• Management Science and Financial Engineering
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• v.21 no.2
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• pp.13-23
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• 2015

This study addresses the question as to whether the option prices have useful predictive information on the direction of stock markets by investigating a forecasting power of volatility curvatures and skewness premiums implicit in S&P 500 index option prices traded in Chicago Board Options Exchange. We begin by estimating implied volatility functions and risk neutral price densities every minute based on non-parametric method and then calculate volatility curvature and skewness premium using them. The rationale is that high volatility curvature or high skewness premium often leads to strong bullish sentiment among market participants. We found that the rate of return on the signal following trading strategy was significantly higher than that on the intraday buy-and-hold strategy, which indicates that the S&P500 index option prices have a strong forecasting power on the direction of stock index market. Another major finding is that the information contents of S&P 500 index option prices disappear within one minute, and so one minute-delayed signal following trading strategy would not lead to any excess return compared to a simple buy-and-hold strategy.

• Journal of Intelligence and Information Systems
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• v.2 no.2
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• pp.43-54
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• 1996

Financial markets are operating 24 hours a day throughout the world and interrelated in increasingly complex ways. Telecommunications and computer networks tie together markets in the from of electronic entities. Financial practitioners are inundated with an ever larger stream of data, produced by the rise of sophisticated database technologies, on the rising number of market instruments. As conventional analytic techniques reach their limit in recognizing data patterns, financial firms and institutions find neural network techniques to solve this complex task. Neural networks have found an important niche in financial a, pp.ications. We a, pp.y neural networks to Standard and Poor's (S&P) 500 stock index futures trading to predict the futures marker behavior. The results through experiments with a commercial neural, network software do su, pp.rt future use of neural networks in S&P 500 stock index futures trading.

• The Korean Journal of Financial Management
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• v.13 no.1
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• pp.341-357
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• 1996

Some empirical studies have shown that asset prices respond to announcements of economic news, however, others also have found little evidence. This study assesses how market participants of the S&P 500 Index Futures reacted to the U.S. economic news announcements. For this purpose, using a GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model, we use several U.S. news variables, its each surprise component and interest rates. We find that some economic news variables affected significantly on the S&P 500 Index Futures. In other words, we find that weekend variable, lagged volatility, and surprise component of trade deficit increased level of volatility. However, interest rate, M1, unemployment announcements caused the variance of the S&P 500 Index Futures to reduce, and each of the surprise component of M1 and trade deficit increased it. The result suggests that resolution of uncertainty, through economic news announcement, while, in some cases, causes market participants to reduce their forecast of volatility, a large difference between the market's forecast and the realization of the series causes the volatility to increase.

• International Area Studies Review
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• v.13 no.2
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• pp.255-276
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• 2009

This article has examined the international transmission of returns among S&P500, Nikkei225 and SENSEX stock index cash markets using the daily closing prices covered from January 4, 2002 to February 6, 2009. For this purpose we employed dynamic time series models such as the Granger causality analysis and variance decomposition analysis based on VAR model. The main empirical results are as follows; First, according to Granger causality tests we find that S&P500 stock index has a significant prediction power on the changes of SENSEX and Nikkei225 stock index market and vice versa. However, US stock market's influence is dominant to the other stock markets at a significant level statistically. Second, according to variance decomposition, SENSEX stock index is more sensitive to the movement of S&P500 than that of Nikkei225 stock index. These kinds of empirical results shows that the three stock markets are integrated over times and these results will be informative for the international investors to build the world-wide investment portfolio and risk management strategies, etc.

• International Journal of Quality Innovation
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• v.1 no.1
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• pp.106-120
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• 2000

The purpose of this research is to understand the effects of Quality Management Award on stock prices movement and to examine the comparative advantages of quality award system in Korea and the U.S. This study compares the performances of QM Award companies in the stock market with those of the market index in both countries. We develop Korean Quality Award Index(KQA Index) based on the Baldrige Index of NIST in the U.S. We inspect three studies. Study 1 tests if the performances of MB Award winners and S&P500 index have a difference in the stock market. Study 2 tests if the performances of KQA winners and KOSPI(Korean Composite Stock Price Index) have a difference in the stock market. Study 3 tests if the performances of KQA winners and MB Award winners have a difference in the stock market. From the empirical tests, the performances of KQA winners are superior to those of KOSPI and the performances of MB Award winners are superior to those of S&P500 and the performances of MB Award winners are superior to those of KQA winners.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.107-118
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• 2022

In this study, daily data from January 2002 to June 2022 were used to investigate the relationship between risk-return relationship and market fear, uncertainty, stock market, and maritime freight index for the crude oil market. For this study, the time varying EGARCH-M model was applied to the risk-return relationship, and the wavelet consistency model was used to analyze the relationship between market fear, uncertainty, stock market, and maritime freight index. The analysis results of this study are as follows. First, according to the results of the time-varying risk-return relationship, the crude oil market was found to be related to high returns and high risks. Second, the results of correlation and Granger causality test, it was found that there was a weak correlation between the risk-return relationship and VIX, EPU, S&P500, and BDI. In addition, it was found that there was no two-way causal relationship in the risk-return relationship with EPU and S&P500, but VIX and BDI were found to affect the risk-return relationship. Third, looking at the results of wavelet coherence, it was found that the degree of the risk-return relationship and the relationship between VIX, EPU, S&P500, and BDI was time-varying. In particular, it was found that the relationship between each other was high before and after the crisis period (financial crisis, COVID-19). And it was found to be highly associated with organs. In addition, the risk-return relationship was found to have a positive relationship with VIX and EPU, and a negative relationship with S&P500 and BDI. Therefore, market participants should be well aware of economic environmental changes when making decisions.

• The Korean Journal of Financial Management
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• v.12 no.2
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• pp.239-271
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• 1995

본 연구는 현재 미국에서 거래되고 있는 세 가지 주가지수선물 상호간의 일중(intradaily) 가격선도(price leadership) 관계에 관한 실증분석이다. 본 연구가 기존의 연구와 다른점은, 기존의 연구가 주가지수선물과 그 기준이 되는 현물 가격사이의 가격 선도 관계에 초점을 두고 있는데 반하여 본 연구는 주가지수선물 시장 사이에서 존재하는 가격 선도관계를 분석하고 있다는 점이다. 실증 분석의 대상이 된 주가지수선물들은 Chicago Mercantile Exchange의 Standard and Poor's 500 Index(S&P 500), New York Futures Exchange의 New York Stock Exchange Composit Index (NYSE), 그리고 Chicago Board of Trade의 Major Market Index(MMI)이다. 만약 이들 시장들이 정보의 전달에 있어서 효율적(informationally efficient) 이라면 이들 가격간에 선도-지연(lead-lag) 현상은 존재하지 않을 것이다. 그러나 어느 한 시장이 새로운 정보를 선물가격에 반영하는데 다른 시장에 비해 상대적으로 느리다면, 이들 시장 상호간에는 가격의 전이(transmission)현상이 존재하게 될 것이다. 이들 선물간의 일중 가격선도 관계 연구는 이러한 시장의 효율성 문제를 밝히는데 의의가 있을 뿐만 아니라, 시장간의 단기적 가격 괴리를 이용하려는 차익거래자들에게도 유용하게 쓰일 수 있을 것이다. 본 연구는 위에서 언급한 각각의 주가지수선물들이 가격 선도성을 가질 수 있는 이유와 관련된 다음과 같은 세 가지 가설을 설정하였다. 첫째 가설은, 가격의 선도성은 거래량과 관련이 있다는 것이다. 즉, 이들 주가지수선물 중 가장 거래량이 많은 S&P 500 선물이 다른 선물을 선도할 것이라는 가설이다. 둘째, 가격의 선도성은 주가지수를 구성하는 주식의 수에 비례한다는 가설이다. 다시 말하면, 보다 않은 수로 구성된 주가지수일수록 정보처리 속도가 빠르다는 가설이다. 따라서, 본 연구에 포함된 주가지수선물 중 가장 많은 수의 주식을 대상으로 하는 NYSE 선물이 다른 선물을 선도할 것이다. 마지막 가설은 정보의 처리는 대형주 혹은 기관선호주(institutionally-favored)들이 주도한다는 것이다. 따라서, 주로 이와 같은 주식들로 구성 된 MMI 선물이 선도성을 가질 수 있다는 것이다. 위의 가설들을 검증하고 시장간의 가격 선도관계를 분석하기 위하여 본 연구는 vector autoregressive(VAR) 모형을 이용하여 충격-반응 함수(impulse response functions)를 계산하고, 분산분해(variance decomposition)를 수행하였다. 또한 가격 상호간에 존재할지도 모르는 공적분(cointegration)관계를 Johansen(1991)과 Jokansen and Juselius (1992) 등이 제시한 다변량 공적분 검정(multivariate cointegration test)를 통하여 분석하였다. 분석기간은 1986년 1월부터 1990년 7월까지이며, 각 주가지수선물들의 5분 간격 data를 사용하였다. 연구결과, 충격-반응 분석은 어느 한 시장에서의 충격(shock)은 다른 시장으로 매우 빠르게 전달되고 있음을 보여 주었다. 그러나 충격의 지속정도는 그 충격의 진원지에 따라 달랐다. 즉, NYSE나 MMI 선물로부터 발생 한 충격은 다른 시장의 가격에 5분 안에 반영을 끝냈지 만 S&P 500 선물에서 발생한shock은 그 이상 지속되었다. 또한, 분산분해 결과 S&P 500 선물이 자기자신 뿐만 아니라 다른 시장의 예상하지 못했던 움직임(unexpected movements)을 설명하는데 가장 큰 설명력(explanatory power)을 가지고 있었다. 결론적으로 S&P 500 선물이 다른 선물을 약 5분 간격으로 선도하였다. 이는 가격의 선도가 거래량과 밀접한 관계가 있음을 보여 주는 것이다.

• Management & Information Systems Review
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• v.33 no.1
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• pp.45-63
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• 2014

A trading system is a computer trading program that automatically submits trades to an exchange. Mechanical a trading system to execute trade is spreading in the stock market. However, a trading system to trade a single asset might occur instability of the profit because payoff of this system is determined a asset movement. Therefore, it is necessary to develop a trading system that is trade two assets such as a pair trading that is to sell overvalued assets and buy the undervalued ones. The aim of this study is to propose a relative value based trading system designed to yield stable and profitable profits regardless of market conditions. In fact, we propose a procedure for building a trading system that is based on the rough set analysis of indicators derived from a price ratio between two assets. KOSPI 200 index futures and S&P 500 index futures are used as a data for evaluation of the proposed trading system. We intend to examine the usefulness of this model through an empirical study.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.57-62
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• 2023

This research is a comparative analysis of the U.S. S&P 500 index using the volatility breakout strategy against the Buy and Hold approach. The volatility breakout strategy is a trading method that exploits price movements after periods of relative market stability or concentration. Specifically, it is observed that large price movements tend to occur more frequently after periods of low volatility. When a stock moves within a narrow price range for a while and then suddenly rises or falls, it is expected to continue moving in that direction. To capitalize on these movements, traders adopt the volatility breakout strategy. The 'k' value is used as a multiplier applied to a measure of recent market volatility. One method of measuring volatility is the Average True Range (ATR), which represents the difference between the highest and lowest prices of recent trading days. The 'k' value plays a crucial role for traders in setting their trade threshold. This study calculated the 'k' value at a general level and compared its returns with the Buy and Hold strategy, finding that algorithmic trading using the volatility breakout strategy achieved slightly higher returns. In the future, we plan to present simulation results for maximizing returns by determining the optimal 'k' value for automated trading of the S&P 500 index using artificial intelligence deep learning techniques.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.2
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• pp.15-21
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• 2014

The long memory properties of the hedge ratio for stock and futures have not been systematically investigated by the extant literature. To investigate hedge ratio' long memory, this paper employs a data set including KOSPI200 and S&P500. Coakley, Dollery, and Kellard(2008) employ a data set including a stock index and commodities foreign exchange, and suggested the S&P500 to be a fractionally integrated process. This paper firstly estimates hedge ratios with two dynamic models, BEKK(Bollerslev, Engle, Kroner, and Kraft) and diagonal-BEKK, and tests the long memory of hedge ratios with Geweke and Porter-Hudak(1983)(henceforth GPH) and Lo's modified rescaled adjusted range test by Lo(1991). In empirical results, two hedge ratios based on KOSPI200 and S&P500 show considerably significant long memory behaviours. Thus, such results show the hedge ratios to be stationary and strongly reject the random walk hypothesis on hedge ratios, which violates the efficient market hypothesis.