We develop a deep reinforcement learning (RL) framework for an optimal market-making (MM) trading problem, specifically focusing on price processes with semi-Markov and Hawkes Jump-Diffusion dynamics. We begin by discussing the basics of RL and the deep RL framework used; we deployed the...

Different types of mathematical models can be used to forecast the development of diseases as well as associated costs and analyse the cost-effectiveness of interventions. The set of models available to assess these parameters, reach from simple independent equations to highly complex...

Background As the number of randomized clinical trials (RCTs) demonstrating the survival benefits of combination therapies in previously treated multiple myeloma (MM) patients increases, it is essential to determine the most cost- effective treatment through robust economic evaluation. This...

At the start of the Coronavirus Disease (COVID-19) vaccination campaign in Mexico, the vaccine was the world's most essential and scarce asset. Managing its administration to optimize its use was, and still is, of paramount importance. However, when the first vaccine was developed at the end of...

In the present study, we model the migration process and the changes in the market environment. The migration process is being modeled as an F -inhomogeneous semi-Markov process with fuzzy states. The evolution of the migration process takes place within a stochastic market environment with...

This study introduces a novel composite approach to nonlinear inflation dynamics in identifying historical inflation patterns and forecasting future regime shifts. Assuming inflation's responsiveness to its determinants varies across inflation regimes and that inflation shock magnitude shapes...

Markov switching models are a common tool used in many disciplines as well as in Economics, and estimation methods are available in many software packages. Estimated models are commonly used for allocating observations to regimes. This allocation is usually done using a rule based on the...

The COVID-19 pandemic potentially affected stock prices in two non-mutually exclusive ways: discount rates and cash flows. This paper focuses on the latter and analyzes it through the lens of an asset-pricing model. It shows how workplace resilience and financial resilience interacted and...

This study investigates the impact of data length on daily demand forecasting accuracy within a horizontal time series structure. While time series data can be structured hierarchically or as forecast intervals, this research focuses on optimizing data length to enhance forecasting...

The withdrawal of public sector intervention from Malta's housing market commenced in the early 1990s, while financial markets were liberalised in 1994. These developments were likely behind the significant expansion in credit and house price appreciation experienced over the past two decades,...

Background: Corporate bonds are crucial for corporations as they provide a flexible and often less costly alternative to equity financing. However, rising corporate debt levels, along with rating downgrades and economic uncertainty, can cause corporations to face financial distress, exacerbating...

This study aimed to evaluate the conditional effect of exchange rate volatility on stock prices and returns in the emerging markets of BRICS nations. Using daily data from 1 January 2000 to 30 December 2023, wavelet and quantile analysis were conducted. The Markov-regime model was estimated for...

In Japan, the inflation rate declined to near-zero, whereas the monetary policy faced a zero lower bound (ZLB) in the 1990s. We examine whether trend inflation had fallen to near-zero prior to the ZLB. To achieve this, we estimate Japanese pre-2000 trend inflation developing a Markov-switching...