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The US–China conflicts surrounding the imposition of tariffs have caused a stir in the global markets. Various attempts have been made to understand the rationale and causes as well as its impact on the various ­aspects of the international market. There are many unanswered questions pertaining to China’s emergence as a global superpower and the ­possible threats that it poses to the Western dominated market. Based on this background, the chapter is an attempt to investigate the impacts of the Economic Policy Uncertainty (EPU) of the United States and China on three most important global markets, namely, crude oil, credit market, and commodity ­market. To attain the objectives of the chapter, the study has utilized Vector Auto Regressive model and has analyzed the results. The study concludes that China’s EPU has lesser impact on the global market as compared to the US EPU. On the basis of the results obtained, few policy implications have been proposed.

This study aims to find out the dynamic and causal long-run and the short-run relationship between energy consumption (electricity usage) and energy production (electricity creation) and also find out the relationship of these two variables based on past values for the SAARC nations (Pakistan, India, Bangladesh, Sri Lanka and Nepal).

Vector auto-regressive (VAR), auto-regressive distributive Lag (ARDL) and Granger causality test have been used in this study to estimate the dynamic and causal relationship between variables.

The unit-root tests were found insignificant at a magnitude but significant at the initial difference. VAR test results were found insignificant, which means co-integration among variables exists, which was tested by ARDL approach. Results suggested that energy consumption has a short-run relationship with energy production, but it was found insignificant in the other way round. The results of this study also suggest that both variables cause each other in the long run.

This study was conducted in a limited environment as we do not have access to energy policies of SAARC countries, and also data access was limited; only five countries’ data was available. This study can help government bodies and policymakers to exchange the electricity across borders to diminish the electricity shortage in the SAARC region, as countries with abandoned resources can produce electricity at a little cost.

Penal data for this study was collected from World Development Indicators from the year 1971 to 2015.

The existing literature on the Black-Litterman (BL) model does not offer adequate guidance on how to generate investors’ views in an objective manner. Therefore, the purpose of this paper is to establish a generalized multivariate Vector Error Correction Model (VECM)/Vector Auto-Regressive (VAR)-Dynamic Conditional Correlation (DCC)/Asymmetric DCC (ADCC) framework, and applies it to generate objective views to improve the practicality of the BL model.

This paper establishes a generalized VECM/VAR-DCC/ADCC framework that can be utilized to model multivariate financial time series in general, and produce objective views as inputs to the BL model in particular. To test the VECM/VAR-DCC/ADCC preconditioned BL model’s practical utility, it is applied to a six-asset China portfolio (including one risk-free asset).

With dynamically optimized view confidence parameters, the VECM/VAR-DCC/ADCC preconditioned BL model offers clear advantage over the standard mean-variance method, and provides an automated portfolio optimization alternative to the classic BL approach.

The VECM/VAR-DCC/ADCC framework and its application in the BL model proposed by this paper provide an alternative approach to the classic BL method. Since all the view parameters, including estimated mean return vectors, conditional covariance matrices and pick matrices, are generated in the VECM/VAR and DCC/ADCC preconditioning stage, the model improves the objectiveness of the inputs to the BL stage. In conclusion, the proposed model offers a practical choice for automated portfolio balancing and optimization in a China context.

The purpose of this paper is to assess whether oil price shocks emanating from oil price increase and decrease have a different impact on the macroeconomic activity.

This study conducts the empirical analysis using structural vector auto-regressive model on Indian data for the period from 1996 to 2017. This paper uses four key macroeconomic variables, namely, real gross domestic product (GDP), the real rate of interest, real money supply, wholesale price index inflation and various linear and non-linear measures of oil price shock.

Empirical results confirm that oil price shock has a significant impact on various macroeconomic variables used in the study. Specifically, shocks emanating from a decline in oil price have a stronger positive impact on real GDP, whereas, a shock due to the rise in oil price has a weaker negative impact on real GDP. Impulse responses confirm that shocks due to a decline in oil prices are long-lasting compared to similar shocks due to a rise in oil prices. Therefore, this study concludes that the macroeconomic impact of oil price shock is asymmetric in India.

This paper adds the following new insights: First, this paper presents a distinct relationship between the growth rate of oil price and GDP during increasing and decreasing phases of oil price to drive home the case for this study. Second, India has adopted crucial administrative initiatives such as deregulation of the market for petroleum products and the promotion of renewable energy during the study period. Finally, previous studies have revealed specific behavioral and economic features of people in India with respect to the demand for petroleum products. In light of these factors, this paper based on Indian experience would be justified.

Expectations of future market conditions are acknowledged to be crucial for the development decision and hence for shaping the built environment. The purpose of this paper is to study the central London office market from 1987 to 2009 and test for evidence of rational, adaptive and naive expectations.

Two parallel approaches are applied to test for either rational or adaptive/naive expectations: vector auto‐regressive (VAR) approach with Granger causality tests and recursive OLS regression with one‐step forecasts.

Applying VAR models and a recursive OLS regression with one‐step forecasts, the authors do not find evidence of adaptive and naïve expectations of developers. Although the magnitude of the errors and the length of time lags between market signal and construction starts vary over time and development cycles, the results confirm that developer decisions are explained, to a large extent, by contemporaneous and historic conditions in both the City and the West End, but this is more likely to stem from the lengthy design, financing and planning permission processes rather than adaptive or naive expectations.

More generally, the results of this study suggest that real estate cycles are largely generated endogenously rather than being the result of large demand shocks and/or irrational behaviour.

Developers may be able to generate excess profits by exploiting market inefficiencies but this may be hindered in practice by the long periods necessary for planning and construction of the asset.

This paper focuses the scholarly debate of real estate cycles on the role of expectations. It is also one of very few spatially disaggregate studies of the subject matter.

This paper aims to uncover the nexus between budget deficits, money growth and inflation in Vietnam in the period 1995–2012.

The paper uses a structural vector auto-regressive model of five endogenous variables including inflation, real GDP growth, budget deficit growth, money growth and the interest rate.

It is found that inflation rose in response to positive shocks to money growth and that budget deficits had no significant impact on money growth and therefore inflation. This empirical evidence supports the hypothesis that fiscal and monetary policies were relatively independent. Money growth significantly decreased in response to a positive shock to inflation; interest rates had no significant effect on inflation but considerably increased in response to positive inflation shocks. This implies that the monetary base was more effective than interest rates in fighting inflation.

This paper sheds light into understanding the link between budget deficits, money growth and inflation in Vietnam during the high-inflation period 1995–2012. The finding supports the hypothesis that fiscal and monetary policies were relatively independent over the period.

Proposes to re‐examine empirically the causal relationship between defence spending and economic growth in mainland China. First, using a VAR modelling technique with suitable diagnostics, e.g. Akaike’s FPE statistics and a likelihood ratio test for over‐ and under‐fitting the causal model, the results indicate a positive unidirectional causality flowing from defence spending to economic growth. Second, by evaluating a dynamic vector error‐correction model, variance decomposition and impulse response functions, then analyses the direction, duration and strength of Granger‐causality between defence spending and economic growth. The results broadly indicate that defence spending and economic growth did share a common trend over the sample period under analysis, but it was the former which stimulated the latter. Moreover, it is defence spending that has a much more perceptible and prolonged effect on economic growth, giving rise to implications that although expenditure on defence may have been politically motivated, over the long‐run this spending did play a significant indirect role in enhancing the growth potential of this, for many years, closed‐door economy.

The purpose of this paper is to capture the pattern of return volatility and information spillover and the extent of conditional correlation among the stock markets of leading South American economies. It also examines the connectedness of market returns within the region.

The time series properties of weekly stock market returns of benchmark indices spanning from the second week of 1995 to the fourth week of December 2015 are analyzed. Using univariate auto-regressive conditional heteroscedastic, generalized auto-regressive conditional heteroscedastic, and dynamic conditional correlation multivariate GARCH model approaches, the study finds evidence of returns and volatility linkages along with the degree of connectedness among the markets.

The findings of this study are consistent with increasing market connectedness among a group of leading South American economies. Stocks exhibit relatively fewer asymmetries in conditional correlations in addition to conditional volatility; yet, the asymmetry is relatively less apparent in integrated markets. The results demonstrate that co-movements are higher toward the end of the sample period than in the early phase. The stock markets of Argentina, Brazil, Chile, and Peru are closely and strongly connected within the region followed by Colombia, whereas Venezuela is least connected with the group.

The implication is that foreign investors may benefit from the reduction of the risk by adding the stocks to their investment portfolio.

The unique features of the paper include a large sample of national stock returns with updated time series data set that reveals the time series properties and empirical evidence on volatility testing. Unlike other studies, this paper uncovers the relation between the stock markets within the same region facing the same market condition.

This paper aims to examine whether the Indian banking system is robust to withstand unexpected shocks from external and domestic macroeconomic factors after financial liberalization in 1992. As proposed by Demirgüç-Kunt and Detragiache (1998) and Kaminsky and Reinhart (1999) banking crisis follows financial liberalization. India embarked financial deregulation from 1992, whereas the ongoing global financial crisis (GFC) could jeopardize bank portfolios.

Stress test is undertaken through the vector auto regressive (VAR) model to examine if decline in GDP, exchange rate volatility and foreign capital portfolio funds adversely impact bank asset quality through higher defaults. The VAR model is run for banks belonging to public, private or foreign ownership. Soundness of banks is measured by the non-performing assets (NPAs) with quarterly data from 1997 to 2014. Post-VAR estimation technique, Granger causality test (GC) and impulse response function (IRF) are used to check for robustness of the VAR model findings.

The authors found that there is little divergence among banks of different ownership in responding to the shocks from REER, foreign capital flows and GDP output gap. IRF shows that GDP shock to NPA of public and private banks takes more than nine and eight quarters to stabilize. Foreign banks are impacted by the same macroeconomic factors. The stress test exhibits that public banks are more vulnerable and need recapitalization. Moreover, domestic banks are not adversely affected by the GFC, and credit for this could be attributed to the Reserve Bank of India’s (RBI’s) regulatory policy.

Surprisingly, capital market indices do not influence banks’ NPA, and this needs further investigation. The limitation arises from the fact that stock market index for banks was launched only in the early 2000. Missing data and limited number of banks shares traded in the market could explain the trivial results.

Findings of this study will be useful to RBI policymakers and bank managers. The exchange-rate risk faced by borrowers that lead to increased NPAs is an issue that the RBI would be interested to examine. The impact of foreign capital flows, adversely influencing the NPAs of banks, is a significant issue that the RBI is concerned with.

Banking sector crisis has serious repercussions, causing loss of household savings and decline in confidence in the banking sector.

This topic was explored in India only by Bhattacharya and Roy in (2008). No other similar work has been done to the authors’ knowledge in stress test of banks in India across different ownership. The authors’ study period covers the GFC and shows that it has not caused devastation as it has in developed countries.