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Purpose – This chapter reports on a rapidly growing trend in the analysis of data about emerging market (EM) economies – the use of baseline models as comparisons for explanatory models. Baseline models estimate expected values for the dependent variable in the absence of a hypothesized causal effect but set higher standards than do traditional null hypotheses tests that expect no effect.

Design/methodology/approach – Although the use of baseline models research originated in the 1960s, it has not been widely discussed, or even acknowledged, in the EM literature. We surveyed published EM studies to determine trends in the use of baseline models.

Findings – We categorize and describe the different types of baseline models that scholars have used in EM studies, and draw inferences about the differences between more effective and less effective uses of baseline models.

Value – We believe that comparisons with baseline models offer distinct methodological advantages for the iterative development of better explanatory models and a deeper understanding of empirical phenomena.

The purpose of this paper is to provide an extensive review of the monetary model of exchange rate determination which is the main theoretical framework on analyzing exchange rate behavior over the last 40 years. Furthermore, we test the flexible price monetarist variant and the sticky price Keynesian variant of the monetary model. We conduct our analysis employing a sample of 14 advanced economies using annual data spanning the period 1880–2012.

The theoretical background of the paper relies on the monetary model to the exchange rate determination. We provide a thorough econometric analysis using a battery of unit root and cointegration testing techniques. We test the price-flexible monetarist version and the sticky-price version of the model using annual data from 1880 to 2012 for a group of industrialized countries.

We provide strong evidence of the existence of a nonlinear relationship between exchange rates and fundamentals. Therefore, we model the time-varying nature of this relationship by allowing for Markov regime switches for the exchange rate regimes. Modeling exchange rates within this context can be motivated by the fact that the change in regime should be considered as a random event and not predictable. These results show that linearity is rejected in favor of an MS-VECM specification which forms statistically an adequate representation of the data. Two regimes are implied by the model; the one of the estimated regimes describes the monetary model whereas the other matches in most cases the constant coefficient model with wrong signs. Furthermore it is shown that depending on the nominal exchange rate regime in operation, the adjustment to the long run implied by the monetary model of the exchange rate determination came either from the exchange rate or from the monetary fundamentals. Moreover, based on a Regime Classification Measure, we showed that our chosen Markov-switching specification performed well in distinguishing between the two regimes for all cases. Finally, it is shown that fundamentals are not only significant within each regime but are also significant for the switches between the two regimes.

The results are of interest to practitioners and policy makers since understanding the evolution and determination of exchange rates is of crucial importance. Furthermore, our results are linked to forecasting performance of exchange rate models.

The present analysis extends previous analyses on exchange rate determination and it provides further support in favor of the monetary model as a long-run framework to understand the evolution of exchange rates.

Starting in the 1980s, financial liberalization and technological developments have enabled individual investors to participate in financial markets and carry out easy transactions. With these developments, academics began to wonder how the individual investors decide to invest and what factors affect these decisions.

According to traditional finance theory, it is suggested that markets are efficient and investors show rational behaviors in their financial purchasing decisions. However, in many studies conducted in recent years, it was determined that investors included emotional elements as well as rational elements in their decision-making process and therefore exhibited irrational behaviors by believing rumors instead of real information. It is thought that many factors such as personal characteristics, psychological factors, demographic and socio-economic factors play a role in the behavior of investors in purchasing a financial product.

In this study, the importance of herd behavior, which is one of the psychological factors that play a very important role in financial markets, on financial product purchasing process is examined in the light of the behavioral finance theory. It is thought that information included in the study will be useful for researchers who want to study herd behavior and for those who are interested in the subject.

Design/Methodology/Approach: This chapter applies tests associated with the adaptive market hypothesis (AMH) and Johansen cointegration test. AMH acknowledges the views of the efficient market hypothesis and behavioural finance approach.

Purpose: Cryptocurrencies are considered a new asset class by multiasset portfolio managers. Hence, we examine the AMH and cointegration in the cryptocurrency market to know whether select cryptocurrencies can be diversified.

Findings: We find that cryptocurrencies are efficient and there is a long-run relationship among constituent series, and there is no short-run causality derived from bitcoin, Ethereum and litecoin to bitcoin, while stellar and Dogecoin have short-run causality to bitcoin.

Originality/Value: This chapter is different from the existing one as this is the first study in which the AMH and Johansen cointegration test are applied to check the efficiency and relationship of Bitcoin, Ethereum, and Monero, Stellar, litecoin and Dogecoin.

Standard financial risk management practices proved unable to provide an adequate understanding and a timely warning of the financial crisis. In particular, the theoretical foundations of risk management and the statistical calibration of risk models are called into question. Policy makers and practitioners respond by looking for new analytical approaches and tools to identify and address new sources of financial risk. Financial markets satisfy reasonable criteria of being considered complex adaptive systems, characterized by complex financial instruments and complex interactions among market actors. Policy makers and practitioners need to take both a micro and macro view of financial risk, identify proper transparency requirements on complex instruments, develop dynamic models of information generation that best approximate observed financial outcomes, and identify and address the causes and consequences of systemic risk. Complexity analysis can make a useful contribution. However, the methodological suitability of complexity theory for financial systems and by extension for risk management is still debatable. Alternative models drawn from the natural sciences and evolutionary theory are proposed.

Anticipating mergers and acquisitions (M&A) helps executives and investors to design their firms’ strategies and decide on their investments. However, a review of the literature shows that we know relatively little about the determinants of M&A activity, and that former research often falls short of theoretical foundations. Hence the question: in what conditions can we make accurate practical predictions of M&A activity? Relying on neo-institutional theory, we suggest that M&A activity gains from being predicted at national level and that its determinants tend to depend on the country under scrutiny. We also draw on economic contagion theory pertaining to linkages between national economies to identify possible foreign institutional influences on a country's M&A activity. We tested our framework in three countries, the United States, the UK, and Japan, with a prediction model based on the Kalman filter that is rarely used in the field of international business. Our findings broadly corroborate our hypotheses, show the relevance of neo-institutional theory for studying the topic, and confirm that accurate practical predictions of M&A activity can be made at national level.

The economic doctrine of market efficiency plays an essential role in securities fraud litigation. In lawsuits alleging violations of SEC Rule 10b-5, the plaintiffs typically must argue that the market for the relevant security is efficient, and therefore that the “fraud on the market” doctrine applies. However, the term “market efficiency” is often applied imprecisely. In this chapter, we discuss properties of efficient markets that have been proposed in academic research, legal scholarship, and case law. We explore what must be assumed about capital markets for each of these properties to hold. We then ask how, in practice, each property could be rebutted.