Springer Science and Business Media LLC

Seven different Japanese Yen interest rates recorded on a daily basis for the period from 1986 to 1992 are simultaneously analyzed. By introducing a new concept of ‘short term trend’, we decompose each interest rate series into three components, ‘long termtrend’, ‘short term trend’ and ‘irregular’. It is obtained by a two step lowess smoothing technique. After that, a multivariate autoregressive model (MAR) is fitted to the vector valued time series obtained by combining those seven irregular components. The decomposition and MAR model fitting were quite satisfactory. It enables us to understand well various aspects of interest rate series from the trends, the MAR (2) coefficients and its residuals. The result is compared with the decomposition through sabl and the advantages of our procedure will be demonstrated in relations to other parametric model fitting like ARCH or GARCH. Based on the decomposition we can have better daily prediction and more stable long term forecasting.

This paper evaluates and compares the performance of three-asset pricing models—the capital asset pricing model of Sharpe (J Finance 19:425–442, 1964), the three-factor model of Fama and French (J Financ Econ 33:3–56, 1993), and the five-factor model (Fama and French in J Financ Econ 123:1–22, 2015)—in the Shanghai A-share exchange market. Our results do not support the superiority of the five-factor model and show that the three-factor model outperforms the other models. We also verify the redundancy of the book-to-market factor and confirm the findings of Fama and French (2015).

An efficient method for valuing credit derivatives based on three entities is developed in an affine framework. This includes interdependence of market and credit risk, joint credit migration and counterparty default risk of three firms. As an application we provide closed form expressions for the joint distribution of default times, default correlations, and default swap spreads in the presence of counterparty default risk.

This study assesses the effects of real exchange rate and remittance inflows on India's total service exports, comprising traditional and modern service exports, spanning the annual data from 1990 to 2020. The control variables for the service export function include developments in the banking sector and the stock market and net inflows of foreign direct investment. The ARDL model is the estimating technique of the present study. The real exchange rate has an adverse effect on total, traditional, and modern service exports, according to the long-run outcomes of the ARDL model. Remittance inflows are interestingly shown to support modern service exports while impeding total and traditional service exports. The growth of the banking sector is beneficial for traditional and total service exports, but it has a negative impact on modern service exports. All service exports are benefited by stock market development; however, net FDI inflows negatively impact all forms of service exports. Based on these results, the policymakers in India are advised to maximize the effective utilization of remittance inflows in traditional service exports. Additionally, proactive intervention by the central bank is recommended to mitigate the adverse effects of the real exchange rate on traditional and modern service exports. This study also provides valuable insights for the policymakers and practitioners seeking to enhance India's service export performance while navigating the complexities of real exchange rates, remittance inflows, and financial factors.

This study examines the relationship between industry concentration and level of firm efficiency and their effect on cross-sectional stock returns in Australian market. Our analysis shows that industry concentration and firm efficiency have independent effects on stock returns. By forming 25 double-sorted portfolios based on industry concentration and firm efficiency, INEFFICIENT firms in concentrated industry earn highest stock returns, while EFFICIENT firms in concentrated industry earn lowest stock returns. Also we find that industry concentration appears to be associated with market share while efficiency has a greater effect on firm earnings. In our cross-sectional regressions, industry concentration shows a positive relationship with average stock returns while firm efficiency shows a negative association with average stock returns. The concentration and efficiency effects are persistent throughout the sample period and is robust after controlling for size and book-to-market.

In the present paper, a discrete version of Itô’s formula for a class of multi-dimensional random walk is introduced and applied to the study of a discrete-time complete market model which we call He’s framework. The formula unifies continuous-time and discrete-time settings and by regarding the latter as the finite difference scheme of the former, the order of convergence is obtained. The result shows that He’s framework cannot be of order 1 scheme except for the one dimensional case.

The paper re-investigates the efficiency of the East European emerging markets of the Czech Republic, Hungary, Poland and Russia analyzed by Rockinger and Urga (2000, 2001) based on the data from September, 1995 through December, 2004. We propose a first-order autoregressive (AR (1)) type time varying parameter model with a non-stochastic linear time trend including the random walk (RW) type model as a special case. The observed data rejects the RW type model for the AR (1) type one. The markets exhibit dynamic efficiency for all the four countries in the sense that the linear time trend approaches to zero over time. The empirical result for the Russian markets differs from that of Rockinger and Urga (2000).

We present a derivative pricing and estimation methodology for a class of stochastic volatility models that exploits the observed 'bursty' or persistent nature of stock price volatility. Empirical analysis of high-frequency S&P 500 index data confirms that volatility reverts slowly to its mean in comparison to the tick-by- tick fluctuations of the index value, but it is fast mean- reverting when looked at over the time scale of a derivative contract (many months). This motivates an asymptotic analysis of the partial differential equation satisfied by derivative prices, utilizing the distinction between these time scales. The analysis yields pricing and implied volatility formulas, and the latter provides a simple procedure to 'fit the skew' from European index option prices. The theory identifies the important group parameters that are needed for the derivative pricing and hedging problem for European-style securities, namely the average volatility and the slope and intercept of the implied volatility line, plotted as a function of the log- moneyness-to-maturity-ratio. The results considerably simplify the estimation procedure. The remaining parameters, including the growth rate of the underlying, the correlation between asset price and volatility shocks, the rate of mean-reversion of the volatility and the market price of volatility risk are not needed for the asymptotic pricing formulas for European derivatives, and we derive the formula for a knock-out barrier option as an example. The extension to American and path-dependent contingent claims is the subject of future work.