This study investigates the presence of the MAX effect, as defined by Bali et al. (2011), in the stock market of Borsa Istanbul, aiming to validate and extend previous findings in international markets. A comprehensive analysis of 439 firms from December 2013 to November 2023 reveals that stocks...

This paper presents an innovative approach to financial market modelling by integrating fuzzy discount factors into the decision-making process, thereby reflecting the complexities of human behaviour. Traditional financial models often fail to account for market dynamics' psychological factors....

The increasing interaction between the equity market and cryptocurrencies has raised concerns about volatility spillovers; however, empirical evidence about sectoral-specific spillover effects in emerging markets is scarce and hard to find. Existing research mainly concentrates on developed...

Retrieval-augmented generation (RAG) has emerged as a promising way to improve task-specific performance in generative artificial intelligence (GenAI) applications such as large language models (LLMs). In this study, we evaluate the performance implications of providing various types of...

In several countries, digital financial advisory services, particularly those supported by robo-advisors, are becoming increasingly popular in retail banking. These tools assist users with financial decisions such as risk assessment, portfolio selection, and rebalancing-all at a reduced cost....

Distributed ledger technology (DLT) and cryptocurrency have revolutionized the financial landscape and relevant applications, particularly in investment opportunities. Despite its growth, the market's volatility and technical complexities hinder widespread adoption. This study proposes a...

This study evaluates the effectiveness of the Non-dominated Sorting Genetic Algorithm III (NSGA-III) in comparison to the traditional Mean-Variance optimization method for financial portfolio management. Leveraging a dataset of global financial assets, we applied both approaches to optimize...

We introduce a new type of shrinkage estimator that is not based on asymptotic optimality, but instead learns a state-dependent shrinkage policy via supervised learning in a contextual bandit setup. The proposed estimator applies to both linear and nonlinear shrinkage and shows improved...

We put forward a Dynamic Regularized Parametric (DRP) approach for active portfolio policies. We build upon the parametric policy framework of Brandt et al. (2009) that directly links the portfolio weights to a limited set of asset characteristics. This yields a parsimonious specification that...

We introduce a simple yet powerful method for enhancing mutual fund performance prediction by combining individual predictors into a composite predictor. This composite approach integrates information from 19 well-established return-based and portfolio holdings-based predictors from the...

The literature on derivative pricing in illiquid markets has mostly focused on computing optimal hedging controls, but empirical microstructure studies show that large order flow generates persistent and predictable price effects. Therefore, these controls can themselves induce endogenous market...

We test whether forecast bias affects individual investors' stock trading by combining bias measures from laboratory experiments with administrative trade data. Forecast bias is positively associated with past excess returns of purchased stocks: Compared to contrarians, extrapolators purchase...

This article introduces OPENSIMPLEST, a highly parsimonious stock-flow consistent (SFC) model of an open economy. The model is designed as a pedagogical and analytical benchmark that preserves the core mechanisms of more complex open-economy SFC frameworks while remaining complete, transparent,...

We calibrate a lifecycle portfolio-choice model of homeowners facing uninsurable income risk to show that tax deductions for mortgage interest payments and voluntary pension contributions have sizable effects on household portfolios and macroprudential risks. The deductions reduce the after-tax...

We calibrate a lifecycle portfolio-choice model of homeowners facing uninsurable income risk to show that tax deductions for mortgage interest payments and voluntary pension contributions have sizable effects on household portfolios and macroprudential risks. The deductions reduce the after-tax...

We investigate the impact of structural shocks on the joint distribution of future real GDP growth and inflation in the euro area. We model the conditional mean of these variables, along with selected financial indicators, using a VAR and perform quantile regressions on the VAR residuals to...

The diverse rating scales used by brokerage firms pose significant challenges for aggregating analyst recommendations in financial research. We develop a momentum-based normalization framework that transforms heterogeneous rating changes into standardized sentiment signals using firm-relative,...

This study examines quantitative investment strategies for Brazilian equity funds, integrating traditional financial performance indicators with machine learning techniques to enhance fund selection. The main objective was to construct and validate predictive models for fund selection. The...

Although there is an extensive literature on the impact of volatility on asset returns correlation, investigating this in relation to broad asset selection and in perspective of different timelines has received less attention. In comparison to the previous papers, we use a much broader set of 35...

The relevance of the study is the need to improve the efficiency of managing the portfolio of medical projects for the development of hospital districts. The purpose of the article was to develop and use a model of synergistic management of a portfolio of medical projects for the development of...

Managing a portfolio whose value closely tracks an index by trading only in a subset of the index constituents involves an NP-hard optimisation problem. In the prior literature, it has been suggested that this problem be solved using sequential Monte Carlo (SMC, also known as particle filter)...

The aim of this study is to identify crypto assets with similar characteristics and to explore the similar responses of these assets to market-priced events. This process is carried out in two stages. Cluster analysis and association analysis were applied in the research. First of all, cluster...

We develop a novel approach to understand the dynamic diversification of decision makers with quantile preferences. Due to unavailability of analytical solutions to such complex problems, we suggest to approximate the behavior of agents with a Quantile Deep Reinforcement Learning (Q-DRL)...

In this study, we unpack the ESG ratings of four prominent agencies in Europe and find that (i) each single E, S, G pillar explains the overall ESG score differently, (ii) there is a low co-movement between the three E, S, G pillars and (iii) there are specific ESG Key Performance Indicators...

After 2010, the consumer price index fell to a low level in the EU. In the euro area, it remained low between 2010 and 2020. The European Central Bank has even had to take action against the emergence of deflation. The situation changed significantly in 2021. Inflation jumped to levels not seen...

This study investigates the asymmetric responses of AI and ESG Exchange Traded Funds (ETFs) to geopolitical and financial uncertainty, with a focus on resilience across market regimes. The NASDAQ-100 and MSCI ESG Leaders indices are used as proxies for thematic ETFs, and their dynamic...

This study develops an integrated risk modeling framework to assess capital adequacy and optimize portfolio performance for Thai life and non-life insurers. Leveraging ARMA-GJR-GARCH models with skewed Student-t innovations, extreme value theory, and dynamic R-vine copulas, the framework...

This study examined the factor structure of Green, Grey, and Red EU securities using extended asset pricing models built on the Fama–French and Carhart frameworks. The findings show improved return predictability and consistently negative risk-adjusted alpha across categories post-Global...

In this paper, we propose a novel optimization model for portfolio selection that integrates the classical mean-variance criterion with a second-order Tsallis entropy term. This approach enables a trade-off between expected return, risk, and diversification, extending Markowitz's theory to...

This paper examines the pricing effect of cross-sectional patterns in the cryptocurrency market, aiming to enhance the composition of asset pricing factors for a better explanation of cross-sectional variability in cryptocurrency returns.The study utilizes data from 1,160 cryptocurrencies...