Purpose of this study: In view of the global financial crises and the ensuing consequences, this research presents the utility of demonstrating an assessment that can forecast the Bangladeshi financial market’s well-being by analysing episodes of economic crises which may prevent market distress. By graphically demonstrating eventual economic episodes in the financial sector, this study sets out to illustrate the chronological scenario of economic turning points. The scope of this research is to study the vulnerable aspects of financial instability in Bangladesh and seek possible remedies. Methodology: The Bangladeshi financial market regimes will be constructed based on Hamilton's Markov Switching Model (1989). This paper is the first attempt in utilising a standardised methodology found in business cycle literatures so as to determine the turning points of economic episodes in the Bangladeshi financial dynamic cycle. Main Findings: This study examines the financial crises and economic distress experienced by banks as forms of economic vulnerabilities. Thus, it describes the financial regimes of transition period movements in the context of the vulnerability of the Bangladeshi financial market sector using the Markov Switching Modeling (MSM) Approach and shows ways to possibly achieve recovery. Research Limitations/Implications: This research focuses on the current financial episodes of the economic sector’s dynamic movements in a condensed area, while the selection of a broad financial arena of parameters results in more significant and robust outcomes. Novelty/Originality: Further studies are needed to define and measure the financial cycle concept and its relationship with business cycles, as well as to delineate dynamic models that can offer substantial probabilistic assessments regarding changes in financial cycle regimes. This can significantly develop the capability of the financial market supervisory authorities to forecast macro-prudential systemic risks and to avoid or reduce the consequences of economic crises. This current study provides a platform for future studies in similar fields.

Purpose of this study: In the aggregate industrial sector, government intervention to influence demand within the economy is generally counterproductive, while the optimal policy is to concentrate on supply-side reforms that help the economy become efficient. The objective of this study was to construct a unique industry cycle indicator for Bangladeshi aggregate firms within this industrial sector. The specific objectives were to assemble a unique industry cycle indicator which recommends early signals of a firm’s industrial vulnerability, identify industry cycle indicator turning points and evaluate the predictive performance of the industry. The industry cycle indicator model demonstrates the macroeconomic fluctuations in the industrial sector. Methodology: The industry cycle indicator was constructed following the approach of the Conference Board (2000). The result wasthen tested for robustness with a macro-stress test. Lagged independent variables were used in this study to allow early predictions by the ICI for the year in which the financial crisis happened. Main Findings: The industry cycle indicator model underplays the role of aggregate industrial efficiency in influencing the economic cycle. By forecasting directional changes, this leading indicator allows policymakers to be made aware of revolutions in the financial industry and to undertake early precautionary steps to prevent vulnerability. Here, the constructed industry cycle indicator demonstrates a remarkable lead time of around 6 months for predictions and outperforms by the leading against the reference series. Research Limitations/Implications: The industry cycle indicator model rejects the Keynesian approach and also rejects monetarism. It tends to be associated with neo-classical economics. The ICI generally assumes that shocks to productivity lead to economic fluctuations. In other words, a temporary fall in output is an inevitable consequence of a drop in productivity within the industrial sector. It also leads to adjustments to this new equilibrium and enables resources to discover more productive uses. Novelty/Originality: This research demonstrates that enhanced knowledge of components of the macro-prudential policy framework combined with the existence of a certain degree of standardisation of the macro-prudential tools and indicators is essential. This can significantly develop the capability of the financial markets supervisory authorities to forecast systemic risk and to avoid or reduce the consequences of industrial crises. The present study reflects a situation for upcoming researchers who intend to study and develop their interests in this area.

In perspective of the economic vulnerability faced by banks in financial sector, this study mirrors the methodology used by Shumway (2001) – the dynamic hazard model that is able to forecast systemic risk in financial market arena. Here, the terminology followed is based on the CAMELS framework variables: capital adequacy, asset, management, earnings, liquidity and sensitivity to market risk. The objective of this study is to construct a macroprudential indicator (MPI) for the case of Bangladeshi financial market. The result will then be tested for robustness with macro-stress test. Lagged independent variables will be used in the simple hazard model to allow early prediction of MPI in the year in which the crisis happens. The empirical findings can be used as a guideline for the Bangladesh Government and policy makers in accessing, examining and forecasting the health of the Bangladeshi financial system and formulate suitable financial system policies for control. MPI generates information about systemic risk allowing the detection of potential economic crises functioning as an early warning indicator. Government and policy makers will be able to make early preparation in cushioning any potential crises by means of the MPI. Thus the impact of the crises could be minimized and eventually reduce its impact on the Bangladesh economy. The specific objectives are to assemble a novel MPI that is able to recommend early signals of financial market vulnerability, to identify the MPI turning points and establish a comprehensive reference chronology for Bangladeshi financial market and to evaluate the predictive performance of newly constructed MPI on characterizing Bangladeshi financial sector.

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Abstract For risk and capital measurement, banks and other financial institutions need to meet forthcoming regulatory requirements. However, it is a serious issue to think that meeting regulatory requirements is the sole or even the most important reason for establishing a scientific, sound risk management system. To direct capital to activities with the best risk/reward ratios, managers need reliable risk measures. To stay within the limits imposed by readily available liquidity, by creditors, customers, and regulators, they need estimates of the size of potential losses. They need mechanisms to monitor positions and create incentives for prudent risk-taking by divisions and individuals. Risk measurement deals with the quantification of risk exposures, whereas risk management refers to the overall process by which managers satisfy these needs and follows to define a business strategy, to detect the risks to which are visible, quantifying those risks, and to control and understand the nature of the risks it faces. This research focuses on the economic vulnerability faced by banks in the financial sector in terms of the crises issues perspective of economic distress. Here, the methodology followed is based on the CAMELS framework variables. CAMELS is an abbreviation for: capital adequacy (C), asset (A), management (M), earnings (E), liquidity (L) and sensitivity to market risk (S). Based on these terminologies, a couple of variables should be selected, such as capital asset ratio, non-performing loan, cost income ratio, industry production index, non-interest income, reserve of gold, inflation, stock turnover ratio, real interest rate as component series and return on equity (RoE) as reference series to identify the turning points of economic vulnerability in the banking sector in Bangladesh. Thus, by forecasting the directional changes it could make policymakers aware of changes in the financial markets and banking economy and allow them to undertake preventive steps for remedial purposes. The constructed MPI should have a remarkable lead time of about not less than 6 months on average in case of prediction against the leading for reference Series.By mending the financial efficacy of investment banks. Bangladesh also should improve their corresponding banking system to implement these suggestions.