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Investor
Confidence in an Underdeveloped Stock Market
--
Diganta Mukherjee
This
paper studies the behavior of the stock price in a market
characterized by the presence of one large trader and a
fringe of marginal `noise' traders. The study shows that
price volatility and sensitivity excessively depend on the
large trader's behavior. The paper also comments on the
implications of these properties for the derivatives market.
©
2007 IUP . All Rights Reserved.
Persistence
Characteristics of European Stock Indices
--
Joanna M Lipka and Cornelis A Los
This
paper measures the degrees of persistence of the daily returns
of eight European stock market indices, after their lack
of ergodicity and stationarity has been established. The
proper identification of the nature of the persistence of
financial time series forms a crucial step in deciding what
kind of diffusion modeling of such series might provide
invariant results. The results indicate that ergodicity
and stationarity are very difficult to establish with only
daily observations of market indices and thus, various price
diffusion models cannot be successfully identified. However,
the measured degrees of persistence point to the existence
of long-term dependencies or Long Memory (LM), most likely
of a non-linear nature. Global Hurst exponents, computed
from wavelet multi-resolution analysis using a fractal Brownian
motion model, measure the degree of persistence of the data
series. The FTSE turns out to be anti-persistent, i.e.,
an ultra-efficient market with abnormally fast mean-reversion,
faster than that of a geometric Brownian motion. The various
measurement methodologies reported in the financial literature
produce non-unique empirical results. Thus, it is very difficult
to obtain definite conclusions regarding the presence or
absence of long-term dependence phenomena based on the global
Hurst exponents. Most stock markets in Europe appear to
be slightly anti-persistent, but more powerful methods,
such as the computation of the multifractal spectra of financial
time series from intra-day pricing data, may be required
to establish this as a definite scientific conclusion. Still,
we demonstrate that the visualization of the wavelet resonance
coefficients and their power spectra, in the form of localized
scalograms and averaged scalegrams, forcefully assist the
detection and measurement of several types of persistent
market price diffusion.
©
2007 IUP . All Rights Reserved.
Convergence
of Futures and Spot Prices: A Cointegration Analysis
-- Naveen Prakash Singh and
V Shanmugam
National
online future exchanges were allowed to be set up in the
late 2003 by the government with the purpose of helping
efficient price discovery and providing them with an effective
mechanism to hedge their price risk. This would not have
been possible if the prices discovered by the futures market
participants were not relevant to the spot market situation.
This pioneering effort taken to analyze the convergence
of future prices with the spot market prices using cointegration
analysis proved that the future and the spot prices have
effectively converged, asserting that futures markets offer
the perfect mechanism for hedging their price risk in selected
crops.
©
2007 IUP . All Rights Reserved.
A
Simulation-Based Approach to Measure Concentration Risk
-- Joocheol Kim and Duyeol Lee
Asymptotic
Single Risk Factor (ASRF) model is used to derive the regulatory
capital formula of Internal Ratings-Based approach in the
new Basel accord (Basel II). One of the important assumptions
in ASRF model for credit risk is that, the given portfolio
is well-diversified so that one can easily calculate the
required capital level by focusing only on systematic risk.
In real world, however, idiosyncratic risk of a portfolio
cannot be fully diversified away, causing the so-called
concentration risk problem. This paper suggests the simulation-based
approach for measuring concentration risk using bank capital
dynamic model. This approach is especially suitable for
a portfolio with relatively small to medium number of obligors
and relatively large-sized loans.
©
2007 IUP . All Rights Reserved.
Loss
Distribution Estimation, External Data and Model Averaging
-- Ethan Cohen-Cole and Todd Prono
This
paper discusses a proposed method for the estimation of
loss distribution using information from a combination of
internally derived data and data from external sources.
The relevant context for this analysis is the estimation
of operational loss distributions used in the calculation
of capital adequacy. A robust, easy-to-implement approach
that draws on Bayesian inferential methods has been presented.
The principal intuition behind the method is to let the
data itself determine how they should be incorporated into
the loss distribution. This approach avoids the pitfalls
of managerial choice on data weighting and cut-off selection
and allows for the estimation of a single loss distribution.
©
2007 IUP . All Rights Reserved.
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