3,205 research outputs found
The International CAPM and a Wavelet-Based Decomposition of Value at Risk
In this article, we formulate a time-scale decomposition of an international version of the CAPM that accounts for both market and exchange-rate risk. In addition, we derive an analytical formula for time-scale value at risk and marginal value at risk (VaR) of a portfolio. We apply our methodology to stock indices of seven emerging economies belonging to Latin America and Asia, for the sample period 1990-2004. Our main conclusions are the following. First, the estimation results hinge upon the choice of the world market portfolio. In particular, the stock markets of the sampled countries appear to be more integrated with other emerging countries than with developed ones. Second, value at risk depends on the investor's time horizon. In the short run, potential losses are greater than in the long run. Third, additional exposure to some specific stock indices will increase value at risk to a greater extent, depending on the investment horizon. Our results go in line with recent research in asset pricing that stresses the importance of heterogeneous investors.
An Empirical Analysis of Dynamic Multiscale Hedging using Wavelet Decomposition
This paper investigates the hedging effectiveness of a dynamic moving window
OLS hedging model, formed using wavelet decomposed time-series. The wavelet
transform is applied to calculate the appropriate dynamic minimum-variance
hedge ratio for various hedging horizons for a number of assets. The
effectiveness of the dynamic multiscale hedging strategy is then tested, both
in- and out-of-sample, using standard variance reduction and expanded to
include a downside risk metric, the time horizon dependent Value-at-Risk.
Measured using variance reduction, the effectiveness converges to one at longer
scales, while a measure of VaR reduction indicates a portion of residual risk
remains at all scales. Analysis of the hedge portfolio distributions indicate
that this unhedged tail risk is related to excess portfolio kurtosis found at
all scales.Comment: To Appear: Journal of Futures Market
An analysis of spending behaviour under liquidity constraints with an application to financial hedging
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An Empirical Analysis of Dynamic Multiscale Hedging using Wavelet Decomposition
This paper investigates the hedging effectiveness of a dynamic moving window OLS hedging model, formed using wavelet decomposed time-series. The wavelet transform is applied to calculate the appropriate dynamic minimum-variance hedge ratio for various hedging horizons for a number of assets. The effectiveness of the dynamic multiscale hedging strategy is then tested, both in- and out-of-sample, using standard variance reduction and expanded to include a downside risk metric, the time horizon dependent Value-at-Risk. Measured using variance reduction, the effectiveness converges to one at longer scales, while a measure of VaR reduction indicates a portion of residual risk remains at all scales. Analysis of the hedge portfolio distributions indicate that this unhedged tail risk is related to excess portfolio kurtosis found at all scales.
The Effects of International F/X Markets on Domestic Currencies Using Wavelet Networks: Evidence from Emerging Markets
This paper proposes a powerful methodology wavelet networks to investigate the effects of international F/X markets on emerging markets currencies. We used EUR/USD parity as input indicator (international F/X markets) and three emerging markets currencies as Brazilian Real, Turkish Lira and Russian Ruble as output indicator (emerging markets currency). We test if the effects of international F/X markets change across different timescale. Using wavelet networks, we showed that the effects of international F/X markets increase with higher timescale. This evidence shows that the causality of international F/X markets on emerging markets should be tested based on 64-128 days effect. We also find that the effects of EUR/USD parity on Turkish Lira is higher on 17-32 days and 65-128 days scales and this evidence shows that Turkish lira is less stable compare to other emerging markets currencies as international F/X markets effects Turkish lira on shorten time scale.F/X Markets; Emerging markets; Wavelet networks; Wavelets; Neural networks
On the Co-movement of Crude, Gold Prices and Stock Index in Indian Market
This non-linear relationship in the joint time-frequency domain has been
studied for the Indian National Stock Exchange (NSE) with the international
Gold price and WTI Crude Price being converted from Dollar to Indian National
Rupee based on that week's closing exchange rate. Though a good correlation was
obtained during some period, but as a whole no such cointegration relation can
be found out. Using the \textit{Discrete Wavelet Analysis}, the data was
decomposed and the presence of Granger Causal relations was tested.
Unfortunately no significant relationships are being found. We then studied the
\textit{Wavelet Coherence} of the two pairs viz. NSE-Nifty \& Gold and
NSE-Nifty \& Crude. For different frequencies, the coherence between the pairs
have been studied. At lower frequencies, some relatively good coherence have
been found. In this paper, we report for the first time the co-movements
between Crude Oil, Gold and Indian Stock Market Index using Wavelet Analysis
(both Discrete and Continuous), a technique which is most sophisticated and
recent in market analysis. Thus for long term traders they can include gold
and/or crude in their portfolio along with NSE-Nifty index in order to decrease
the risk(volatility) of the portfolio for Indian Market. But for short term
traders, it will not be effective, not to include all the three in their
portfolio
International comovement of stock market returns: a wavelet analysis
The assessment of the comovement among international stock markets is of key interest, for example, for the international portfolio diversification literature. In this paper, we re-examine such comovement by resorting to a novel approach, wavelet analysis. Wavelet analysis allows one to measure the comovement in the time-frequency space. In this way, one can characterize how international stock returns relate in the time and frequency domains simultaneously, which allows one to provide a richer analysis of the comovement. We focus on Germany, Japan, UK and US and the analysis is done at both the aggregate and sectoral levels.
Portfolio management implications of volatility shifts: Evidence from simulated data
Based on weekly data of the Dow Jones Country Titans, the CBT-municipal bond, spot and futures prices of commodities for the period 1992-2005, we analyze the implications for portfolio management of accounting for conditional heteroskedasticity and structural breaks in long-term volatility. In doing so, we first proceed to utilize the ICSS algorithm to detect volatility shifts, and incorporate that information into PGARCH models fitted to the returns series. At the next stage, we simulate returns series and compute a wavelet-based value at risk, which takes into consideration the investor’s time horizon. We repeat the same procedure for artificial data generated from distribution functions fitted to the returns by a semi-parametric procedure, which accounts for fat tails. Our estimation results show that neglecting GARCH effects and volatility shifts may lead us to overestimate financial risk at different time horizons. In addition, we conclude that investors benefit from holding commodities as their low or even negative correlation with stock indices contribute to portfolio diversification.volatility shifts, wavelets, value at risk
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