As a
counter to the challenges of recurring financial crisis faced by the
international financial architecture since the early 1980s, the Bank for International
Settlements has designed certain financial standards and codes that are commonly referred to as
the Basel Committee recommendations. The first of such recommendations came in
the form of a set of minimal capital requirements for banks, popularly known as
Basel I standards. These recommendations primarily focused on the definition of
the capital that can absorb losses resulting from credit risk. As recommended
by the Narasimham Committee-I, the Reserve Bank of India implemented the Basel
I norms in April 1992. The banking system of the country responded to these
directives positively and implemented the norms quite successfully.
However, over a period of time, banking systems all over the
world felt Basel I was just a ‘one-fit-all’ approach for capital regulation as
all the corporate borrowings carried the same risk weight of 100%. Secondly, it
resulted in a significant gap between the measurement of regulatory risk
and economic risk, as actually
experienced by individual banks. Thirdly, the norm was considered to be procyclical
as the default risks were normally linked to the levels of activity. Fourthly,
with the convergence of financial markets and technology, banks have become
more sophisticated in measuring and managing risks hence demanding a change in
the regulatory norms. As a sequel to the Basel I norms, the Basel Committee on
Banking Supervision drafted the Basel II
norms, which are to be implemented by the end of 2006. Basel II rests on
three essentials: One, the capital adequacy norms to be improved by making banks
put aside higher levels of capital for high credit risk borrowers and vice
versa; two, effective supervisory review of risk management and capital
allocation by central banks; and three, banks are to be transparent in their
public reporting so that market discipline can ensure better management of
banks. The Reserve Bank of India has in turn released its draft guidelines on
Basel II, thus directing banks to draw a road map for its implementation from
March 2007.
Against this backdrop, the article, “Indian Banking
System—Gearing up for Basel II” attempts to assess the preparedness of the
Indian banking system for the New Basel Capital Accord. It also throws light on
the challenges that the banking system may face while implementing Basel II. The article reveals
that the proportion of risk weighted assets to total funded assets is likely to
go up by 15 to 30% owing to increased operational and market risk. This is
likely to pose a challenge to the ability of nationalized banks other than the
State Bank group and private sector banks, in order to maintain a capital
adequacy of 12% after implementation of Basel II. To meet these challenges, the
article proposes consolidation of banking system through an orderly merger and
acquisition process, based purely on expected synergies. Secondly, it directs
banks to build up reliable databases on risk management practices, particularly
under credit risk, for a minimum period of five years to effectively switch
over to Basel II. Thirdly, banks are advised to nurture a robust credit culture
in terms of credit appraisal, delivery and its monitoring, which alone can help
them remain competitive. Lastly, the Indian banking system has to put corporate
governance of international standards into practice. The article, however, does
not comment on other vital issues such as the competency of human resources to
handle newer technologies being brought into banks for data management; risk
management in forex and money markets and others; delivering business in new
areas such as derivatives, securitization and so on; the need for developing
and creating a pool of leaders who can think strategically and can provide
direction for organizational rebuilding and repositioning in the complex time
that lies ahead. The article, thus, throws open new areas under Basel II
implementation for further research.
The next article, “Computation of EVA in Indian Banks”,
throws light on the current soundness of Indian banking system by computing EVA
for major banks, and states that contrary to the earlier belief, Indian banks
are creating economic value for their shareholders. The study also reveals that
public sector banks outperform their private counterparts, though their cost of
capital is high. Interestingly, the article identifies a negative relationship
between EVA and non-performing assets of banks. It also incidentally supports
the assertion voiced by the previous article that Indian banks are today
prepared well to adopt Basel II, than they were while implementing Basel I.
Market structure is an
important determinant of both competitiveness and consumer welfare. The ongoing
reforms in the banking sector are expected to result in a more competitive
structure but the scope for emergence of a monopolistic market cannot be ruled
out. The article, “Market Structure of the Indian Banking Sector”, attempts to
examine the market structure of Indian banks, using standard methods like
Herfindahl Index, Concentration Index and H-Statistic. The study reveals that
the market structure is monopolistic. This conclusion, however, calls for
further research as banking market structure, unlike other market segments, is
governed by the Central Bank directives. Hence, the delivery process of the
services, pricing of services, modalities of contracts, etc., tend to look
alike and may mislead one to conclude that the market is monopolistic, though
it is actually monolithic.
The relationship between
exchange rates and exports is quite an exciting area of research. It is often
believed that a depreciating domestic currency vis-à-vis a trading partner’s
currency, makes exports more competitive thereby giving a big boost to exports.
However, as more and more countries are deregularizing, and the exchange rate
determination is moving away from the central banks’ regulation to
market determination, depreciation or appreciation of currency is losing its
potency in impacting exports. In fact, research reveals that international
goods market and the foreign exchange market are jointly efficient in the
random walk sense. As a result, there exists no room for arbitrage between the
two markets to profit from temporary price discrepancies. Against this
backdrop, the article “Exchange Rate Volatility and Trade Balance: An Indian
Study”, makes an attempt to find the relationship between the trade balance of
India and exchange rate volatility by using the data for the period, January
1993 to March 2004. The author has used two measures of volatility to find out
its impact on the trade balance of India. The study reveals that exchange rate
volatility has no significant impact on the trade balance of India, while
exchange rate has a significant positive impact. World trade is found to
influence the trade balance negatively. It is also revealed that lagged values
of exchange rate do not have significant impact on the trade balance. In other
words, the study states that there is no ‘J-curve effect’ on Indian economy.
As the corporate world is fast
becoming multi-locational, and markets are getting integrated, forecasting of
exchange rate has become a critical input for corporate decisions. Usually,
those in the corporate world having exposure to foreign currencies stand
exposed to two kinds of risks: Account exposure, where changes are effected in
the value of a firm’s foreign currency denominated accounts due to the change
in exchange rates; and cash flow
exposure, which has a direct impact on the profitability of a firm. Normally,
exchange rates are forecast in two broad ways: By using a multivariate
approach, where it is perceived that a country’s exchange rate has a
relationship with other macroeconomic fundamentals such as money supply,
inflation, interest rate, balance of payments, etc.; and by using univariate
models, such as the autoregressive integrated moving average model. Against this
backdrop, the article, “Forecasting Exchange Rate: A Univariate Out-of-Sample
Approach” uses the Box-Jenkins methodology (ARIMA model) to forecast the
exchange rate movement by using the data from March 1992 to December 2002, and
checks its forecasting ability by using the data from January 2003 to June
2004. The study reveals that the ARIMA model provides a better forecasting of
exchange rates than the simple autoregressive models or moving average models.
The findings of the article encourages further research to check the
superiority of newer models, such as the Bayesiam Vector Auto Regression,
Bayesiam Vector Error Correction Model, Exponential Smooth Transition Auto
Regressive Model, and such others.
Courtesy : IJBM Vol IV No 2 2005
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