stochastic volatility model.
Develops a PIDE framework for option pricing with stochastic volatility and jumps.
DeFi lending protocols faced challenges during Ethereum's merge, but avoided major liquidations.
This paper examines the problem of pricing spread options under some models with jumps driven by Compound Poisson Processes and stochastic volatilities in the form of Cox-Ingersoll-Ross(CIR) processes. We derive the characteristic function for two market models featuring joint normally distributed jumps, stochastic vol…
Modeling financial markets with sandpile model to understand price volatility and arbitrage constraints.
A deep learning strategy outperforms traditional methods in stocks portfolio management.
Paper examines GCHP for mid-price prediction in financial data.
A self-organized model with social percolation process is proposed to describe the propagations of information for different trading ways across a social system and the automatic formation of various groups within market traders. Based on the market structure of this model, some stylized observations of real market can…
The paper develops Hawkes-based models for LOB and applies them to European, spread, and basket option pricing.
This paper proposes a general model for synchronized crowding behavior. An order parameter is introduced to quantify the level of synchronization which is shown a function of percentage of agents in reactive state. Further, synchronization is shown to be driven by the most active agents with the highest volatility. A t…
In this paper we present a new method to compute the first-order approximation of the price of derivatives on futures in the context of multiscale stochastic volatility of Fouque \textit{et al.} (2011, CUP). It provides an alternative method to the singular perturbation technique presented in Hikspoors and Jaimungal (2…
We investigate the trading behavior of a large set of single investors trading the highly liquid Nokia stock over the period 2003-2008 with the aim of determining the relative role of endogenous and exogenous factors that may affect their behavior. As endogenous factors we consider returns and volatility, whereas the e…
Study short maturity Asian options in jump-diffusion models with local volatility.
We explore a simple lattice field model intended to describe statistical properties of high frequency financial markets. The model is relevant in the cross-disciplinary area of econophysics. Its signature feature is the emergence of a self-organized critical state. This implies scale invariance of the model, without tu…
We study simultaneous price drops of real stocks and show that for high drop thresholds they follow a power-law distribution. To reproduce these collective downturns, we propose a minimal self-organized model of cascade spreading based on a probabilistic response of the system elements to stress conditions. This model …
Modified Jones-Faddy skew t-distribution captures asymmetry in stock returns.
The new framework for finance is proposed. This framework based on three known approaches in econophysics. Assumptions of the framework are the following: 1. For the majority of situations market follows non-arbitrage condition. 2. For the small number of situations market influenced by the actions of big firms. 3. If …
Organic Solar Cells are a promising technology for solving the clean energy crisis in the world. However, generating candidate chemical compounds for solar cells is a time-consuming process requiring thousands of hours of laboratory analysis. For a solar cell, the most important property is the power conversion efficie…