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Purpose: The purpose of this paper is to explore the dynamic interdependence structure and risk spillover effect between the Chinese stock market and the US stock market. Design/methodology/approach: This paper mainly uses the multivariate R-vine copula-complex network analysis and the multivariate R-vine copula-CoVaR model and selects stock price indices and their subsector indices as samples. Findings: The empirical results indicate that the Energy, Materials and Financials sectors have leading roles in the interdependent structure of the Chinese and US stock markets, while the Utilities and Real Estate sectors have the least important positions. The comprehensive influence of the Chinese stock market is similar to that of the US stock market but with smaller differences in the influence of different sectors of the US stock market on the overall interdependent structure system. Over time, the interdependent structure of both stock markets changed; the sector status gradually equalized; the contribution of the same sector in different countries to the interdependent structure converged; and the degree of interaction between the two stock markets was positively correlated with the degree of market volatility. Originality/value: This paper employs the methods of nonlinear cointegration and the R-vine copula function to explore the interactive relationship and risk spillover effect between the Chinese stock market and the US stock market. This paper proposes the R-vine copula-complex network analysis method to creatively construct the interdependent network structure of the two stock markets. This paper combines the generalized CoVaR method with the R-vine copula function, introduces the stock market decline and rise risk and further discusses the risk spillover effect between the two stock markets. [ABSTRACT FROM AUTHOR]

This article introduces a rational expectations model that explains exchange rate dynamics and the predictability of forecast errors using private (aggregated via order flow) and public (probabilities of a binary event) information. We test the model for the periods leading up to the presidential impeachment vote in Brazil, the Brexit Referendum, and Donald Trump's election in 2016. Proxies of the physical probabilities of these events reveal that they are a crucial source of pricing information for the BRL, GBP, and MXN currency pairs with the US dollar. They also explain forecast errors. The information content of order flow changes before and after an actual regime change resolves uncertainty. [ABSTRACT FROM AUTHOR]

Purpose: The primary objective of this research is to provide a precise interpretation of the constructed machine learning model and produce definitive summaries that can evaluate the influence of investor sentiment on the overall sales of non-fungible token (NFT) assets. To achieve this objective, the NFT hype index was constructed as well as several approaches of XAI were employed to interpret Black Box models and assess the magnitude and direction of the impact of the features used. Design/methodology/approach: The research paper involved the construction of a sentiment index termed the NFT hype index, which aims to measure the influence of market actors within the NFT industry. This index was created by analyzing written content posted by 62 high-profile individuals and opinion leaders on the social media platform Twitter. The authors collected posts from the Twitter accounts that were afterward classified by tonality with a help of natural language processing model VADER. Then the machine learning methods and XAI approaches (feature importance, permutation importance and SHAP) were applied to explain the obtained results. Findings: The built index was subjected to rigorous analysis using the gradient boosting regressor model and explainable AI techniques, which confirmed its significant explanatory power. Remarkably, the NFT hype index exhibited a higher degree of predictive accuracy compared to the well-known sentiment indices. Practical implications: The NFT hype index, constructed from Twitter textual data, functions as an innovative, sentiment-based indicator for investment decision-making in the NFT market. It offers investors unique insights into the market sentiment that can be used alongside conventional financial analysis techniques to enhance risk management, portfolio optimization and overall investment outcomes within the rapidly evolving NFT ecosystem. Thus, the index plays a crucial role in facilitating well-informed, data-driven investment decisions and ensuring a competitive edge in the digital assets market. Originality/value: The authors developed a novel index of investor interest for NFT assets (NFT hype index) based on text messages posted by market influencers and compared it to conventional sentiment indices in terms of their explanatory power. With the application of explainable AI, it was shown that sentiment indices may perform as significant predictors for NFT sales and that the NFT hype index works best among all sentiment indices considered. [ABSTRACT FROM AUTHOR]

Purpose: Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge. Design/methodology/approach: The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms. Findings: The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting. Research limitations/implications: Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further. Practical implications: Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully. Originality/value: To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms. [ABSTRACT FROM AUTHOR]

Purpose: This paper examines the relationship between sovereign credit default swaps (CDS) and several macroeconomic factors in an asymmetric setting and distinguishes between short-run and long-run impacts. Country-specific factors (e.g. equity index, international reserves, interest rate and industrial production) and global factors (e.g. US stock volatility [VIX], geopolitical risk and oil price) are the main explanatory variables. Design/methodology/approach: This analysis uses a nonlinear autoregressive distributed lag approach that enables us to study both long-run and short-run dynamics. Findings: This study results show that two country-specific factors (equity index and international reserves) and two global factors (VIX and oil price) are the most important factors and affect CDS asymmetrically. Research limitations/implications: The asymmetric relationships between sovereign CDS and variables in bull and bear markets can also be studied. Consideration of asymmetries in the variance could also be a fruitful step taken for further research. Practical implications: The findings imply that investors and portfolio managers should design their investment and hedging decisions related to government bonds by taking into account the existence of an asymmetric relationship. Social implications: Moreover, policymakers can benefit from this asymmetric information in the timing of debt issuance. Originality/value: This paper examines the relationship between sovereign CDS and several macroeconomic factors in an asymmetric setting and distinguishes between short-run and long-run impacts. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate the determinants of Islamic stock returns listed on Jakarta Islamic Index (Indonesia) between 2008 and 2018. Design/methodology/approach: This study uses a quantile bounded autoregressive distributed lag (QBARDL) model to uncover relevant relationships. Findings: This study finds that the Dow Jones Islamic Market Index, gold returns, world oil prices and exchange rates are the determinants of the Indonesia's Islamic stock returns. However, the relationship is time varying developing intra-/inter-quantile bounded. Practical implications: Integration of the Islamic stock returns with the real economic indicators changes over time. The findings have important implications for the policymakers, the fund managers and the investors to anticipate consequences when considering the macroeconomic conditions before participating in the Indonesian Islamic stock market. Originality/value: Using a QBARDL, this study finds that the Islamic stock returns have on net and "time-varying intra-/inter-quantile developing" relationship with its determinants as data quantiles progressed from 25% to 75%. [ABSTRACT FROM AUTHOR]

Purpose: Given the importance of credit rating agencies' (CRAs) assessment in affecting international financial markets, it is useful for policymakers and investors to be able to forecast it properly. Therefore, this study aims to forecast sovereign risk perception of the main agencies related to Brazilian bonds through the application of different machine learning (ML) techniques and evaluate their predictive accuracy in order to find out which one is best for this task. Design/methodology/approach: Based on monthly data from January 1996 to November 2018, we perform different forecast analyses using the K-Nearest Neighbors, the Gradient Boosted Random Trees and the Multilayer Perceptron methods. Findings: The results of this study suggest the Multilayer Perceptron technique is the most reliable one. Its predictive accuracy is relatively high if compared to the other two methods. Its forecast errors are the lowest in both the out-of-sample and in-sample forecasts' exercises. These results hold if we consider the CRAs classification structure as linear or logarithmic. Moreover, its forecast errors are not statistically associated with periods of changes in CRAs' opinion of any sort. Originality/value: To the best of the authors' knowledge, this study is the first to evaluate the performance of ML methods in the task of predicting sovereign credit news, including not only the sovereign ratings but also the outlook and credit watch status. In addition, the authors investigate whether the forecasts errors are statistically associated with periods of changes in sovereign risk perception. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to examine the impact of the COVID-19 pandemic on Association of Southeast Asian Nations (ASEAN) Islamic and conventional equities. Design/methodology/approach: To study the impact of the COVID-19 pandemic on ASEAN Islamic and conventional equities, first, the authors calculated the volatility by using exponential generalized autoregressive conditional heteroscedasticity methodology and then used Wavelet methodology to see the co-movement between the volatility and returns of ASEAN equity market indicators and COVID-19 cases. Findings: The authors find that until the beginning of August, COVID-19 adversely relates to the returns of both the indices. The conventional index seemed to have increased volatility during the time period, whereas the Islamic index seemed to have declined volatility. Originality/value: To the best of the authors' knowledge, this is one of the very few studies examining the impact of the COVID-19 pandemic on ASEAN Islamic and conventional equities. Additionally, this study adds value by comparing Islamic and conventional equities. [ABSTRACT FROM AUTHOR]

We study the economic value of market timing in foreign exchange (FX) markets, that is, using information about the conditional Sharpe ratio to adjust the notional value of a conditionally mean–variance efficient currency portfolio. Our strategy trades more (less) aggressively when the conditional risk-return trade-off is more (less) favorable. This leads to a significant improvement in the out-of-sample unconditional Sharpe ratio, skewness, and maximum drawdown per 1% expected excess return. The strategy's market timing predicts returns, volatility, and skewness in FX markets. Popular currency pricing factors do not explain the strategy's high average excess returns. Our findings suggest that it is costly to impose leverage or risk (i.e., conditional volatility) limits or other inferior market timing policies when constructing currency trading strategies. [ABSTRACT FROM AUTHOR]

In this study, I formulate a present value model of the exchange rate with a risk premium and introduce exchange rate risk exposure as a factor of the persistently time-varying risk premium. The present value model incorporates expectations for the distant future, and therefore, indicates that spot exchange rate variations reflect changes in long-run future interest rate differential and exchange rate expectations, in addition to a risk premium for long-run risk exposure. I also conduct empirical analyses using mainly the USD/JPY rate and other exchange rates against the USD. The Japanese current account balance provides a better estimation of the change in USD/JPY rate market risk exposure as USD invoiced trades are prevalent in Japan. Then, I demonstrate the possibility that a persistently time-varying risk premium offsets the effect of the interest rate differential on exchange rate variations, which can be a solution to the uncovered interest rate parity puzzle. [ABSTRACT FROM AUTHOR]

In this paper, we argue that the ECB's unconventional monetary policy announcements have generated significant spillover effects in Russia and Eastern Europe. The hypothesis is tested using OLS estimations of event-based regressions on monetary policy event dummies and seven financial variables in eleven East European countries including Russia. Overall, the empirical results associate the ECB's unconventional policy announcements with the appreciation of East European currencies, rising stock market indices as well as falling long-term government bond yields and lower sovereign CDS spreads in Eastern Europe and Russia. Bilateral integration with the eurozone is a key determinant of the strength of spillovers, with spillovers strongest in non-euro EU countries and weakest in non-EU East European countries. Furthermore, we find differentiated strength of spillovers to Russia compared to other non-EU East European countries, which we attribute to its fixed exchange rate regime. We also argue for the presence of portfolio rebalancing and confidence transmission channels. [ABSTRACT FROM AUTHOR]

We use factor-augmented predictive regressions to analyze the relation between nominal exchange rates and macroeconomic variables. Using a panel of 121 US macroeconomic time series, we estimate eight factors through principal component analysis. Those estimated factors have significant predictive power and can substantially improve the predictive power of purchasing power parity through both in-sample and out-of-sample analyses. The estimated macroeconomic factor, which co-moves with US stock market variables, has strong predictive power for nominal exchange rate fluctuations in the short run, while estimated factors, co-moving with interest rate spreads, government-issued bond yields and employment variables, have strong predictive power in the long run. Moreover, optimal factors selected by the BIC in the out-of-sample analysis differ greatly depending on the time points when forecasts are made. Finally, we show that factors extracted from a panel of 121 US time series data and those extracted from a panel of 215 Korean macroeconomic series together can predict a substantial portion of movements in the Korea–US bilateral exchange rate. [ABSTRACT FROM AUTHOR]

The recent financial crisis has made (il)liquidity research more significant than ever. Galariotis and Giouvris (Int Rev Financ Anal 38:44–69, 2015) find evidence that market liquidity may contain information for predicting the state of the economy. Similar to (il)liquidity, oil is an important indicator of the future state of the economy (GDP). We consider five predictive variables, namely national/global illiquidity, foreign exchange, Baltic Dry, and oil. Our findings show that (1) global illiquidity provides greater overall explanatory power compared to national illiquidity (even for developed oil exporters: Norway, Canada, and Denmark). (2) Oil is the most important predictive variable for oil exporters (especially for emerging oil exporters suggesting over-reliance), while Baltic Dry appears to be more important for oil importers. (3) FX has extra power over financial variables mainly for emerging oil exporters. Finally, there is a two-way causality between GDP and our predictive variables: (4) For oil exporters, the two-way causality between oil and GDP remains, while for net oil importers, we observe a one-way causality from GDP to oil. [ABSTRACT FROM AUTHOR]

This paper investigates empirically whether time-series momentum returns can explain the performance of hedge funds in the cross section. Relying on the trend-following literature, a volatility-adjusted time-series momentum signal is applied on a daily basis across a large set of futures, covering the major asset classes. We build a hierarchical set of trend factors: the full version TREND can be split in summable factors across two dimensions: the horizon of the signals and the traded asset class. We show that Managed Futures, Global Macro and Fund of Hedge Funds strategies can be partly explained by a TREND exposure. Moreover, a TREND exposure is a significant determinant of hedge funds returns at the fund level, for Managed Futures and Global Macro but also, and more surprisingly, for the other styles. [ABSTRACT FROM AUTHOR]

This paper analyses the evolution of the banking system sensitivity to cross-border contagion in 2006-2011. The study is performed on the basis of the BIS data on cross-border exposures and the Bankscope data on Tier 1 capital of 20 banking systems (Australia, Austria, Belgium, Canada, Finland, France, Germany, Greece, India, Ireland, Italy, Japan, the Netherlands, Portugal, Spain, Sweden, Switzerland, Turkey, the UK, and the USA). Since the European sovereign debt crisis took a decisive turn at the end of 2009, markets started looking at its main protagonists—Greece, Ireland, Italy, Portugal, and Spain (GIIPS)—with a lot of anxiety. However, unexpectedly, we find that a single failure among GIIPS could be absorbed by the network. Our results reveal that the USA, the UK, France, and Germany pose the highest threat to the systemic stability. Moreover, the resilience of the banking systems to contagion risks tends to improve over the years. [ABSTRACT FROM AUTHOR]

Using linear and nonlinear correlations, copulas, quantile dependence and lower tail dependence, we find that (1) equity markets of the advanced European Union (EU) countries comove more closely with each other than with the peripheral economies, (2) comovements with non‐EU countries are lower, (3) relative comovement structure before, during, and after the global financial crisis has been very stable, and (4) the level of comovements remained virtually the same between the crisis and post‐crisis periods. Our results are robust to controlling for Fama‐French, U.S. and global risk factors, as well as monetary policy, market interest rates, exchange rates, and uncertainty. [ABSTRACT FROM AUTHOR]

We characterize the equilibrium of a complete markets economy with multiple agents featuring a preference for the timing of the resolution of uncertainty. Utilities are defined over an aggregate of two goods. We provide conditions under which the solution of the planner's problem exists, and it features a nondegenerate invariant distribution of Pareto weights. We also show that perturbation methods replicate the salient features of our recursive risk‐sharing scheme, provided that higher‐order terms are included. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to examine the impact of real exchange rate misalignment on economy and economic sectors, namely construction, manufacturing and mining and quarrying in Malaysia.Design/methodology/approach The equilibrium real exchange rate and economic models are estimated using the autoregressive distributed lag approach.Findings An increase in productivity differential or reserve differential will lead to an appreciation of real exchange rate in the long run. An increase in positive (negative) real exchange rate misalignment will lead to an increase (decrease) in economy. An increase in long-run real exchange rate misalignment will lead to a decrease in economy. Real exchange rate misalignment or long-run real exchange rate misalignment can influence the manufacturing sector in Malaysia. More specifically, undervaluation will promote whereas overvaluation will hurt the manufacturing sector.Originality/value Real exchange rate misalignment can be a policy to influence economy but may not be the best choice. [ABSTRACT FROM AUTHOR]

This paper employs a VAR-BEKK GARCH model to examine the shock transmission and volatility spillover (STVS) effects among daily stock market indices of the US, UK, France, Germany, Japan, Turkey, China, South Korea, South Africa and India, together with the five major commodity spot price—crude oil, natural gas, platinum, silver and gold—over the period 05 July, 2005 and 14 October, 2016, i.e., covering the pre-crisis, crisis and post global financial crisis periods. In the full period, the primary trend in advanced and emerging countries is the bidirectional STVS effects between stock and the commodity returns. However, the results also illustrate relatively less unilateral STVS effects from the commodity to stock returns, but significant unilateral STVS effects from the stock returns to the commodity returns in advanced and emerging countries. We also find more cases of significant STVS effects between commodity and stock markets in all countries during the crisis and post-crisis periods compared to the pre-crisis period. Therefore, it indicates that STVS effects are the new normal for stock and commodity markets, despite the efforts of central banks during post-global crisis period. In practical terms, our findings suggest that resource allocation decision between stocks and commodities should involve the analysis of the direction of the STVS effects in particular stock/commodity markets and cycles of the global economy. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented on topics including international financial architecture; U.S. President Trump's trade policies; and China's infrastructure development finance.

It is often said that the 21st century will be the Asian century. Based on population and gross domestic product projections, it certainly looks as if this will be so. Will the existing international financial institutions give more voices, votes, and top positions to Asia? Or will Asia create its own institutions that would rival the old architecture? This present paper argues, first, that China, and possibly India, will be in a position to be so influential that the international financial architecture may have to go through significant changes. Second, the three large crises in the last 20 years have made Asian countries more confident that they can manage capital flows by accumulating large foreign reserves and by adopting sound macrofinancial policies. After 2009, China started to push various initiatives that will amount to creating its own sphere of influence with new regional institutions in the future. [ABSTRACT FROM AUTHOR]

The aim of this article is to analyse the inflation persistence phenomenon in the theory of economics and in Croatian economy. In the economic literature there are only few studies on the phenomenon of inflation persistence in Croatia. That is why we try to fill the gap in this area by analysing the phenomenon of inflation persistence in the Croatian economy, with particular emphasis of this phenomenon for different groups of goods and services. In this article we use a research method based on literature studies in the field of macroeconomics and international finance and econometric methods (Bayesian Vector Autoregression Model [BVAR]). All statistical data used in this article were monthly data and covered the period from January 2005 to December 2013 (108 months) and their source was United Nations Economic Commission for Europe (UNECE) Statistical Division Database. It provides detailed statistical information on countries in Europe, North America and Central Asia. The calculated inflation persistence coefficient in Croatia stood at 0.88 in the period 2005–2013, which apparently confirmed the occurrence of high inflation persistence in this economy. High inflation persistence means a slow return of inflation to its long-run value after a shock. A high degree of inflation persistence should be a signal for the economic authorities of a country to initiate indispensable institutional and labour market reforms which usually increase flexibility of domestic economy and lead to a reduced degree of inflation persistence. [ABSTRACT FROM PUBLISHER]

This study tries to fill a vacuum in the literature on the relevance of economic fundamentals for the Euro / USD exchange rate determination. We adopt the Monetary Model for the Exchange Rate Determination as our testing vehicle and investigate the relevance of various versions of this model over a long time horizon, spanning the period from the inception of Euro till the present time. We rely on cointegration analysis to conduct our empirical research and in accordance to the relevant literature we fail to accept most of the variants of this model. However, we get encouraging results from an expanded version of the Monetary Model where demand and productivity factors appear in the set of the exchange rate determinants. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to investigate the relationship between capital flow surges, reversals and sudden stops.Design/methodology/approach Emphasizing the importance of looking at the behavior of domestic as well as foreign capital flows, the authors distinguish sudden stops from capital flow reversals by attributing the former to foreign capital flows only.Findings It is found that, despite the large differences in the number of surges identified by several different measures in the literature, a majority of surges do end in reversals of some type. The percentages tend to be slightly over half for surges in net capital flows, but on average, 70 per cent of gross surges end in sudden stops. Furthermore, contrary to popular belief, approximately half of sudden stops and net capital flow reversals are not preceded by surges. It is also found that surges that persist longer are more likely to turn into sudden stops and reversals.Research limitations/implications The authors find substantial empirical differences in the characteristics of sudden stops (based on gross foreign flows) and reversals (based on net flows).Practical implications Large inflows of financial capital are not always a strong indicator that a country’s economic policies will continue to provide stability in the future. They may signal an increase rather than reduction in the risk of future instability.Originality/value This study focuses on an issue that has been less explored to date, the relationship between capital flow surges, reversals and sudden stops. The authors distinguish, redefine and document differences among capital flow reversals and sudden stops. Duration of surges is related to the likelihood of having reversals and sudden stops. [ABSTRACT FROM AUTHOR]

This paper analyses volatility, persistence, predictability, correlation, comovement (or contagion risk) and sudden stop (reversibility) of capital flows (foreign direct investment (FDI), foreign portfolio equity investment, long-term and short-term debt flows) using time series econometric techniques for 24 emerging economies over 1970–2014. This is informative on the pattern and relationship between capital inflows, with implications for accommodating macroeconomic policies in countries receiving inflows. The paper also addresses the predictions of conventional theory, that differences are associated with the maturity of the capital (long-term vs. short-term), with the information-based trade-off model of Goldstein and Razin [(2006). An information-based trade off between foreign direct investment and foreign portfolio investment. Journal of International Economics, 70(1), 271–295], that differences are associated with the structure of the capital (equity vs. debt). In line with the latter, equity flows (FDI and portfolio) are less volatile and persistent, more predictable and less susceptible to sudden stops than debt flows. Contrary to conventional theory, short-term flows are not more volatile, but there is evidence that correlations and risks of contagion are strong within all capital flow components. [ABSTRACT FROM AUTHOR]

Recent literature has shown that the volatility of exchange rate returns displays long memory features. It has also been shown that if a short memory process is contaminated by level shifts, the estimate of the long memory parameter tends to be upward biased. In this article, we directly estimate a random level shift model to the logarithm of the absolute returns of five exchange rates series, in order to assess whether random level shifts (RLSs) can explain this long memory property. Our results show that there are few level shifts for the five series, but once they are taken into account the long memory property of the series disappears. We also provide out-of-sample forecasting comparisons, which show that, in most cases, the RLS model outperforms popular models in forecasting volatility. We further support our results using a variety of robustness checks. [ABSTRACT FROM AUTHOR]

This study aims to analyze the impact of the development and stability of the financial sector on economic growth on the basis of the quantitative methods that produce robust results. The following research hypotheses are tested: /H1/ The relationship between financial sector development (stability) and economic growth is nonlinear; /H2/ An excessively large size of the financial system does not lead to more rapid economic growth: it may even negatively affect GDP dynamics; /H3/ The inclusion of the post-crisis period gives new insights of the nature of the relationship between financial system and economic growth. The analysis covers the 28 EU and 34 OECD economies and the 1993-2013 period. The following variables are used to measure the financial sector: domestic credit provided by financial sector, bank nonperforming loans, bank capital to assets ratio, market capitalization of listed companies, turnover ratio of stocks traded, and the monetization ratio. A new element of the empirical analysis is the application of the extended econometric and economic modelling, including testing nonlinear relationships, analyzing both levels and changes of the financial variables, as well as estimating the models on the basis of a moving panel with overlapping observations. The regression equations are estimated by Blundell and Bond's GMM system estimator. Our results indicate that all the research hypotheses have been positively verified. [ABSTRACT FROM AUTHOR]

Purpose This study aims to analyse the conditional volatility of the Vietnam Index (Ho Chi Minh City) and the Hanoi Exchange Index (Hanoi) with a specific focus on their application to risk management tools such as Expected Shortfall (ES).Design/methodology/approach First, the author tests both indices for long memory in their returns and squared returns. Second, the author applies several generalised autoregressive conditional heteroskedasticity (GARCH) models to account for asymmetry and long memory effects in conditional volatility. Finally, the author back tests the GARCH models’ forecasts for Value-at-Risk (VaR) and ES.Findings The author does not find long memory in returns, but does find long memory in the squared returns. The results suggest differences in both indices for the asymmetric impact of negative and positive news on volatility and the persistence of shocks (long memory). Long memory models perform best when estimating risk measures for both series.Practical implications Short-time horizons to estimate the variance should be avoided. A combination of long memory GARCH models with skewed Student’s t-distribution is recommended to forecast VaR and ES.Originality/value Up to now, no analysis has examined asymmetry and long memory effects jointly. Moreover, studies on Vietnamese stock market volatility do not take ES into consideration. This study attempts to overcome this gap. The author contributes by offering more insight into the Vietnamese stock market properties and shows the necessity of considering ES in risk management. The findings of this study are important to domestic and foreign practitioners, particularly for risk management, as well as banks and researchers investigating international markets. [ABSTRACT FROM AUTHOR]

Accurately measuring and forecasting value-at-risk (VaR) remains a challenging task at the heart of financial economic theory. Recently, quantile regression models have been used successfully to capture the conditional quantiles of returns and to forecast VaR accurately. In this paper, we further explore nonlinearities in data and propose to couple realized measures with the nonlinear quantile regression framework to explain and forecast the conditional quantiles of financial returns. The nonlinear quantile regression models are implied by the copula specifications and allow us to capture possible nonlinearities, tail dependence, and asymmetries in the conditional quantiles of financial returns. Using high frequency data that covers most liquid US stocks in seven sectors, we provide ample evidence of asymmetric conditional dependence with different levels of dependence, which are characteristic for each industry. The backtesting results of estimated VaR favour our approach. [ABSTRACT FROM AUTHOR]

The paper examines conditional risk relationships among sovereign CDS prices and stock market indices for 11 economies with particular relevance for international portfolio investment holdings (Canada, China, Brazil, France, Germany, Italy, Japan, Russia, Spain, the USA, and the UK). The analysis is based on delta conditional value at risk (ΔCoVaR). The UK, France, and Italy significantly contribute to the overall systemic risk in both markets. The USA, the UK, and Russia appear to be important contributors to it in the stock market. In the meantime, the advanced economies exhibit much higher resilience to the systemic risk propagation in comparison with China, Brazil and Russia. Gross government debt to GDP, state fragility index, EU membership and world gross GDP share of a country in distress are key determinants of ΔCoVaRs for the sovereign CDS prices. Stock market total value traded to GDP and world gross GDP share of a country in distress drive ΔCoVaRs in the stock market. In both cases geographic distance tends to deter systemic risk propagation. Inflation, trade and financial openness as well as common language and time zone differences are less important predictors of bilateral ΔCoVaR exposures. [ABSTRACT FROM AUTHOR]

The choices of policy targets and the formation of agents’ expectation have been critical issues for reconsidering monetary policy management since 2008. The purpose of this article is to evaluate macroeconomic stability in a New Keynesian open economy in which agents experience cognitive limitations. The (im)perfect credibility of various monetary policies (e.g., a Taylor-type rule, strict domestic inflation targeting, strict CPI inflation targeting, exchange rate peg) may lead agents to react according to their expectation rules, and then create various degrees of booms and busts in output and inflation. Therefore, relaxation of the rational expectation hypothesis has potential consequences for policy designs. Our simulations confirm that the business cycles induced by animal spirits are enhanced by strict inflation targeting. Furthermore, a Taylor-type (CPI or domestic inflation) rule or a credible exchange rate pegging system can improve social welfare and stability in an open economy. [ABSTRACT FROM PUBLISHER]

This article predicts the daily movement of monthly foreign exchange (FX) rate volatility using a linear combination of a time-series model and implied volatilities from options. The focus is on analysing the FX volatilities in three developing economies (the Brazilian real (BRL), the Indian rupee (INR) and the Russian ruble (RUB)) against the US dollar (USD). The empirical exercise utilizes two time-series models, mixed data sampling (MIDAS) and GARCH. The analysis indicates that for both developed and developing economies the predictive power of MIDAS and that of GARCH is comparable. Further on in this article, we will ascertain whether the relationship between realized and implied volatility is fundamentally different in the case of developing economies from that among developed economies. Thus, we compare the pairs USD/BRL, USD/INR and USD/RUB against EURO/USD and USD/Japanese yen to determine the information content and predictive power of implied volatilities. Plots of the MIDAS coefficients show that the volatility is more persistent in developing economies than in developed economies. [ABSTRACT FROM AUTHOR]

This study takes a novel approach to testing the monetary model of exchange rate determination by allowing for distortions from the underground economy to be reflected via inclusion of the parallel exchange rate. Using a VECM methodology, an augmented model is tested and compared to a traditional flexible-price monetary model for Turkey over 1987–1998. While in-sample results are supportive of both models, out-of-sample analysis favors inclusion of the parallel exchange rate. Furthermore, the augmented model beats a random walk with and without drift over to mid-range forecast horizons. These results highlight the need to consider potential market distortions of exchange rate movements. [ABSTRACT FROM AUTHOR]

I develop a two-country New Keynesian model with capital accumulation and incomplete international asset markets that provides novel insights on the effect that imperfect international risk-sharing has on international business cycles and RER dynamics. I find that business cycles appear similar whether international asset markets are complete or not when driven by a combination of non-persistent monetary shocks and persistent productivity (TFP) shocks. In turn, international asset market incompleteness has sizeable effects if (persistent) investment-specific technology (IST) shocks are a main driver of business cycles. I also show that the model with incomplete international asset markets can approximate the RER volatility and persistence observed in the data, for instance, if IST shocks are near-unit-root. Hence, I conclude that the nature of shocks, the extent of financial integration across countries and the existing limitations on asset trading are central to understand the dynamics of the real exchange rate and the endogenous international transmission over the business cycles. [ABSTRACT FROM AUTHOR]

One of the stylized facts about the behaviour of time series is that their volatility exhibits asymmetrical responses to good and bad news. In the case of stock markets, volatility seems to rise when the stock price decreases and fall when the stock price increases. This so-called 'leverage effect' was first described by Black (Proceedings of the 1976 meeting of the business and economic statistics section, pp 177-181, 1976). The concept is not new and has already been comprehensively studied and implemented in many volatility models (GARCH and SV) in the form of an additional parameter in the volatility equation. However, there is no study or a theoretical explanation of the leverage effect in sovereign credit default swap spreads (hereinafter: sCDS). In this article, we discuss the possible behaviour of sCDS volatility and explain it by way of reference to the Prospect Theory by Kahneman and Tversky (Econometrica 47(2):263-292, 1979). We estimate a series of stochastic volatility models with the leverage effect, proposed by Yu (J Econom 127(2):165-178, 2005). In this model, the 'leverage effect' is, in fact, the same as a coefficient of the correlation between the current return of an asset and its expected future volatility. We show that the effect does exist and differs across markets. As far as the safe European markets are concerned, the parameter is negative; in the case of extremely risky economies-it is positive. In markets of medium risk the effect varies depending on the relationship between the perceived risk and the value of the sCDS premium. [ABSTRACT FROM AUTHOR]

To explore possible sources of the well-documented uncovered interest parity (UIP) violation in the foreign exchange market, this paper scrutinizes structural changes in monetary reactions to inflationary pressure in the conventional approaches to nominal exchange rate and examines how this small but important change has an effect on the empirical implications of the UIP condition. In addition to some salient features found in the euro exchange rate, by introducing occasional monetary policy regime shifts into an otherwise standard open-economy dynamic general equilibrium model, we found some important findings that potentially help better understand exchange rate dynamics. During the entire sample period, 1999:M1–2014:M8, exchange rate disconnect puzzle still exists. However, sub-sample analysis suggests that relatively passive monetary reaction implying less frequent intervention by monetary authority tends to be more consistent with the UIP relation. Simulation results support the empirical regularities. [ABSTRACT FROM PUBLISHER]

This study surveys the literature on saving–investment (SI) correlations and international mobility of capital (IMC) generated over more than three decades since the 1980s. Several studies have shown the presence of paradoxically high SI correlations for the developed countries with observed high IMC, and low SI correlations for the developing countries with observed low IMC. The studies accounting for structural breaks in model parameters provide dominant support for the decrease in SI correlations and increase in IMC after the switch from fixed to flexible exchange rate regime and the removal of policy restrictions on capital flows. The intertemporal optimisation approach to current account and the open-economy growth and dynamic stochastic general equilibrium models mainly provide theoretical predictions and suggest that it is possible to find high SI correlations in the wake of high IMC. The increases in international capital flows have been the natural corollary of the growth of international trade in goods and services and increases in foreign direct investment flows. It is these factors, rather than international trade in capital market securities (bonds and equities) driven by the diversification benefits of financial portfolios per se, that have been the key levers of international financial flows. [ABSTRACT FROM AUTHOR]

In order to analyze the definition effect on prediction powers of Early Warning Systems (EWS), we construct an EWS model with 20 different crisis definitions. Furthermore, to analyze the probability threshold effect, we identify 11 different threshold levels and forecast the different versions of our model for each of those threshold levels. Our results show that crisis definitions and threshold choices significantly affect the prediction powers of the EWS models. To put it more explicitly, Exchange Market Pressure (EMP) Index based definition is shown to be a better predictor compared to depreciation based definition. Furthermore, EMP Index is found to give better results with higher standard deviation multiplier. Last but not least, it is empirically proven that 50 % threshold is the optimal level for EWS analyses as until that level the prediction powers of the models significantly increase but keep constant above it. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to investigate whether the factors that summarise the information in the yield curves of Australia and the USA can predict changes in the Australian–USA exchange rate (i.e. the AUD/USD rate) and Australian dollar excess returns.Design/methodology/approach The paper extracts the three Nelson–Siegel factors (level, slope and curvature) from the relative yield curve of Australia with the USA to predict changes in the bilateral exchange rate and excess returns on the Australian dollar. The full sample regressions allow for a shift in the coefficient on the relative curvature factor which can account for the impact of the Fed’s changed monetary policy to one of quantitative easing.Findings The paper finds that the relative curvature factor strongly predicts changes in the AUD/USD exchange rate and Australian dollar excess returns out to 12 months ahead in the sample that precedes the Fed’s policy of quantitative easing. The relative curvature factor retains its predictive power in the full sample regressions but anticipates smaller exchange rate changes and excess currency returns in in-sample predictions made from August 2007.Practical implications The yield curves of Australia and the USA reliably reflect investor’s expectations about prospective monetary policies in each economy.Originality/value The paper investigates the predictive content of the relative Nelson–Siegel factors for changes in the AUD/USD exchange rate and for Australian dollar excess returns over various forecast horizons for a period that covers the Fed’s policy of quantitative easing. [ABSTRACT FROM AUTHOR]

This paper brings four new insights into the Purchasing Power Parity (PPP) debate. First, we show that a half-life PPP (HL) model is able to forecast real exchange rates better than the random walk (RW) model at both short and long-term horizons. Second, we find that this result holds if the speed of adjustment to the sample mean is calibrated at reasonable values rather than estimated. Third, we find that it is preferable to calibrate, rather than to elicit as a prior, the parameter determining the speed of adjustment to PPP. Fourth, for most currencies in our sample, the HL model outperforms the RW also in terms of nominal exchange rate forecasting. [ABSTRACT FROM AUTHOR]

This paper studies the predictive power of external imbalances for exchange rate returns. We focus on Switzerland, a very open economy where exchange rate movements have a strong effect on external imbalances through valuation effects and trade flows. Using a simple modification of the Gourinchas and Rey (J Polit Econ 115(4):665-703, ) approach to make their approximation applicable to Switzerland, we find that measures of deviations from trends in Swiss net foreign assets and net exports help to forecast Swiss franc nominal effective exchange rate movements, both in and out of sample. [ABSTRACT FROM AUTHOR]

The Dutch disease is a concern when a country is blessed with positive terms of trade (ToT) shocks. This article assesses the effects of a structural balance fiscal rule – which saves part of the revenues from better ToT – in limiting the real exchange rate (RER) appreciation. We find that the elasticity of the RER to ToT has declined (or is zero) in Chile and Norway, during the years in which the fiscal rule has been in place, although only for the part of ToT that accrue to government revenues. [ABSTRACT FROM PUBLISHER]

Three models (the flexible-price monetary model, PPP and a univariate ARIMA model) are estimated for 45 currency pairs to find out if the profitability of forecasting-based currency trading is more related to the ability of the underlying model to predict the direction of change than the magnitude of the forecasting error. Theoretical considerations show that a correct prediction of the direction of change is neither a necessary nor a sufficient condition for a profitable trade. The results of the exercise indicate that profitability is more strongly correlated with directional accuracy than with the magnitude of the error. [ABSTRACT FROM AUTHOR]

This paper focuses on trade elasticities by analysing the case of China, France, Germany, Italy, Japan, UK, and the USA over the period 1990-2012. While the empirical setting mainly refers to panel data techniques for non-stationary data, the VECM model complements the analysis at single-country level. After having shown that long-run relationships are stable to any structural break, it is found that exports and imports are price inelastic for most of the countries in the sample. Furthermore, exports and imports are determined by domestic and foreign income, with asymmetric income elasticities. This helps to explain why global trade imbalances are persistent. [ABSTRACT FROM AUTHOR]

This study examines the asymmetry of the loss function for private forecasters in exchange rate forecasts of the South African rand. It tests rationality under the possibility of an asymmetric loss function. The results indicate less evidence of asymmetry for a horizon of 1 month but considerable evidence of asymmetry for a horizon of 3 months. However, the shapes of the distributions formed by estimated asymmetry parameters of sub-samples for each forecaster are symmetric, regardless of the forecast horizons, which implies that these forecasters do not herd or antiherd. In fact, the results of our empirical herding test show that forecasters neither herd nor antiherd, which is in sharp contrast to recent findings on antiherding for foreign exchange rates in emerging market economies. Our findings provide consistent evidence for a recent suggestion that antiherding might result in the rejection of rationality, even under asymmetric loss functions. Our findings also suggest that central bank transparency might be associated with herding behaviours. [ABSTRACT FROM PUBLISHER]

This study investigates the directional accuracy of Chinese renminbi exchange rate forecasts by professional forecasters. The forecast with a horizon of one year is useful, whereas the forecasts with forecast horizons of one and three months are not useful in predicting the direction of the exchange rate change. The results for the long-term forecasts suggest that forecasters believe that the government maintains its foreign exchange rate policy of renminbi appreciation. In contrast, short-term forecasts show consistent evidence of exchange rate unpredictability. [ABSTRACT FROM AUTHOR]

This paper provides new evidence on export price elasticities by analyzing the cases of China, France, Germany, Italy, Japan, UK and the USA over the period 1990–2012. Estimates have been made using panel data techniques for non‐stationary data. After demonstrating that long‐run relationships are stable to any structural break, it is found that exports are significantly determined by foreign demand, with long‐run income elasticity significantly higher than unity for China, Japan, Germany, the UK and the USA. Conversely, exports are price inelastic for most of the countries in the sample, in both the long run and the short run. The exception is France, whose export price elasticity is lower (higher) than unity in the short run (long run). [ABSTRACT FROM AUTHOR]

Motivated by recurrent neural networks, this paper proposes a recurrent support vector regression (SVR) procedure to forecast nonlinear ARMA model based simulated data and real data of financial returns. The forecasting ability of the recurrent SVR based ARMA model is compared with five competing models (random walk, threshold ARMA model, MLE based ARMA model, recurrent artificial neural network based ARMA model and feed-forward SVR based ARMA model) by using two forecasting accuracy evaluation metrics (NSME and sign) and robust Diebold-Mariano test. The results reveal that for one-step-ahead forecasting, the recurrent SVR model is consistently better than the benchmark models in forecasting both the magnitude and turning points, and statistically improves the forecasting performance as opposed to the usual feed-forward SVR. [ABSTRACT FROM AUTHOR]

This study compares returns from the traditional buy and hold (B&H) strategy to well-known technical oscillators applied to diverse indices leading the global market (DJI, FTSE, NK225 and TA100) during the period 2007–2012. Our aim was to establish whether technical tools can consistently achieve returns exceeding those of the B&H strategy across various financial markets. We found the relative strength index (RSI) to be the best oscillator, outperforming the DJIA, the FTSE100 and the NK225 for five of the six years examined. The only index that did better than the RSI was TA100, which outperformed all the examined oscillators. In second place was the moving average convergence/divergence (MACD) oscillator, which outperformed the NK225 B&H strategy and came in second for TA100. The results show that during bear markets the RSI and MACD generally produce better gains than the indices, while the opposite occurs during bull markets. [ABSTRACT FROM PUBLISHER]

Most international financial market studies that compare across countries utilize the US dollar as the common numeraire. We explore the little studied question of the appropriate choice for the base currency and ask if currency choice can affect the final conclusion of whether predictability exists. We provide empirical results for stock return predictability that demonstrate the importance of the numeraire. For example, the existence (absence) of predictability for a US investor does not necessarily imply the existence (absence) of predictability for other foreign investors. [ABSTRACT FROM PUBLISHER]