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...

This WBG study examines what makes distressed asset markets work — and how governments can create the right conditions for private sector engagement. It provides policymakers, regulators, and financial institutions with a practical framework to assess market readiness, identify policy and...

Infrastructure development is crucial for the continued economic growth and prosperity of emerging markets and developed economies (EMDEs). The demand for infrastructure, propelled by population growth and ever-increasing rate of urbanization, has resulted in the need to build, and improve...

Standard optimal capital tax theory abstracts from modeling asset prices, making it unsuitable for thinking about capital gains and wealth taxation. We study optimal redistributive taxation in an environment with asset price movements, adopting the modern finance view that asset prices fluctuate...

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...

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...

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 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...

As global climate and sustainable challenges gain more attention, green finance has emerged as a significant focus of worldwide financial reform, with green bonds serving as a key indicator. Retail investors, as an important part of the financial market, have a significant impact on the...

In deregulated electricity markets, Generation Companies (GENCOs) are exposed to substantial financial risk due to volatile and uncertain electricity prices. Traditional generation asset valuation approaches, which rely primarily on expected profit, fail to adequately capture downside risk under...

Despite the economic relevance of climate-transition risk, firm-level carbon exposure often fails to appear as a robustly priced factor when ESG measures and sustainability shocks are conflated. This study examines whether carbon exposure is conditionally priced in European equity returns using...

This study builds on the concept of loss tolerance by introducing investment grip, a behavioral interpretation that captures investors' commitment to long-term objectives under adverse market conditions. While loss tolerance traditionally measures the maximum financial loss an investor can...

We study how sustainability disclosure regulation affects mutual fund flows and portfolio choices, accounting for investor heterogeneity. Guided by a model of ESG investing under uncertainty, we exploit the introduction of the European Sustainable Finance Disclosure Regulation (SFDR) as a...

Managers of actively managed funds do not maintain a constant investment style. Instead, their factor loadings change over time. These changes are especially large following quarters with extreme returns and fund flows and arise from both active portfolio reallocations and passive style drift....

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...

In this paper, we study an intertemporal utility maximization problem in which an investor chooses consumption and portfolio strategies in the presence of a stochastic factor and a no-borrowing constraint. In the spirit of the Kim-Omberg model, the stochastic factor represents the excess return...

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 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...

For many decades, time-series forecasting has been applied to different problems by scientists and industries. Many models have been introduced for the purpose of forecasting. These advancements have significantly improved the accuracy and reliability of predictions, especially in complex...

This study investigates the interplay between asset quality, financial ratios, and market valuation in Indian commercial banks over a twelve-year period (2014-2025). Using a hybrid approach combining Structural Equation Modeling, correlation analysis, and trend evaluation, the research examines...

Using granular security-level data from bond funds domiciled in the US and the euro area, we identify a market-based risk-taking channel of monetary policy transmission via the credit-risk and the maturity structure of bond funds' portfolios. We measure credit risk at the fund level as the...

In this paper we employ the natural experiment of German Division and Reunification in order to study the effect of institutional reform on the decision to hold risky assets. We present empirical evidence indicating that even 16 years after German Reunification risky portfolios of East and West...

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...