Stock Insurers Research Articles

The Construction of Investment Portfolios under the Minimization of VarianceTaking the Hong Kong Insurance Market as an Example

Abstract: In the context of a decline in the Hang Sheng Index, this paper intended to study the different effect between using Markowitz Model and Index Model to invest insurance industrys stock in Hongkong, especially for those who are risk-averse. A recent ten years of adj close for 9 typical insurance stocks from Hongkong as well as the Heng sheng index has been chosen as the target data. The result illustrates that there is no significant difference between these two models. This study intends to give some reference for those who focus on Hong Kong insurance industrys investment and hate taking risk. This study find that the constraints minimal variance is the smallest at 16.832(The index model of constraint 2) and the constraints highest sharp ratio is around 0.26(The index model of constraint 4). The findings of this paper provide the investors empirical evidence on how to construct optimal investment portfolio in Hong Kong insurance market.

Connectedness and systemic risk between FinTech and traditional financial stocks: Implications for portfolio diversification

The rapid growth in FinTech is attracting significant investor attention. There are concerns that FinTech stocks may be a source of systemic risk and this has implications for the stability of the financial sector. This study uses a TVP-VAR model to estimate the dynamic connectedness between global FinTech stocks and the stocks of large US banks, regional US banks, US insurance, and global private equity. The findings reveal that FinTech and insurance stocks are net receivers of shocks while large US banks are a major source of shocks. Thus, FinTech stocks are not a source of systemic risk but can be affected by financial contagion and systemic risk originating from large US banks. The highest connectedness was observed at the onset of the COVID-19 lockdowns illustrating the dramatic impact that a health pandemic can have on systemic risk. Systemic risk also increased during the 2023 US bank panic. Connectedness has implications for constructing investment portfolios. The equally weighted, risk parity, and risk parity connectedness portfolios have similar portfolio summary statistics, but lower risk adjusted returns than the maximum Sharpe ratio portfolio which better captures the low correlation between FinTech stocks and traditional financial stocks. These results are robust across various portfolio rebalancing periods (daily, weekly, monthly).

Asset pricing models for Vietnamese non-life insurance companies

This paper aims to perform an extensive asset pricing analysis for the Vietnamese non-life insurance industry between 2008 and 2023. We document that well-known asset pricing models, such as the three-factor and five-factor models developed by Fama and French (1993, 2015), are unable to explain adequately the returns of non-life insurance stocks. Therefore, based on the results of Ammar et al. (2018) and He et al. (2021), we built a five-factor asset pricing model adapted to the Vietnamese non-life insurance industry. Empirical evidence shows that this model is better than other models in explaining the cross-section of non-life insurance stock returns. Significant factors are the excess market return, the size factor, the price-to-earnings ratio, the return on equity, and the reimbursement rate.

Substantiating the reliability conditions for the production process at metallurgical enterprises through the fault-tolerant functioning of the system «extraction of raw materials – technological railroad routes – metallurgical production»

The object of this study is the process of formation of insurance reserves at enterprises in the metallurgical industry. Under conditions of uneven supply of raw materials to metallurgical enterprises due to disruption of the transportation process or other reasons, there is a need to create insurance stocks in order to ensure the continuity of production. At the same time, it is necessary to take into account existing restrictions, such as the limited capacity of railroad sections and the impossibility of organizing parallel movement of trains, etc. The presence of these limitations makes it impossible to use classical methods for solving similar problems, such as linear programming. Therefore, to resolve the task, a simulation model was built, based on the discrete-event principle in the AnyLogic University Researcher environment using Oracle libraries and the Java SE compiler. With the help of the model, the process of rotation of dispatch routes at the railroad yard with multiple suppliers and one consignee was formalized. The optimization criterion was chosen to be the minimum deviations of fluctuations in reserves of iron ore concentrate and coke. Analysis of the simulation results revealed that the optimal size of the fleet of railroad routes on the selected rotation polygon is 30 units; at the same time, their utilization rate will be 65 %. It was also established that fluctuations in raw material stocks have a «natural character», which is confirmed by the normal distribution of the density of stock volumes. Under these conditions, the value of fluctuations in the volumes of the main raw materials will be ±13115 t/day for iron ore concentrate, and ±5298 t/day for coke. Reducing the range of fluctuation of raw materials volumes could make it possible to optimize the costs of creating stocks and streamline the transport work of the enterprise for providing raw materials

Exploring the Relationship Between Natural Disasters and Insurance Stock Market

Currently, the impact of natural disasters is increasingly substantial and conspicuous. This influence has implications not only for individuals' livelihoods, a country's overall economic output, and the rate of joblessness, but also for the financial market. The objective of this article is to investigate the effects of natural catastrophes on the stock price of the insurance business. This article uses four different insurance firms' stock values as a data sample. Moreover, this article uses the Long Short-Term Memory (LSTM) model to forecast the stock values of the insurance industry in the absence of catastrophic events. The study then compares the projected prices with the actual prices. Furthermore, this study diverges from past research by specifically examining storms as opposed to other forms of damage, with a particular emphasis on analyzing the effects on insurance firms' stock values. The findings suggest that the stock prices of the four firms are experiencing distinct forms of decline. This study establishes that storm catastrophes have an immediate detrimental impact on the stock markets of insurance firms. Consequently, insurance firms have to formulate policies that mitigate losses, while investors should exercise prudence during storm catastrophes.

Impact of Fundamental Factors on Share Price of Non-life Insurance Companies in Nepal

The aim of this research is to ascertain the direction in which fundamental factors impact Nepali non-life insurance businesses' stock values. This paper examines all twelve Nepal Stock Exchange (NEPSE)-listed non-life insurance companies using a quantitative, analytical, and descriptive research methodology. Nepal Rastra Bank, the Ministry of Finance and the insurance firms' websites served as secondary sources of information. The results has indicated that two significant elements affecting stock prices are the Price-to-Earnings (P/E) Ratio and Earnings Per Share (EPS). The Market Price of Shares (MPS) and EPS have the most positive association (r = 0.606, p < 0.01), whereas the P/E Ratio and EPS have the least positive correlation (r = 0.400, p = 0.003). Dividend per share (DPS) and MPS do not have a statistically significant link (B = 0.738, p = 0.854), whereas book value per share (BVS) and MPS have a marginally significant but positive correlation (B = 1.874, p = 0.061). The stock prices of the organizations in Nepal are significantly influenced by the EPS and P/E ratios. These findings suggest that higher P/E and EPS ratios are associated with better returns for investors. While DPS has minimal effect on stock prices, governments should make accurate and transparent financial reporting a priority to help investors. This paper analyzes the financial variables influencing the pricing of Nepalese non-life insurance stocks and offers advice on investment strategy and policy development. Int. J. Soc. Sc. Manage. Vol. 11, Issue-3: 76-82.

Technical and fundamental analysis of insurance stock prices on the Indonesian Stock Exchange (2018–2022)

Purpose: This study was conducted to determine the influence of fundamental (ROA, TATO, DER, NPM, and EPS) and technical (past share price, share volume, and past share volume) variables on share prices. in insurance companies listed on the IDX. Method: This study uses secondary data in the form of panel data, namely a combination of time series data for quarterly periods for five years, namely 2018-2022 and cross-sectional data from 11 insurance companies on the Indonesia Stock Exchange. The relationship between the research variables was tested using a panel data regression analysis. Results: The t-test results from the fixed effects model show that TATO and DER have a positive and significant influence on stock prices. ROA, NPM, and EPS do not significantly influence share prices. Past share prices and share volume have a significant positive influence on stock prices, whereas past share volume has a significant negative influence on share prices. The F-test results from the fixed effects model show that there is a significant influence of the independent variables, namely fundamental and technical variables, on stock prices. Limitations: This study only analyzes insurance companies (other than reinsurance) listed on the IDX from to 2018-2022, issue quarterly financial reports continuously from to 2018-2022, and have never been delisted during that period. Contribution: The contribution of this research is that it considers investors in making investment decisions, especially in selecting insurance company shares.

ESG controversies and insolvency risk: evidence from the insurance industry

PurposeThis study investigates the relationships between environmental, social, and governance (ESG) controversies and insolvency risk in the insurance sector. Drawing from legitimacy and stakeholder theories, the authors explore the impact of ESG controversies on insurers’ insolvency risk and the moderating effect of ESG practices on this relationship.Design/methodology/approachThis study utilises a dataset comprising 120 stock insurance firms spanning from 2011 to 2022. The authors employed system-GMM estimations to control for potential endogeneity and conducted several robustness checks.FindingsESG controversy positively influences insurers’ insolvency risk, with ESG practices mitigating these positive effects. The Governance (G) component of ESG practices plays a key role in counteracting the effects of ESG controversies on insurance companies’ insolvency risk.Originality/valueThis is the first study to investigate the direct relationship between ESG controversies and insolvency risk in the insurance industry. It underscores the critical influence of stakeholders’ perceptions of the company’s legitimacy, which is determined by the number of ESG controversies undertaken by the insurer company, on its insolvency risk. Additionally, by examining the three components of ESG practices individually, the authors offer insights into how managers can gain a competitive edge, particularly by utilising governance practices as safeguards against the adverse effects of ESG controversies on their financial risk.

Models for optimising the volume of material flows in the technological chain of corporate vertically integrated structures of the agricultural sector

The relevance of this study lies in the need to optimise supply cycles and volumes in value chains, which helps to reduce costs and increase the profitability of agricultural enterprises. The purpose of this study was to investigate and optimise the costs of initial material flows in the production subsystems of corporate vertically integrated structures of the agricultural complex under conditions of non-stationary demand. To fulfil this purpose, the study investigated the relationship between the amount of raw material stock stored in the production subsystem and the time of its consumption, based on which an extended model of the economic order quantity (EOQ) was considered, which, apart from the defined costs, also considers the costs of raw material shortages associated with the inability to fulfil deliveries and losses associated with supply failures caused by the unpredictability (stochasticity) of the order flow itself. It was found that in continuous production systems there is an opportunity to reduce the costs associated with failures by using an additional regular supply batch. For this, the mathematical “point-of-order” model was built based on the theory of mass service, which allows determining not only the best point to order, but also the optimal amount of the safety stock. A model for optimising the volume of material flows was proposed, which combines the model of the economic order quantity order adapted for use in product subsystems of corporate integrated structures of the agricultural complex and the “point-of-order” model, which allows calculating the minimum size of the insurance stock of raw materials using the tools of operations research. As an example, the material flow was optimised for Kivshovata Agro LLC. The findings of the study, such as the use of analytical tools and models for determining the economic order quantity and safety stock, can be used by the management of agricultural enterprises to improve the efficiency of material flow management

Volatility Spill-Over and Financial Contagion Effect of Conventional Stock on Islamic Equity in Nigeria: Evidence from Covid-19

This study empirically investigated volatility spill-over and financial contagion effect between conventional stocks and shariah compliant equities before and during covid-19 pandemic in Nigeria. Banking and insurance sectoral stocks indices were selected to represent conventional equities while Nigerian stock exchange lotus islamic index represent islamic stocks. Daily closing stock price data from 02-01-2018 to 26-02-2020 for pre-covid and 27-02-2020 to 31-12-2021 for pre-covid and during covid were considered. DCC-GARCH model (Dynamic conditional correlation- Generalized Autoregressive Conditional Heteroskedasticity Model) was deployed to examine the spill-over effect while t-test was applied to check the consistency of the DCC coefficient before and during the pandemic. The result of the multivariate GARCH show that both banking and insurance stocks have long run volatility spillover effect on lotus islamic index, the result also revealed no significant increase in conditional correlation during covid-19 pandemic which indicate absence of financial contagion from the conventional to islamic stocks. The results provide important information to researchers, investors, and policymakers

Fama’s model of efficient market: Analysis of the performance of insurance companies and the insurance stock price movement in Nigeria

The study analyzed the performance of insurance companies and the insurance stock price movement in Nigeria using Fama’s model of efficient market approach. Lack of information about insurance stock prices movement can influence investor’s decision making on insurance stock investments. An ex post facto research design was employed in the study. The research covers the activities of 19 insurance companies that are listed on the Nigerian Stock Exchange as at December 31, 2022. The data sample of the study comprises of daily stock prices data of 19 listed insurance companies for the period January 4, 2022 December 30, 2022. Fama-French three factor coefficient estimates obtained from quantile regression was used to test the hypothesis. The results revealed that there is a significant relationship between the insurance stock price movement and the performance of insurance companies in Nigeria, and that such relationship is negative. Recommendations were that there should be perfect information about stock market forces of demand and supply because if there is information asymmetry through which borrowers (securities issuers) know more about the risks than the lenders to (securities purchasers), the market participants may be reluctant to trade with insurance stocks, whose characteristics and behaviour under varying economic conditions are not well known. Also, it is important for the regulator in formulating policies that encourage diversification of investments among others.

Enhancing Predictive Accuracy of Insurance Stock Market in Jordan using Hyprid GFS.Thrift Model: A Genetic Fuzzy System-based Fintech Approach

This study focuses on improving the predicting accuracy of the daily ASE's weighted price index of the insurance sector (ICI) using a nonlinear spectral model called maximum overlapping discrete wavelet transform (MODWT) with five mathematical functions, namely, Haar, Daubechies (d4), least square (la8), best localization (bl14), and Coiflet (c6). Using a nonlinear spectral model called maximum overlapping discrete wavelet transform (MODWT) with five mathematical functions—Haar, Daubechies (d4), least square (la8), best localization (bl14), and Coiflet (c6)—this study aims to increase the daily ASE's weighted price index of the insurance sector's (ICI) prediction accuracy. The model utilizes a genetic fuzzy system based on Thrift's methodology (GFS.Thrift). The Amman Stock Exchange (ASE) supplied a dataset with 4,478 observations for the purpose of the study. The dataset represented daily data from January 2, 2006, to March 24, 2024. The adaptive GFS.THRIFT model was trained with 90% of the dataset, while the remaining 10% was used to test its prediction performance. Multiple egressions and multicollinearity tests were used to select input variables such as standardized foreign direct investment (FDI), standardized value traded (VT) and consumer price index (CPI). Insights from this study indicate that all input variables are positively related to the output variable. Secondly, the proposed model (MODWT-Haar-GFS. Thrift) significantly outperforms other existing models including the GFS. Thrift model.

ВЫБОР МОДЕЛИ УПРАВЛЕНИЯ ЗАПАСАМИ В РОЗНИЧНОЙ ТОРГОВЛЕ

The organization of effective product distribution in retail trade is based on the choice of a flexible production program for the production of products, the correct distribution channel and coordination of the work of transport units and warehouse facilities at all stages of product promotion in the retail network. First of all, the effective interaction of transport and warehouse is achieved by choosing the appropriate inventory management strategy in warehouses in the finished product distribution system. The article discusses the issues of choosing an effective inventory management model for organizing a transit form of goods movement in retail trade. Using the example of organizing the delivery of alcoholic beverages from the wholesale warehouse of Siberian Vodka Company LLC in Kemerovo (SVK LLC) to the stores of the Begemag retail chain, the effective interaction of the transport and warehouse subsystem of commodity movement is analyzed. The uneven delivery of products to Begemag stores is shown, which is explained by uncoordinated actions between transport and warehouse departments. Based on statistical processing of information, a linear relationship is established between delivery times and consumption volumes in Begemag stores, which, in the future, is the basis for determining the projected volumes of product deliveries and time intervals between regular deliveries, reducing the level of insurance stocks in the warehouses of the retail chain and leveling the uneven volume of deliveries to the places of sale of goods. Using the example of four stores of the Begemag retail chain, the effectiveness of the application of the inventory management model considered in the article is shown, which allows to free up more than 2 million rubles per year due to coordinated interaction of departments of the transport and warehouse subsystem of commodity movement management.

The Role of Net Profit Margin, Asset Turnover, and Equity Multiplier in Driving Stock Returns: Moderating Effect of ROE Dupont

This study aims to test whether DuPont's ROE can moderate the effect of net profit margin, total asset turnover, and equity multiplier ratio on the stock returns of insurance companies listed on the Indonesia Stock Exchange. This research includes quantitative research. Purposive sampling techniques are used to find stocks of insurance companies that meet the research criteria. The data in this study is panel data sourced from financial statements and historical data on the closing prices of 14 insurance companies for the observation period of January 2018-December 2022. The research model uses SEM-PLS with a data analysis method, moderated regression analysis (MRA), through the Warp Pls 8.0 program. The results showed that the NPM variable did not affect stock returns, while TATO and EMR significantly affected insurance stock returns positively. Furthermore, Dupont's ROE moderation variable interactions were found to have varying classifications. Dupont's ROE role in NPM relationships acts as a homologizer, meaning it can influence the strength of the relationships built. While in the TATO relationship, Dupont's ROE acts as quasi-moderation, which means having a pseudo-interaction between the two. In the EMR relationship, Dupont's ROE acts as a moderation predictor, which means that Dupont's ROE variable only acts as an independent variable in the relationship model formed.

Exploring the market risk profiles of US and European stock insurers

AbstractMarket risks account for an integral part of insurers' risk profiles. We explore market risk sensitivities of insurers in the United States and Europe. Based on panel regression models and daily market data from 2012 to 2018, we find that sensitivities are particularly driven by insurers' product portfolio. The influence of interest rate movements on stock returns is 60% larger for US than for European life insurers. For the former, interest rate risk is a dominant market risk with an effect that is five times larger than through corporate credit risk. For European life insurers, the sensitivity to interest rate changes is only 44% larger than toward credit default swap of government bonds, underlining the relevance of sovereign credit risk.

Boardroom gender diversity and risk-taking in the insurance industry: do organizational form and ownership structure matter?

PurposeThis study aims to investigate the relationship between boardroom gender diversity (BoGD) and risk-taking by property-liability (P-L) stock insurers from an analytical framework that control for organizational form and ownership structure. It relies on the behavioral agency model, the resource dependency theory and the concept of socioemotional wealth (SEW).Design/methodology/approachThis study builds on an unbalanced panel of 2,285 firm-year observations from 232 European and US P-L stock insurers covering the period 2010–2019 and measure risk-taking by using four proxies: total risk (TR), upside risk (UpR), downside risk (DwR) and default risk (DR). Reverse causality and endogeneity concerns are treated by applying different approaches.FindingsFindings suggest that BoGD mitigates the TR, DwR and DR but does not interfere with the UpR, which conceptualizes firm expectations to enhance patrimony and safeguard SEW for heirs, especially in family-owned insurers. The findings hold in various robustness checks including endogeneity and alternative specifications of BoGD and risk-taking.Practical implicationsThis study contributes to practice by contrasting the role of female directors’ bevahior when assuming risk, which seems significantly different depending on the risk-taking specification and the organizational form. The author advises policyholders and policymakers to look at closely on BoGD and ownership structure as they affect insurance company risk-taking.Originality/valueThis study takes a more direct approach to highlight the BoGD’s effect on corporate risk-taking by focusing on the insurance sector which is characterized by risk and uncertainty bearing. To the best of the author’s knowledge, this is the first study to consider the full range of the stock organizational forms and the degree of family control in displaying this effect in both widely traded and closely traded insurers and to assess risk-taking from both market-based and accounting-based aspects.

Analysis of the structure of consumption of feed nutrients by animals in agricultural enterprises of dairy cattle breeding

The annual structures of harvested fodder by agricultural enterprises with different levels of productivity of the dairy herd have been established. The share of harvested hay was higher in agricultural enterprises of the second group and amounted to 6.7-8.4%. The maximum consumption of straw was typical for agricultural enterprises of the first group - 1.6-4.1%. The established shares of corn silage indicate that its use was largely due to the productivity of dairy herd animals. The share of corn silage in the farms of the first group was 19.2-24.7%. In 2021, the share of corn silage increased, mainly due to the formation of insurance stocks of feed on farms, especially the third group - 12.3-14.8%. The higher the productivity of cows and young animals, the more effectively grain forage is used in combination with other energy-protein feeds and feed additives that balance the diet. For 2021, on average, the use of grain fodder in the farms of the first and second groups was 37.9-42.8% and 36.9-46.4%, which is higher than in 2018-2020. by 7.2-9.0% and 8.9-11.0%. In general, regardless of the level of productivity of the dairy herd of farms, the provision of harvested feed with exchangeable energy and crude protein remains quite low due to their quality.

Extreme spillovers between insurance tokens and insurance stocks: Evidence from the quantile connectedness approach

This study examines potential tail spillovers between insurance tokens and conventional stocks using the quantile connectedness approach by Ando et al. (2022). In particular, this study explores static and dynamic spillovers at lower and upper tails of the return distribution. In line with previous studies, tokens and conventional stocks within the insurance market may show positive but low connectedness levels. Furthermore, our findings confirm a higher sensitivity of the insurance system at both tails of the distribution in comparison with the median (Q=0.50). As expected, dynamic connectedness measures change over time, intensifying at the extremes of the distribution. This finding is confirmed by the robustness test that consists of analyzing the RTD (Relative Tail Dependence) measure, as we reject the symmetric response, since its values are clearly different from zero in most of the sample period. These results are of interest to portfolio managers, as the findings will allow them to suggest adjustments to investment portfolios according to the evolution of the dynamic spillovers found.

The Influence of Force Majeure of Non-government Factors on People's Willingness to Insurance in China

Except for investors, people usually regard insurance as a tool to transfer unknown risks. We believe that insurance can minimise financial losses when a risk occurs and reduce people's fears when disaster strikes. Therefore, some scholars put forward the hypothesis that people's willingness to buy insurance is related to some force majeure. From the perspective of behavioral finance, this paper selects indicators such as the rate of return of insurance stocks and insurance search index as proxy variables for insurance willingness. It also selects natural disasters and epidemics as proxy variables for force majeure other than government actions (referred to as force majeure in the text). Regression analysis was carried out on the above variables, and it was concluded that force majeure other than government actions was positively correlated with people's willingness to purchase insurance.

Efficiency: Mutual vs. Stock P-L Insurers

This paper reviews evidence from the U.S. property-liability insurance industry that examines technical efficiency between mutual and stock organizational forms. I exploit a modified slacks-based measure data envelopment analysis methodology to estimate technical efficiency of a property-liability insurer relative to a reference set consisting of all such insurers with the same organizational form. Then, I distinguish relative technical efficiency between insurers’ capacity to maximize social capital (reputational efficiency) and to maximize investment returns (investment efficiency). I document statistically significant evidence that mutual insurers outperform stock insurers in terms of reputational and investment efficiencies. My findings thus reflect a newer appreciation of organizational forms in insurance and illuminate how households make key insurance decisions.