Testing for Systemic Risk Using Stock Returns

2015 ◽  
Author(s):  
Paul H. Kupiec ◽  
Levent Guntay
Keyword(s):  
Stock Returns ◽  
Systemic Risk

scholarly journals Average Conditional Volatility: A Measure Of Systemic Risk For Commercial Banks

2011 ◽  
Vol 9 (2) ◽  
Author(s):  
Harikumar Sankaran ◽  
Manish Saxena ◽  
Christopher A. Erickson
Keyword(s):  
Stock Returns ◽  
Systemic Risk ◽  
Equity Capital ◽  
Capital Adequacy ◽  
Probability Of Default ◽  
Conditional Volatility ◽  
Cross Sectional ◽  
Bank Stock Returns ◽  
Bank Stock ◽  
High Level

<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt; mso-pagination: none;"><span style="color: black; font-size: 10pt; mso-themecolor: text1;"><span style="font-family: Times New Roman;">We propose using the cross-sectional (daily) average conditional volatility of commercial bank stock returns as a measure of systemic risk for the U.S. banking industry. The performance of this measure is tested using data from the 2008 pre-crisis period. The measure is shown to incorporate individual bank risk as well as the cumulative riskiness of a cross-section of banks. Cross-sectional regressions indicate that individual bank&rsquo;s probability of default is unrelated to the bank&rsquo;s conditional volatility during times of low, industry wide risk (as measured by average conditional volatility). However, the bank&rsquo;s conditional volatility significantly affects its probability of default when the industry is experiencing a high level risk. Regardless of the industry level risk, a bank&rsquo;s probability of default has a significant negative relation with its capital adequacy (as measured by the proportion of equity capital). Additionally, at an aggregate level, Granger causality tests indicate that the conditional volatility of &lsquo;big&rsquo; banks causes the riskiness of medium and small banks to increase.</span></span></p>

scholarly journals Ricci curvature: An economic indicator for market fragility and systemic risk

2016 ◽  
Vol 2 (5) ◽  
pp. e1501495 ◽  
Author(s):  
Romeil S. Sandhu ◽  
Tryphon T. Georgiou ◽  
Allen R. Tannenbaum
Keyword(s):  
Stock Returns ◽  
Ricci Curvature ◽  
Systemic Risk ◽  
Economic Indicator ◽  
System Level ◽  
Geometric Feature ◽  
Financial Systems ◽  
Standard And Poor's ◽  
High Level ◽  
Business As Usual

Quantifying the systemic risk and fragility of financial systems is of vital importance in analyzing market efficiency, deciding on portfolio allocation, and containing financial contagions. At a high level, financial systems may be represented as weighted graphs that characterize the complex web of interacting agents and information flow (for example, debt, stock returns, and shareholder ownership). Such a representation often turns out to provide keen insights. We show that fragility is a system-level characteristic of “business-as-usual” market behavior and that financial crashes are invariably preceded by system-level changes in robustness. This was done by leveraging previous work, which suggests that Ricci curvature, a key geometric feature of a given network, is negatively correlated to increases in network fragility. To illustrate this insight, we examine daily returns from a set of stocks comprising the Standard and Poor’s 500 (S&P 500) over a 15-year span to highlight the fact that corresponding changes in Ricci curvature constitute a financial “crash hallmark.” This work lays the foundation of understanding how to design (banking) systems and policy regulations in a manner that can combat financial instabilities exposed during the 2007–2008 crisis.

Testing for Systemic Risk Using Stock Returns

2016 ◽  
Vol 49 (2-3) ◽  
pp. 203-227 ◽  
Author(s):  
Paul Kupiec ◽  
Levent Güntay
Keyword(s):  
Stock Returns ◽  
Systemic Risk

High-frequency Characterisation of Indian Banking Stocks

2018 ◽  
Vol 17 (2_suppl) ◽  
pp. S213-S238 ◽  
Author(s):  
Mohammad Abu Sayeed ◽  
Mardi Dungey ◽  
Wenying Yao
Keyword(s):  
Stock Returns ◽  
Information Content ◽  
Systemic Risk ◽  
High Frequency ◽  
Banking Sector ◽  
Bank Capital ◽  
Firm Characteristics ◽  
Meaningful Change ◽  
Continuous Component

Using high-frequency stock returns in the Indian banking sector, we find that the beta on jump movements substantially exceeds that on the continuous component, and that the majority of the information content for returns lies with the jump beta. We contribute to the debate on strategies to decrease systemic risk, showing that increased bank capital and reduced leverage reduce both jump and continuous beta with slightly stronger effects for capital on continuous beta and stronger effects for leverage on jump beta. However, changes in these firm characteristics need to be large to create an economically meaningful change in beta.

scholarly journals Pengukuran Risiko Sistemik di Negara-negara Berkembang ASIA-7

2020 ◽  
Vol 4 (1) ◽  
pp. 183
Author(s):  
Harun Arasyid ◽  
Rinda Siaga Pangestuti
Keyword(s):  
Sri Lanka ◽  
Stock Returns ◽  
Systemic Risk ◽  
Risk Mitigation ◽  
Academic Research ◽  
Social Engineering ◽  
The Philippines ◽  
Mitigation Measures ◽  
Engineering Models ◽  
Almost All

The research on systemic risk is important to carry out in view of the alleged repetition of the eight-year crisis cycle affecting the market. The data of average stock returns calculation in almost all sample countries was negative in 2011 and repeated again in 2019 that the average banking stock returns in Malaysia, Thailand, the Philippines, Pakistan, and Sri Lanka showed a negative value. Even since 2018, the Philippines, Pakistan and Sri Lanka have consistently been shown to experience negative average returns. Systemic risk measurement is done by two methods, namely ΔCoVaR and MES. Furthermore, this research is very supportive and has been in line with the research roadmap of Islamic University 45 which states that in 2018-2026 the academic research is more focused on the application of regional technology and social engineering models that instead the products in the form of policies to then develop international standard research. In this study, the sample of countries used covers the Asian region, the topic discussed is a very important issue in the financial sector considering that systemic risk cannot be eliminated. In general, there are three findings that are explained from the results of the ΔCoVaR calculation that: (a) most developing countries experienced a decrease in their contribution to systemic events after the 2008 global crisis period; (b) large banks make the biggest contribution to systemic events, except for banks in Malaysia both small and large banks make equal contributions to systemic events; (c) There is a potential for systemic event to increase after 2019 that the contribution to systemic events by individual banks in the Philippines, Indonesia, Sri Lanka show an upward trend in the past year so that risk mitigation measures need to be taken in the form of policies and analysis of banking financial performance and global economic conditions. Based on the overall MES calculation the bank contributes more than 50% of potential systemic events to the system.

Macroprudential Policy Instruments of Central Banks

2012 ◽  
pp. 32-47
Author(s):  
S. Andryushin ◽  
V. Kuznetsova
Keyword(s):  
Systemic Risk ◽  
Financial Stability ◽  
Financial System ◽  
Policy Instruments ◽  
Central Banks ◽  
Macroprudential Policy ◽  
Policy Studies ◽  
The Future ◽  
Financial Cycles

The paper analyzes central banks macroprudencial policy and its instruments. The issues of their classification, option, design and adjustment are connected with financial stability of overall financial system and its specific institutions. The macroprudencial instruments effectiveness is evaluated from the two points: how they mitigate temporal and intersectoral systemic risk development (market, credit, and operational). The future macroprudentional policy studies directions are noted to identify the instruments, which can be used to limit the financial systemdevelopment procyclicality, mitigate the credit and financial cycles volatility.

Freedom Indices and Capital Asset Pricing Model: Some Malaysian Evidence

2020 ◽  
Vol 1 (1) ◽  
pp. 1-21
Author(s):  
Ying Tay Lee ◽  
Devinaga Rasiah ◽  
Ming Ming Lai
Keyword(s):  
Human Rights ◽  
Asset Pricing ◽  
Stock Returns ◽  
Firm Size ◽  
Explanatory Power ◽  
Least Square ◽  
Press Freedom ◽  
Capital Asset Pricing ◽  
Capital Asset ◽  
Cross Sectional

Human rights and fundamental freedoms such as economic, political, and press freedoms vary widely from country to country. It creates opportunity and risk in investment decisions. Thus, this study is carried out to examine if the explanatory power of the model for capital asset pricing could be improved when these human rights movement indices are included in the model. The sample for this study comprises of 495 stocks listed in Bursa Malaysia, covering the sampling period from 2003 to 2013. The model applied in this study employed the pooled ordinary least square regression estimation. In addition, the robustness of the model is tested by using firm size as a controlled variable. The findings show that market beta as well as the economic and press freedom indices could explain the cross-sectional stock returns of the Malaysian stock market. By controlling the firm size, it adds marginally to the explanation of the extended CAP model which incorporated economic, political, and press freedom indices.

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