Stock Index Returns Research Articles

A dynamic equilibrium model for U-shaped pricing kernels

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.

PENGUJIAN KAUSALITAS ANTARA VARIABEL MAKROEKONOMI DENGAN RETURN PASAR DI BURSA EFEK INDONESIA : SEBUAH PENDEKATAN VECTOR AUTO

Indicators of macroeconomic have major impact on capital markets in general and stocks in particular. Influence of these indicators can be positive or negative. Vector Auto Regression (VAR) is a method of analysis used to predict the time series variable and analyze the dynamic impact factor interference in a system variable. VAR analysis is very useful to assess the linkages between economic variables. This research aims to see the influence of iIndicators of macroeconomic such as the exchange rate (EXCHANGE), interest rate Bank Central of Indonesia Certificates (SBI) and rate of inflation (INFLATION) to market return (REIHSG) in Indonesian Stock Exchange in the period 2004:1-2011:10. Data obtained from the Monthly Stock Price Index Statistics JSX. This research appllying several stages of testing as follows: unit root test, the optimal lag test, Granger causality test and Vector Auto Regression model (VAR). The results of unit root test in this study suggests that the data used for processing in the first degree and VAR Granger test because only the stationary stock index return variable in zero degree (level). On the test results suggested the optimal lag is the lag 3. On the Granger causality test is known that the Granger test variable rate (EXCHANGE) has a one-way impact or the exchange rate (EXCHANGE) affect market return (REIHSG) interest rate of Bank Central of Indonesia Certificates (SBI) and the rate of inflation (INFLATION) has a two direction or impact mutual Causality. These results indicate that there is a weak Granger causality between interest rates Bank Central of Indonesia Certificates (SBI) and rate of inflation (INFLATION) to market return (REIHSG).Keywords: Vector Auto Regressive (VAR), Macroeconomic, Granger Causality, IHSG stock return

How Can We Interpret the Estimates of the Full BEKK Model with Asymmetry? The Case of French and German Stock Returns

This study conducts careful interpretations of the model parameters from the full Baba-Engle-Kraft-Kroner (BEKK) model with asymmetric effects. This study also includes a case study, in which we interpret the full BEKK model parameter estimates from the empirical examinations using French and German stock index returns. More concretely, in this paper, we firstly examine the model formula and obtain general interpretations of the full BEKK model parameters. This shall be particularly helpful to understand not only the structure of the full BEKK model but also the mechanisms of similar multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) models. After the above general considerations, this study also interprets the case results, in which the full BEKK model is applied to French and German stock index returns. The concrete illustrations demonstrated in this case study shall be also very useful for future related research.

On equity risk prediction and tail spillovers

AbstractThis paper studies the impact of modelling time‐varying variances of stock returns in terms of risk measurement and extreme risk spillover. Using a general class of regime‐dependent models, we find that volatility can be disaggregated into distinct components: a persistent stable process with low sensitivity to shocks and a high volatility process capturing rather short‐lived rare events. Out‐of‐sample forecasts show that, once regime shifts are accounted for, accuracy is improved compared to the standard generalized autoregressive conditional heteroscedasticity or the historical volatility model. Volatility plays an important role in controlling and monitoring financial risks. Therefore, by means of a risk management application, we illustrate the economic value and the practical implications of risk control ability of the models in terms of value at risk. Finally, tests for predictability in co‐movements in the tails of stock index returns suggest that large losses are strongly correlated, supporting asymmetric transmission processes for financial contagion in the left tail of return distributions, whereas contagion in reverse direction (gains) is weak.

A Tourism Financial Conditions Index for Tourism Finance

The paper uses monthly data on tourism related factors from April 2005–June 2016 for Taiwan that applies factor analysis and Chang’s (2015) novel approach for constructing a tourism financial indicator, namely the Tourism Financial Conditions Index (TFCI). The TFCI is an adaptation and extension of the widely-used Monetary Conditions Index (MCI) and Financial Conditions Index (FCI) to tourism stock data. However, the method of calculation of the TFCI is different from existing methods of constructing the MCI and FCI in that the weights are estimated empirically. The empirical findings show that TFCI is statistically significant using the estimated conditional mean of the tourism stock index returns (RTS). Granger Causality tests show that TFCI shows strong feedback on RTS. An interesting insight is that the empirical results show a significant negative correlation between F1_visitors (Foreign Visitor Arrivals) and RTS, implying that tourism authorities might promote travel by the “rich”, and not only on inbound visitor growth. The use of market returns on the tourism stock sub-index as the sole indicator of the tourism sector, as compared with the general activity of economic variables on tourism stocks, is shown to provide an exaggerated and excessively volatile explanation of tourism financial conditions.

Historical high and stock index returns: Application of the regression kink model

Motivated by Kahneman and Tversky (1979) and Yuan (2015), this paper investigates whether the influence of the historical high ratio on subsequent stock index returns varies with the distance of the current stock index from its historical high. To explore this issue, a regression kink model with an unknown threshold proposed by Hansen (2017) is used for analysis. Using data from visible stock indices for G7 countries, our empirical evidence shows the presence of threshold effects for most of the G7 stock indices. Moreover, the evidence indicates that the historical high ratio has a strong negative effect on subsequent stock index returns, as the current stock index price is far from its historical high. Overall, these findings support the prospect theory developed by Kahneman and Tversky (1979), in that investors are instinctively risk-seeking (averse) when they face a loss (gain).

A behavioural explanation to the asymmetric volatility phenomenon: Evidence from market volatility index

This study examines how the behavioural explanations, in particular loss aversion, can be used to explain the asymmetric volatility phenomenon by investigating the relationship between stock market returns and changes in investor perceptions of risk measured by the volatility index. We study the behaviour of India volatility index vis-à-vis Hong Kong, Australia and UK volatility index, and provide a comprehensive comparative analysis. Using Bai-Perron test, we identify structural breaks and volatility regimes in the time series of volatility index, and investigate the volatility index-return relation during high, medium and low volatility periods. Regardless of volatility regimes, we find that volatility index moves in opposite direction in response to stock index returns, and contemporaneous return is the most dominating across the four markets. The negative relation is strongest for UK followed by Australia, Hong Kong and India. Second, volatility index reacts significantly different to positive and negative returns; negative return has higher impact on changes in volatility index than positive return across the markets over full-sample and sub-sample periods. The asymmetric effect is stronger in low volatility regime than in high and medium volatility periods for all the markets except UK. The strength of asymmetric effect is strongest for Hong Kong and weakest for India. Finally, negative returns have exponentially increasing effect and positive returns have exponentially decreasing effect on the changes in volatility index.

Modelling asymmetric conditional dependence between Shanghai and Hong Kong stock markets

This paper investigates the asymmetric conditional dependence between Shanghai and Hong Kong stock index returns, to assess the impact of the recent financial recession on Chinese equity markets using the Copula approach. We first propose methods for optimal model selection when constructing the conditional margins. The joint conditional distribution is then modelled by the time-varying copula, where the generalised autoregressive score (GAS) model of Creal et al. (2013) is used to capture the evolution of the copula parameters. Upper and lower parts of the bivariate tail are estimated separately in order to capture the asymmetric property. We find the conditional dependence between the two markets is strongly time-varying. While the correlation decreased before the crisis, it increased significantly prior to 2008, pointing to the existence of contagion between the two markets. Moreover, we find a slightly stronger bivariate upper tail, suggesting the conditional dependence of stock returns is more significantly influenced by positive shocks in China. This finding is further confirmed by a test for asymmetry which shows that the difference between upper and lower joint tails is significant.

Capital Asset Pricing Model, Theory and Practice: Evidence from USA (2009-2016)

This study discussed the Capital Assets Pricing model (CAPM) and its ability to measure the required return, the researcher tested this model on Amazon Company listed in S&P 500 during the period (2009-2016), to measure the impact of beta stock and market index return on the required return. Multiple regression model was used to test the effect of independent variables (Beta stock, Market Index Return) on the dependent variable (Required return), it should be noted that there is a statistically significant impact of the US stock market Return (S&P500) and Amazon stock Beta factor on Amazon stock required return, and the study model explanatory was 20% , this means that 20% of the changes in the required return are due to beta and market return, and 80% of the changes due to other factors, also find that CAPM can be applied on efficiency markets and huge companies.The researcher recommends applying the variables of the study on a group of large companies in the S&P 500 index, and looking for other factors that may affect the required return.

Intraday online investor sentiment and return patterns in the U.S. stock market

Abstract We implement a novel approach to derive investor sentiment from messages posted on social media before we explore the relation between online investor sentiment and intraday stock returns. Using an extensive dataset of messages posted on the microblogging platform StockTwits, we construct a lexicon of words used by online investors when they share opinions and ideas about the bullishness or the bearishness of the stock market. We demonstrate that a transparent and replicable approach significantly outperforms standard dictionary-based methods used in the literature while remaining competitive with more complex machine learning algorithms. Aggregating individual message sentiment at half-hour intervals, we provide empirical evidence that online investor sentiment helps forecast intraday stock index returns. After controlling for past market returns, we find that the first half-hour change in investor sentiment predicts the last half-hour S&P 500 index ETF return. Examining users’ self-reported investment approach, holding period and experience level, we find that the intraday sentiment effect is driven by the shift in the sentiment of novice traders. Overall, our results provide direct empirical evidence of sentiment-driven noise trading at the intraday level.

Predicting international stock returns with conditional price-to-fundamental ratios

Abstract Taking the perspective of international asset allocation, this paper tests if predictive regressions conditional on time-series and cross-sectional information can improve forecasts of stock index returns. We use different current price-to-fundamental ratios as predictors and condition the sample on the indicator if time-series and cross-section deliver consistent versus opposing signals. Using panel regressions, we find that only consistent ratios (i) display significant mean-reverting behavior, (ii) provide strong in-sample as well as out-of-sample evidence for return predictability, and (iii) yield economic gains in a Bayesian asset allocation framework.

American Option Pricing Under GARCH With Non-Normal Innovations

As it is well known from the time-series literature, GARCH processes with non-normal shocks provide better descriptions of stock returns than GARCH processes with normal shocks. However, in the derivatives literature, American option pricing algorithms under GARCH are typically designed to deal with normal shocks. We thus develop here an approach capable of pricing American options with non-normal shocks. The approach uses an equilibrium pricing model with shocks characterized by a Johnson Su distribution and a simple algorithm inspired from the quadrature approaches recently proposed in the option pricing literature. Numerical experiments calibrated to stock index return data show that this method provides accurate option prices under GARCH for non-normal and normal cases.

Forecasting the variance of stock index returns using jumps and cojumps

Modeling and forecasting the variance of asset returns is an important issue in many financial applications. Previous studies have examined the roles of both the continuous and jump components of the total variance in forecasting. This paper considers how index-level jumps and cojumps can be used across index constituents for forecasting the variance of index-level returns. A range of jump and cojump detection methods, based on daily and intraday data, are used. Moving beyond the magnitudes of the past index jumps used in existing models, it is found that incorporating the estimated jump intensity from a point process model leads to forecast accuracy gains. Another important contribution is the finding that cojumps across underlying constituent stocks are also useful for forecasting index-level behaviour. Improvements in forecast performance are particularly apparent on the days when jumps or cojumps occur.

Semi-Monthly and Turn-of-the-Month Seasonality in Stock Returns : Evidence from Emerging Markets

Behaviour of stock prices has often challenged the established theories and models of financial literature. Monthly effect is also termed as semi-monthly effect and turn-of-the-month effect are among such anomalies which have been documented in stock markets across the world. It refers to the tendency of financial assets to exhibit abnormal returns during the first of the month and at the turn of the month. The objective of the present study was to explore the existence of semi-monthly effect and turn-of-the-year effect in the stock index returns of nine emerging stock markets namely, Argentina, Brazil, China, India, Indonesia, Malaysia, Mexico, Russia, and Taiwan over a time span of more than 17 years commencing from January 1997 through March 2014. The returns of the first half of the month and turn-of-the-month have been compared with the return of second half and rest of the trading month using independent sample t - test, Mann-Whitney U test, and dummy variable regression. The results indicated the presence of semi-monthly effect in four stock markets namely India, Indonesia, Russia, and Taiwan, which exhibited higher mean returns during the first half of the trading month, indicating the presence of semi-monthly effect. The turn-of-the-month represented by sequence of four trading days (-1 to +3) recorded statistically significant positive and higher mean returns than the remaining trading days of the month in the majority of the stock markets investigated.

Time-varying dependence structures of equity markets of China, ASEAN and the USA

ABSTRACTPopular time-varying Copulas are used to analyse the dependence structure between the CSI 300 index return, the S&P 300 index return and the Association of South East Asian Nations (ASEAN) 80 index return. Results show that these three types of stock index returns have obvious time-varying characteristics. The US sub-prime mortgage crisis has strengthened the correlation among the three-stock index returns, whereas the dependence between China and the ASEAN stock markets is more sensitive to the financial crisis. The time-varying features of the extreme dependence risk between China-ASEAN and China-US are very different.

ANALISIS VARIABEL MAKROEKONOMI TERHADAP KINERJA REKSADANA CAMPURAN

Saat ini semakin banyak tersedia pilihan instrumen investasi. Salah satu instrumen investasi adalah reksadana. Kondisi makroekonomi Indonesia mempengaruhi kinerja investasi, termasuk investasi reksadana. Salah satu jenis reksadana adalah reksadana campuran. Penelitian ini bertujuan menguji dan menganalisis pengaruh return IHSG, return Kurs USD, return JIBOR Interest Rate dan return Obligasi Pemerintah Indonesia terhadap kinerja reksadana campuran. Periode penelitian adalah selama satu tahun (2012), menggunakan data harian. Total reksadana campuran di BEI berjumlah 120, yang memenuhi kriteria menjadi sampel sebanyak 86. Metode yang digunakan untuk menjawab permasalahan penelitian adalah regresi linier berganda. Ditemukan bahwa faktor makroekonomi yang berpengaruh signifikan terhadap return reksadana campuran adalah return IHSG dan Suku Bunga JIBOR.Nowadays investment instruments are growing. One of the investment instruments is mutual fund. Indonesian macroeconomic conditions affected the performance of investments, including on mutual funds. One type of mutual fund is balance mutual funds. This study aims to examine and analyze the effect of stock index returns, return of USD exchange rate, return of JIBOR Interest Rate, and return of government bonds of Indonesia to the performance of balance mutual funds. Observation period is one year (2012), using daily data. Total balance mutual funds in IDX are 120, which meets the criteria of the sample were 86. Method used to answer the research problem is multiple linear regressions. It found that macroeconomic factors that significantly influence the performance of balance mutual funds are returns JCI and JIBOR interest rate return.

Apakah Indeks Saham Syariah Indonesia (ISSO) Memediasi Pengaruh Nilai Tukar Terhadap Return Saham Syariah ?

This study aims to analyze the effect of Exchange Rate on Stock Return with Sharia Stock Index as Mediation.
 The population in this study is the sharia shares listing on the Indonesia Stock Exchange. Sampling using purposive sampling method, with criteria List of sharia firms in the Property and Real Estate sectors which are categorized as Sharia (ISSI) Index which is constant (fixed) during December 2015-May 2016 period. Data analysis using regression analysis.
 The result of the research shows that the exchange rate has an effect on the Return of Sharia Shares and Sharia Stock Index of Indonesia influential on Sharia Return Shares. Indonesia Sharia Stock Index is able to mediate between Exchange Rate and Sharia Return Shares
 Keywords : Nilai Tukar, Indeks Saham Syariah Indonesia, Return Saham Syariah.

Explore the Impact of the Trading Value, The Oil Price and Quantitative Easing Policy on the Taiwan and Korea Stock Market Return with Quantile Regression

This paper aims to apply the quantile regression analysis to explore the impacts of the stock market trading value, change in international oil prices, and the US implementation of Quantitative easing monetary policy on Taiwan’s and Korea’s stock index returns. This study is in accordance with the 2008 US implementation of quantitative policy to conduct research on 53-month data collected from April 2004 to February 2013 in order to explore the differences between before and after the US implementation of quantitative policy. The results find that under situations of high distribution of stock index returns, Taiwan’s and Korea’s stock markets reveal the same phenomenon of “the stock price increases and the trading volume rises, the stock price declines and the trading volume descends”. Meanwhile, under situations of low distribution of stock index returns, the Korea’s increasing stock trading value will cause stock index returns to fall. Noteworthy, under situations of low distribution of stock index returns, oil price changes are found to have positive effects on Taiwan’s and Korea’s stock index returns. Finally, the US implementation of quantitative easing monetary policy is indicated to have non-significant influence on Taiwan’s and Korea’s stock index returns. Further investigating whether there are inconsistencies before and after the implementation of quantitative policy regarding the impacts between these two nations’ stock trading values and oil price changes on stock index returns, the results show no differences.

A Dynamic Equilibrium Model for U-Shaped Pricing Kernels

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 risk-neutral return distribution relative to 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 the time-changed Levy 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 the aggregate consumption as well as the investor's risk aversion.

Linkage between India Implied Volatility Index and Stock Index Returns

The present study examines the linkage between the change in implied volatility index and the underlying stock index return in the Indian stock market. The empirical results revealed that the contemporaneous return is the most important factor that determines the changes in the current India implied volatility. Besides, the empirical evidences confirm the negative asymmetry volatility-return relation, supporting the behavioral explanations (the affect and representativeness heuristics) rather than financial leverage hypothesis.