The Skewness of the Stock Market over Long Horizons

2020 ◽  
Author(s):  
Anthony Neuberger ◽  
Richard Payne
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Stock Index ◽  
Leverage Effect ◽  
Higher Moments ◽  
Data Generating Process ◽  
Short Horizon ◽  
Stock Index Returns ◽  
Standard Techniques ◽  
Daily Returns

Abstract Higher moments of long-horizon returns are important for asset pricing but are hard to measure accurately using standard techniques. We provide theory showing that short-horizon (e.g., daily) returns can be used to construct precise estimates of long-horizon (e.g., annual) moments without making strong assumptions about the data-generating process. Skewness comprises two components: skewness of short-horizon returns and a leverage effect, that is, covariance between variance and lagged returns. We provide similar results for kurtosis. An application to U.S. stock index returns shows that skew is large and negative and attenuates only slowly as one moves from monthly to multiyear horizons.

In Search of Stock Market Proxy to Calculate Systematic Risk (Beta) of Stocks in Indonesia Stock Exchange

2020 ◽  
Vol 29 (2) ◽  
pp. 80-88
Author(s):  
Mochammad Chabachib
Keyword(s):  
Stock Market ◽  
Real World ◽  
Stock Price ◽  
Price Index ◽  
Stock Exchange ◽  
The Other ◽  
Stock Index ◽  
Market Return ◽  
Stock Market Return ◽  
Stock Index Returns

The calculation of beta stock in Indonesia is still debatable to this day. Though many researchers who have used sophisticated methods mathematically, the assumptions applied in developing the methods are impossible to happen in the real world, such as the ability of stock market return the day after (lead) affects the market return today. This study was conducted to assess the stock price index in Indonesia Stock Exchange that can be used as a proxy of stock market in Indonesia. The results of this study showed that there was a gap between beta stocks counted with JCI return as a market proxy with beta stocks counted with index returns of LQ-45, SRI-KEHATI, PEFINDO-25, BISNIS-27, IDX-30 and KOMPAS-100. This study has also found that the beta counted by using KOMPAS-100 return produced the smallest standard error of the estimate (SEE) that it was more applicable compared to the other stock index returns.

Volatility transmission within financial markets during the COVID-19 pandemic: are faith-based investors well off in Tunisia?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mustapha Ishaq Akinlaso ◽  
Aroua Robbana ◽  
Nura Mohamed
Keyword(s):  
Stock Market ◽  
Stock Index ◽  
Lower Amount ◽  
Leverage Effect ◽  
Market Returns ◽  
Content Type ◽  
Volatility Transmission ◽  
Standard And Poor's ◽  
Future Return ◽  
Diversification Benefit

Purpose This paper aims to investigate the risk-return and volatility spillover within the Tunisian stock market during the COVID-19 pandemic analyzing both the Islamic and conventional stocks’ performance. Design/methodology/approach Both symmetric (GARCH and GARCH-M) and asymmetric (Threshold GARCH and Exponential GARCH) models are used to analyze the market returns and volatility response. Standard and Poor’s (S&P) index has been used to test both the Islamic and conventional stocks within the Tunisian stock market. Findings The findings suggest that both Tunisia Islamic and conventional stock markets are highly persistent; however, the conventional stock index showed a negative return spillover on the Islamic stocks during the pandemic. The conventional stock index has also shown a higher exposure to risk for a lower amount of return, and evidence of potential diversification benefit between both indexes was found during the pandemic, whereas the Islamic market showed a positive leverage effect, indicating a positive correlation between past return and future return; the conventional index implied a negative leverage effect. Originality/value The value of this paper emerges in studying three main aspects that are specific to the Tunisian stock market. This includes COVID-19 effect of return spillovers, volatility transmission across both conventional and Islamic stock market within the local financial market.

scholarly journals A STUDY OF INDONESIA’S STOCK MARKET

2019 ◽  
pp. 465-476 ◽  
Author(s):  
Dinh Hoang Bach Phan ◽  
Thi Thao Nguyen Nguyen
Keyword(s):  
Exchange Rate ◽  
Interest Rate ◽  
Stock Market ◽  
Least Squares ◽  
Generalized Least Squares ◽  
Stock Index ◽  
Monthly Data ◽  
Generalized Least Squares Estimator ◽  
The Interest Rate ◽  
Stock Index Returns

Using monthly data from January 1995 to December 2017, this paper tests whetherIndonesian stock index returns are predictable. In particular, we use eight macrovariables to predict the Indonesian composite and six sectoral index returns using thefeasible generalized least squares estimator. Our results suggest that the Indonesianstock index returns are predictable. However, the predictability depends not only onthe macro predictor used but also on the indexes examined. Second, we find that themost popular predictor is the exchange rate, followed by the interest rate. Finally, ourmain findings hold for a number of robustness tests.

scholarly journals The Disappearing Calendar Anomalies in the Singapore Stock Market

2006 ◽  
Vol 11 (2) ◽  
pp. 123-139 ◽  
Author(s):  
Wing-Keung Wong ◽  
Aman Agarwal ◽  
Nee-Tat Wong
Keyword(s):  
Stock Market ◽  
Efficient Market Hypothesis ◽  
Stock Index ◽  
January Effect ◽  
Trading Behavior ◽  
Recent Period ◽  
Efficient Market ◽  
Day Of The Week ◽  
Calendar Anomalies ◽  
Stock Index Returns

This paper investigates the calendar anomalies in the Singapore stock market over the recent period from 1993-2005. Specifically, changes in stock index returns are examined surrounding January (the January effect), on different days of the week (the day-of-the-week effect), around the turn of the month (the turn-of-the-month effect) and before holidays (the pre-holiday effect). The findings reveal that these anomalies have largely disappeared from the Singapore stock market in recent years. The disappearance of these anomalies has important implications for the efficient market hypothesis and the trading behavior of investors.

Volatility in the Indian Stock Market: Evidence from S&P CNX 500

2020 ◽  
Vol 17 (4) ◽  
pp. 1826-1830
Author(s):  
V. Shanthaamani ◽  
V. B. Usha
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Risk Premium ◽  
Conditional Variance ◽  
Leverage Effect ◽  
Volatility Clustering ◽  
Expected Stock Returns ◽  
High Volatility ◽  
Indian Stock Market ◽  
Daily Returns

This paper uses the Generalized Autoregressive Conditional Heteroskedastic models to estimate volatility (conditional variance) in the daily returns of the S&P CNX 500 index over the period from April 2007 to March 2018. The models include both symmetric and asymmetric models that capture the most common stylized facts about index returns such as volatility clustering and leverage effect. The empirical results show that the conditional variance process is highly persistent and provide evidence on the existence of risk premium for the S&P CNX 500 index return series which support the positive correlation hypothesis between volatility and the expected stock returns. Our findings also show that the asymmetric models provide better fit than the symmetric models, which confirms the presence of leverage effect. These results, in general, explain that high volatility of index return series is present in Indian stock market over the sample period.

NONLINEARITIES AND GARCH INADEQUACY FOR MODELING STOCK MARKET RETURNS: EMPIRICAL EVIDENCE FROM LATIN AMERICA

2010 ◽  
Vol 15 (5) ◽  
pp. 713-724 ◽  
Author(s):  
Claudio A. Bonilla ◽  
Rafael Romero-Meza ◽  
Carlos Maquieira
Keyword(s):  
Stock Market ◽  
Latin American ◽  
Spillover Effects ◽  
Stock Index ◽  
Output Volatility ◽  
Stock Market Index ◽  
Market Returns ◽  
Stock Market Returns ◽  
Market Index ◽  
Data Generating Process

In this paper, we analyze the adequacy of using GARCH as the data-generating process to model conditional volatility of stock market index rates-of-return series. Using the Hinich portmanteau bicorrelation test, we find that a GARCH formulation or any of its variants fail to provide an adequate characterization for the underlying process of the main Latin American stock market indices. Policymakers need to be careful when using autoregressive models for policy analysis and forecast because the inadequacy of GARCH models has strong implications for the pricing of stock index options, portfolio selection, and risk management. In particular, measures of spillover effects and output volatility may not be correct when GARCH-type models are used to evaluate economic policy.

scholarly journals Stock Market Autoregressive Dynamics: A Multinational Comparative Study with Quantile Regression

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Lili Li ◽  
Shan Leng ◽  
Jun Yang ◽  
Mei Yu
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Trading Volume ◽  
Stock Index ◽  
State Dependent ◽  
Advanced Economies ◽  
Quantile Autoregression ◽  
Conditional Information ◽  
Nonlinear Autoregressive ◽  
Stock Index Returns

We study the nonlinear autoregressive dynamics of stock index returns in seven major advanced economies (G7) and China. The quantile autoregression model (QAR) enables us to investigate the autocorrelation across the whole spectrum of return distribution, which provides more insightful conditional information on multinational stock market dynamics than conventional time series models. The relation between index return and contemporaneous trading volume is also investigated. While prior studies have mixed results on stock market autocorrelations, we find that the dynamics is usually state dependent. The results for G7 stock markets exhibit conspicuous similarities, but they are in manifest contrast to the findings on Chinese stock markets.

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