Chaotic dynamic behavior analysis and control for a financial risk system

According to the risk management process of financial markets,a financial risk dynamic system is constructed in this paper.Through analyzing the basic dynamic properties,we obtain the conditions for stability and bifurcation of the system based on Hopf bifurcation theory of nonlinear dynamic systems.In order to make the system＇s chaos disappear,we select the feedback gain matrix to design a class of chaotic controller.Numerical simulations are performed to reveal the change process of financial market risk.It is shown that,when the parameter of risk transmission rate changes,the system gradually comes into chaos from the asymptotically stable state through bifurcation.The controller can then control the chaos effectively.

Intelligent Feature Selection with Deep Learning Based Financial Risk Assessment Model

Due to global financial crisis,risk management has received significant attention to avoid loss and maximize profit in any business.Since the financial crisis prediction(FCP)process is mainly based on data driven decision making and intelligent models,artificial intelligence(AI)and machine learning(ML)models are widely utilized.This article introduces an intelligent feature selection with deep learning based financial risk assessment model(IFSDL-FRA).The proposed IFSDL-FRA technique aims to determine the financial crisis of a company or enterprise.In addition,the IFSDL-FRA technique involves the design of new water strider optimization algorithm based feature selection(WSOA-FS)manner to an optimum selection of feature subsets.Moreover,Deep Random Vector Functional Link network(DRVFLN)classification technique was applied to properly allot the class labels to the financial data.Furthermore,improved fruit fly optimization algorithm(IFFOA)based hyperparameter tuning process is carried out to optimally tune the hyperparameters of the DRVFLN model.For enhancing the better performance of the IFSDL-FRA technique,an extensive set of simulations are implemented on benchmark financial datasets and the obtained outcomes determine the betterment of IFSDL-FRA technique on the recent state of art approaches.

Financial Risk: a Major Threat in the Development of the World Economy

By the mid-1990s, following nearly a century of struggles-two worldwars, continuous coups and clashes, and 40 years of Cold War with itsnuclear threat-mankind seemingly entered a new period of peace, stabili-

The Value Choice for Legal Regulation of Financial Risks in Shadow Banking

It is of vital importance for shadow banking supervision to have correct targets for the curtailment of financial risks.In fact,the process of selecting legal regulation targets for shadow banking financial risks is equivalent to a process of achieving specific goals or objectives by means of legal regulation.The establishment of a regulatory system for shadow banking should consider the objective and practical needs of the sector,prioritize security as the desired value,and reasonably establish a value system for risk control.

Averting Financial Risks

THE Chinese economy faces three major risks： burst of real estate bubbles, risks of local gov ernment financing platforms and split of capital chains for private lending.

The Formation Mechanism of Systemic Financial Risk under External Shocks

By incorporating both the fire sales contagion mechanism and the bankruptcy contagion mechanism into a bank network model,this paper examines how risks are generated under dynamic shocks.In particular,this paper constructs systemic risk indicators suitable for analyzing multiple rounds of contagion under different shocks(time dimension)and from institutions and assets(spatial dimension).Indicators that measure the indirect relevance between institutions and between assets are also innovatively built.It is found that due to deleveraging or bankruptcy among a large number of banks,the systemic risk exhibits an upward trend marked by intermittent jumps under varying intensities of shocks.Risks are generated mainly through the fire sales contagion mechanism of deleveraging under small shocks,and through the bankruptcy contagion mechanism under large shocks.In terms of influencing factors,a stronger indirect relevance,a lower leverage skewness and a higher leverage level in the banking system lead to higher risks.In particular,the influence of leverage skewness on systemic risk is stronger than that of leverage level.

Estimates for the Finite-time Ruin Probability with Insurance and Financial Risks

The paper gives estimates for the finite-time ruin probability with insurance and financial risks. When the distribution of the insurance risk belongs to the class L（γ） for some γ〉0 or the subexponential distribution class, we abtain some asymptotic equivalent relationships for the finite-time ruin probability, respectively. When the distribution of the insurance risk belongs to the dominated varying-tailed distribution class, we obtain asymptotic upper bound and lower bound for the finite-time ruin probability, where for the asymptotic upper bound, we completely get rid of the restriction of mutual independence on insurance risks, and for the lower bound, we only need the insurance risks to have a weak positive association structure. The obtained results extend and improve some existing results.

Can"Concerted"Macroprudential Policies Mitigate Cross-border Contagion of Financial Risks?Evidence from China and Its Financially Connected Economies

We construct a connected network between China and the economies that are financially linked to it,based on the network topology of variance decompositions,and measure the cross-border contagion of financial risks among these economies.We then examine whether the concerted use of macroprudential policies mitigates the cross-border contagion of financial risks.The empirical results show that the tightening of macroprudential policies,especially counter-cyclical capital buffers and limits on credit growth,in economies with net spillover risk(e.g.the US and China).can reduce the cross-border spillover of domestic financial risks to other economies.The concerted use of macroprudential policies can contribute to global financial stability.However,the tightening of"capital"macroprudential policy tools will increase domestic cross-border absorption of financial risks.Hence,macroprudential regulation of cross-border capital flows must be strengthened.

Combating emerging financial risks in the big data era:A perspective review

financial services:for example,GPS and Bluetooth inspire location-based services,and search and web technologies motivate online shopping,reviews,and payments.These business services have become more connected than ever,and as a result,financial frauds have become a significant challenge.Therefore,combating financial risks in the big data era requires breaking the borders of traditional data,algorithms,and systems.An increasing number of studies have addressed these challenges and proposed new methods for risk detection,assessment,and forecasting.As a key contribution,we categorize these works in a rational framework:first,we identify the data that can be used to identify risks.We then discuss how big data can be combined with the emerging tools to effectively learn or analyze financial risk.Finally,we highlight the effectiveness of these methods in real-world applications.Furthermore,we stress on the importance of utilizing multi-channel information,graphs,and networks of long-range dependence for the effective identification of financial risks.We conclude our survey with a discussion on the new challenges faced by the financial sector,namely,deep fake technology,adversaries,causal and interpretable inference,privacy protection,and microsimulations.

The Odd Log-Logistic Weibull-G Family of Distributions with Regression and Financial Risk Models

A new generalization of the Weibull-G family is proposed with two extra shape parameters.The mathematical properties are derived in great detail.Using the Weibull and normal distributions as baseline distributions,two models are introduced.The first model is a location-scale regression model based on a new extension of the Weibull distribution.The second model is a new two-step financial risk model to forecast the daily value at risk.The flexibility and applicability of the proposed models are investigated by means of five real data sets on the lifetime and financial returns.Empirical findings of the study show that proposed models work well and produce better results than other well-known models for financial risk modeling and censored lifetime data analysis.

Financial risk assessment model based on big data

Conventional financial risk assessment is not accurate and its adaptive assessment ability is low.In order to solve this problem,a financial risk assessment model based on big data is proposed.In this method,the quantitative analysis method is adopted to analyze the explanatory variable model and the control variable model of financial risk assessment.The market-to-book ratio,asset–liability ratio,cash flow ratio and financing structure model are adopted as constraint parameters to construct a big data analysis model for financial risk assessment.On this basis,the adaptive fuzzy weighted control method is adopted for information fusion of financial risk assessment data and big data classification,and the asset income control and innovative evaluation model are adopted for linear planning and square fitting during financial risk assessment.Based on the intervention factors of financial market participants,quantitative regression analysis is performed,and according to the economic game theory,big data analysis and prediction of financial risk assessment are performed through the regression analysis method.Then the big data fusion and clustering algorithms are adopted for financial risk assessment.The simulation results show that this method can provide a relatively high accuracy in financial risk assessment,and has relatively strong adaptive evaluation capability to the risk coefficient,so it has a good application value in the prevention and control of risk factors in financial systems.

Thwarting Financial Risk In East Asia

Regional countries set up a foreign exchange reserve fund to help avoid financial risks The U.S.subprime mortgage loan cri- sis has stirred fears and worries about possible global financial risks and economic recession throughout the world.On May 4,China,Japan and South Korea announced that they would jointly set up a foreign exchange reserve

A Tougher Stance on Financial Risk

This year China’s top banking regulator has scaled up its efforts to place f inancial markets under stricter scrutiny in order to better guard the sector against potential risks.By the end of November,the China Banking Regulatory Commission(CBRC)had imposed administrative penalties relating to more than 2,500 cases involving irregularities within the sector,covering state-owned banks,joint-equity banks and city commercial banks,statistics from the

Impact of risk management strategies on the credit risk faced by commercial banks of Balochistan

This study aims to identify risk management strategies undertaken by the commercial banks of Balochistan,Pakistan,to mitigate or eliminate credit risk.The findings of the study are significant as commercial banks will understand the effectiveness of various risk management strategies and may apply them for minimizing credit risk.This explanatory study analyses the opinions of the employees of selected commercial banks about which strategies are useful for mitigating credit risk.Quantitative data was collected from 250 employees of commercial banks to perform multiple regression analyses,which were used for the analysis.The results identified four areas of impact on credit risk management(CRM):corporate governance exerts the greatest impact,followed by diversification,which plays a significant role,hedging and,finally,the bank’s Capital Adequacy Ratio.This study highlights these four risk management strategies,which are critical for commercial banks to resolve their credit risk.

Interprovincial Effects of Fiscal Decentralization on Financial Decentralization in China

By motivating local governments to fight for financial resources,China's tax sharing reform has affected the structure of financial decentralization and inflated local financial systems,thus spawning regional financial risks.Based on theoretical analysis and empirical evidence,this paper has arrived at the following findings:due to different policy objectives,central and local governments exhibit different fiscal and financial behaviors;public finance and financial sector have become financing instruments with certain convertibility under local economic growth framework;fiscal decentralization inevitably affects financial decentralization and lays the foundation for provincial fiscal disparities,resulting in a certain spatial effect of interprovincial fiscal variable;financial explicit centralization/implicit decentralization and fiscal centralization have fueled local competition for financial resources and resulted in correlation between the spatial effects of provincial financial and fiscal variables,and moreover,their mismatch has also spawned fiscal and financial risks on various fronts.Hence,setting clear boundaries of financial centralization and decentralization and ensuring local government fiscal accountability is the key to the prevention and mitigation of fiscal and financial risks in China.

Review of Financial Pressure

Different from foreign capital markets,china’s domestic capital markets are special,which also determines that the research on financial pressure starts from the reform of state-owned enterprises,and draws lessons from the relevant theories of financial risk and financial fraud,thus gradually forming a more diversified research results.

eterminants of financial-risk preparedness for climate change:Case of Fiji

There is a growing concern among central bankers that climate change poses not only serious environmental problems but also a potentialeconomic and financial crisis.This study first confirms a hypothesized theoretical framework with different dimensions of the overall pre-paredness for climate related financial risk in the Fijian context,and then utilizes this framework to assess the present risk preparedness in Fiji.We tested two Confirmatory Factor Analysis(CFA)models in Structural Equation Modeling(SEM)Framework to analyse the survey data.Weevaluated these models using several fit indices.The first CFA model included four correlated latent factors defined by multiple indicators(items)reflecting four hypothesized dimensions.The four latent factors were correlated significantly.The second CFA model included a second-order multi-level constructs reflecting overall preparedness along with four constituent dimensions.The four dimensional factors showed sig-nificant and substantial loadings towards overall risk preparedness suggesting that there also exists an overall higher order construct.The modelfit indices showed that this second-order CFA model has an acceptable model fit.These results confirm that the four hypothesised dimensionsepolitical leadership(Political),administrative direction(Administration),international standards(Standards)and supervisory mechanisms(Supervision)eare identifiable and distinct aspects.In addition to the four dimensions,the results suggest that overall preparedness should alsobe tackled in a multi-level integrated manner.The results also reveal that political initiatives would be futile without proper administrativedirection and strong supervisory mechanisms.This theoretical framework can also be used to assess financial systems in other developingcountries with similar socioeconomic contexts.

The Dynamic Relationship of China’s Financial Sub-Markets:From the Perspective of Risk and Stability

The development of financial technology has made financial sub-markets increasingly interconnected,and this interdependence magnifies the instability of financial markets and the possibility of risk.The literature documents the relation of financial sub-markets from time domain,but empirical evidence that effectively identify the patterns of co-movement of multiple financial sub-markets from frequency domain is lacking.This study assesses the dynamic relationship among interest rates,stock prices and exchange rates in China from January 2006 to December 2021 using the Wavelet model.Furthermore,we introduce the TVP-VAR-SV model to study whether the dynamic relationship has changed structurally under the impact of COVID-19.We find the following:1) with the deepening of the financial market and the improvement of the informatization level,the frequency of risk transmission among financial sub-markets decreases,and the linkage relationship changes from frequent linkage in the medium term to relatively stable linkage relationship in the long term;2) the relationship between the three variables in short-term fluctuations is more complex,while the relationship between financial variables in long-term fluctuations is more stable;3) after the outbreak of COVID-19,the positive impact of interest rates and stock prices has brought about a larger range of changes in exchange rate volatility,with a longer impact period and a stronger linkage.