The Risk Management and Financial Stability in Developing Stock Market Name

The Risk Management and Financial Stability in Developing Stock Market

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ABSTRACT

In this paper has been developed in two sections; the first part attempts to examine the financial instability indicators while the second part attempts to examine the operational risk management in the developing stock markets. The financial instability indicators can be divided on different ways. It can be divided on the different perspective: liquidity indicators, solvency indicators, profitability indicators and activity indicators. The liquidity indicators explore the firm’s ability to meet its short-term liabilities or to cover its long-term liabilities with long-term assets. Higher liquidity implies a lower probability of default. However, to avoid the crises in the first instance, market participants, and financial authorities should be effectively alert to the stress of the financial system at its earliest stage.

It is therefore highly desirable from a financial policy point of view to construct an early warning system, constituted by a core set of economic and financial indicators, for facilitating pre-emptive actions to prevent financial crises. The solvency indicators describe the firm’s ability to meet its long-term liabilities. Generally, a higher debt ratio and a longer debt repayment period result in a higher probability of default. By contrast, an ability of the company to generate sufficient funds for debt repayment and a higher proportion of internal funds educe this probability. The profitability indicators explain how the company generates profit and the quantity of inputs it uses to do so. Generally, higher profitability implies a lower probability of default.

The activity indicators measure the efficiency of use of various inputs by the company. From the financial point of view, it would be ideal if the company generated sales/profit by using the minimum amount of resources.

However, we will focus mainly on the JT index as the financial instability indicator and some other minor ones such as the liquidity measure.

The potential influence of the individual indicators on corporate bankruptcy can be demonstrated on the following simplified example. One classic symptom of declining solvency is when a company fails to make efficient use of inputs (its activity indicators deteriorate). Cash flows into the firm consequently shrink, leading to a decline in the firm’s ability to meet its short-term liabilities (its liquidity indicators deteriorate).  It also examines how these indicators can be used to predict the upcoming stock correction in the emerging markets. This essay has also attempted to examine the operational risk management in the emerging markets as compared to the developed stock markets such as United States stock market and some of the contributions on the modeling of the economic capital.

Furthermore, this paper also examines the performance benefits of using conditioning information in mean-variance strategies in the US stock returns. This essay finds that after adjusting for trading costs, there are no significant performance benefits in using conditioning information in mean-variance strategies. However, this result stems from the high turnover that is required to implement dynamic trading strategies.

1. INTRODUCTION

The global financial turmoil has shaped financial markets and brought many issues into the light. Over the past two decades, the Asian Financial Crisis and the global financial crisis originated from US subprime loans have rekindled the awareness of financial authorities worldwide of the importance of a sound financial system for sustainable growth. As a result, research on effective framework for monitoring financial stability has drawn increased attention in policy discussions.

We are going to examine the JT Index as an indicator of financial stability of emerging markets presents a financial scoring model estimated on Czech corporate accounting data. Using the model estimated in this way, an aggregate indicator of the creditworthiness of the Czech corporate sector (named as JT index) is then constructed and its evolution over time is shown. The aggregate indicator of financial stability is constructed as a weighted average of a set of selected indicators covering different aspects of financial stability.

The second is operational risk management and implications for Bank’s Economic

Capital analyses and models the real operational data of an anonymous Central European Bank.

However, this research showed that the probability weighed moment (PWM) is quite consistent when the data is limited as it was able to provide reasonable and consistent capital estimates. From a policy perspective it should be hence noted that banks from emerging markets such as the Central Europe are also able to register operational risk events and the distribution of these risk events can be estimated with a similar success than those from more mature markets.

Aim/ Objective

• To construct a financial stability indicator based on the prediction of business failure.
• To predict the risk management in the developing markets in future
• To determine some of the recommendations to be applied in trying to solve the financial instability.
• To assess financial-system stability.

LITERATURE REVIEW

2. Financial stability indicators:

2.1: JT index as the financial indicator

JT index is constructed from the estimated aggregate indicator of the creditworthiness of the Czech corporate sector and its evolution over time is shown. The indicator assist in the estimation of the risks of this sector going forward and broadens the existing analytical set-up used by the Czech National Bank for its financial stability analyses. The outcome shows that the creditworthiness of the Czech corporate sector steadily improved between 2004 and 2006, but deteriorated in 2007 and 2008 what could be explained through global market turbulences. The index is an equal-variance weighted average of seven variables associated with stock market  returns, the volatility of stock returns and foreign exchange, liquidity, sovereign debt spreads, international reserves, and the risk and profitability of the banking system.

2.11: Assessing the financial stability of the economy.

Financial scoring is routinely used to assess the creditworthiness of individual firms. If we have aggregated data for the whole non-financial sector, we can imagine this sector as one large hypothetical firm with an aggregated balance sheet. Furthermore, given the use of relative indicators only, we can view the aggregated indicators as elements of the average firm in the sector. Assuming a degree of homogeneity, the estimated model can be applied to the aggregated indicators of non-financial corporations. If the situation in the sector takes a turn for the worse, the financial indicators of firms will deteriorate on average. This will be reflected in a falling score of the average representative firm.  But, however, the scope and in homogeneity of the sample of firms on which the model was estimated place some challenges on the model. We could get better results by decomposing the sample into several of more homogeneous segments and then estimating the model for these groups of firms separately. In the ideal scenario, we would decompose the firms by size and area of economic activity. Compared to the small number of bad firms in the data source used, however, this is not possible. Given the aforementioned challenge, the leading score is probably underestimated and thus the creditworthiness is overestimated, compared to the higher level of risk of the small enterprises excluded from the aggregate data.

However, for appropriate credit risk management methods both backward and forward are recommended to be applied. In other words, modifications of the JT index should be aided by forward looking indicators such as stock market data, consumers/producers confidence indices, management surveys, consensus forecasts, number of purchase orders etc.

2.2: Liquidity measure:

This essay attempts to investigate the information content of the limit order book (LOB) on the developing stock markets such as the Saudi Arabia stock market, a purely order-driven market, for predicting future stock price volatility. It also tries to analyze how this relationship evolves during extreme market conditions. An electronic limit order book (LOB) is a sample of the aid which allows traders to post bids and offers on the system provides information about aggregate liquidity supply and trading interests measures which incorporate information beyond the top of the LOB presents a more combined assessment of current LOB liquidity because buy and sell orders can cluster away from the best bid and ask prices (Rosu, 2009).

2.21 Liquidity-Volatility relation

Traditionally, limit orders are viewed as non-aggressive orders that supply liquidity to the market while market orders are viewed as aggressive orders that demand liquidity (Glosten, 1994; Seppi, 1997). And therefore, the information content of the LOB is joined to the question of whether informed traders use the limit orders.

However, using an experimental design, Bloomfield, O’Hara, and Saar (2005) find that in an electronic market, informed traders submit more limit orders than market orders.

According to Foucault, (Moinas and Theissen 2007), the LOB is a conduit for volatility information because of the option-like features of limit orders. As prices of option depend on volatility, limit order traders should incorporate volatility information in their limit order submissions and therefore, the LOB should contain private volatility information.

On the other hand (Naes and Skjeltorp 2006) capture the LOB liquidity by measuring the LOB slope and find a negative relationship between the liquidity and future return volatility for the large and medium cap stocks listed on the Oslo Stock Exchange (OSE). This chapter argues that policies are most effective if they target the constraints that underlie the weakness in credit. But it cautions policymakers to be aware of the fiscal costs and implications for financial stability of credit-supporting policies.

2.22 Predictive power of LOB during extreme market movement

Limit order traders are considered as passive traders who supply liquidity to the market and hence they are faced with many risks such as the pickoff risk, and the risk associated with price uncertainty. However, during periods when these risks are heightened, limit order traders may strategically choose to reduce liquidity supply, either by shifting depth away from the quotes or reducing the depth provided at a given price.

Goldstein and Kavajecz (2004) examined that during periods with heightened uncertainty, the value of the free option associated with supplying liquidity via an electronic LOB becomes so high that market participants protect themselves by withdrawing depth and in certain cases, moving away from the LOB. Hence, information content of.............