File Name: the subprime credit crisis and contagion in financial markets .zip
Risk contagion is becoming a research hotspot in the field of econophysics with the rise of interdisciplinary studies and gains more and more attention from theoretical circles and practical departments. This paper proposes a new research frame to discuss the microscopic mechanism of risk contagion based on agent modeling technology and complex network theory and reveals nonlinear dynamics characteristic of risk contagion from the perspective of market participants in financial market. Based on the proposed SICM model, financial risk can transmit from susceptible agents to infected agents, to contagious agents, or to immune agents.
In this paper, we aim at the study of the contagion of the global financial crisis on Moroccan stock market. Our study focuses to examine whether contagion effects exist on Moroccan stock market, during the current financial crisis.
Risk contagion is becoming a research hotspot in the field of econophysics with the rise of interdisciplinary studies and gains more and more attention from theoretical circles and practical departments. This paper proposes a new research frame to discuss the microscopic mechanism of risk contagion based on agent modeling technology and complex network theory and reveals nonlinear dynamics characteristic of risk contagion from the perspective of market participants in financial market.
Based on the proposed SICM model, financial risk can transmit from susceptible agents to infected agents, to contagious agents, or to immune agents. With the increases of contagious probabilities, the simulation experiments show that 1 the amount of susceptible agents continuously decreases; 2 the amount of infected agents increases first and then decreases; 3 the amount of contagious agents increases first and then decreases with a lower speed, relative to the amount of infected agents; and 4 the amount of immune agents continuously increases.
The major contribution of this paper is a new method for studying nonlinear dynamics characteristic of risk contagion, which can be used as a theoretic basis for further researches on the behavioral features of microcosmic subject and the inner mechanisms of risk contagion. With the rapid development of society, the financial industry has gotten more attention and support from governments.
Because the financial development can obviously promote the economy development in theory and practice, governments around the world have always committed to developing domestic finances, especially in financial markets and financial institutions.
Many world economic centers can lead the development direction of globe economy because they also serve as world financial centers, such as New York, London, and Hong Kong.
But due to the influence of financial risks, the development of finance has not been smooth. Many famous financial crises are still remembered by market participants, for example, Asian financial crisis in , American subprime crisis in , and European debt crisis in These serious international financial crises brought many destructive impacts on the world economy in the past.
In essence, the outbreaks of financial crises are always the results of risk transmission and risk accumulation in financial markets. Therefore, the research of risk contagion not only has significant theoretical values to reveal the interaction mechanisms of participants in financial markets, but also great practical values for the prevention of financial risks for governments.
In the existing literature, a part of researchers mainly focus on the fluctuation of asset prices, which causes the transmission of financial risk from one market to another. Although these researches often adopt empirical analysis method, the behavioral features of microcosmic subject are not well revealed.
And another part of researchers depend on complex network theory and agent modeling technology to analyze risk contagion in financial markets. These findings are more focused on the design of network structure and the construction of artificial financial market. The contributions of this paper are twofold. First, we propose a new model of risk contagion based on agent modeling and complex network, which can explain the nonlinear dynamics characteristics of risk contagion from the aspect of microcosmic subject in financial market, compared with the existing literature.
In simulation experiments, we discuss the interaction process of investor behavior and the dynamic evolution mechanism of risk contagion.
The second contribution of this paper is a theoretic expansion of risk contagion. The contagious model built in this paper is a basic theory model, which can explain risk contagion caused by interaction behaviors of market participants. For different types of financial markets, this theoretic model can be used as a basis for discussing the investor behavior and the resulting risk contagion.
The remainder of this paper is organized as follows. Section 2 gives a brief review about the existing literature of risk contagion in financial market. Subsequently, Section 3 presents the theoretical model of risk contagion. Next, Section 4 conducts a series of simulation experiments that discusses the evolution characteristics of risk contagion. Finally, Section 5 concludes the work and points out the direction for future researches. The underlying mechanism of risk contagion can hardly be explained from traditional finance theories because risk contagion shows some characteristics, such as global influences, systematic influences, and interactive influences [ 1 ].
Global influences indicate that financial risk may well transmit to neighbor region from original region and ultimately to spread from one country to another. And systematic influences emphasize that risk contagion probably causes multiple crises in many financial markets, such as debt crisis, liquidity crisis, and credit crisis. At last, interactive influences involve two parts: the interaction between commodity market and financial market and the interaction among different participants.
For the researches on risk contagion in financial markets based on agent modeling and complex network, the literature reviews are shown from the following three aspects. The early scholars often explained risk contagion in financial markets from the perspective of international trades, economic fundamentals, and international capital flows [ 2 — 8 ].
In international trades, a country could increase its international competitiveness of goods and services through a devaluation. And the successive devaluations of different currencies caused the international transmission of financial risks in international scenes [ 9 , 10 ]. For example, it was easy to be found that financial risks transmitted among the countries having closer trade ties, after analyzing three decades of panel data coming from industrialized nations [ 11 ].
And the worse economic fundamentals easily led to risk contagion from economic fields to financial fields [ 12 ]. When a financial crisis broke out in a country, the economic fundamentals of neighbor countries began deteriorating generally. The process of risk contagion involved three effects: monsoonal effects, spillovers effects, and pure contagion effects [ 13 ].
However, international capital inflows could not always promote economic growth. When the domestic economy was overheating, international capital inflows would increase the appreciation pressure of domestic currency and then realize risk contagion among different countries [ 14 ]. Besides, more scholars increasingly focused on the behaviors of market participants to explain the inner mechanism of risk contagion. They gave up the hypothesis of rational economic man and insisted that the investor had the bounded rationality [ 15 — 18 ].
In the framework of bounded rationality, investors were mainly divided into two kinds: rational traders and noise traders [ 19 — 22 ]. Essentially, noise was a signal caused by the shortcomings of market mechanisms or the decision-making mistakes of market subjects [ 23 ].
A small-scale noise trader could increase market liquidity, but a large-scale noise trader was likely to cause excessive price fluctuations in financial markets [ 24 — 26 ]. Moreover, rational traders and noise traders were not unchangeable. And in some cases, rational traders likely turned into noise traders [ 27 ]. On the basis of the hypothesis of bounded rationality, the more researches explained risk contagion in financial markets from the perspective of investor behavior bias, such as equity premium puzzle [ 28 — 30 ], idiosyncratic volatility puzzle [ 31 — 33 ], closed-end fund puzzle [ 34 — 36 ], and dividend puzzle [ 37 — 39 ].
In addition, the cognitive bias and irrational behavior of investors were often associated with overconfidence theory. But the studies found that the irrational behaviors of overconfident investors did not generate excess returns in the long term [ 40 , 41 ].
Furthermore, the behaviors of institutional investors could make a dramatic impact on risk contagion. As institutional investors had larger amounts of money and professional investment strategies, the herd behaviors of institutional investors were easily observed in financial markets [ 42 , 43 ].
The study of risk contagion was always based on efficient market hypothesis and rational expectation theory since long times ago. But in reality, the investor showed the obvious heterogeneity due to the differences of knowledge structure, analytical ability, and risk preference.
And investor behavior became more complicated under the influence of interaction effects. It was difficult to reveal the dynamic characteristics of risk contagion for traditional analysis methods, such as theoretical analysis and empirical analysis [ 44 — 46 ]. However, agent modeling technology could solve this dilemma very well [ 47 ].
A key reason for heavy-tail distributions in financial markets was sheep-flock effect. After analyzing the relationship of peek distribution of return series, market transaction order, and investor imitation, the findings showed that the group decision was a common strategy among agents and the return series followed a power-law distribution [ 49 , 50 ]. Based on [ 49 ], Iori paid more attention to individual decisions and found that agents tended to adjust their investment strategies according to an information set received at every time point [ 52 ].
Pascual et al. In addition, artificial stock market model was a common method to study risk contagion caused by the interactive behaviors of agents. For example, agents could be divided into three types: fundamental analysts, optimistic analysts, and pessimistic analysts, which transformed into any of types according to the changes of returns rates in financial markets [ 54 ].
Bertella constructed an artificial stock market including fundamental investors and technical investors and found that the volatility of stock price increased with the increasing heterogeneity of agents [ 55 ]. Besides, the high-frequency transaction data were usually used to build an artificial stock market in order to reveal the characteristics of risk contagion.
By studying the relation between price restraint and risk contagion, the simulation experiment showed that both price ceiling and price floor led to the spillover effect of financial risks [ 56 ].
Based on SFI-ASM model, Liu and Han constructed a multiagent stock market model and found that the volatility of stock returns was decreasing with the increasing of simulation period [ 57 ]. Along with the increasing development of complex network theory, more and more scholars tried to apply this theory to financial markets and studied the inner mechanism of risk contagion [ 59 — 61 ].
Taking stock market as an example, a stock can be abstracted as an agent in a complex network, and the correlation coefficient between two stocks can be seen as an edge in this network. Thus, both agents and edges together form a complex network. Mantegna built a complex network model through the minimum spanning tree algorithm and analyzed risk contagion in stock market [ 62 ]. On the basis of [ 62 ], the results from Bonanno et al.
On a scale-free network, the network structure was changing with the adjustment of threshold value [ 64 ]. In addition, the closing price in financial market was often used for studying risk contagion.
Emmertstreib and Dehmer used the daily closing price data to investigate the formation of network structure and the dynamic evolutionary process of financial network [ 65 ].
Some researchers found that financial market probably had the small-world feature. For example, after analyzing the correlation coefficients between different stocks in Chinese stock market, Li and Li found the obvious small-world feature in Chinese stock market and discussed the interaction effect among different stocks and the risk contagion caused by stock price variation [ 66 ].
The similar conclusions could be found from [ 67 ], which found the small-world feature of Chinese stock market by building a complex network model based on multiagent modeling. Besides, the changing investor attention could cause the fluctuation of asset price and the intensity of herd behavior in a small-world network [ 68 ]. Under the background of global financial crisis, financial risk was easier to transmit from one investor to another.
By using stock prices in the Korean stock, Nobi discussed the characteristics of risk contagion, during and after global financial crisis, based on the hierarchical network and the minimum spanning tree algorithm [ 69 ]. Network linkage played a major role in the process of formatting network structure.
The dynamic conditional correlations method could be used to study network linkage effects of financial market, especially in stock market. By using the GMM model, Qiao discussed the influences of inner nodes in different positions on stock returns and found that financial risks were easier to transmit from the central area to the marginal area of network [ 70 ]. The researches on transmission dynamics are always the focuses and forefront projects in the academic world.
By means of complex network theory, many scholars explain microscopic mechanisms and dynamic characteristics of some practical issues in society. For example, complex network can be used to reveal the transmission mechanism of computer viruses [ 70 — 72 ], the spread process of epidemics [ 73 , 74 ], and the diffusion intensity of rumor [ 72 , 75 ]. For the researches on dynamics of complex network, many research achievements are based on the traditional model of virus spread, such as epidemic models.
This part introduces the classic infection models at first and then constructs the new risk contagious model in financial market based on agent modeling and complex network. In above models, every agent is probably in a different state in different time points. The main states can be classified into susceptible states, infected states, exposed states, resistant states, etc. Concretely speaking, susceptible states indicate that agents are not infected yet in a model, but they are probably infected by viruses in subsequently time.
Infected states show that agents are infected by viruses, and they tend to spread the viruses to others. Exposed states emphasize that agents may keep latent states instead of becoming the infected states, after contacting with viruses. Resistant states contain two types of situations: 1 agents gain the immunity to viruses owing to vaccine injection or rehabilitation and 2 agents are removed from a model owing to the death.
No matter which type of situations, agents are no longer able to continue to spread the viruses. In SI model, all agents are assumed not to be immune to viruses.
The study of the contagion law of credit risk is very important for financial market supervision. The existing credit risk contagion models based on complex network theory assume that the information between individuals in the network is symmetrical and analyze the proportion of the individuals infected by the credit risk from a macro perspective. However, how individuals are infected from a microscopic perspective is not clear, besides the level of the infection of the individuals is characterized by only two states: completely infected or not infected, which is not realistic. In this paper, a credit risk contagion model based on asymmetric information association is proposed. The model can effectively describe the correlation among individuals with credit risk. The model can analyze how the risk individuals are infected in the network and can effectively reflect the risk contagion degree of the individual.
Skip to main content. Using data for the ABX subprime indexes, we find strong evidence of contagion in the financial markets. These contagion effects spread first from lower-rated ABX indexes to higher-rated ABX indexes, and then from the subprime markets to the Treasury bond and stock markets. Surprisingly, ABX index returns forecast stock and Treasury bond returns by as much as three weeks ahead during the crisis. Furthermore, ABX index shocks map into contractions in the short-term credit markets and increases in the trading activity of financial stocks over the next several weeks. These results support the hypothesis that financial contagion was spread through liquidity and risk-premium channels.
Other versions of this item: Flavin, Thomas J. Sebastiano Manzan, Discussion Papers. Longstaff, Francis A. Dwyer, Gerald P. Gerald P. Tkac,
This study aims to investigate the existence of contagion between liquid and illiquid assets in the credit default swap CDS market around the recent financial crisis. The authors perform analyses based on vector autoregression model and the dynamic conditional correlation model. The estimation of vector autoregression models reveals that changes in liquid CDS LCDS spreads lead to changes in illiquid CDS spreads at least one week ahead during the financial crisis period, whereas the leading direction is reversed during the post-crisis period. Moreover, the results are robust after controlling for structural variables which are proven as determinants of CDS spreads and are empirically supported.
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The global contagion has a major impact on global stock markets, with the U. DJIA falling to 6, Other stock markets also had a precipitous drop during the financial crisis. However, some equity markets have recovered while others have not. This paper looks at how global markets compared in their recovery.
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Ну, мне было все равно. Я просто хотела от него избавиться. - Когда вы отдали ей кольцо. Росио пожала плечами. - Сегодня днем. Примерно через час после того, как его получила.
Трюк, старый как мир. Никуда я не звонил. ГЛАВА 83 Беккеровская веспа, без сомнения, была самым миниатюрным транспортным средством, когда-либо передвигавшимся по шоссе, ведущему в севильский аэропорт. Наибольшая скорость, которую она развивала, достигала 50 миль в час, причем делала это со страшным воем, напоминая скорее циркулярную пилу, а не мотоцикл, и, увы, ей не хватало слишком много лошадиных сил, чтобы взмыть в воздух.
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Мидж и раньше были свойственны фантазии, но ведь не. Он попробовал ее успокоить: - Джабба, похоже, совсем не волнуется. - Джабба - дурак! - прошипела. Эти слова его удивили. Никто никогда не называл Джаббу дураком, свиньей - быть может, но дураком - .
Если бы вы только… - Доброй ночи, сэр. - Кассирша опустила металлическую шторку и скрылась в служебной комнате. Беккер шумно вздохнул и поднял глаза к потолку.
Подойдя поближе, она увидела, что в руке Хейла зажат какой-то предмет, посверкивавший в свете мониторов. Сьюзан сделала еще несколько шагов и вдруг поняла, что это за предмет. В руке Хейл сжимал беретту. Вскрикнув, она оторвала взгляд от неестественно выгнутой руки и посмотрела ему в лицо. То, что она увидела, казалось неправдоподобным.
Нет, сэр. Казалось, старик испытал сильнейшее разочарование. Он медленно откинулся на гору подушек. Лицо его было несчастным. - Я думал, вы из городского… хотите заставить меня… - Он замолчал и как-то странно посмотрел на Беккера.
Наклонные стены помещения, образуя вверху широкую арку, на уровне глаз были практически вертикальными. Затем они приобретали как бы полупрозрачность, завершаясь у пола непроницаемой чернотой - посверкивающей черной глазурью кафеля, отливавшей жутковатым сиянием, создававшим какое-то тревожное ощущение прозрачности пола. Черный лед.
Managerial economics and business strategy pdf chapter 1 the situation of filipino youth a national survey pdfMercer M. 19.06.2021 at 16:35
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