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.
A new approach to continuous-time universal portfolios using pathwise Itô calculus.
New method solves continuous time mean-variance model for consistent investment strategy.
We prove continuity of a controlled SDE solution in Skorokhod's and topologies and also uniformly, in probability, as a non-linear functional of the control strategy. The functional comes from a finance problem to model price impact of a large investor in an illiquid market. We show that -continuity is…
A new method for portfolio allocation in continuous-time markets.
This paper develops a mathematical framework for the analysis of continuous-time trading strategies which, in contrast to the classical setting of continuous-time mathematical finance, does not rely on stochastic integrals or other probabilistic notions. Our purely analytic framework allows for the derivation of a path…
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…
Study efficient rebalancing strategies for portfolio tracking error.
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…
Study optimal growth strategies in a continuous-time asset market.
Avanzi et al. (2016) recently studied an optimal dividend problem where dividends are paid both periodically and continuously with different transaction costs. In the Brownian model with Poissonian periodic dividend payment opportunities, they showed that the optimal strategy is either of the pure-continuous, pure-peri…
Study stability of trading strategy under market perturbations.
This tutorial introduces the CMA Evolution Strategy (ES), where CMA stands for Covariance Matrix Adaptation. The CMA-ES is a stochastic, or randomized, method for real-parameter (continuous domain) optimization of non-linear, non-convex functions. We try to motivate and derive the algorithm from intuitive concepts and …
Model optimal growth strategy in a market with short-lived assets.
In this paper we consider long-run risk sensitive average cost impulse control applied to a continuous-time Feller-Markov process. Using the probabilistic approach, we show how to get a solution to a suitable continuous-time Bellman equation and link it with the impulse control problem. The optimal strategy for the und…
Paper develops a continuous-time framework for financial markets without stochastic calculus.
Deep Hedging learns optimal strategies for various risk levels.
Study evaluates discretized arbitrage strategies in fractional financial markets.
Parallelizes MCTS for continuous domains using leaf and root parallelization.
Study on optimal portfolio selection with varying borrowing and saving rates in continuous-time markets.
We study multistep Bayesian betting strategies in coin-tossing games in the framework of game-theoretic probability of Shafer and Vovk (2001). We show that by a countable mixture of these strategies, a gambler or an investor can exploit arbitrary patterns of deviations of nature's moves from independent Bernoulli trial…
We establish a super-replication duality in a continuous-time financial model where an investor's trades adversely affect bid- and ask-prices for a risky asset and where market resilience drives the resulting spread back towards zero at an exponential rate. Similar to the literature on models with a constant spread, ou…
RL approach for continuous-time mean-variance portfolio selection with empirical validation.
We consider a family of learning strategies for online optimization problems that evolve in continuous time and we show that they lead to no regret. From a more traditional, discrete-time viewpoint, this continuous-time approach allows us to derive the no-regret properties of a large class of discrete-time algorithms i…
A financial market model with general semimartingale asset-price processes and where agents can only trade using no-short-sales strategies is considered. We show that wealth processes using continuous trading can be approximated very closely by wealth processes using simple combinations of buy-and-hold trading. This ap…
The paper studies problem of continuous time optimal portfolio selection for a incom- plete market diffusion model. It is shown that, under some mild conditions, near optimal strategies for investors with different performance criteria can be constructed using a limited number of fixed processes (mutual funds), for a m…
This paper studies the properties of discrete time stochastic optimal control problems associated with portfolio selection. We investigate if optimal continuous time strategies can be used effectively for a discrete time market after a straightforward discretization. We found that Merton's strategy approximates the per…
Paper proposes a RL approach for ALM with superior performance.
Time inconsistency leads to intra-personal conflict and reconciliation strategies.
Improved genetic programming by optimizing mutation operators for continuous program search.
Study of discrete-time mean-variance model using reinforcement learning.
Paper tackles continual learning with single-index models, proving regret bounds.
New method for portfolio management learns from past wealth evolution.
Study coevolutionary trading-agent dynamics in continuous strategies.
Study shows time matters in automated trading, improving simple strategies over complex ones.
Investment strategy optimization from discrete to continuous models.
Investment strategies for rank-dependent utility agents are derived in a continuous-time market.
Optimal trading strategy in Proof-of-Stake blockchain using continuous-time control.
Evolutionary Strategies optimize hyper-parameters for off-policy learning.
This text explores strategies for learning discrete latent structures in neural networks.
Consider power utility maximization of terminal wealth in a 1-dimensional continuous-time exponential Levy model with finite time horizon. We discretize the model by restricting portfolio adjustments to an equidistant discrete time grid. Under minimal assumptions we prove convergence of the optimal discrete-time strate…
The expected present value of dividends is one of the classical stability criteria in actuarial risk theory. In this context, numerous papers considered threshold (refractive) and barrier (reflective) dividend strategies. These were shown to be optimal in a number of different contexts for bounded and unbounded payout …
Study optimal strategy for maximizing exponential utility in financial market with linear price impact.
We study a continuous-time financial market with continuous price processes under model uncertainty, modeled via a family of possible physical measures. A robust notion of no-arbitrage of the first kind is introduced; it postulates that a nonnegative, nonvanishing claim cannot …
A continual learning agent should be able to build on top of existing knowledge to learn on new data quickly while minimizing forgetting. Current intelligent systems based on neural network function approximators arguably do the opposite---they are highly prone to forgetting and rarely trained to facilitate future lear…
The aim of this work consists in the study of the optimal investment strategy for a behavioural investor, whose preference towards risk is described by both a probability distortion and an S-shaped utility function. Within a continuous-time financial market framework and assuming that asset prices are modelled by semim…
This paper studies arbitrage pricing theory in financial markets with implicit transaction costs. We extend the existing theory to include the more realistic possibility that the price at which the investors trade is dependent on the traded volume. The investors in the market always buy at the ask and sell at the bid p…
This paper proposes a trading strategy using TD3 for stock and cryptocurrency markets.
In a continuous-time model with multiple assets described by càdlàg processes, this paper characterizes superhedging prices, absence of arbitrage, and utility maximizing strategies, under general frictions that make execution prices arbitrarily unfavorable for high trading intensity. Such frictions induce a duality bet…