Macroeconomic Situations and Policy Adjustments in China

2021

Empir Econ

We propose a novel risk measure that is built on comparing high-frequency time-varying volatility and low-frequency return spillover estimates. This measure permits to identify the markets that are epidemic in their complex interdependence. We conjecture that initially a highly volatile market experiences episodes of risk transmission, but only later absorbs risk and becomes an epidemic market. Moreover, we can detect newly emerging ‘contagion’ in the system. We examine the behaviour of 30 global equity markets and compare spillover measures, which encapsulate many large and small crises episodes. Instead of relying on ex post crisis information, our model identifies crises periods. An important implication of the proposed approach is that highly interrelated markets, such as China, are less likely to transmit a global economic crisis under the current interdependence setting.

Section: Resultsmentioning

confidence: 99%

Contagion or interdependence? Comparing spillover indices

2021

Empir Econ

“…The Chinese market is fraught with speculations of a crisis in the market (Forum, 2015;Mauldin, 2017;Elliott, 2017;Chiang et al, 2017;Mao, 2009). The speculations are fuelled further with the building up of 2015-16 stock market crash preceding a pronounced rise in both vulnerability and transmission.…”

Section: Export Crisismentioning

confidence: 99%

Crisis transmission: Visualizing vulnerability

Dungey

Pacific-Basin Finance Journal

2020

This paper develops a means of visualizing the vulnerability of complex systems of financial interactions around the globe using Neural Network clustering techniques. We show how time-varying spillover indices can be translated into two dimensional crisis maps. The crisis maps have the advantage of showing the changing paths of vulnerability, including the direction and extent of the effect between source and affected markets. Using equity market data for 31 global markets over 1998-2017 we provide these crisis maps. These tools help portfolio managers and policy makers to distinguish which of the available tools for crisis management will be most appropriate for the form of vulnerability in play.

“…Chinese economic growth plunges to 25-year low. Leading up to this, speculations and warnings reflected engendered fears of a global meltdown, including warnings issued by the International Monetary Fund (Mauldin, 2017;Liang, 2016;Mao, 2009;Elliott, 2017;Cheng, 2017). The Chinese authority responded by imposing new trading curbs and devaluing currency.…”

Section: Identifying Contagionmentioning

confidence: 99%

“…The Chinese authority responded by imposing new trading curbs and devaluing currency. While commentators, including the China Securities Regulatory Commission blamed surging speculation and irrational investment behaviour for sourcing the crisis, Mao (2009)suggested that the colossal shadow banking industry was responsible for heightening the risks in the Chinese markets much earlier. Presumably, potential risks are predominant in the shadow banks in China, which have quadrupled at an annual rate of 34 per cent since 2008, and at that time the size of the Chinese shadow banks (US $8 trillion) is equal to 4.3 per cent of Chinese GDP (Mao, 2009).…”

Section: Identifying Contagionmentioning

confidence: 99%

“…While commentators, including the China Securities Regulatory Commission blamed surging speculation and irrational investment behaviour for sourcing the crisis, Mao (2009)suggested that the colossal shadow banking industry was responsible for heightening the risks in the Chinese markets much earlier. Presumably, potential risks are predominant in the shadow banks in China, which have quadrupled at an annual rate of 34 per cent since 2008, and at that time the size of the Chinese shadow banks (US $8 trillion) is equal to 4.3 per cent of Chinese GDP (Mao, 2009). Liang (2016) asserted that the burgeoning shadow economy, amidst the goal of boosting productivity against an overall drop in the labour market, posed a high risk to the financial stability of China given its current regulatory framework.…”

Section: Identifying Contagionmentioning

confidence: 99%

See 1 more Smart Citation

Contagion or Interdependence? Comparing Signed and Unsigned Spillovers

2020

SSRN Journal

Differentiating between 'good' and 'bad' spillovers we disentangle sources of potential crisis from the intricately complex web of connections across international equity markets. In particular, we analyze the behaviour of 30 global equity markets and compute multiple spillover measures, which encapsulate many large and small crises episodes. Instead of relying on ex-postcrisis information, our model identifies crises periods. Moreover, we are able to detect newly emerging contagion in the system.