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Abstract As financial derivative products and systemic risk management tools, stock index futures and options have been greatly developed and widely issued in many countries. Taking the Shanghai Stock Exchange 50 (SSE 50) Index and its derivatives as the research objects, we first analyze the lead–lag relationship between stock index, index futures and index options in the Chinese mainland stock market based on a thermal optimal path (TOP) method whose essence is a non-parametric methodology, and compare the results with two mature markets, namely the Hong Kong and US stock markets. We find: (I) In US and Hong Kong stock markets, the index future leads the index. The index option leads the index future when the index remains stable or in an up-trend, but their lead–lag relation reverses when the index collapses; (II) In the Chinese mainland stock market, the index leads the index future, and the index option leads the index future in the whole period of our investigation; (III) In all three markets, the index option leads the index when the index remains stable or in an up-trend, but their lead–lag relation reverses when the index collapses. Our work gives new and strong evidence that the lead–lag relationship varies in different markets and with different market conditions, which has an important contribution to the reveal of the price discovery function of derivative products. Highlights • Dynamic evolution of lead-lag relationship revealed by a non-parametric TOP method. • Index future leads index in US and Hong Kong, but it's opposite in Chinese mainland. • Index option leads the index in general, but it reverses when index collapses. [ABSTRACT FROM AUTHOR]

Investment is a way of investing the funds in different asset class available such as equity, debt, bonds, fixed deposits, real estate, gold etc. Each asset class has different risk return trade off. This study compares historical returns of different asset class namely Nifty 50, Sensex 30, Equity Mutual fund, Debt Mutual fund, Gold and Real Estate for 10 years horizon i.e 2007-2016. It also takes 20 years data for Nifty 50,Sensex 30 and goldi.efrom 1997-2016 and compares the returns over the years. Further, itdiscusses the impact of recent change in the Indian Financial Budget relating to Long Term Capital Gain Tax (LTCG) over Real Estate investor's returns. This study shows that Debt Mutual fund has given better returns as compared to other asset classes for shorter period of time i.e. for one year period. However, for long term investors, equity mutual funds have performed consistently better as compared to other asset class. This study also reveals that change in budget relating to LTCG holding period for immovable property has made the real asset investment class more attractive for wealthy investors. [ABSTRACT FROM AUTHOR]

Copyright of Financial & Credit Activity: Problems of Theory & Practice is the property of University of Banking of the National Bank of Ukraine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article examines the interdependence of East Asian stock and bond markets. Hierarchical cluster analysis of bond markets of ten regional countries shows that the most similar ones are the following: Indonesia, Malaysia, the Philippines and Singapore. In 2006-2009 Thailand also belonged with this group, however, since 2010 it is a separate cluster. The second cluster includes Hong Kong, the Republic of Korea and China, the third one - Japan, the fourth one - Vietnam. As for regional equity markets, the study shows that regional stock indices respond to the dynamics of American ones to a greater extent than to the dynamics of each other. In addition, Asian indices’ interconnection is chiefly negative. To assess stock indices’ convergence the author employs cluster analysis which divides 16 studied stock exchanges in 7 different groups. According to the obtained results, the author concludes that integration of regional capital markets is the long-term goal. Besides, markets’ integration will be easier and faster within clusters; inter-cluster mergers will be the next step. The basic problem here arises from the Japanese market, which, in the case of forced or ill-conceived program of events, will absorb all other markets or end up outside the integration processes

This study investigates empirically the validity of three hypotheses that have been advanced to explain the tendency of stock market and volatility indices to move in opposite directions, using the notion of Brownian distance correlation. We consider three stock market-implied volatility index pairs, namely, the S&P 500 and the VIX, the DAX 100 and the V1XI, and the N225 and the JNIV. The empirical results support the leverage hypothesis relative to the volatility feedback hypothesis for the pairs S&P 500 and VIX, and N225 and JNIV, and the representativeness and affect heuristics hypothesis relative to the leverage hypothesis for the pairs DAX 100 and V1XI, and N225 and JNIV.

The aim of this study are: (i) to develop an index based on Islamic stock from List of Islamic Securities (DES) and integrate them with the concept of Socially Responsible Investment (SRI) and (ii) to compare the performance of the constructed index with Jakarta Islamic Index (JII) and SRI Kehati Index. We construct the index using Equally Weighted Method from extensive dataset of more than 300 Islamic securities listed in the List of Islamic Securities (DES). Our result is fairly striking as the Islamic SRI index outperform JII and SRI Kehati as well. We conclude that additional screening with ESG parameter does not impact the index performance. To our knowledge, this research is the first to introduce an Islamic SRI stock Index, particularly in Indonesia. Hence, the result could be a consideration for the Indonesia stock exchange (IDX) stakeholder to introduce this index to the market. Furthermore, the results is expected to help investors in selecting stock that meet the standards of Islamic stocks while also fulfill the ESG criteria into their investment portfolios.

The aim of the article is to determine the degree of interdependence of stock markets in separate countries of the European Union, namely: France, Germany, Great Britain, Poland, the Czech Republic and Hungary on the basis of studying the changes in stock indexes, as well as determining the existence of tendencies of approximating the dynamics of the national stock index «PFTS Index» to the corresponding dynamics of stock indexes in surveyed countries. The article analyzes the dynamics of changes in stock indices in the UK (FTSE), Germany (DAX 30), France (CAC 40) and pan-European ones (EURO STOXX 50), as well as changes in stock indices in Poland (WIG 20), Czech Republic (PX), Hungary (BUX). Calculations of the coefficients of pair correlation between changes in stock indices in the studied countries have been performed. The calculation results show a substantial connection between the indicators of changes in stock indices and allow to make a conclusion that in the dynamics of stock indices of national stock markets of the studied EU countries some common trends are observed, moreover, in the behavior of the considered indices common local trends are noticed as well. The author calculated the coefficient of pair correlation between the indicators of changes in the national stock index «PFTS Index» and the stock indices of the «old» and «new» EU countries. The calculations showed that the PFTS Index does not demonstrate a high level of correlation with stock indices of the «old» EU countries and has a tendency of approaching the corresponding dynamics of stock indices of the «new» EU countries.

The paper investigates the effects of financial and investment processes on the Ukrainian share market. The research analyzed and estimated investment climate in Ukraine. The study highlights a comparison of the domestic share market with share markets of other countries. In terms of share capitalization of listed companies in the GDP determined that equity is the most developed in the USA and UK. Largest share markets with highest capitalization rate characterized. The regional distribution of the share market capitalization by continents are shown. The study of the dynamics of Ukrainian and global share indexes revealed that the Ukrainian share market indexes show a constant volatility and unpredictability. Correlation Ukrainian stock indexes with indexes in Europe, Russia and America is very weak, which is a very negative trend of the stock market of Ukraine. The key problems and risks of the domestic investments are defined which are consequences of downturn in the Ukrainian share market.

Copyright of Mexican Journal of Economics & Finance / Revista Mexicana de Economia y Finanzas is the property of Instituto Mexicano de Ejecutivos de Finanzas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Financial Politic & Economic Reviews / Finans Politik & Ekonomik Yorumlar is the property of Journal of Financial Politic & Economic Reviews / Finans Politik & Ekomomik Yorumlar and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To provide accurate value-at-risk (VaR) forecasts for the returns of international stock indices portfolio, this paper proposes a dynamic spatial panel with generalized autoregressive conditional heteroscedastic model (DSP-GJR-GARCH). The proposed model considers the spatiotemporal dependence as well as asymmetric volatility of returns, with the theories of spatial econometrics. We construct an economic spatial weight matrix and set part of the initial estimated values as unknown parameters to get more acute of parameter estimations. After that, we compare the proposed model with three closely related models including GARCH, spatiotemporal-AR, dynamic spatial panel GARCH models, with respect to the performances of daily volatility and VaR forecasting. The empirically comparative data involve six composite indices of major countries, namely USA (DJI), German (DAX), France (FCHI), U.K. (ISEQ), Japan (N225) and China (SSE). The comparative computational results show that, since the proposed model considers spatial dependence and time series correlation simultaneously, it could get more accurate prediction of VaR than the three ones. Moreover, the findings reveal that the predictive accuracy of a spatial regressive model can be improved by considering asymmetric volatility in the disturbances. Thus, we can conclude that DSP-GJR-GARCH model performs better than the other three compared models. [ABSTRACT FROM AUTHOR]

This study examines the efficiency of Borsa Istanbul 100 stock exchange index. For the time series in question, although the most widely used linear and structural break tests detects non-stationarity, in other words, presence of unit root, the non-linear unit root test developed by Kapatenios, Snell and Shin claims the opposite. In that regard, for certain periods there exists a non-linear trend formation. This finding not only precludes supirious differencing for the researcher but also is beneficial for investors while analysing the movement of the stock index. [ABSTRACT FROM AUTHOR]

Copyright of Revue du Financier is the property of Societe Cybel and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this work, we analyze time series on the basis of the visibility graph algorithm that maps the original series into a graph. By taking into account the all-round information carried by the signals, the time irreversibility and fractal behavior of series are evaluated from a complex network perspective, and considered signals are further classified from different aspects. The reliability of the proposed analysis is supported by numerical simulations on synthesized uncorrelated random noise, short-term correlated chaotic systems and long-term correlated fractal processes, and by the empirical analysis on daily closing prices of eleven worldwide stock indices. Obtained results suggest that finite size has a significant effect on the evaluation, and that there might be no direct relation between the time irreversibility and long-range correlation of series. Similarity and dissimilarity between stock indices are also indicated from respective regional and global perspectives, showing the existence of multiple features of underlying systems. [ABSTRACT FROM AUTHOR]

This paper proposes a dynamic equilibrium model that can provide a unified explanation for the stylized facts observed in stock index markets such as the fat tails of the risk-neutral return distribution relative to the physical distribution, negative expected returns on deep OTM call options and negative realized variance risk premiums. In particular, we focus on the U-shaped pricing kernel against the stock index return, which is closely related to the negative call returns. We assume that the stock index return follows a time-changed Lévy process and that a representative investor has power utility over the aggregate consumption that forms a linear regression of the stock index return and its stochastic activity rate. This model offers a macroeconomic interpretation of the stylized facts from the perspective of the sensitivity of the activity rate and stock index return on aggregate consumption as well as the investor’s risk aversion. [ABSTRACT FROM AUTHOR]

Copyright of Studies in Law & Economics / Studia Prawno-Ekonomiczne is the property of Lodz Scientific Society / Lodzkie Towarzystwo Naukowe and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Gated recurrent unit (GRU) networks perform well in sequence learning tasks and overcome the problems of vanishing and explosion of gradients in traditional recurrent neural networks (RNNs) when learning long-term dependencies. Although they apply essentially to financial time series predictions, they are seldom used in the field. To fill this void, we propose GRU networks and its improved version for predicting trading signals for stock indexes of the Hang Seng Indexes (HSI), the Deutscher Aktienindex (DAX) and the S&P 500 Index from 1991 to 2017, and compare the GRU-based models with the traditional deep net and the benchmark classifier support vector machine (SVM). Experimental results show that the two GRU models proposed in this paper both obtain higher prediction accuracy on these data sets, and the improved version can effectively improve the learning ability of the model. [ABSTRACT FROM AUTHOR]