Speculative bubbles in emerging stock markets and macroeconomic factors: A new empirical evidence for Asia and Latin America

The purpose of this study is firstly to test for the existence of periodically collapsing stock price bubbles in Asian and Latin American emerging stock markets for the period 1990–2009. We use the new non-cointegration test developed by Taylor and Peel (1998) with the Residuals-Augmented Least Squares (RALS) method of Im (1996) and Im and Schmidt (2008) for monthly data of price indexes and dividends. The results show that the hypothesis of formation of bubbles cannot be rejected for all of the studied emerging stock markets. This evidence implies that the co-integration relation between the prices and the dividends is not always supported, indicating that the stock prices do not reflect their fundamental values in the emerging stock markets. We then link speculative bubbles with macroeconomic and financial factors, which is an interesting contribution of this study. The degree of equity market openness is found to be the key factor, positively related to the formation of speculative bubbles in these markets.     

Can (unusual) weather conditions in New York predict South African stock returns?

This paper investigates the explanatory power of certain weather variables, measured as deviations from their monthly averages, in a leading international financial trading centre, i.e., New York, for South African stock returns, over the daily period January 2nd, 1973 to December, 31, 2015. The empirical results highlight that these unusual deviations of weather variables have a statistically significant negative effect on the stock returns in South Africa, indicating that unusual weather conditions in New York can be used to predict South African stock returns, which otherwise seems to be highly unpredictable. In fact, a forecasting exercise recommends that a trading rule that considers those weather variables through a GARCH modelling approach seems to outperform the random walk model and thus beat the market.     

Examining dynamic currency linkages amongst South Asian economies: An empirical study

In this paper, we examine the currency market linkages of South Asian member countries using daily data from 6 January 2004 to 31st March 2016. Time invariant and varying Copula GARCH models show that South Asian countries, except for India and Nepal/Bhutan, have low levels of currency market linkages which can be ascribed to poor levels of intra-regional trade intensity and portfolio flows. We reconfirm the copula results through Diebold and Yilmaz methodology and document that currency market connectedness is very limited in the South Asian region. The trends of the fundamental determinants of currency co-movements for the South Asian member countries were compared with its neighbouring regional economic bloc in Asia which has a much longer history and a wider membership base i.e ASEAN + 6. From a comparative analysis, it was found that South Asia member states have to work on their governance parameters, improve on their trade linkages and trade tariffs and work towards greater degree of capital account convertibility with adequate safeguards to achieve higher levels of currency market linkages.     

Central banks and macroeconomic policy choices: Relaxing the trilemma

Macroeconomic policy choices in open economies are constrained by the trilemma according to which the objectives of exchange rate stability, monetary independence and capital mobility cannot be attained jointly. This paper shows that foreign exchange interventions provide an effective instrument to relax the trilemma. An active reserve policy allows central banks to pursue independent monetary and exchange rate policies when the capital account is liberalised.We use the framework of the portfolio balance model to show that exchange market interventions may substitute for capital controls. Both allow a country to achieve the other two objectives of the trilemma. Our empirical analysis of a large country panel data set covering the period 1970–2010 confirms this theoretical insight: the weighted sum of the three trilemma objectives increases in the degree of foreign exchange market intervention. The capacity to relax the trilemma constraint has increased over time and has been most effective in emerging markets.     

Assessing time-varying stock market integration in Economic and Monetary Union for normal and crisis periods

In this paper, we examine the stock market integration process amongst 17 Economic and Monetary Union (EMU) countries from January 2002 to June 2013 over a normal period as well as for the Global Financial Crisis (GFC) and Eurozone Debt Crisis (EDC) periods. We classify the economies in three groups (A, B and C) based on their GDP to examine whether the economic size influences financial integration. Seven indicators are used for the purpose, namely, beta convergence, sigma convergence, variance ratio, asymmetric DCC, dynamic cointegration, market synchronisation measure and common components approach. The results suggest that large-sized EMU economies (termed as Group A) exhibit strong stock market integration. Moderate integration is observed for middle-sized EMU economies with old membership (termed as Group B). Small-sized economies (termed as Group C) economies seemed to be least integrated within the EMU stock market system. The findings further suggest presence of contagion effects as one moves from normal to crisis periods, which are specifically stronger for more integrated economies of Group A. We recommend institutional, regulatory and other policy reforms for Group B and especially Group C to achieve higher level of integration.     

Oil price shocks and volatility spillovers in the Nigerian sovereign bond market

This paper investigates volatility spillover in the Nigerian sovereign bond market arising from oil price shocks, using Vector Autoregressive Moving Average ‐ Asymmetric Generalized Autoregressive Conditional Heteroscedasticity (VARMA‐AGARCH) model. The paper covers the period March 22, 2011 to April 14, 2016 and makes use of the daily data of the Nigerian Sovereign Bond, Brent oil and West Texas Intermediate (WTI), respectively. We endogenously and sequentially detect structural break points using the test of Bai and Perron (2003) framework. In order to accurately estimate the model, we modify it by incorporating the break points into the VARMA‐AGARCH model, a process which if ignored would lead to model misspecification. The results obtained demonstrate a significant cross‐market volatility transmission between oil and sovereign bond market with ample sensitivity to structural breaks. The study also computes optimum weight portfolio and hedge ratio both with and without structural breaks and results equally indicate sensitivity to structural breaks.     

Dimensions of strategic intervention for risk reduction and mitigation: a case study of the MV Sewol incident

Organizations in disaster management system should learn from previous experience and strategically use their lesson for the refinement of a system’s competencies for risk management. However, the MV Sewol incident revealed the absence of the organizational learning in the Korean disaster management system. With mixed methods of content analysis, in-depth interview, and social network analysis, this study identified key failure factors in response to the incident and categorized them by managerial, structural, and institutional domains. While the Korean government took bold steps to rebuild its risk management system, those efforts were biased to structural reforms and lacked fundamental changes in human and informational resources management. Based on the findings, this study suggests the balanced efforts for system refinement for effective risk management.     

Contagion risk in the interbank market: a probabilistic approach to cope with incomplete structural information

One lesson of the financial crisis erupting in 2008 has been that domino effects constitute a serious threat to the stability of the financial sector, i.e. the failure of one node in the interbank network might entail the danger of contagion to large parts of the entire system. How important this effect is, depends on the exact topology of the network on which the supervisory authorities have typically very incomplete knowledge. In order to explore the extent of contagion effects and to analyse the effectiveness of macroprudential measures to contain such effects, a reconstruction of the quantitative features of the empirical network would be needed. We propose a probabilistic approach to such a reconstruction: we propose to combine some important known quantities (like the size of the banks) with a realistic stochastic representation of the remaining structural elements. Our approach allows us to evaluate relevant measures for the contagion risk after default of one unit (i.e. the number of expected subsequent defaults, or their probabilities). For some quantities we are able to derive closed form solutions, others can be obtained via computational mean-field approximations.     

Open Market Operation Effectiveness in China

This paper examines the effectiveness of target rate guidance in open market operation by the central bank in China (PBOC). We find that target rate change in open market operation is effective in adjusting the short-term Treasury rates. The target rate changing direction is more effective than the target rate changing level. There is no significant asymmetry in the effectiveness between the target rate increase and target rate decrease. We also document that the effectiveness of the target rate is conditional on liquidity operation of the same direction, especially when they both aim to loosen the monetary policy. Furthermore, consecutive operations with higher intensity appear to be more effective in adjusting the market interest rate.     

Decision-making in incomplete markets with ambiguity—a case study of a gas field acquisition

We apply utility indifference pricing to solve a contingent claim problem, valuing a connected pair of gas fields where the underlying process is not standard Geometric Brownian Motion and the assumption of complete markets is not fulfilled. First, empirical data are often characterized by time-varying volatility and fat tails; therefore, we use Gaussian generalized autoregressive score (GAS) and GARCH models, extending them to Student’s t-GARCH and t-GAS. Second, an important risk (reservoir size) is not hedgeable. As a result, markets are incomplete which makes preference free pricing impossible and thus standard option pricing methodology inapplicable. Therefore, we parametrize the investor’s risk preference and use utility indifference pricing techniques. We use Least Squares Monte Carlo simulations as a dimension reduction technique in solving the resulting stochastic dynamic programming problems. Moreover, an investor often only has an approximate idea of the true probabilistic model underlying variables, making model ambiguity a relevant problem. We show empirically how model ambiguity affects project values, and importantly, how option values change as model ambiguity gets resolved in later phases of the projects. We show that traditional valuation approaches will consistently underestimate the value of project flexibility and in general lead to overly conservative investment decisions in the presence of time-dependent stochastic structures.