Use of Unit Root Methods in Early Warning of Financial Crises

This chapter highlights the facts about financial crises and their fundamental causes on specific incidents, including the 1929 Great Depression that lasted until the early-1940s, 1997 Asian Financial Crises, 1998 Russian Financial Crises, and the Liquidity Crises of 2008, and makes a comparison among them and their various outcomes. In doing so, the study specifies the cues that emerge in the financial system that may help governments predict upcoming financial crises through those early warning signals. This case study specifically analyses the Turkish Banking System that was restructured after the enormous financial crises in Turkey in 2001, which caused many Turkish banks to collapse. However, the precautions taken in the aftermath of the financial turmoil allowed them to survive the liquidity crises in 2008. The indicators of an upcoming crisis are examined, the lessons learned from this case are analyzed, and important recommendations to overcome banking crises are provided.

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Early Warning System for Financial Crises

Risk and Contingency Management ◽

10.4018/978-1-5225-3932-2.ch001 ◽

2018 ◽

pp. 1-25 ◽

Cited By ~ 1

Author(s):

Amir Manzoor

Keyword(s):

Financial Crisis ◽

Early Warning ◽

Financial Crises ◽

Early Warning System ◽

Financial Stability ◽

Time Horizon ◽

Warning System ◽

False Alarms ◽

Financial Risks ◽

Policy Makers

To maintain financial stability, prevention of financial crisis is very important. This prevention is especially is especially important for developing countries where we need robust instruments for prediction of financial crises. One such instrument is Early Warning System (EWS). An EWS provided signals that could reflect the likelihood of a financial crisis over a given time horizon. Changing nature of financial risks due to liberalization of economies has increased the importance of an effective EWS. This chapter explores the state of the art of EWS. It is suggested that policy makers should take into account their objectives and related thresholds of various while developing an EWS since there exists a sharp trade-off between correctly calling crises and false alarms.

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Toward an early warning system of financial crises: What can index futures and options tell us?

The Quarterly Review of Economics and Finance ◽

10.1016/j.qref.2014.07.004 ◽

2015 ◽

Vol 55 ◽

pp. 87-99 ◽

Cited By ~ 11

Author(s):

Wei-Xuan Li ◽

Clara Chia-Sheng Chen ◽

Joseph J. French

Keyword(s):

Early Warning ◽

Financial Crises ◽

Early Warning System ◽

Warning System ◽

Index Futures ◽

Futures And Options

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Notice of Retraction: Development of research paradigm of the early-warning financial crises: A Pressure-State-Impact-Response methodological framework

2010 IEEE International Conference on Advanced Management Science(ICAMS 2010) ◽

10.1109/icams.2010.5553177 ◽

2010 ◽

Author(s):

Yin Yu ◽

WeiPing Wang ◽

Naihe Li ◽

Fanghua Wang

Keyword(s):

Early Warning ◽

Financial Crises ◽

Impact Response ◽

Methodological Framework ◽

Research Paradigm ◽

Pressure State

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Validity of EMH; A Case Study of KSE-100 Index

Sukkur IBA Journal of Management and Business ◽

10.30537/sijmb.v1i1.83 ◽

2018 ◽

Vol 1 (1) ◽

pp. 112 ◽

Cited By ~ 1

Author(s):

Salma Naz ◽

Seema Razaque ◽

Hyder Ali Khuwaja ◽

Niaz Ahmed Bhutto

Keyword(s):

Time Series ◽

Unit Root ◽

Financial Crises ◽

Weak Form ◽

Return Time ◽

Unit Root Tests ◽

Stock Index ◽

Random Walk Hypothesis ◽

Q Statistic

The emerging markets offer major investments opportunities for a range of investors over the last decades especially after the global financial crises,which attracted the attention of investors and financial researchers towards the market efficiency.This research paper is designed to verify other researchers work, because some of them have provided contradictory results to test the market efficiency of Pakistani stock index (KSE-100). Average daily observations are considered for the period of twenty two years (November 02, 1991 to December 31, 2012). Unit Root tests (ADF, PP and KPSS), Runs test, Serial Autocorrelation (L-Jung-Box Q statistic) techniques are used to analyze the market’s informational weak form efficiency. Return time series is not normally distributed because it is negatively skewed and leptokurtic. All of the tests applied provide sufficient statistical evidence to reject the Random Walk Hypothesis thus KSE-100 shares index is informational weak form inefficient.

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