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This paper tries to investigate whether there exist international integrated markets among East Asian economies, by employing the Generalized Purchasing Power Parity (G-PPP) model, then, it would help to suggest whether the East Asian region is the Optimum Currency Area (OCA) or not. The empirical results in this paper suggest that holding the G-PPP among nine Asian countries (China, Indonesia, Japan, Korea, Malaysia, the Philippines, Singapore, Thailand and Vietnam) becomes more applicable in 2000–2013 than of that in 1984–1997. In the period of “globalization,” which is characterized by expansion of world trade, increase of international capital flows, and development of information and communications technologies, Asian economic development has been promoting not only economic integrations but also constructing the stable linkages of real exchange rates. Therefore, it would help to adopt regional coordination for monetary policies to assure the feasibility of a possible monetary union.

This paper employs Granger causality tests to analyze the role of speculators using weekly COTR (commitment of traders reports) data covering the period of August 2014 to July 2017. The paper presents statistically significant evidence that the position changes of speculators, such as hedge funds and CTAs (commodity trading advisors), unidirectionally Granger-cause the prices of base metals, such as aluminum, copper, and zinc. This finding is a result of causality going from the levels of net futures positions of money managers to futures price changes on the London Metal Exchange (LME). However, producers&rsquo, and swap dealers&rsquo, speculative roles in price-formation are rejected in Granger causality tests. This paper presents clear results with important market implications.

Crude oil is the dominant energy resource worldwide. The focus of this paper is on its historical behaviour and subsequent implications for the global economy with an emphasis on the lead–lag relationship between spot and future prices. The paper examines the behaviour of oil spot and future prices and their determinants during periods of market uncertainty, particularly in the context of economic and financial crises. The analysis highlights a key controversy within the extant literature, as to whether spot or futures prices are the main crude oil price indicator. The literature review indicates that the lead–lag relationship is a dynamic one, especially during periods of sustained uncertainty, which leads to significant disagreements and incongruities among researchers regarding the price that plays a dominant role.

This paper investigates the risk-return relations in Chinese equity markets. Based on a TARCH-M model, evidence shows that stock returns are positively correlated with predictable volatility, supporting the risk-return relation in both aggregate and sectoral markets. Evidence finds a positive relation between stock return and intertemporal downside risk, while controlling for sentiment and liquidity. This study suggests that the U.S. stress risk or the world downside risk should be priced into the Chinese stocks. The paper concludes that the risk-return tradeoff is present in the GARCH-in-mean, local downside risk-return, and global risk-return relations.

Previous research has assessed the impact of policy uncertainty on a few macro variables. In this paper, we consider its impact on oil prices. Oil prices are usually determined in global markets by the law of demand and supply. Our concern in this paper is to determine which country’s policy uncertainty measure has an impact on oil prices. Using both the linear and the nonlinear Autoregressive Distributed Lag (ARDL) methods, we find that while policy uncertainty measures of Canada, China, Europe, Japan, Russia, South Korea, and the U.S. have short-run effects, short-run effects last into the long-run asymmetric effects only in the case of China. This may reflect the importance and recent surge in China’s engagement in world trade.

The purpose of this study is to investigate the fluctuations that occur in stock returns of US stock indices when there is an increase in the volume of Google internet searches for the phrase “quantitative easing” in the US. The exponential generalized autoregressive conditional heteroscedasticity model (EGARCH) was applied based on weekly data of stock indices using the three-factor model of Fama and French for the period of 1 January 2006 to 30 October 2020. The existence of a statistically significant relationship between searches and financial variables, especially in the stock market, is evident. The result is strong in three of the four stock indices studied. Specifically, the SVI index was statistically significant, with a positive trend for the S&amp, P 500 and Dow Jones indices and a negative trend for the VIX index. Investor focus on quantitative easing (QE), as determined by Google metrics, seems to calm stock market volatility and increase stock returns. Although there is a large body of research using Google Trends as a crowdsourcing method of forecasting stock returns, this paper is the first to examine the relationship between the increase in internet searches of “quantitative easing” and stock market returns.

Farmland valuation models usually incorporate local purchasing power as one of the pricing factors. A plausible rationale is that a larger population and higher income per capita imply increasing demand for agricultural products and farmland. In this paper, we study the relationship between the agricultural land prices, the regional population, and income per capita in an open economy setting in nominal and real variable terms using data from 1929 to 2018 at the state level. We show that in most areas of the United States, agricultural land prices are less affected by the state population or personal income. The valuation of agricultural land should not factor in the local purchasing power factors, with a few exceptions.

This study explored the option value embedded in a reverse mortgage in Korea through an empirical analysis, using the Black&ndash, Scholes option-pricing model. The value of a reverse mortgage is affected by the variation in house prices. However, older homeowners using reverse mortgages are able to choose this option due to the unique characteristics of reverse mortgages, such as non-recourse clauses or being able to redeem the loan. This paper found the following results. First, the call option value is 5.8% of the house price at the age of 60, under the assumption of a KRW three hundred million house value, while the put option value is only 2.0%. Contrary to what it is at sixty years of age, only the call option value will remain when the homeowner reaches the age of 80. Second, this article analyzed the sensitivity of the key variables of real-option analytical models, such as the change of the exercise price, the change of the risk-free rate, volatility, and maturity, on the option value of a reverse mortgage. The sensitivity results of the key variables supported economic rationales for the option pricing model.

Bitcoin&rsquo, s evolution has attracted the attention of investors and researchers looking for a better understanding of the efficiency of cryptocurrency markets, considering their prices and volatility. The purpose of this paper is to contribute to this understanding by studying the degree of persistence of the Bitcoin measured by the Hurst exponent, considering prices from the Brazilian market, and comparing with Bitcoin in USD as a benchmark. We applied Detrended Fluctuation Analysis (DFA), for the period from 9 April 2017 to 30 June 2018, using daily closing prices, with a total of 429 observations. We focused on two prices of Bitcoins resulting from negotiations made by two different Brazilian financial institutions: Foxbit and Mercado. The results indicate that Mercado and Foxbit returns tend to follow Bitcoin dynamics and all of them show persistent behavior, although the persistence in slightly higher for the Brazilian Bitcoin. However, this evidence does not necessarily mean opportunities for abnormal profits, as aspects such as liquidity or transaction costs could be impediments to this occurrence.

This paper aims at identifying a validated risk model for the cryptocurrency market. We propose a stochastic volatility model with co-jumps in return and volatility (SVCJ) to highlight the role of jumps in returns and volatility in affecting Value-at-Risk (VaR) and Expected Shortfall (ES) in cryptocurrency market. Validation results based on backtesting show that SVCJ model is superior in terms of statistical accuracy of VaR and ES estimates, compared to alternative models such as TGARCH (Threshold GARCH) volatility and RiskMetrics models. The results imply that for the cryptocurrency market, the best performing model is a stochastic process that accounts for both jumps in returns and volatility.

This paper estimates the amount of liquidity created by Syrian banks between 2004 and 2016, and further investigates the effect of liquidity creation on bank performance, controlling for a set of bank-level, industry-level, and macroeconomic variables. The findings show bank liquidity creation improved during the pre-war period and showed positive figures, but started to decline sharply during wartime. The results also show a negative relationship between liquidity creation and bank profitability (return on assets) during wartime, however, this relationship was insignificant before the war. Finally, this study conducted robustness checks to confirm its findings.

In this paper, we examined and compared the forecast performances of the dynamic Nelson&ndash, Siegel (DNS), dynamic Nelson&ndash, Siegel&ndash, Svensson (DNSS), and arbitrage-free Nelson&ndash, Siegel (AFNS) models after the financial crisis period. The best model for the forecast performance is the DNSS model in the middle and long periods. The AFNS is inferior to the DNS model for long-period forecasting. In U.S. bond markets, AFNS is shown to be superior to DNS in the U.S. However, for Japanese data, there is no evidence that the AFNS is superior to the DNS model in the long forecast horizon.

Using the panel vector autoregression (VAR) method, this paper documents relationships between investor attention and stock market activities, i.e., return, volatility, and trading volume, respectively. In sum, bidirectional dynamic interdependence of the SVI&ndash, stock market activities relationship exists, in which the SVI&ndash, trading volume relationship shows the strongest evidence. This is consistent with prior literature using trading volume as a proxy of investor attention. However, the relationships in the developed and developing markets are statistically significantly different. The stock markets in the developed markets over-react more to the search volume than those in the developing markets. We postulate that investor attention is one of the key elements in asset pricing in stock markets.

The debate on the UK leaving the European Union is still hot and ongoing today due to many economic, political, social, and other consequences on many different countries over the world. This paper focuses on the reactions of selected Central and Eastern European (CEE) and South and Eastern European (SEE) stock markets to the Brexit vote on 23 June 2016. Using daily data for the time span from January 2010 until July 2016 and the event study methodology (ESM), the return and volatility series are being tested for significant reactions to the Brexit event. The results indicate mixed results regarding the abnormal cumulative return series, but the volatility series were found to be significantly affected by the mentioned event. This is important for international investors and gives information on the reaction of mentioned markets to big political and economic events in order to tailor international portfolios in a way to hedge from risk.

The Chinese liquid natural gas (LNG) import price has been unstable because the stability of LNG import prices is related to changes in the exchange rates. This paper analyzes the pass-through rate of the Chinese Yuan (CNY) and Japanese Yen (JPY) on the Chinese LNG import price. The Time-Varying Parameter vector autoregressive (TVP-VAR) model is adopted to verify the pass-through rate of the exchange rates on the LNG import price using the Markov chain Monte Carlo (MCMC) method. Since September 2005, the JPY pass-through rate on the Chinese LNG import price has been decreasing while that of the CNY has been increasing. Notably, the pass-through rate of CNY began to exceed that of JPY after 2008. Moreover, since 2005, the lag effect of the CNY on the Chinese LNG import price became longer compared to JPY. If any new currency reform of the CNY is implemented in the future, then the impact of JPY on the Chinese LNG import price could be reduced and the lag effect of the CNY on the Chinese LNG import price could become longer. Therefore, the fluctuation of the CNY is becoming an important factor in understanding the movements of the Chinese LNG import price. This implies the significance of considering the effect of the exchange rate on an energy market when the market is influenced by a monetary reform of the importing country.

The topic of contagion has gained importance in the last few decades, earning its place amongst the most debated topics in international economics. Contagion is a phenomenon where market disturbances in crisis times are observed to spread from one country to the other in the form of comovements in exchange rates, stock prices, bond spreads, capital and trade flows. Analysing contagion and, more important, being able to make an on-coming prediction successfully helps economic planners to take appropriate rectificatory action toward establishing stable macroeconomic conditions. In previous studies, various proxies for distance have been used to test their explanatory power on a suitable dependent variable, typically a crisis index. In this paper, the separate impacts of geographic distance, psychic distance and cultural factors are tested on the correlation of real exchange rate returns to assess their predictive power. Using a sample of 30 countries for a period of 24 years (1993 to 2016) and data at monthly intervals, a panel regression is conducted. The findings of the analysis are that there is a negative effect of all the three explanatory variables on the correlation of real exchange rate returns. Moreover, a rolling regression conducted across the whole period shows coefficients going back to zero just before a crisis event and tending to fall afterwards. These findings contribute to the literature on contagion analysis by taking a different approach and exploring the separate impacts of geographic distance, psychic distance and cultural factors as explanatory variables and assessing their predictive power. The findings of the research are thus useful for policy makers towards restoring stable economic conditions.

The description of the dynamics and fluctuations of macro variables remains one of the most exciting problems of financial economics. This paper models macro variables via the description of transactions between agents. We use risk ratings x of agents as their coordinates in the economic space. Transactions like buy-sell, investment, credits, etc., between agents change their extensive financial and economic variables. Aggregates of transactions between all agents with risk ratings x and y define the macro transactions between points x and y. Macro transactions determine the evolution of macro variables. Interactions between different transactions outline their dynamics and fluctuations. We model macro transactions and the interactions between them by economic hydrodynamic-like equations in the economic space. As an example, for simple model interactions between credit-loans and loans-repayment transactions we derive economic hydrodynamic-like equations and wave equations for near perturbations of macro transactions and study simple wave solutions and their consequences. Waves of macro transactions in the economic space propagate from high to low risk agents or vice versa and define the fluctuations of macro financial variables. The existence and diversity of waves and fluctuations of macro transactions in simple models clarifies the importance of wave processes for macro financial modeling and forecasting.

This paper empirically examines the significance of credit ratings for optimal capital structure decisions. Non-financial Asian listed companies, evaluated by Standard and Poor's, are selected from 2000 to 2016. Panel data analysis with pooled ordinary least square (OLS), fixed effect (FE), and generalized method of moment (GMM) estimation techniques are employed to test the effect of each credit rating scale on capital structure choices. For the problem of heteroskedasticity in OLS, the heteroskedastic white consistent variance is used for the best fit of the model. Findings of all estimation techniques show that the relationship between credit rating scales and leverage ratio is a non-linear inverted U shape. High- and low-rated companies have a low level of leverage, whereas mid-rated companies have a high level of leverage. It is evident that costs and benefits of each rating scale have a substantial effect on the behavior of a company's choices for optimal capital structure. The study suggests that policymakers, investors, and financial officers should consider credit rating as an important measure of financing decisions.

The maritime industry is one of those rare industries that are both highly international integrated to international trade and also highly capital intensive dependent on substantial investment amount. In the literature, ship investments have not been widely examined through the firm-level investment theories to explore the link between investment level and asset price valuation. The general trend in the literature of ship investments is to analyse the relationship among the shipping markets (newbuilding, second-hand, freight rate and scrap) and their impact on asset price valuation, the timing of investments and market entry and exit conditions. In this paper, we extensively reviewed the literature of firm-level investment theories and ship investments. We showed that the application of firm-level investment theories to the ship investments is confined to the basic investment valuation models, such as Net Present Value and Real Option Analysis. Ship investments need to be examined by firm-level investment theories to define firm/industry value maximization level within the approach of the solid investment theories.

It is well known that that there is an intrinsic link between the financial and energy sectors, which can be analyzed through their spillover effects, which are measures of how the shocks to returns in different assets affect each other’s subsequent volatility in both spot and futures markets. Financial derivatives, which are not only highly representative of the underlying indices, but can also be traded on both the spot and futures markets, include Exchange Traded Funds (ETFs), a tradable spot index whose aim is to replicate the return of an underlying benchmark index. When ETF futures are not available to examine spillover effects, “generated regressors” are useful for constructing both Financial ETF futures and Energy ETF futures. The purpose of the paper is to investigate the co-volatility spillovers within and across the US energy and financial sectors in both spot and futures markets, by using “generated regressors” and a multivariate conditional volatility model, namely Diagonal BEKK. The daily data used are from 1998/12/23 to 2016/4/22. The data set is analyzed in its entirety, and are also subdivided into three distinct subsets. The empirical results show there is a significant relationship between the Financial ETF and Energy ETF in the spot and futures markets. Therefore, financial and energy ETFs are suitable for constructing a financial portfolio from an optimal risk management perspective, and also for dynamic hedging purposes.

This paper analyses the issue of the dynamics of the TARGET2 system balances during the sovereign debt crisis, when some countries registered a decisive inflow of the central bank liquidity and others showed an outflow. The dynamics in the TARGET2 are here explained as being due to a fall in the level of confidence in the capacity of the Economic and Monetary Union to survive, rather than to disparities in the level of competitiveness among countries of the Eurozone. This crisis of confidence has to be considered as the consequence of the implicit refusal of the European institutions to create a mechanism working as lender of last resort for the euro area member States, indeed, only when the ECB took this responsibility by launching the Outright Monetary Transactions clear signs of improvement were observed in the sovereign debt crisis.

The paper provides probability estimates of the state of the GDP growth. A regime-switching model defines the probability of the Greek GDP being in boom or recession. Then probit models extract the predictive information of a set of explanatory (economic and financial) variables regarding the state of the GDP growth. A contemporaneous, as well as a lagged, relationship between the explanatory variables and the state of the GDP growth is conducted. The mean absolute distance (MAD) between the probability of not being in recession and the probability estimated by the probit model is the function that evaluates the performance of the models. The probit model with the industrial production index and the realized volatility as the explanatory variables has the lowest MAD value of 6.43% (7.94%) in the contemporaneous (lagged) relationship.

Financial disasters to hedge funds, bank trading departments and individual speculative traders and investors seem to always occur because of non-diversification in all possible scenarios, being overbet and being hit by a bad scenario. Black swans are the worst type of bad scenario: unexpected and extreme. The Swiss National Bank decision on 15 January 2015 to abandon the 1.20 peg against the Euro was a tremendous blow for many Swiss exporters, but also Swiss and international investors, hedge funds, global macro funds, banks, as well as the Swiss central bank. In this paper, we discuss the causes for this action, the money losers and the few winners, what it means for Switzerland, Europe and the rest of the world, what kinds of trades were lost and how they have been prevented.

This paper draws on network theory to investigate European banks’ sovereign debt exposures. Banks’ holdings of sovereign debt build a network of financial linkages with European countries that exhibits a long-tail distribution of node degrees. A highly connected network core of 15 banks is identified. These banks accounted for the majority of sovereign debt investments between December 2010 and December 2013 but exhibited only average and sometimes even below average capitalizations. Consequently, they constituted a potential source and transmission channel of systemic risk, especially due to their proneness to portfolio contagion. In a complementary regression analysis, the effect of counterparty risk on Credit Default Swap (CDS) spreads of 15 EU sovereigns is investigated. Among the banks exposed to the debt of a particular issuer, the biggest institutions in terms of their own asset sizes are identified and some of their balance sheet characteristics included into the regression. The analysis finds that the banks’ implied volatilities had a significant and increasing effect on CDS spreads during the recent crisis years, providing evidence of the presence of counterparty risk and its effect on EU sovereign debt pricing. Furthermore, the role of the domestic financial sectors is assessed and found to have affected the CDS spreads.

This paper compares the “simplesum” monetary aggregates - M2) (M1 andpublished by the Saudi Arabian Monetary Agency (SAMA) with the new monetary aggregates (D1 andD2)—known as the Divisia monetary indexes. The former aggregates are constructed from a simple accounting identity, whereas the Divisia aggregates are constructed using statistical index number theory and aggregation theory. The findings suggest that both D1 and M1 are identical, given the perfect substitutab ility of the monetary components within those aggregates. For the broader monetary aggregates where perfect substitutability assumption is not realistic, the two monetary indexes differ substantially. SAMA could benefit by using both monetary indexes simultaneously to better monitor liquidity in the market. Keywords: monetary aggregation; Divisia monetary aggregates; index number theory JEL Classifications: E41; E51; E52; E58 1. Introduction Simple-sum monetary aggregates (widely denoted by M1, M2, and M3) are commonly used by central banks worldwide. Those monetary indexes are derived from a simple accounting identity. The implicit assumption made when using simple -sum monetary aggregates is that all components are perfect

In the aftermath of the European sovereign debt crisis (2009–2014), the management of expectations has risen in importance. However, policy responses have emphasized the management of fiscal spending without examining the impact changes in the business confidence have on the economy. This paper uses a Factor-Augmented Vector Autoregressive specification, which allows for a larger information set covering both domestic and international developments, to measure the responses of five Euro Area economies to a one percent shock in government consumption and business confidence. The evidence suggests that even though the response to a government consumption shock is strong, a shock in expectations has an even greater effect. This points out to the fact that perceptions about the future and trust in the policymaker are much more important than previously considered. Thus, especially in (but not limited to) times of turbulence, or during efforts of stabilization and/or structural reforms, more emphasis should be placed on the overall credibility of the decisions, which could help to mitigate any potential adverse effects from the policies.

This paper develops methods and a framework of financial market theory. We model financial markets as a system of agents which perform market transactions with other agents under the action of numerous expectations. Agents&rsquo, expectations are formed of economic and financial variables, market transactions, the expectations of other agents, and other factors that impact financial markets. We use the risk ratings of agents as their coordinates and approximate a description of financial variables, market transactions, and expectations of numerous separate agents by density functions of aggregated agents in the economic domain. The motion of separate agents in the economic domain due to a change of agents&rsquo, risk rating produces collective financial flows of variables, transactions, and expectations. We derive equations on collective financial variables, market transactions, expectations, and their flows in the economic domain. These flows define the evolution of financial markets. As an example, we present a simple model with linear dependence between disturbances of volume and the cost of transactions on one hand, and disturbances of expectations that determine transactions on the other hand. Our model describes harmonique oscillations of these disturbances with numerous frequencies and allows an explicit form for fluctuations of price and return to be derived. These relations show a direct dependence between price, return, and volume perturbations.

The Turn of the month effect is one of the better-known calendar anomalies. If a stock market is affected by the Turn of the month effect, it records significantly higher returns during a relatively short time period around the end of the old month and the beginning of the new one, than during the remainder of the month. This paper investigates the presence of the Turn of the month effect in the stock markets of 11 Central and Eastern European (CEE) countries. We focused not only on the anomaly in returns, but also on the anomaly in price volatility. The results show that, during a 20-year period (1999&ndash, 2018), a statistically significant Turn of the month effect was present in the stock markets of seven out of 11 investigated countries. However, the anomaly affected only the stock market returns, not price volatility.

In this paper, we propose a semi-Markov chain to model the salary levels of participants ina pension scheme. The aim of the models is to understand the evolution in time of the salary of activeworkers in order to implement it in the construction of the actuarial technical balance sheet. It isworth mentioning that the level of the contributions in a pension scheme is directly proportional tothe incomes of the active workers; in almost all cases, it is a percentage of the worker’s incomes. As aconsequence, an adequate modeling of the salary evolution is essential for the determination of thecontributions paid to the fund and thus for the determination of the fund’s sustainability, especiallycurrently, when all jobs and salaries are subject to changes due to digitalization, ICT, innovation, etc.The model is applied to a large dataset of a real compulsory Italian pension scheme of the first pillar.The semi-Markovian hypothesis is tested, and the advantages with respect to Markov chain modelsare assessed.

Foreign Direct Investment (FDI) can bring in much needed capital, particularly to developing countries, help improve manufacturing and trade sectors, bring in more efficient technologies, increase local production and exports, create jobs and develop local skills, and bring about improvements in infrastructure and overall be a contributor to sustainable economic growth. With all these desirable features, it becomes relevant to ascertain the factors which attract FDI to an economy or a group of adjacent economies. This paper explores the determinants of FDI in ten sub-Saharan economies: Liberia, Sierra Leone, Ivory Coast, Ghana, Nigeria, Mali, Mauritania, Niger, Cameroun, and Senegal. After an extensive literature review of theories and empirical research, using a set of cross-sectional data over the period 1990&ndash, 2017, two econometric models are estimated with FDI/GDP (the ratio of Foreign Direct Investment to Gross Domestic Product) as the dependent variable, and with inflation, exchange rate changes, openness, economy size (GDP), income levels (GNI/capita (Gross National Income) per capita), and infrastructure as the independent variables. Over the period, higher inflows of FDI in relation to GDP appear to be have been attracted to the markets with better infrastructure, smaller markets, and lower income levels, with higher openness and depreciation in the exchange rate, though the coefficients of the last two variables are not significant. These results show the type of FDI attracted to investments in this region and are evaluated from theoretical and practical viewpoints. FDI is an important source of finance for developing economies. On average, between 2013 and 2017, FDI accounted for 39 percent of external finance for developing economies. Policy guidelines are formulated for the enhancement of FDI inflows and further economic development in this region. Such a study of this region has not been made in the recent past.

This paper follows an incomplete market pricing approach to analyze the evaluation of weather derivatives and the viability of a weather derivatives market in terms of hedging. A utility indifference method is developed for the specification of indifference prices for the seller and buyer of a basket of weather derivatives written on rainfall and temperature. The agent&rsquo, s risk preference is described by an exponential utility function and the prices are derived by dynamic programming principles and corresponding Hamilton Jacobi-Bellman equations from the stochastic optimal control problems. It is found the indifference measure is equal to the physical measure as there is no correlation between the capital market and weather. The fair price of the derivative should be greater than the seller&rsquo, s indifference price and less than the buyer&rsquo, s indifference price for market viability and no arbitrage opportunities.

Stock market prediction has always caught the attention of many analysts and researchers. Popular theories suggest that stock markets are essentially a random walk and it is a fool’s game to try and predict them. Predicting stock prices is a challenging problem in itself because of the number of variables which are involved. In the short term, the market behaves like a voting machine but in the longer term, it acts like a weighing machine and hence there is scope for predicting the market movements for a longer timeframe. Application of machine learning techniques and other algorithms for stock price analysis and forecasting is an area that shows great promise. In this paper, we first provide a concise review of stock markets and taxonomy of stock market prediction methods. We then focus on some of the research achievements in stock analysis and prediction. We discuss technical, fundamental, short- and long-term approaches used for stock analysis. Finally, we present some challenges and research opportunities in this field.

In response to the global financial crisis of 2007–2009, risk-based capital requirements have been reinforced in the new Basel III Accord to counter excessive bank risk-taking behavior. However, prior theoretical as well as empirical literature that studies the impact of risk-based capital requirements on bank risk-taking behavior is inconclusive. The primary purpose of this paper is to examine the impact of risk-based capital requirements on bank risk-taking behavior, using a panel dataset of 21 listed commercial banks of Pakistan over the period 2005–2012. Purely regulatory measures of bank capital, capital adequacy ratio, and bank assets portfolio risk, risk-weighted assets to total assets ratio, are used for the main analysis. Recently developed small N panel methods (bias corrected least squares dummy variable (LSDVC) method and system GMM method with instruments collapse option) are used to control for panel fixed effects, dynamic dependent variables, and endogenous independent variables. Overall, the results suggest that commercial banks have reduced assets portfolio risk in response to stringent risk-based capital requirements. Results also confirm that all banks having risk-based capital ratios either lower or higher than the regulatory required limits, have decreased portfolio risk in response to stringent risk-based capital requirements. The results are robust to alternative proxies of bank risk-taking, alternative estimation methods, and alternative samples.

This paper uses the most recent wave of a nationally representative dataset to examine the factors associated with elderly homeowners' decision to obtain reverse mortgage loans. The findings of this study suggest that very few homeowners participated in the reverse mortgage market, and homeowners younger than 67 were less likely to have reverse mortgage loans. However, homeowners who were risk averse, and homeowners in the two highest quartiles of net worth were more likely to have reverse mortgage loans. Further analyses reveal that among the reverse mortgage participants, homeowners with long-term care insurance coverage were less likely to have reverse mortgage loans. Implications for financial economists, financial planners, policy-makers, and scholars of retirement economics are included.

In this paper, a level set analysis is proposed which aims to analyze the S&P 500 return with a certain magnitude. It is found that the process of large jumps/drops of return tend to have negative serial correlation, and volatility clustering phenomenon can be easily seen. Then, a nonparametric analysis is performed and new patterns are discovered. An ARCH model is constructed based on the patterns we discovered and it is capable of manifesting the volatility skew in option pricing. A comparison of our model with the GARCH(1,1) model is carried out. The explanation of the validity on our model through prospect theory is provided, and, as a novelty, we linked the volatility skew phenomenon to the prospect theory in behavioral finance.

This paper investigates the determinants of credit risk from a broad perspective. Particular attention is given to the role of housing affordability and household indebtedness. However, the impact of credit market developments and regulations is also closely examined. Using a large panel of countries it is found that housing affordability and household fragility significantly affect the risk of banks’ loan portfolios. In addition, an analysis of the conditional quantiles of non-performing loan ratios reveals that financial institutions in countries with greater levels of financial liberalization and less regulated markets also experience greater credit risk.

Does speculation facilitate price discovery or instability? If it is price discovery, it is beneficial and should be encouraged; if it is instability, welfare is enhanced by its reduction. This paper seeks to distinguish between these two characteristics by analysing those times when speculation in the foreign exchange market is most extreme. A series of event studies are conducted on the extremes of speculative sentiment and speculative activity. If speculation is noise, extreme sentiment and extreme positions should lead to overshooting and increase risk of subsequent reversals. The finding that speculative extremes do not provide information about subsequent returns implies that speculation is part of the process of price discovery and that efforts to reduce it would reduce the informational efficiency of financial markets.

The insurance industry plays an important role for European economic stability and the threats and opportunities it faces should be carefully determined. In this paper we highlight the main challenges by using a Political, Economic, Social and Technological (PEST) analysis. This work applies conventional actuarial thought on this area by focusing strictly on the European sector.

Capital structure decision plays an imperative role in firm’s performance. Recognizing the importance, there has been many studies inspected the rapport of capital structure with performance of firms and findings of those studies are inconclusive. In addition, there is relative deficiency of empirical studies examining the link of capital structure with performance of banks in Bangladesh. This paper attempted to fill this gap. Using panel data of 22 banks for the period of 2005-2014, this study empirically examined the impacts of capital structure on the performance of Bangladeshi banks assessed by return on equity, return on assets and earnings per share. Results from pooled ordinary least square analysis show that there are inverse impacts of capital structure on bank’s performance. Empirical findings of this study is of greater significance for the developing countries like Bangladesh because it will call upon concentration of the bank management and policy makers to pursue such policies to reduce reliance on debt and to accomplish optimal level capital structure. This research also contributes to empirical literatures by reconfirming (or otherwise) findings of previous studies.

This paper investigates the interaction between stock prices and real exchange rates by applying monthly data from Turkey for the period between January 2001 and September 2016. This study uses the autoregressive distributed lag (ARDL) model and the Error Correction Model (ECM) in order to investigate the existence of a long-run equilibrium relationship between the variables. The evidence reveals that there is a strong long-run cointegration. The robustness of the ARDL bounds test cointegration was confirmed using the newly-developed combined cointegration, which also provided the same evidence for a strong long-run relationship. The Granger causality test results indicate a long-run bidirectional causality between stock prices and real exchange rates, and also a unidirectional causality from the real exchange rates to the stock prices in the short-run. In order to analyze the validity and reliability of the test results, diagnostic tests were applied in both the short-run and long-run models.

This paper measures and analyzes the technical efficiency of Islamic banks in the Middle East and North Africa (MENA) region during the period 2007–2012. To do this, the bootstrap Data Envelopment Analysis (DEA) approach was employed in order to provide a robust estimation of the overall technical efficiency and its components: pure technical efficiency and scale efficiency in the case of MENA Islamic banks. The main results show that over the period of study, pure technical inefficiency was the main source of overall technical inefficiency instead of scale inefficiency. This finding was confirmed for all MENA Islamic banks as well as for the two subsamples: Gulf Cooperation Council (GCC) and non-GCC Islamic banks. Furthermore, our results show that GCC Islamic banks had stable efficiency scores during the global financial crisis (2007–2008) and in the early post-crisis period (2009–2010). However, a decline in overall technical efficiency of all panels of MENA Islamic banks was recorded in the last two years of the study period (2011–2012). Thus, we recommend that MENA Islamic bank managers focus more on improving their management practices rather than increasing their sizes. We also recommend that financial authorities in MENA countries implement several regulatory and financial measures in order to ensure the development of MENA Islamic banking.

This paper examines the relationship between infrastructure investment activity, capital market development, the role of public institutions and economic development in the Asia Pacific. It adopts a review approach drawing on empirical evidence over recent decades. Infrastructure is shown to be an important asset class playing a central role in a nation’s output, growth, productivity and microeconomic performance. Infrastructure investment also requires investment and predictions of a widening gap in the future supply of infrastructure in the Asia Pacific will require new forms of capital from both traditional and new sources including wider use of private participation, institutional investment, asset recycling and revenue bonds. Capital market development is also necessary to raise long-term local currency finance and evidence suggests that progress with regional capital market integration is slow and a continuing reform agenda is required. The dividend for regional countries is the prospect of higher levels of economic growth with infrastructure investment, capital market development, and foreign direct investment shown to have a strong and positive association with growth. A crucial link in this association identified in the review is the part played by national and regional institutions in improving the efficiency with which infrastructure is managed and providing promising ground for further research where the importance of these links can be researched in greater depth.