Purpose This study develops a comprehensive discrete numerical model for option valuation that explicitly incorporates risk preferences, which may deviate from risk neutrality. Unlike the traditional binomial tree models – strictly under the risk-neutral paradigm – our framework embeds a constant relative risk aversion (CRRA) utility specification, capturing heterogeneous attitudes toward risk while preserving the arbitrage-free pricing rule. Design/methodology/approach The model extends the multiplicative binomial recombination tree (MBRT) by adjusting key parameters – transition probabilities, growth factors, discount rates and drift/diffusion terms – to reflect the investor's degree of risk aversion. The classical Cox-Ross-Rubinstein binomial tree (CRR) emerges as a special case when risk aversion is set to zero. The methodology remains consistent with geometric Brownian motion (GBM) dynamics and is benchmarked against a modified Monte Carlo simulation to ensure robustness. Findings Results show that option values can be consistently derived under both traditional risk-neutral settings and preference-driven settings. Sensitivity analysis highlights the impact of time to maturity, volatility, strike price and the risk-free rate under varying levels of risk aversion. Research limitations/implications While this research offers significant theoretical and practical contributions, certain limitations warrant further study. Computational complexity: the CRRA-based valuation method introduces additional numerical challenges, requiring precise calibration and advanced optimization techniques. Dependence on risk aversion estimates: the model assumes that investor risk preferences can be accurately measured and remain stable, which may not always reflect dynamic market conditions. Absence of a closed-form solution: our proposed approach lacks an analytical closed-form solution. Therefore, it is crucial to dedicate efforts to its development. Practical implications The integration of CRRA utility functions into derivative valuation represents a key innovation, as it explicitly accounts for investor risk preferences beyond the traditional risk-neutral paradigm. This framework advances the literature on utility-based and nonlinear risk-adjusted pricing by demonstrating how variations in the relative risk aversion (RRA) coefficient shape option values. From a practical perspective, the model offers a flexible tool for portfolio managers, traders and policymakers by aligning valuations with observed market behavior while preserving consistency with classical models under specific conditions. Accurate calibration of risk preferences thus becomes essential for reliable pricing and policy design. Originality/value The novelty of this research lies in bridging utility-based preferences with recombining lattice valuation: while prior studies focused exclusively on risk-neutral or arbitrage-based approaches, our model incorporates explicit risk aversion into the numerical structure. By deriving general algebraic expressions and validating the framework through numerical experiments, this study offers a tractable and versatile tool for analyzing option prices under heterogeneous risk attitudes, without losing the analytical clarity of traditional methods.

Purpose In this study, we aim to show the effect of entrepreneurs’ overconfidence on their required rates of return. Accordingly, we show the implication of two levels of overconfidence: moderate and excessive. Design/methodology/approach We use a hyperbolic absolute risk aversion utility function with a payoff function affected by an ego component to derive different expressions of required rates of return for non-diversified entrepreneurs. Findings Using simulations of these expressions, we show that a confident entrepreneur will require an annual average required return of 76.49%, an entrepreneur with moderate overconfidence will require an average return of 20.80% and an entrepreneur with excessive overconfidence will require an average return of 1.77%. Research limitations/implications Our expressions for the required rate of return depend on the assumption of the hyperbolic utility function. Other expressions will arise from other functions. Practical implications While moderate overconfidence can help overcome the fear of failure, entrepreneurs suffering from excessive overconfidence will underestimate the total risk of a startup. Social implications Excessive overconfidence could lead to bankruptcy. Originality/value This is the first research that addresses overconfidence in relation to required rates of return.

Purpose This study examines the impact of green finance (GFIN) and green innovation (GTI) on environmental sustainability in seven South American countries from 2000 to 2020. Design/methodology/approach The study employs panel data econometric techniques using the Method of Moments Quantile Regression approach to explore the relationships between carbon dioxide (CO2) emissions, GFIN, GTI, economic growth (GDP), renewable energy (REN) and non-renewable energy (NRE) globalization (GLO) and population (POP). The robustness of the results is confirmed through additional analyses using bootstrap quantile regression, feasible generalized least squares and panel corrected standard errors. Findings The findings reveal that GFIN significantly reduces CO2 emissions across all quantiles, with stronger effects at higher quantiles. However, GTI shows a positive association with emissions in higher quantiles, suggesting rebound effects. Renewable energy decreases emissions, while NRE, GLO, population and GDP growth contribute to environmental degradation, indicating no evidence of the environmental Kuznets curve hypothesis. Additionally, the Dumitrescu-Hurlin causality test reveals bidirectional causality between carbon dioxide (CO2), GDP, NRE and POP, and unidirectional causality from CO2 to GFIN, GTI and REN, highlighting dynamic interactions. Practical implications The results suggest that policymakers should promote accessible GFIN, enhance the efficiency of green innovation and invest in REN sources to support environmental sustainability. Originality/value This study offers novel insights by applying a quantile-specific approach to examine the impacts of GFIN and innovation on environmental sustainability in South America, addressing a significant gap in the literature where such distributional effects in emerging economies have been largely overlooked.

PurposeThis research aims to answer the question of to what extent managerial ability (MA) impacts the level of employing income smoothing (IS) through loan loss provision (LLP) and how this influences the banks’ financial performance.Design/methodology/approachThe research confirms LLPs used to smooth income through the relationship between LLPs and pre-provisioning income in Asia–Pacific banks from 2012 to 2021. Then, it explores the role of managerial ability in IS behavior by using a two-stage procedure: estimating the profit efficiency by employing a four-error stochastic frontier analysis (SFA) and generating MA by calculating residuals from regressing profit efficiency on bank-specific factors. Next, it explores the relationship between IS, managerial ability and banks’ performance.FindingsThere is IS through LLP among Asia–Pacific banks, and high-ability managers generally have no special taste in utilizing IS. However, these situations could be modified by contexts such as bank types, profitability levels, credit risk or economic conditions. Besides, talented managers are expected to propose a positive impact on performance in case they use discretionary LLP as a tool of IS.Originality/valueThis study is among the first to discover IS behavior and its association with MA and performance in the banking industry and Asia–Pacific region. Furthermore, a four-error SFA can solve the problems of inability and improve the measurement framework of managerial ability measurement. The research also enhances the understanding of upper echelon theory.

PurposeThis study examines how institutions in both home and host countries affect firms’ cross-border mergers and acquisitions (CBM&As) activity in the six most significant Latin American (LATAM) economies (1995–2018).Design/methodology/approachData from 1,094 transactions by LATAM companies were used to develop two data panels to examine the impact of institutions on CBM&A activity. Additionally, the influence of the target industry on CBM&A activity is explored. And to operationalize the independent variables, concepts from economic institutionalism are applied.FindingsThe research findings indicate that the primary motive of acquirers for investing abroad is not to find better formal institutional conditions, but rather to pursue new markets. In contrast, the home country’s formal institutions motivate LATAM firms to invest overseas. Contrary to previously published studies, there is evidence of an inverted U-shaped relationship between institutional informal distance and CBM&A activity conducted by LATAM firms.Originality/valueThis study analyzes the impact of the formal institutional quality of home and host countries as well as formal and informal institutional distances, on the accumulated value of CBM&As from LATAM. These relationships are underexplored in the literature. This study uses a large and representative sample of complete CBM&As in the region.

PurposeThis study investigates the extent to which bilateral trade with China and the United States (US) influences the productivity of trading partners.Design/methodology/approachThis study uses panel data estimates to identify the export and import policy channels separately and then their combination with trade integration and trade balance at both the country and sectoral levels between 99 countries and China and the US, incorporating institutional quality and geopolitical risks. The sample period covers the years 2002–2019, and the two-step generalized method of moments (GMM) is employed as the main estimation method.FindingsTrade with China boosts total productivity at constant prices through exports and imports, especially in manufacturing, but reduces welfare-relevant total factor productivity through total trade and trade balance, particularly in agriculture. In contrast, trade with the US consistently enhances all productivity across all channels, except for agricultural imports, which lower welfare-relevant total factor productivity. Institutional quality amplifies the positive effects, while trade uncertainty and US–China tensions reduce them.Originality/valueThis study provides a comparative, channel-specific and sector-sensitive analysis of trade-productivity links with China and the US, offering timely insights for policymakers involved in navigating shifting global trade dynamics.

PurposeGiven that government financial assets represent a large proportion of gross debt accumulation, this study examines their impact on debt leveraging and potential returns on the gap between interest rates and economic growth (r-g).Design/methodology/approachThis research focuses on the co-movements of r-g differentials, government financial assets and the primary deficit through a channel of gross debt, investment, external balance and ratings, using a sample of 27 European Union economies from 2000 to 2022. The following co-integration methods were estimated: (1) for the aggregate, panel quantile autoregressive distributed lags (QARDL), ARDL- pooled mean group (PMG) for panel data, implemented with a (PMG) and (2) ARDL-error correction (EC) for individual countries at a granular level.FindingsWhile government financial assets drive short- and long-run debt trajectories, granular country heterogeneities reveal differentiated results for financial assets leveraging potential returns on the differential between interest rates and output growth (r-g). Government financial assets may enhance r-g, but may risk even undermining gains from primary deficit consolidation efforts. By comparing aggregate estimations with country granular approaches, outliers from non-statistically significant estimations reveal the epistemological limits of aggregation, statistics and probability theory, warning against overconfidence in such mere guidance tools, which are not safeguarding guarantees.Research limitations/implicationsStatistical asymptotics and instability of non-independent and identical distributions may underestimate variance. Furthermore, skewness and leptokurtosis may benefit from extreme value theory. In addition, technological changes, policy regimes, geopolitical events and economic crises can change in-built long-run relationships.Practical implicationsHeterogeneity of government financial assets effects depend on socio and macrofinance conditions, advocating the principle of subsidiarity. Financial assets, such as sovereign wealth funds linked to natural resources, oil in Norway, copper in Chile, may benefit from financial assets assessments. The strengthening of democratic accountability calls for transparency about financial assets contribution to debt trajectories, r-g effects and risks of potential undermining primary deficit consolidations. Accounting reporting should appropriately disclose changes in assets value from exposition to market volatility, accumulation of holding costs due to constraints to asset liquidation, due to non-active secondary markets, or long investment horizons.Social implicationsTo strengthen democratic accountability, there should be transparency about their contribution to debt trajectories, r-g effects and risks to potential undermining primary deficit consolidation. Their performance depends on financial markets and socio- and macro-finance conditions, calling for the principle of subsidiarity.Originality/valueRather than the traditional emphasis on government debt, this study examines the leverage effect on the gap between interest rates and economic growth (r-g differential). While the literature primarily addresses stock-flow adjustments (SFAs), the focus is narrowed to financial assets underlying government interventions on the supply side of the economy. Evidence is provided on the risks of financial assets undermining primary deficit consolidation efforts. While the literature highlights the short and medium terms, estimates are divided into short-term dynamics and hypothetical in-built long-run cointegrations. Panel aggregation is compared with granular estimates, uncovering heterogeneities and supporting governance subsidiarity. Support for statistical pluralism is provided by comparing results and methodological limitations.

PurposeThis research explores the influence of intellectual capital (IC) efficiency (ICE) and institutional quality (IQ) on a firm’s capital structure (CS) in Indian firms.Design/methodology/approachThe analysis was conducted on a sample of Indian companies from 2015 to 2019. Data were collected from the S&P database, and regression and additional analyses were performed to achieve the objectives of this research.FindingsThe findings show a significant positive effect of ICE on a firm’s CS from debt (CSD) and an insignificant positive effect of IQ on CSD and CS from equity (CSE). The findings also indicate that human-capital efficiency (HCE) and capital-employed efficiency (CEE) are the main IC sub-dimensions influencing a firm’s CS, compared to the structural-capital efficiency (SCE) dimension.Practical implicationsThe results of this study have several practical implications, as they examine the influence of ICE and IQ on CS as potential determinants, which could help business leaders adopt optimal CS strategies.Originality/valueThe results of this study offer several novel contributions to the existing literature on CS by examining unexplored factors, such as ICE as a knowledge management strategy, ICE sub-dimensions, and IQ in the context of CS.

PurposeThe objective of this study is to analyze the influence of the following variables – technological innovation, creativity and innovation management and business model innovation – on two variables: value creation in companies and value capture in companies.Design/methodology/approachThe sample consisted of 222 informants employed by companies listed in the Top 1,000 in the city of Lima. A questionnaire was designed to examine the five variables under study (three independent variables and two dependent variables). Confirmatory and structural factor analyses were performed using structural equations with the SPSS AMOS software.FindingsThe study shows that value capture is influenced by technological innovation, creativity and innovation management, as well as business model innovation, while value creation is influenced only by technological innovation and business model innovation.Research limitations/implicationsOne limitation of this study is that its results are generalized for companies from different business sectors, so its conclusions cannot be associated with specific business sectors. Another limitation of the study is that the data from this research are cross-sectional, so the relationships found between the study variables are not sufficient to establish a definitive causal relationship.Practical implicationsFor executives, this study offers valuable insights into the significance of their management roles in driving innovation, particularly concerning the dual objectives of value creation and capture within their organizations.Originality/valueA research model is proposed to identify the factors that influence value creation and value capture in companies in a developing country, where consumers have different purchasing power and purchasing preferences compared to consumers in developed countries. Executives focus their efforts on creating and implementing innovative ideas only if they perceive that doing so will achieve monetary results, and it is necessary to emphasize the innovation of internal processes to create value in a way customers will perceive.