Futures and Option Prices After the Stock Market Close: Evidence from the Korean Markets

2008 ◽  
Vol 16 (2) ◽  
pp. 95-125
Author(s):  
Jae Ha Lee ◽  
Sang Soo Kwon
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Return Volatility ◽  
Option Prices ◽  
Option Markets ◽  
Option Returns ◽  
Time Zones ◽  
The Impact

In the KOSPI2oo futures and option markets. additional fifteen minutes (15 : 00∼15 개5) after the underlying stock market close are given tor the adjustments of the futures and option positions. During the first five minutes. 15: 00∼15 : 05. a continuous auction trading is made. while the trading at a single clearing price is made for the remaining ten minutes. 15: 05∼15: 15. Previous studies focused on the synchronous trading in terms of transaction time in the analysis of the lead-lag relationship. truncating the futures and option data during 15 : 00∼15 : 15. In this article. we explore how the KOSPI2oo futures and option returns for the extra fifteen minutes impact the next day's KOSPI200 cash returns, We also examine the lead-lag relationship during the reggular trading hours (9 : 00∼15 : 00) and the impact of the cash returns during 14 : 20∼15 : 00 on futures and option returns during 15 : 00∼15: 15. Our main findings are summarized as follows. First. the KOSPI200 futures and option returns during 15 : 00∼15 : 15 lead the close-to-open KOSPI200 cash return, even though the trading volume and return volatility during 15: 00∼15: 15 are lower relative to the regular stock market session (9 : 00∼15: 00). The impact of the futures and option returns on the cash return lasts hlK) minutes and one minute‘ repectively. after the next day open. Second. the option return during the continuous auction trading session (15 : 00∼ 15 : 05) leads the close-to-open cash return. while the futures return of trading at a single clearing price during 15 : 05∼15 : 10 impacts the close-to-open cash return. Third, we found that the lead-lag relationships among the KOSPI200 futures, option, and cash returns are not constant during the reg비ar stock market session‘ In partieular. the impact of the KOSPI200 cash ret un during 14 : 40∼15 : 00 on the futures and option retuns for the 15 : 00∼15: 15 Interval is much stronger. compared with other time zones. Finally. the KOSPI200 cash return during the last ten minutes of trading at a Single clearing price (14 : 50∼15 : 00). significantly impacts the option return during 15: 00∼15: 05. while there is no impact on the futures return (15 : 00∼15: 15).

Assessment of Asymmetric Information Cost in Indian Stock Market: A Sectoral Approach

2020 ◽  
pp. 097215091986508
Author(s):  
Aritra Pan ◽  
Arun Kumar Misra
Keyword(s):  
Asymmetric Information ◽  
Stock Prices ◽  
Trading Volume ◽  
Share Price ◽  
Return Volatility ◽  
Information Cost ◽  
Market Conditions ◽  
Price Variation ◽  
Bid Ask Spread ◽  
The Impact

Bid-ask spread, along with profit, also encompass the impact of asymmetric information cost and order processing cost. Asymmetric information influences stock prices with varying degree of investors’ perception. Estimation of asymmetric information cost and its determinants have been explored significantly under low-frequency trading. The literature hardly attempts to study asymmetric information cost under high-frequency trading (HFT). Asymmetric information cost significantly influences bid-ask spread, and hence the nature of its impact under different market conditions needs to be analyzed under HFT. The study attempts to estimate asymmetric information cost in HFT and analyze its determinants under different industry sectors and market conditions. The study followed Affleck-Graves et al. (1994 , The Journal of Finance, 49(4), 1471–1488) model to estimate the asymmetric information cost using 5 minutes interval data for a period of 82 trading days. Information gets reflected in equity through the movement in price, variation in trading volume, and return volatility. The study has found share price, traded volume, return volatility and trading frequency as the major determinants of asymmetric information cost in different market conditions. The findings of the study have significant implications for market microstructure for trading, lowering information asymmetry in market and enhancing market quality.

scholarly journals THE VOLATILITY TRANSMISSION OF MAIN GLOBAL STOCK'S RETURN TO INDONESIA

2017 ◽  
Vol 20 (2) ◽  
pp. 229-256
Author(s):  
Linda Karlina Sari ◽  
Noer Azam Achsani ◽  
Bagus Sartono
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
Stock Return ◽  
Global Financial Crisis ◽  
Symmetric Model ◽  
Return Volatility ◽  
Stock Return Volatility ◽  
Volatility Transmission ◽  
The Impact

Stock return volatility is a very interesting phenomenon because of its impact on global financial markets. For instance, an adverse shocks in one country’s market can be transmitted to other countries’ market through a particular mechanism of transmission, causing the related markets to experience financial instability as well (Liu et al., 1998). This paper aims to determine the best model to describe the volatility of stock returns, to identify asymmetric effect of such volatility, as well as to explore the transmission of stocks return volatilities in seven countries to Indonesia’s stock market over the period 1990-2016, on a daily basis. Modeling of stock return volatility uses symmetric and asymmetric GARCH, while analysis of stock return volatility transmission utilizes Vector Autoregressive system. This study found that the asymmetric model of GARCH, resulted from fitting the right model for all seven stock markets, provides a better estimation in portraying stock return volatility than symmetric model. Moreover, the model can reveal the presence of asymmetric effects on those seven stock markets. Other finding shows that Hong Kong and Singapore markets play dominant roles in influencing volatility return of Indonesia’s stock market. In addition, the degree of interdependence between Indonesia’s and foreign stock market increased substantially after the 2007 global financial crisis, as indicated by a drastic increase of the impact of stock return volatilities in the US and UK market on the volatility of Indonesia’s stock return.

scholarly journals The Price-Trading Volume Relationship in the Brazilian Stock Market, the Impact of Stock Lending and a Role for Technical Analysis

2015 ◽  
Vol 13 (4) ◽  
pp. 631
Author(s):  
Antonio Zoratto Sanvicente ◽  
Antonio Zoratto Sanvicente ◽  
Antonio Zoratto Sanvicente
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Price Change ◽  
Absolute Value ◽  
Daily Data ◽  
Volume Relationship ◽  
Current Price ◽  
The Impact ◽  
The Relationship ◽  
Positive Covariance

We examine the relationship between price and volume in the Brazilian stock market. It tests the “V-shaped relationship” developed by Karpoff (1987), identified in several empirical papers for the U.S. market. This is expressed by positive covariance between a stock’s market turnover and the absolute value of that stock’s price change in the same period. This would contradict the implication from weak market efficiency that current price would impound all information. We analyze daily data for 47 stocks covering the period from January 04, 2010 to June 28, 2013. The results indicate that the V-shaped relationship is significant.

scholarly journals Impact of Macroeconomic Variables on Stock Return Volatility: Evidence from Sub-Sahara Africa

2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Peter Ifeanyichukwu Ali ◽  
Samuel M. Nzotta ◽  
A. B. C. Akujuobi ◽  
Chilaka E. Nwaimo
Keyword(s):  
South Africa ◽  
Stock Market ◽  
Stock Markets ◽  
Inflation Rate ◽  
Return Volatility ◽  
Macroeconomic Variables ◽  
Market Return ◽  
Stock Market Return ◽  
Macroeconomic Indicators ◽  
The Impact

The main purpose of this paper was to investigate the impact of macroeconomic variables on stock market return volatility in Sub-Sahara markets. The study concentrated on three stock markets including Ghana, Nigeria and South Africa using GARCH-X (1,1) model on monthly data from January 2000 to December 2017. Preliminary analyses from descriptive statistics show that show mean monthly returns are positive for all the stock markets. Skewness coefficients show that the stock returns and interest rates distribution of all Sub-Sahara Africa stock markets are negatively skewed but inflation rate is positively skewed for Nigeria and South Africa, and flat for Ghana. Excess kurtoses are positive for all the stock markets and macroeconomic indicators, and Jarque-Bera statistics indicate the stock markets’ series and macroeconomic indicators are not normally distributed. The Unit roots tests results indicate that all the stock markets and macroeconomic indicators are first difference stationary. The results of the GARCH-X (1,1) model show that macroeconomic variables do not significantly impact stock market returns volatility in Nigeria, Ghana and South Africa at the 5% significance Level. We therefore recommend that stock market regulators, market participants and investors should concentrate more efforts on other macroeconomic variables aside interest rate and inflation rate, in estimating stock market return volatility in Sub-Sahara Africa.

scholarly journals Using a Genetic Algorithm to Build a Volume Weighted Average Price Model in a Stock Market

2021 ◽  
Vol 13 (3) ◽  
pp. 1011
Author(s):  
Seung Hwan Jeong ◽  
Hee Soo Lee ◽  
Hyun Nam ◽  
Kyong Joo Oh
Keyword(s):  
Genetic Algorithm ◽  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Trading Volume ◽  
Weighted Average ◽  
Market Liquidity ◽  
Average Price ◽  
Volume Data ◽  
The Impact

Research on stock market prediction has been actively conducted over time. Pertaining to investment, stock prices and trading volume are important indicators. While extensive research on stocks has focused on predicting stock prices, not much focus has been applied to predicting trading volume. The extensive trading volume by large institutions, such as pension funds, has a great impact on the market liquidity. To reduce the impact on the stock market, it is essential for large institutions to correctly predict the intraday trading volume using the volume weighted average price (VWAP) method. In this study, we predict the intraday trading volume using various methods to properly conduct VWAP trading. With the trading volume data of the Korean stock price index 200 (KOSPI 200) futures index from December 2006 to September 2020, we predicted the trading volume using dynamic time warping (DTW) and a genetic algorithm (GA). The empirical results show that the model using the simple average of the trading volume during the optimal period constructed by GA achieved the best performance. As a result of this study, we expect that large institutions will perform more appropriate VWAP trading in a sustainable manner, leading the stock market to be revitalized by enhanced liquidity. In this sense, the model proposed in this paper would contribute to creating efficient stock markets and help to achieve sustainable economic growth.

scholarly journals Indian Stock Market during the COVID-19 Pandemic: Vulnerable or Resilient?: Sectoral analysis

2021 ◽  
Vol 12 (1) ◽  
pp. 131-159
Author(s):  
Rishika Shankar ◽  
Priti Dubey
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Consistent Pattern ◽  
Daily Average ◽  
Sectoral Analysis ◽  
Indian Stock Market ◽  
The Impact

This study examines the impact of COVID-19 pandemic on the performance of Indian stock market, measured by daily average returns and trading volume. The analysis is aimed at discovering the vulnerability of the general market as well as nine crucial sectors to the pandemic while also checking the impact on overall volatility in the market. The findings suggest that all the sectors followed a consistent pattern of being significantly impacted by the pandemic. However, the benchmark index remained resilient in the context of average returns. The entire market witnessed decreased returns and increased liquidity, which is explained by reduced volatility in the market.

scholarly journals Stock Market Reforms and Stock Market Performance

2021 ◽  
Vol 12 (2) ◽  
pp. 202
Author(s):  
Karthigai Prakasam Chellaswamy ◽  
Natchimuthu N ◽  
Muhammadriyaj Faniband
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Positive Impact ◽  
Market Performance ◽  
Market Reforms ◽  
Disclosure Requirements ◽  
Stock Market Performance ◽  
Event Study Method ◽  
Unfair Trade ◽  
The Impact

This paper analyses the impact of stock market reforms on the stock market performance in India using regression based event-study method. We consider nine stock market reforms introduced from 1998 to 2018. We find that the impact of stock market reforms on Nifty trading volume and Nifty return is different. This paper documents that the impact of the additional volatility measures, T+3 and T+2 settlement cycles, and margin provisions for intra-day crystallized losses reforms show a positive impact on trading volume post-reform. In contrast, internet trading, prohibition of fraudulent and unfair trade practices, delisting of equity shares, substantial acquisition of shares and takeovers listing obligations and disclosure requirements reforms decrease the trading volume post-reform. Our results of Nifty return reveal that the additional volatility measures, the T+2 settlement cycle, the prohibition of fraudulent and unfair trade practices, substantial acquisition of shares and takeovers, listing obligations and disclosure requirements have a significant and positive impact on return post-reform. It is evident that the impact of all nine stock market reforms is insignificant on Nifty return.

scholarly journals Impact of Trading Volume on Prediction of Stock Market Development

2014 ◽  
Vol 62 (6) ◽  
pp. 1373-1380
Author(s):  
Rudolf Plachý
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Trading Volume ◽  
Financial Time Series ◽  
Market Development ◽  
Return Volatility ◽  
Stock Market Development ◽  
Series Development ◽  
Class Models

The paper focuses on the influence of trading volume on quality of prediction of stock market development. The main objective of this article is to assess the influence of stock trading volume level on quality of prediction with use of technical analysis. The research was applied on stocks included in the S & P 500 index. Based on average daily trading volume, three aggregate indexes were constructed. The dynamics of index return volatility was modeled by GARCH-class models. GARCH(1,1), GJR and EGARCH models were estimated for each time series. The in-sample evidence indicated that the return volatility of the indexes can be characterized by significant persistence and asymmetric effects. The best estimate of each model was produced for the index of stocks with the highest average trading volume.However the result could differ based on the observed period, the volatility structure of the examined data supports the idea that influential investors respond to various shocks in the market primarily by closing or opening their largest position.The importance of the level of trading volume for the prediction of financial time series development was shown in the paper. This finding could help generate such volatility structure of time series which would allow to explain development of the time series by various models with better results.

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