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Fiscal and monetary policies are essential to the development of a capital market. In this chapter, authors present how fiscal and monetary policy in Poland evolved and adjusted to economic challenges in 1998–2022. It is worth noticing that the Polish economy and financial market have been built from scratch after 45 years of socialism. Hence, it is scientifically interesting to study the relationship between fiscal and monetary policy, and capital market in a developing country, and in a relatively young economy.

Both – the macroeconomic policy mix and development of the capital market – are the subject of analysis how fiscal and monetary policy impacted the capital market. As so the main aim of the chapter is the assessment of the nexus and dependencies between fiscal and monetary policy and the capital market.

In the chapter, multiple linear regression was used for each dependent variable to discover which monetary and fiscal policy parameters significantly predicted selected variables describing the development of the capital market in Poland. Fiscal and monetary policy variables served as descriptors explaining capital market parameters in seven separate models.

Multiple regression models explain 77.3%–95.4% of the volatility of the capital market characteristics. The level of the central bank's reference rate is a variable that influences the capital market the most. In six out of seven models, the interest rate was a significant parameter. The development of the capital market was accompanied by a higher tax-to-GDP ratio. At the same time, a strong negative impact of the tax-to-GDP increase was noticed in domestic institutional investors' stock trading.

The framework of this paper is financial mathematics and, more specifically, the control of data fraud and manipulation with their subsequent economic effects, namely, in financial markets. The purpose of this paper is to calculate the global loss or gain, which supposes, for the borrower, a change of the interest rate while the contracted loan is in force or, in another case, the loan has finished.

The methodology used in this work has been, in the first place, a review of the existing literature on the topic of manipulability and abusiveness of the loan interest rates applied by banks; in the second place, the introduction of a mathematical-financial analysis to calculate the interests paid in excess; and, finally, the compilation of several sentences issued on the application of the so-called mortgage loan reference index (MLRI) to mortgage loans in Spain.

There are three main contributions in this paper. First, the calculation of the interests paid in excess in the amortization of mortgage loans referenced to an overvalued interest rate. Second, an empirical application shows the amount to be refunded to a Spanish consumer when amortizing his/her mortgage loan referenced to the MLRI instead of the Euro InterBank Offered Rate (EURIBOR). Third, consideration has been made to the effects and the possible solutions to the legal problems arising from this type of contract.

This research is a useful tool capable of implementing the financial calculation needed to find out overpaid interests in mortgage loans and to execute the sentences dealing with this topic. However, a limitation of this study is the lack of enough sentences on mortgage loans referenced to the MLRI to get some additional information about the number of borrowers affected by these legal sentences and the amount refunded by the financial institutions.

To the best of the authors’ knowledge, this is the first time that deviations in the payment of interests have been calculated when amortizing a mortgage.

Brazil uses the dollar as a vehicle currency to invoice its exports. This fact produces a tendency toward equalizing the prices of products in dollars in the international market and reducing the ability of firms to practice pricing-to-market (PTM). This study aims to evaluate the hypothesis by estimating error correction models in panel data, obtaining estimates of PTM for 25 manufacturing products exported by Brazil between 2010 and 2020.

This study uses the correlated common effect estimator proposed by Pesaran (2006) and Chudik and Pesaran (2015b) to estimate the PTM coefficients.

Results of this study indicate that exporters practice local-currency pricing stability for dollar prices. This study obtains that Brazilian exporters tend to stabilize their dollar price for exports, reducing heterogeneity between destination markets. The results are in agreement with the hypothesis of the prevalence of the coalescing effect of Goldberg and Tille (2008) and lower sensitivity of the markup adjustment to the specific market, as pointed out by Corsetti et al. (2018). The pricing of Brazilian exports in dollars reflects a profit maximization strategy that considers an international price system based on global demand for products.

In addition to analyzing the dollar role in the pricing of Brazilian exports through the triangular decomposition, this study also shows the importance of examining the cross-section dependence of errors, considering the heterogeneous cointegration in export pricing models and producing PTM estimates for short-term and long-term.

This paper examines whether target returns act as specific goals that impact risk-taking when individuals make investment decisions.

Using an experimental setting, the authors assign either a low or a high target return to participants and ask them to make independent investment decisions as the risk-free rate fluctuates around their target return and, for some of them, becomes negative.

Building on cumulative prospect theory, the authors find that the prevailing reference point of participants is the target return, regardless of the level of the risk-free rate. This result still holds even when the risk-free rate is negative, suggesting that (1) the target return drives risk-taking more than does a zero-threshold and (2) negative rates are limited as a tool to stimulate appetites for risk. In a follow-up study, the authors show that these conclusions remain valid when the target return is endogenously determined.

The authors' original approach, which pioneers the use of target returns in both the positive and negative interest rate contexts, provides insightful results about the “reach for yield” among regular people.

This study focuses on listed and over-the-counter (OTC) companies in the Taiwan Stock Exchange. It found that an increase in the ownership proportion of institutional investors (INs), including foreign investors, investment trusts, and dealers can enhance the informativeness of stock prices. The relationship between these factors follows an inverted U-shaped pattern, indicating that excessively high ownership ratios can actually lead to a decrease in the informativeness of stock prices. Additionally, increasing the ownership proportions of foreign investors and investment trusts can reduce the risk of stock price collapse, while dealers show no significant relationship in this regard. This study also reveals that the technical variable of the price deviation rate is an important explanatory factor for post-collapse returns. It is positively correlated with the magnitude of the price decline after a collapse, meaning that stocks with weaker pre-collapse performance experience larger post-collapse declines. When the data during the 2020 pandemic period are excluded, changes in foreign ownership ratios show a significant positive correlation with postcrash returns in both the long and short term. The significant correlation in the short term may be due to a high proportion of foreign ownership. Any reduction in this could put pressure on stock prices, and retail investors may follow suit and sell-off, using foreign investors as a reference. The significant correlation in the long term might be due to foreign investors themselves possibly also trying to avoid the pressure that their own short-term sell-offs could exert on stock prices. The changes in the ownership ratios of investment trusts and dealers indicate that medium and long-term changes have a significant impact on postcrash returns, while the changes in the major players' ownership show no significant correlation. When data from 2020 are included in the analysis, the significance of all INs decreases.

This paper provides a structural model to value startup companies and determine the optimal level of research and development (R&D) spending by these companies.

This paper describes a new variant of float-the-money options, which can act as a financial instrument for financing R&D expenses for a specific time horizon or development stage, allowing the investor to share in the startup's value appreciation over that duration. Another innovation of this paper is that it develops a structural model for evaluating optimal level of R&D spending over a given time horizon. The paper deploys the Gompertz-Cox model for the R&D project outcomes, which facilitates investigation of how increased level of R&D input can enhance the company's value growth.

The author first introduces a time-varying drift term into standard Black-Scholes model to account for the varying growth rates of the startup at different stages, and the author interprets venture capital's investment in the startup as a “float-the-money” option. The author then incorporates the probabilities of startup failures at multiple stages into their financial valuation. The author gets a closed-form pricing formula for the contingent option of value appreciation. Finally, the author utilizes Cox proportional hazards model to analyze the optimal level of R&D input that maximizes the return on investment.

The integrated contingent claims model links the change in the financial valuation of startups with the incremental R&D spending. The Gompertz-Cox contingency model for R&D success rate is used to quantify the optimal level of R&D input. This model assumption may be simplistic, but nevertheless illustrative.

Once supplemented with actual transaction data, the model can serve as a reference benchmark valuation of new project deals and previously invested projects seeking exit.

The integrated structural model can potentially have much wider applications beyond valuation of startup companies. For instance, in valuing a company's risk management, the level of R&D spending in the model can be replaced by the company's budget for risk management. As another promising application, in evaluating a country's economic growth rate in the face of rising climate risks, the level of R&D spending in this paper can be replaced by a country's investment in addressing climate risks.

This paper is the first to develop an integrated valuation model for startups by combining the real-world R&D project contingencies with risk-neutral valuation of the potential payoffs.

This paper aims to examine the relationship between environmental, social and governance (ESG) performance and systemic risk sensitivity of Chinese listed companies. From the consumer loyalty and investor structure perspectives, the relationship between ESG performance and systemic risk sensitivity is analyzed.

Since Morgan Stanley Capital International (MSCI) ESG officially began to analyze and track China A-shares from 2018, 275 listed companies in the SynTao Green ESG testing list for 2015–2021 are selected as the initial model. To measure the systematic risk sensitivity, this study uses the beta coefficient, from capital asset pricing model (CPAM), employing statistics and data (STATA) software.

The study reveals that high ESG rating companies have high corresponding consumer loyalty and healthy trading structure of institutional investors, thereby the systemic risk sensitivity is lower. This paper reveals that companies with high ESG rating are significantly less sensitive to systemic risk than those with low ESG rating. At the same time, ESG has a weaker impact on the systemic risk of high-cap companies than low-cap companies.

The study helps the companies understand the influence of market value on the relationship between ESG performance and systemic risk sensitivity. Moreover, this paper explains explicitly why ESG performance insulates a firm’s stock from market downturns with the lens of consumer loyalty theory and investor structure theory.

The paper provides new insights on the company’s ESG performance that significantly affects the company’s systemic risk sensitivity.

The unexpected outbreak of COVID-19 has expedited the trend toward online education. To facilitate undisruptive learning, EdTech companies are continuously working on providing solutions to restore teaching and learning practices. This has caused a significant behavioral shift of the investors in the EdTech market. This study aims to analyze the effects of Web Market Traffic on the increased number of investors funding an EdTech Company in the market.

By drawing on the multi-method web analytics approach, this study analyses the nexus between Web Market Traffic and Investor's Behavior in the US and India, proving the hypothesized relationship in the proposed Model using a data sample of 300 EdTech Players.

There is a significant difference between the investor's behavior in India and the US. This study shows that the investors in the US are more inclined towards investing in EdTech companies in comparison to India. The Results demonstrate that monthly visits of consumers and the number of acquisitions by players positively affect the investor's behavior, while bounce rates take a toll on the number of investors.

This Study suggests that EdTech investors in the US and India should harness Web Traffic to capture the EdTech market. Further, this study offers practical implications that EdTech players can use to attract potential investors and increase brand visibility by improving web market traffic parameters.

This paper's original contribution is to empirically shed light on the effects of web market traffic on the investor's behavior. The study emphasizes the quintessentiality of managing the bounce rates and monthly visits for an EdTech market to attract more investors and capital inflow that enhance brand visibility. The study found that the investors behave distinctly in the developed and emerging markets in the US and India.

This paper aims to investigate the long-run financial and environmental performance of corporate green bond issuers, worldwide.

The data includes 259 corporate green bond issuers from 2013 to 2020. The authors adopt the matching approach, using the nearest neighbor method to select the control firms. The event-time approach is used to examine corporate green bond issuers’ long-run stock market performance, and robustness tests are conducted using the calendar-time method. The authors examine green bond issuers’ long-run environmental performance and carbon dioxide (CO₂₎ emissions using difference-in-differences estimations.

In contrast with the earlier long-run event studies, our results reveal that multiple-time issuers, and issuers operating in industries where the natural environment is financially material, perform financially in the long term relative to the control firms. The authors also document that corporate green bond issuers reduce their CO₂ emissions, and improve their resource use efficiency and environmental performance, in the long run.

To the authors’ knowledge, this is the first study that looks at the long-run effect of corporate green bond issuance on firms’ stock market performance. It has the particularity to document that corporate green bond issuance is beneficial for investors and positively affects the environment. Our findings help us understand that firms do not issue green bonds for greenwashing.

Driven by the anticipated global stagflation, this straightforward yet novel study examines the cost of inflation as a macroeconomic factor by investigating its influence on stock market growth. Thus, this paper aims to examine the impact of inflation on the probability of initial public offering (IPO) withdrawal decision.

The paper employs a large dataset that covers the period January 1995–December 2019 and comprises 33,536 successful or withdrawn IPOs from 22 nations with various legal and cultural systems. This study applies a probit model utilizing version 15 of Stata statistical software.

This study finds that inflation is substantially and positively correlated with the likelihood of IPO withdrawal. Results of this study show that the IPO withdrawal decision increases up to 90% when the inflation rate climbs by 10%. Multiple robustness tests provide consistent findings.

This study's implications are important for researchers, investment banks, underwriters, issuers, regulators and stock exchanges. When processing IPO proposals, investment banks, underwriters and issuers must consider inflation projections to avoid negative effects, as demonstrated by the findings. In addition, regulators and stock exchanges must be aware of the detrimental impact of inflation on competitiveness in attracting new listings.

To the best of the authors’ knowledge, this study is the first to present convincing evidence of a major relationship between IPO withdrawal decision and inflation.