arXiv research

New method solves continuous time mean-variance model for consistent investment strategy.

Inspired by Strotz's consistent planning strategy, we formulate the infinite horizon mean-variance stopping problem as a subgame perfect Nash equilibrium in order to determine time consistent strategies with no regret. Equilibria among stopping times or randomized stopping times may not exist. This motivates us to cons…

We give a method of constructing maps between tubular groups inductively according to a set of strategies. This map will be a quasi-isometry exactly when the set of strategies is consistent. Conversely, if there exists a quasi-isometry between tubular groups, then there is a consistent set of strategies for them. There…

Optimal investment and risk control strategies for insurers are derived using a time-consistent approach.

Unique optimal strategy identified for state-dependent risk aversion.

The paper examines how insurers can select claims for fraud investigation, proposing a randomized approach.

This paper revisits optimal investment strategies for defined contribution pension schemes using forward preferences.

Gaussian process (GP) models have become a well-established frameworkfor the adaptive design of costly experiments, and notably of computerexperiments. GP-based sequential designs have been found practicallyefficient for various objectives, such as global optimization(estimating the global maximum or maximizer(s) of a …

Investigates portfolio selection for rank-dependent utilities in incomplete markets.

Study explores strategies for randomized allocation in delayed rewards bandits.

SCR improves GNN training with consistency regularization.

We consider a stochastic game-theoretic model of an investment market in continuous time with short-lived assets and study strategies, called survival, which guarantee that the relative wealth of an investor who uses such a strategy remains bounded away from zero. The main results consist in obtaining a sufficient cond…

The folk result in Kyle-Back models states that the value function of the insider remains unchanged when her admissible strategies are restricted to absolutely continuous ones. In this paper we show that, for a large class of pricing rules used in current literature, the value function of the insider can be finite when…

The existence of optimal strategy in robust utility maximization is addressed when the utility function is finite on the entire real line. A delicate problem in this case is to find a "good definition" of admissible strategies, so that an optimizer is obtained. Under suitable assumptions, especially a time-consistency …

CLQT benchmarks LLM portfolio managers by evaluating their decision-making process, not just returns.

Study on learning strategies in adaptive Markov games with policy regret as metric.

We propose a novel estimation approach for the covariance matrix based on the $l_1$-regularized approximate factor model. Our sparse approximate factor (SAF) covariance estimator allows for the existence of weak factors and hence relaxes the pervasiveness assumption generally adopted for the standard approximate factor…

We investigate the growth optimal strategy over a finite time horizon for a stock and bond portfolio in an analytically solvable multiplicative Markovian market model. We show that the optimal strategy consists in holding the amount of capital invested in stocks within an interval around an ideal optimal investment. Th…

We propose a general-purpose approach to discovering active learning (AL) strategies from data. These strategies are transferable from one domain to another and can be used in conjunction with many machine learning models. To this end, we formalize the annotation process as a Markov decision process, design universal s…

Paper introduces dynamic strategies for multi-period investment models.

EB improves asset pricing by mining large strategies without lookahead bias.

We consider a game-theoretic model of a market where investors compete for payoffs yielded by several assets. The main result consists in a proof of the existence and uniqueness of a strategy, called relative growth optimal, such that the logarithm of the share of its wealth in the total wealth of the market is a subma…

This paper optimizes cryptocurrency portfolios by integrating sentiment analysis with technical indicators.

In this paper we investigate a utility maximization problem with drift uncertainty in a multivariate continuous-time Black-Scholes type financial market which may be incomplete. We impose a constraint on the admissible strategies that prevents a pure bond investment and we include uncertainty by means of ellipsoidal un…

Study examines if LLMs' trading styles match real market behavior.

Optimizes dividend payments to balance risk and reward.

Standard agglomerative clustering suggests establishing a new reliable linkage at every step. However, in order to provide adaptive, density-consistent and flexible solutions, we study extracting all the reliable linkages at each step, instead of the smallest one. Such a strategy can be applied with all common criteria…

Estimates reliability of nuclear fuel using advanced modeling techniques.

Stratify unifies and improves multi-step forecasting strategies.

FinRL-X unifies trading components for AI and rule-based strategies.

Importance sampling (IS) is a common reweighting strategy for off-policy prediction in reinforcement learning. While it is consistent and unbiased, it can result in high variance updates to the weights for the value function. In this work, we explore a resampling strategy as an alternative to reweighting. We propose Im…

This text explores strategies for learning discrete latent structures in neural networks.

Enhanced stock market strategy using stress index and financial news sentiment analysis.

Study optimizes best-arm identification with minimax and Bayes strategies.

Study optimizes option pricing with robust strategies, ensuring consistency with vanilla option prices.

We approach the development of models and control strategies of susceptible-infected-susceptible (SIS) epidemic processes from the perspective of marked temporal point processes and stochastic optimal control of stochastic differential equations (SDEs) with jumps. In contrast to previous work, this novel perspective is…

Develops optimal trading strategy for illiquid currency pairs.

This paper studies insurers' robust strategies in a stochastic game with model uncertainty and volatility risk.

The paper extends consistency results for sequential design strategies to vector-valued Gaussian processes.

New auction design uses statistical learning to reduce costs and improve fairness.

Investigates RI strategies for life insurers with LRD mortality rates.

Optimizes dividend policies in a Brownian model with controlled rates.

Parallel neural network training yields better long-term prediction accuracy.

The portfolio optimisation problem, first raised by Harry Markowitz in 1952, has been a fundamental and central topic to understanding the stock market and making decisions. There has been plenty of works contributing to development of the mean-variance optimisation (MVO) so far. In this paper, one kind of them, namely…

Trading strategies that were profitable in the past often degrade with time. Since unlucky streaks can also hit "healthy" strategies, how can one detect that something truly worrying is happening? It is intuitive that a drawdown that lasts too long or one that is too deep should lead to a downward revision of the assum…

We study the problem of determining risk-minimizing investment strategies for insurance payment processes in the presence of taxes and expenses. We consider the situation where taxes and expenses are paid continuously and symmetrically and introduce the concept of tax- and expense-modified risk-minimization. Risk-minim…

Paper proposes a new framework for combining investment strategies without market-specific assumptions.

Study optimal portfolio strategies with time-varying discount rates.