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China's stock market, which serves as an example of emerging markets, is steadily maturing in the context of globalization. In order to analyze the pricing mechanism of China's stock market, this paper builds a six-factor model to address the market features that are structurally efficient but not entirely efficient.

This study updates the Fama–French factor model's construction process to account for the unique features of China's stock market before creating a model that incorporates size, volume, value, profitability, and profit-income factors based on institutional investors' trading behavior and research preferences. The SWS three-tier sector stock index's monthly and quarterly data for the years 2016–2021 are used as samples for this study.

The results imply that China's stock market is structurally efficient and exhibits high levels of rationality in the region dominated by institutional investors. Specifically, big-size and high-volume portfolios that perform well in terms of liquidity can receive trading premiums. Growth-style sectors prevail at present, and investing in sectors with strong profitability and reliable financial reporting data can produce better returns.

The research on China's stock market can be extended to improve the understanding of the development process of similar emerging markets, thereby promoting their improvement. To enhance the development of emerging markets, the regulators should attach great importance to the role of local institutional investors in driving the market to maturity. It is crucial to adopt a structured approach to examine the market pricing mechanism throughout the middle stage of the transition from developing to mature markets.

This study offers a structured viewpoint on asset pricing in growing emerging markets by combining the multi-factor pricing model approach with behavioral finance theories.

This study aims to explore the impact of systematic liquidity risk on the averaged cross-sectional equity return of the Indian equity market. It also examines the effects of illiquidity and decomposed illiquidity on the conditional volatility of the equity market.

The present study employs the Liquidity Adjusted Capital Asset Pricing Model (LCAPM) for pricing systematic liquidity risk using the Fama & MacBeth cross-sectional regression model in the Indian stock market from January 1, 2012, to March 31, 2021. Further, the study employed an exponential generalized autoregressive conditional heteroscedastic (1,1) model to observe the impact of decomposed illiquidity on the equity market’s conditional volatility. The study also uses the Ordinary Least Square (OLS) model to illuminate the return-volatility-liquidity relationship.

The study’s findings indicate that the commonality between individual security liquidity and aggregate liquidity is positive, and the covariance of individual security liquidity and the market return negatively affects the expected return. The study’s outcome specifies that illiquidity time series analysis exhibits the asymmetric effect of directional change in return on illiquidity. Further, the study indicates a significant impact of illiquidity and decomposed illiquidity on conditional volatility. This suggests an asymmetric effect of illiquidity shocks on conditional volatility in the Indian stock market.

This study is one of the few studies that used the World Uncertainty Index (WUI) to measure liquidity and market risks as specified in the LCAPM. Further, the findings of the reverse impact of illiquidity and decomposed higher and lower illiquidity on conditional volatility confirm the presence of price informativeness and its immediate effects on illiquidity in the Indian stock market. The study strengthens earlier studies and offers new insights into stock market liquidity to clarify the association between liquidity and stock return for effective policy and strategy formulation that can benefit investors.

This study aims to document the time varying risk premia for market, size, value and momentum factors for an emerging market using a sophisticated conditional asset pricing model. The focus of this study is Turkish stock market denominated in local currency with its peculiar risk premia.

The authors employ Gagliardini et al.'s (2016) econometric method that uses cross-sectional and time series information simultaneously to infer the path of risk premia from individual stocks.

Using this methodology, the authors assess several conditioning information and conclude that local dividend yield, inflation and exchange rates have the most explanatory power. The authors document the time varying risk premia in Turkey over three decades.

Existing studies on dynamic estimation of risk premia lack a consensus as to which state variables should be included and to what extent they impact the magnitude of the premium. The authors extend the conditioning information set beyond the ones existing in the literature to determine variables that are specifically important for an emerging market.

Although the value effect is comprehensively investigated in developed markets, the number of studies examining the Vietnamese stock market is limited. Hence, the first aim of this research is to provide empirical evidence regarding returns on value and growth stocks in Vietnam. The second aim is to explain abnormal returns on Vietnamese growth and value stocks using both risk-based and behavioral points of view.

From the risk-based explanation, the Capital Asset Pricing Model (CAPM), Fama–French three- and five-factor models are estimated. From the behavioral explanation, to construct the mispricing factor, this paper relies on the method of Rhodes-Kropf et al. (2005), one of the most popular mispricing estimations in the financial literature with numerous citations (Jaffe et al., 2020).

While the CAPM and Fama–French multifactor models cannot capture returns on growth and value stocks, a three-factor model with the mispricing factor has done an excellent job in explaining their returns. Three out of four Fama–French mimic factors do not contain additional information on expected returns. Their risk premiums are also statistically insignificant according to the Fama–MacBeth second-stage regression. By contrast, both robustness tests prove the explanatory power of a three-factor model with mispricing. Taken together, mispricing plays an essential role in explaining returns on Vietnamese growth and value stocks, consistent with the behavioral point of view.

There are several value-enhancing aspects in the field of market finance. First, this paper contributes to the literature of value effect in emerging markets. While the evidence of value effect is obvious in numerous developed as well as international markets, both growth and value effects are discovered in Vietnam. Second, the explanatory power of Fama–French multifactor models is evaluated in the Vietnamese context. Finally, to the best of the author's knowledge, this is the first paper that incorporates the mispricing estimation of Rhodes-Kropf et al. (2005) into the asset pricing model in Vietnam.

The aim of the study was to analyze the performance of Black-Litterman (BL) portfolios using a views estimation procedure that simulates investor forecasts based on technical analysis.

Ibovespa, S&P500, Bitcoin and interbank deposit rate (IDR) indexes were respectively considered proxies for the national, international, cryptocurrency and fixed income stock markets. Forecasts were made out of the sample aiming at incorporating them in the BL model, using several portfolio weighting methods from June 13, 2013 to August 30, 2022.

The Sharpe, Treynor and Omega ratios point out that the proposed model, considering only variable return assets, generates portfolios with performances superior to their traditionally calculated counterparts, with emphasis on the risk parity portfolio. Nonetheless, the inclusion of the IDR leads to performance losses, especially in scenarios with lower risk tolerance. And finally, given the impact of turnover, the naive portfolio was also detected as a viable alternative.

The results obtained can contribute to improve investors practices, specifically by validating both the performance improvement – when including foreign assets and cryptocurrencies –, and the application of the BL model for asset pricing.

The main contributions of the study are: performance analysis incorporating cryptocurrencies and international assets in an uncertain recent period; the use of a methodology to compute the views simulating the behavior of managers using technical analysis; and comparing the performance of portfolio management strategies based on the BL model, taking into account different levels of risk and uncertainty.

We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns.

We estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy.

We find a negative relationship between expected idiosyncratic entropy and returns. Specifically, the Carhart alpha of a low expected entropy portfolio exceeds the alpha of a high expected entropy portfolio by −2.37% per month. We also find a negative and significant price of expected idiosyncratic entropy risk using the Fama-MacBeth cross-sectional regressions. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

We propose a risk factor of idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

The Internet of Things (IoT) platform empowers the digital transformation of the manufacturing industry by providing information technology services. Simultaneously, it enters the market by offering smart products to consumers. In light of different service fee scenarios, this article explores the optimal decision-making for the platform. It investigates the pricing models and entry decisions of IoT platforms.

In this study, we have formulated a game-theoretic model to scrutinize the influence of the IoT platform ventured into the smart device market on the pre-existing suppliers operating under subscription-based and usage-based pricing agreements.

Our outcome shows that introducing an IoT platform’s smart device has a differential effect on manufacturers depending on their contract type. Notably, our research indicates that introducing the platform’s own smart device within the subscription-based model does not negatively impact the profitability of incumbent manufacturers, so long as there is a noticeable discrepancy in the quality of the smart devices. However, our findings within the usage-based model demonstrate that despite the variance in smart device quality differentiation, the platform’s resolution to launch their device and impose their pricing agreements adversely affects established manufacturers. Additionally, we obtain valuable Intel regarding the platform’s entry strategies and contractual inclinations. We demonstrate that the platform is incentivized to present its smart device when reasonable entry costs remain. Furthermore, the platform prefers subscription-based contracts when the subscription fee is relatively high in non-platform entry and entry cases.

These findings hold significant practical implications for firms operating in an IoT-based supply chain.

This paper aims to examine the conditions under which small and medium enterprises (SMEs) invest in security services when they migrate their e-commerce applications to the cloud environment. Using a risk management perspective, the paper assesses the impact of security service pricing, security incident prevalence and virulence to estimate SME security spending at the market level and draw out implications for SMEs and security service providers.

Security risks are inherently characterized by uncertainty. This study uses a Monte Carlo approach to understand the role of uncertainty in the decision to adopt security services. A model relating key security constructs is assembled based on key constructs from the domain. By manipulating security service costs and security incident types, the model estimates the market-level adoption of services, security incidents and damages incurred, along with measures of their relative dispersion.

Three key findings emerge from this study. First, adoption of services and protection is higher when tiered security services are provided, indicating that SMEs prefer to choose their security services rather than accept uniformly priced products. Second, SMEs are considered price-sensitive, resulting in a maximum level of spending in the market. Third, results indicate that security incidents and damages can be much higher than the mean in some cases, and this should serve as a cautionary note to SMEs.

Security spending has been modeled at the firm level. Adopting a market-level perspective represents a novel contribution. Additionally, the Monte Carlo approach provides managers with tangible measures of uncertainty, affording additional information and insight when making security service adoption decisions.

Empirical evidence of the value creation process through which internationalizing small and medium-sized enterprises (SMEs) develop international branding capability (IBC) to build a value-creating brand in international markets is incomplete. This research aims to investigate a theoretical framework for the determinants and outcomes of IBC in internationalizing SMEs.

Using surveys of 519 internationalizing SMEs, this research empirically verified the antecedents to and effects of IBC on SMEs’ value creation, which thus translates into superior performance. Furthermore, this research explores contextual factors influencing the value creation process in SME internationalization.

Findings show that SMEs with strong international marketing resource orchestration (IMRO) and relational capability are more competent in developing IBC, which assists resource-constrained SMEs to create value, as manifested through international brand equity (IBE) and improved international performance. Moreover, environmental uncertainty enhances the interplay between IMRO, relational capability, and IBC, while new entrant pressure strengthens the relationship between IBC and IBE, and price competition pressure magnifies the impact of IBE on international performance.

Our study pioneers conceptualization of the value creation process through which SMEs develop IBC to build value-creating brands in international markets, overcoming the liabilities of smallness and outsidership.

This paper originally proposed the fuzzy option pricing method for green bonds. Based on the requirements of arbitrage equilibrium, this paper draws on Merton's corporate bond option pricing model.

Describing the asset value behavior of green bond issuing enterprises through diffusion-jump processes to reflect the uncertainty brought by carbon emission reduction policies and technologies, using approximation methods to get the analytical pricing formula and then, using a fuzzification technique of Choquet expectation under  λ-additive fuzzy measures after considering fuzzy factors, the paper provides fuzzy intervals for the parity coupon rates of green bonds with different subjective levels for investors.

The paper proposes and argues the classical and fuzzy option pricing methods in turn for both corporate ordinary bonds and green bonds, considering carbon risk or climate risk. It implements the scenario analysis varying with industry emission standards and discusses the sensitiveness of the related key parameters of the option.

The fuzzy option pricing for the green bonds provides the scope of the variable equilibrium values, operational theoretical supports and some policy implications of carbon reduction and promoting green funding.

The logic of introducing the fuzziness of the option pricing for the green bonds lies with considering the existence of fuzzy information about the project supported by the green bond and the subjectivity of investors and it also responds to changes in technological uncertainty and policy uncertainty in the process of “carbon peaking and carbon neutrality.”