arXiv research

Study describes periodic controls in step 2 sub-Finsler problems on Carnot groups.

New model optimizes portfolios over multiple periods using predictive control.

Optimal control solves multi-period liability clearing problems.

Study optimal portfolio strategies with periodic evaluation under short-selling prohibition.

The OGY method is one of control methods for a chaotic system. In the method, we have to calculate a stabilizing periodic orbit embedded in its chaotic attractor. Thus, we cannot use this method in the case where a precise mathematical model of the chaotic system cannot be identified. In this case, the delayed feedback…

The paper tackles robust control with uncertain dependence using data-driven methods.

Intelligent control for greenhouses using deep reinforcement learning.

Generalising the idea of the classical EM algorithm that is widely used for computing maximum likelihood estimates, we propose an EM-Control (EM-C) algorithm for solving multi-period finite time horizon stochastic control problems. The new algorithm sequentially updates the control policies in each time period using Mo…

A contextual bandit method evaluates and improves inventory control policies.

Paper tackles inventory management with deep learning, improving performance and adherence to constraints.

This study empirically re-examines fat tails in stock return distributions by applying statistical methods to an extensive dataset taken from the Korean stock market. The tails of the return distributions are shown to be much fatter in recent periods than in past periods and much fatter for small-capitalization stocks …

This paper optimizes periodic dividend strategies for Lévy processes with transaction costs.

New PFPPs based on rank-dependent utility for better performance control.

This work uses QPGPs to improve ILC performance in repetitive tasks.

Inventory control with unknown demand distribution is considered, with emphasis placed on the case involving discrete nonperishable items. We focus on an adaptive policy which in every period uses, as much as possible, the optimal newsvendor ordering quantity for the empirical distribution learned up to that period. Th…

Study optimizes resource allocation in noisy systems for better control.

We consider a version of the stochastic inventory control problem for a spectrally positive Lévy demand process, in which the inventory can only be replenished at independent exponential times. We show the optimality of a periodic barrier replenishment policy that restocks any shortage below a certain threshold at each…

We consider a basic model of multi-period trading, which can be used to evaluate the performance of a trading strategy. We describe a framework for single-period optimization, where the trades in each period are found by solving a convex optimization problem that trades off expected return, risk, transaction cost and h…

Robo-advisors use MPC to create dynamic investment strategies.

Study optimal periodic dividend strategies for risky businesses with transaction costs.

Financial event studies often misestimate causal effects due to misspecified factor models.

Modeling business expansion as a stochastic control problem, the study finds that firms are incentivized to expand but may wait.

Adaptive framework predicts stock prices better during volatile periods.

This study investigates porosity and topological properties of TPMS using machine learning.

The paper examines how macroeconomic control tools lost effectiveness, leading to a 'dark ages' period.

Paper proposes a DRL-based controller for networked AP systems that reduces communication frequency.

Deep RL algorithms can overfit to early experiences, leading to poor performance.

In the era of big data, practical applications in various domains continually generate large-scale time-series data. Among them, some data show significant or potential periodicity characteristics, such as meteorological and financial data. It is critical to efficiently identify the potential periodic patterns from mas…

Complex non-linear interactions between banks and assets we model by two time-dependent Erdős Renyi network models where each node, representing bank, can invest either to a single asset (model I) or multiple assets (model II). We use dynamical network approach to evaluate the collective financial failure---systemic ri…

Estimates treatment effects in time series data with always-missing controls.

The financial crisis clearly illustrated the importance of characterizing the level of 'systemic' risk associated with an entire credit network, rather than with single institutions. However, the interplay between financial distress and topological changes is still poorly understood. Here we analyze the quarterly inter…

We present both, theory and an algorithm for solving time-harmonic wave problems in a general setting. The time-harmonic solutions will be achieved by computing time-periodic solutions of the original wave equations. Thus, an exact controllability technique is proposed to solve the time-dependent wave equations. We dis…

MPC outperforms reactive budgeting in non-stationary return environments.

A new ML algorithm solves complex economic control problems.

Anomaly detection in database management systems (DBMSs) is difficult because of increasing number of statistics (stat) and event metrics in big data system. In this paper, I propose an automatic DBMS diagnosis system that detects anomaly periods with abnormal DB stat metrics and finds causal events in the periods. Rec…

Study optimal portfolio management with periodic evaluations in stochastic models, considering convex constraints.

It is known (E.L. Green (1997), O. Post (2003)) that for an arbitrary $m\in\mathbb{N}$ one can construct a periodic non-compact Riemannian manifold $M$ with at least $m$ gaps in the spectrum of the corresponding Laplace-Beltrami operator $-Δ_M$. In this work we want not only to produce a new type of periodic manifolds …

Game theory model for optimal trading with end-of-day constraints.

A new pricing strategy minimizes regret by controlling strategic buyer behavior.

Ricci flow smooths locally collapsing manifolds with controlled curvature.

The paper uses persistent homology to estimate recurrence times in multi-variate time series.

Study proposes a neural network approach for high inflation investment portfolios with leverage constraints.

High-dimensional models can outperform simpler ones in causal inference.

The FCA improved insider trading regulation after 2012, reducing abnormal returns.

This article presents some methods to control the bottom of the spectrum of the Laplacian $λ_0$ on hyperbolic surfaces with infinite volume. Our first result bounds the $λ_0$ of a geometrically finite surface in terms of the geometry of its convex core. We then focus on infinite type periodic hyperbolic surfaces built …

New spectral theory for non-associative algebras with applications to Moufang dynamics.

LLMs struggle to outperform markets over long periods and diverse stocks.

Paper uses RL to optimize ICU load during COVID-19.