arXiv research

Analyzes compound interest with constant payments and interest rate.

Compound Finance optimizes risk metrics for V3 protocol using Chainrisk simulations.

Study shows convergence rates for BSDEs approximated by compound Poisson processes.

Growth of monetary assets and debts is commonly described by the formula of compound interest which for the case of continuous compounding is the exponential growth law. Its differential form is dc/dt = i c where dc/dt describes the rate of monetary growth, i the compounded interest rate and c the actual principal. Exp…

The understanding of the type of inhibitory interaction plays an important role in drug design. Therefore, researchers are interested to know whether a drug has competitive or non-competitive interaction to particular protein targets. Method: to analyze the interaction types we propose factorization method Macau which …

In this paper we assume the insurance wealth process is driven by the compound Poisson process. The discounting factor is modelled as a geometric Brownian motion at first and then as an exponential function of an integrated Ornstein-Uhlenbeck process. The objective is to maximize the cumulated value of expected discoun…

In this paper we shall prove that the plane of financial events, introduced and applied to financial problems by the author himself (see [2], [3] and [4]) can be considered as a fibration in two different ways. The first one, the natural one, reveals itself to be isomorphic to the tangent- bundle of the real line, when…

Financial investment returns lead to growing wealth inequality.

Statistical detection of a rare class of objects in a two-class classification problem can pose several challenges. Because the class of interest is rare in the training data, there is relatively little information in the known class response labels for model building. At the same time the available explanatory variabl…

Models which postulate lognormal dynamics for interest rates which are compounded according to market conventions, such as forward LIBOR or forward swap rates, can be constructed initially in a discrete tenor framework. Interpolating interest rates between maturities in the discrete tenor structure is equivalent to ext…

Study on risk model with claims, dividends, and random probabilities.

Generative model learns to create molecules with multiple properties using interpretable substructures.

New model uses pretrained biochemical language models to generate drug compounds.

This paper investigates dividend optimization of an insurance corporation under a more realistic model which takes into consideration refinancing or capital injections. The model follows the compound Poisson framework with credit interest for positive reserve, and debit interest for negative reserve. Ruin occurs when t…

Study estimates Medallion's compounded return before fees at 31.8%.

Characterizes measures preserving compound mixed renewal process properties.

This chapter is an attempt to present a mathematical theory of compound fractional Poisson processes. The chapter begins with the characterization of a well-known Lévy process: The compound Poisson process. The semi-Markov extension of the compound Poisson process naturally leads to the compound fractional Poisson proc…

This paper studies the payoff amounts in simple interest loans without arbitrage.

Study shows how margin loan interest rates converge to a choke price, limiting long-term advantage in the broker call money market.

Improves topic modeling for multi-collection corpora.

Compound interest as well as inflation grows exponentially with time, whereas other means to repay debt grow polynomially. For this and other, mostly political, reasons, debt without inflation is unsustainable. We suggest a discontinuous way to eliminate debt by nullifying it. This scenario is preferable to current cen…

Investigates real-world interest rate dynamics using affine models.

Generates natural product-like compounds using GPT models.

High throughput screening of compounds (chemicals) is an essential part of drug discovery [7], involving thousands to millions of compounds, with the purpose of identifying candidate hits. Most statistical tools, including the industry standard B-score method, work on individual compound plates and do not exploit cross…

Develops an efficient method for compound option valuation.

In this paper, we introduce a new model for the risk process based on general compound Hawkes process (GCHP) for the arrival of claims. We call it risk model based on general compound Hawkes process (RMGCHP). The Law of Large Numbers (LLN) and the Functional Central Limit Theorem (FCLT) are proved. We also study the ma…

Semi-supervised learning improves QSAR model predictions for novel compounds.

Normalized compound random measures are flexible nonparametric priors for related distributions. We consider building general nonparametric regression models using normalized compound random measure mixture models. Posterior inference is made using a novel pseudo-marginal Metropolis-Hastings sampler for normalized comp…

Paper proposes a framework to predict therapeutic properties of compounds.

STMT predicts compounds in unknown areas with trend reflection.

This paper examines interest rates and market efficiency in DeFi loanable funds protocols.

New Riemannian geometry for Compound Gaussian distributions applied to efficient change detection.

ChemGrapher uses deep learning to automatically convert chemical compound images into accurate graphs.

In this paper we develop a framework for discretely compounding interest rates which is based on the forward price process approach. This approach has a number of advantages, in particular in the current market environment. Compared to the classical as well as the Lévy Libor market model, it allows in a natural way for…

This study deals with the problem of pricing compound options when the underlying asset follows a mixed fractional Brownian motion with jumps. An analytic formula for compound options is derived under the risk neutral measure. Then, these results are applied to value extendible options. Moreover, some special cases of …

Novel model predicts anticancer compound sensitivity with high accuracy and interpretability.

The study improves compound selection in in silico screening by focusing on model's ability to predict desirable outcomes.

A new method solves complex financial problems using deep learning.

Ethereum's Pectra upgrade introduces 0x02 compounding validators, offering higher stake and potential APR uplifts.

The paper develops generalization bounds for deep compound Gaussian neural networks.

New MGCPP model for order flow in financial markets.

The paper introduces ESG valuation in option pricing using binomial trees.

Study predicts shear stress in compound channels using data mining and machine learning.

We propose an analytical approach to the computation of tail probabilities of compound distributions whose individual components have heavy tails. Our approach is based on the contour integration method, and gives rise to a representation of the tail probability of a compound distribution in the form of a rapidly conve…

Bayesian learning improves reliability of molecular predictions for hit compound discovery.

A multi-step model reduces compounding errors in reinforcement learning.

New approach tackles open compound domain adaptation without clear domain labels.

The study addresses overlooked data-generating processes in time-series asset pricing.