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.
New reward function improves GAIL performance in task-based environments.
Decision trees with binary splits are popularly constructed using Classification and Regression Trees (CART) methodology. For binary classification and regression models, this approach recursively divides the data into two near-homogenous daughter nodes according to a split point that maximizes the reduction in sum of …
New simulation method simplifies Heston model with Poisson conditioning for better accuracy and efficiency.
Deep nets exhibit 'Neural Collapse' during training's final phase, simplifying decision-making.
We characterize the small-time asymptotic behavior of the exit probability of a Lévy process out of a two-sided interval and of the law of its overshoot, conditionally on the terminal value of the process. The asymptotic expansions are given in the form of a first-order term and a precise computable error bound. As an …
Enhanced survival trees improve computational efficiency and inference.
NO approximates non-Markovian BSDEs with polynomial scaling in 1/ε.
To improve the efficient frontier of the classical mean-variance model in continuous time, we propose a varying terminal time mean-variance model with a constraint on the mean value of the portfolio asset, which moves with the varying terminal time. Using the embedding technique from stochastic optimal control in conti…
Eigenoptions improve credit assignment in reinforcement learning.
Gradient descent recovers low-rank matrices from corrupted measurements with double over-parameterization.
In this work, we consider the problem of autonomously discovering behavioral abstractions, or options, for reinforcement learning agents. We propose an algorithm that focuses on the termination condition, as opposed to -- as is common -- the policy. The termination condition is usually trained to optimize a control obj…
Study bounds for prices of European and American options with optional termination.
The paper finds optimal threshold strategies for insurance companies with a positive terminal value at creeping ruin.
New method preserves distances in time series data.
Proves finite step termination of Kähler-Einstein metric singularity formation.
The study proves a key inequality for specific types of three-dimensional spaces.
New test for SGD in binary classification reduces computation time.
Employee stock options (ESOs) are American-style call options that can be terminated early due to employment shock. This paper studies an ESO valuation framework that accounts for job termination risk and jumps in the company stock price. Under general Lévy stock price dynamics, we show that a higher job termination ri…
We establish existence, uniqueness and regularity of solution results for a class of backward stochastic partial differential equations with singular terminal condition. The equation describes the value function of non-Markovian stochastic optimal control problem in which the terminal state of the controlled process is…
We prove that the sum of the -invariants of two different Kollár components of a Kawamata log terminal singularity is less than .
New method for computing terminal embeddings in sublinear time.
Locally adaptive clustering for tree delineation.
Is an option to early terminate a swap at its market value worth zero? At first sight it is, but in presence of counterparty risk it depends on the criteria used to determine such market value. In case of a single uncollateralised swap transaction under ISDA between two defaultable counterparties, the additional unilat…
In reinforcement learning, a decision needs to be made at some point as to whether it is worthwhile to carry on with the learning process or to terminate it. In many such situations, stochastic elements are often present which govern the occurrence of rewards, with the sequential occurrences of positive rewards randoml…
Study optimal liquidation with multiple regimes using BSDEs with singular terminal values.
This paper establishes the existence of a unique nonnegative continuous viscosity solution to the HJB equation associated with a Markovian linear-quadratic control problems with singular terminal state constraint and possibly unbounded cost coefficients. The existence result is based on a novel comparison principle for…
We provide representations of solutions to terminal value problems of inhomogeneous Black-Scholes equations and studied such general properties as min-max estimates, gradient estimates, monotonicity and convexity of the solutions with respect to the stock price variable, which are important for financial security prici…
Develops a learning model predictive controller for competitive racing.
A new BO termination criterion for HPO reduces optimization time without sacrificing test performance.
Circular nets with spherical parameter lines have geometric properties related to Darboux cyclides and terminating Laplace sequences.
We apply the language of the groupoid approach to Lie pseudo-groups, and the classical Cartan-Kuranishi theorem, to prove that Cartan's equivalence method terminates at involution (or at complete reduction) for constant type problems.
TVM improves generative modeling by matching terminal velocities.
The paper analyzes and proposes a new stopping criterion for recursive Bayesian classification.
In this paper, the `Approximate Message Passing' (AMP) algorithm, initially developed for compressed sensing of signals under i.i.d. Gaussian measurement matrices, has been extended to a multi-terminal setting (MAMP algorithm). It has been shown that similar to its single terminal counterpart, the behavior of MAMP algo…
Despite strong performance on a variety of tasks, neural sequence models trained with maximum likelihood have been shown to exhibit issues such as length bias and degenerate repetition. We study the related issue of receiving infinite-length sequences from a recurrent language model when using common decoding algorithm…
Researchers find Kähler-Einstein metrics near isolated log terminal singularities.
In this article we solve the problem of maximizing the expected utility of future consumption and terminal wealth to determine the optimal pension or life-cycle fund strategy for a cohort of pension fund investors. The setup is strongly related to a DC pension plan where additionally (individual) consumption is taken i…
Optimal asset allocation strategy outperforms stochastic benchmark.
ETCNN uses neural networks to price American options accurately.
We study the existence of a minimal supersolution for backward stochastic differential equations when the terminal data can take the value + with positive probability. We deal with equations on a general filtered probability space and with generators satisfying a general monotonicity assumption. With this minim…
Optimizes cash management in ATM networks to reduce costs and increase revenue.
Proof of complex geometry theorem for specific singular spaces.
The paper examines special Q-nets that terminate after a finite number of Laplace steps.
Geometrically interpolates rigid body motions with initial and terminal twists.
This paper works out fair values of stock loan model with automatic termination clause, cap and margin. This stock loan is treated as a generalized perpetual American option with possibly negative interest rate and some constraints. Since it helps a bank to control the risk, the banks charge less service fees compared …
Resource allocation improved using machine learning from terminal positions.
GH-PID uses guided harmonic paths for efficient SOT with interpretable diagnostics.
Deep reinforcement learning has achieved great successes in recent years, but there are still open challenges, such as convergence to locally optimal policies and sample inefficiency. In this paper, we contribute a novel self-supervised auxiliary task, i.e., Terminal Prediction (TP), estimating temporal closeness to te…