• Title/Summary/Keyword: Volatility of stock

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Profitability of Intra-day Short Volatility Strategy Using Volatility Risk Premium (변동성위험프리미엄을 이용한 일중변동성매도전략의 수익성에 관한 연구)

  • Kim, Sun-Woong;Choi, Heung-Sik;Bae, Min-Geun
    • Korean Management Science Review
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    • v.27 no.3
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    • pp.33-41
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    • 2010
  • A lot of researches find negative volatility risk premium in options market. We can make a trading profit by exploiting the negative volatility premium. This study proposes negative volatility risk premium hypotheses in the KOSPI 200 stock price index options market and empirically test the proposed hypotheses with intra-day short straddle strategy. This strategy sells both at-the-money call option and at-the-money put option at market open and exits the position at market close. Using MySQL 5.1, we create our database with 1 minute option price data of the KOSPI 200 index options from 2004 to 2009. Empirical results show that negative volatility risk premium exists in the KOSPI 200 stock price index options market. Furthermore, intra-day short straddle strategy consistently produces annual profits except one year.

A Study on Unfolding Asymmetric Volatility: A Case Study of National Stock Exchange in India

  • SAMINENI, Ravi Kumar;PUPPALA, Raja Babu;KULAPATHI, Syamsundar;MADAPATHI, Shiva Kumar
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.4
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    • pp.857-861
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    • 2021
  • The study aims to find the asymmetric effect in National Stock Exchange in which the Nifty50 is considered as proxy for NSE. A return can be stated as the change in value of a security over a certain time period. Volatility is the rate of change in security value. It is an arithmetical assessment of the dispersion of yields of security prices. Stock prices are extremely unpredictable and make the investment in equities risky. Predicting volatility and modeling are the most profuse areas to explore. The current study describes the association between two variables, namely, stock yields and volatility in equity market in India. The volatility is measured by employing asymmetric GARCH technique, i.e., the EGARCH (1,1) tool, which was used in building the study. The closing prices of Nifty on day-to-day basis were used for analysis from the period 2011 to 2020 with 2,478 observations in the study. The model arrests the lopsided volatility during the mentioned period. The outcome of asymmetric GARCH model revealed the subsistence of leverage effect in the index and confirms the impact of conditional variance as well. Furthermore, the EGARCH technique was evidenced to be apt in seizure of unsymmetrical volatility.

A Study on Automated Stock Trading based on Volatility Strategy and Fear & Greed Index in U.S. Stock Market (미국주식 매매의 변동성 전략과 Fear & Greed 지수를 기반한 주식 자동매매 연구)

  • Sunghyuck Hong
    • Advanced Industrial SCIence
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    • v.2 no.3
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    • pp.22-28
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    • 2023
  • In this study, we conducted research on the automated trading of U.S. stocks through a volatility strategy using the Fear and Greed index. Volatility in the stock market is a common phenomenon that can lead to fluctuations in stock prices. Investors can capitalize on this volatility by implementing a strategy based on it, involving the buying and selling of stocks based on their expected level of volatility. The goal of this thesis is to investigate the effectiveness of the volatility strategy in generating profits in the stock market.This study employs a quantitative research methodology using secondary data from the stock market. The dataset comprises daily stock prices and daily volatility measures for the S&P 500 index stocks. Over a five-year period spanning from 2016 to 2020, the stocks were listed on the New York Stock Exchange (NYSE). The strategy involves purchasing stocks from the low volatility group and selling stocks from the high volatility group. The results indicate that the volatility strategy yields positive returns, with an average annual return of 9.2%, compared to the benchmark return of 7.5% for the sample period. Furthermore, the findings demonstrate that the strategy outperforms the benchmark return in four out of the five years within the sample period. Particularly noteworthy is the strategy's performance during periods of high market volatility, such as the COVID-19 pandemic in 2020, where it generated a return of 14.6%, as opposed to the benchmark return of 5.5%.

Asymmetry of stock market volatility in high frequency data

  • Lee Ji-Hyeon;Kim Dong-Seok;Lee Hoe-Gyeong
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2004.10a
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    • pp.582-586
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    • 2004
  • The purpose of this study is to examine the lead-lag relationship between volatility and returns in high frequency stock market data to see the validity of two hypotheses that explain volatility asymmetry. Specifically, wavelet analysis is applied to decompose the volatility process into permanent and transitory components and then each component is investigated in conjunction with returns. The results from cross-correlation analysis between volatility and returns support the leverage effect hypothesis rather than the volatility feedback hypothesis in all cases.

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주가수익률에 대한 각국별 거시경제변수의 영향분석 - VAR모형 사용 -

  • Kim, Jong-Gwon
    • Proceedings of the Safety Management and Science Conference
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    • 2005.11a
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    • pp.537-557
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    • 2005
  • The estimate on volatility of stock price is related with optimum of portfolio and Important for allocation of capital asset. If the volatility of stock price is varied according to macroeconomic variables on monetary policy and industrial production, it will assist capital asset to allocate. This paper is related with stock market volatilities on macroeconomic variables in U.S. and Europe, Korea. And, it Is pertain to vary in time of this variables. Thus, this paper is related with volatilities of monetary and physical macroeconomic variables on basis of statistics. And, it is ranged front capital investment to portfolio allocation. Also, this paper takes out of sample forecast and study more after this. In case Germany, France, Italy and the Netherlands, the relative importance of monetary policy and Industrial production Is different from these countries. In case Italy and the Netherlands, monetary policy is primary factor at stabilizing for volatility of stock price. In case Korea, increasing monetary policy and industrial production is positively affected stock market. It is that the positive effect of stock price is caused by mollifying monetary policy and economic growth. Specially, this conclusion is similar to US. In Korea, gradual increase in monetary and industrial production is necessary to stability of stock market. It is different to previous results on basis of increasing stock price of money in long period.

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Volatility spillover between the Korean KOSPI and the Hong Kong HSI stock markets

  • Baek, Eun-Ah;Oh, Man-Suk
    • Communications for Statistical Applications and Methods
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    • v.23 no.3
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    • pp.203-213
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    • 2016
  • We investigate volatility spillover aspects of realized volatilities (RVs) for the log returns of the Korea Composite Stock Price Index (KOSPI) and the Hang Seng Index (HSI) from 2009-2013. For all RVs, significant long memories and asymmetries are identified. For a model selection, we consider three commonly used time series models as well as three models that incorporate long memory and asymmetry. Taking into account of goodness-of-fit and forecasting ability, Leverage heteroskedastic autoregressive realized volatility (LHAR) model is selected for the given data. The LHAR model finds significant decompositions of the spillover effect from the HSI to the KOSPI into moderate negative daily spillover, positive weekly spillover and positive monthly spillover, and from the KOSPI to the HSI into substantial negative weekly spillover and positive monthly spillover. An interesting result from the analysis is that the daily volatility spillover from the HSI to the KOSPI is significant versus the insignificant daily volatility spillover of the KOSPI to HSI. The daily volatility in Hong Kong affects next day volatility in Korea but the daily volatility in Korea does not affect next day volatility in Hong Kong.

How Firms Transfer Financial Risks to Employees: Stock Price Volatility and CEO Power

  • Sohn, Joon-Woo;Lee, Jae-Eun;Kang, Yun-Sik;Lee, Jae-Hyun
    • Asia-Pacific Journal of Business
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    • v.13 no.3
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    • pp.59-71
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    • 2022
  • Purpose - We investigate how firms transfer financial risks to employees in a form of flexible employment contracts and layoffs. Design/methodology/approach - Based on the literature on the prevalence of shareholder value ideology and the associated 'risk shift', we examined how stock price volatility is associated with a firm's use and hiring of nonstandard employees, and the number of employees lay-offed. We test our hypotheses using a longitudinal, multi-source, dataset of Korean firms from 2003 to 2011. Findings - We found support for the relationship between stock price volatility and flexible employment contracts and layoffs after controlling for actual risks such as increased debt or decreased sales. However, we found that the relationship is moderated by the power of professional CEOs relative to that of shareholders, in that powerful CEOs are more likely to transfer the external risks, i.e. stock price volatility, to employees. Research implications or Originality - This study contributes the emerging stream of literature that explore the effect of stock market pressures and governance structures on human resource management.

A study of parameter estimation of stochastic volatility model

  • Tsukui, Makiko;Furuta, Katsuhisa
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10b
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    • pp.1858-1863
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    • 1991
  • The theory of stock option pricing has, recently, attracted attention of many researchers interested not only in finance but also in statistics and control theory. In this field, the problem of estimating stock return volatility is, above all, of great importance in calculating actual stock option value. In this paper, we assume that the stock market is represented by the stochastic volatility model which is the same as that of Hull and White. Then, we propose an approximation function of option value. It is a type of Black-Sholes option formula in which the first and the second order moments of logarithmic stock value are modified in a special form from the original model. Finally, an algorithm of estimating the parameters of the stochastic volatility model is given, and parameters are estimated by using Nikkei 225 index option data.

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A Study on Volatility Management of the Smart-beta Portfolio: Focus on Asia-Pacific Stock Market (스마트-베타 포트폴리오의 변동성관리에 관한 연구: 아시아-태평양 지역 주식시장을 중심으로)

  • Liu, Won-Suk
    • Asia-Pacific Journal of Business
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    • v.10 no.3
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    • pp.37-51
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    • 2019
  • In this paper, we investigate the performance of anomaly factors in Asia-Pacific Stock market and show the higher Sharpe ratio of the volatility managed smart beta portfolio. The smart beta portfolio combines the benefit of passive strategy and active strategy. However, the smart beta portfolios are seems to be exposed to the risk of anomaly factors from the perspective of traditional financial equilibrium model. Therefore, the smart beta strategy may generate negatively skewed returns unappealing to investors having lower risk tolerance. Our empirical investigations find that the return of the Asia-Pacific region stock market is more volatile than other regions with the lower efficiency ratio. However, the value factor and the momentum factor of Asia-Pacific region both show good performances. More interestingly, we also find that managing the volatility of the momentum factor in Asia-Pacific stock market almost doubles the efficiency ratio.

The Introduction of KOSPI 200 Stock Price Index Futures and the Asymmetric Volatility in the Stock Market (KOSPI 200 주가지수선물 도입과 주식시장의 비대칭적 변동성)

  • Byun, Jong-Cook;Jo, Jung-Il
    • The Korean Journal of Financial Management
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    • v.20 no.1
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    • pp.191-212
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    • 2003
  • Recently, there is a growing body of literature that suggests that information inefficiency is one of the causes of the asymmetric volatility. If this explanation for the asymmetric volatility is appropriate, then innovations, such as the introduction of futures, may be expected to impact the asymmetric volatility of stock market. As transaction costs and margin requirements in the futures market are lower than those in the spot market, new information is transmitted to futures prices more quickly and affects spot prices through arbitrage trading with spots. Also, the merit of the futures market may attract noise traders away from the spot market to the futures market. This study examines the impact of futures on the asymmetry of stock market volatility. If the asymmetric volatility is significant lower post-futures and exist in the futures market, it has validity that the asymmetric volatility is caused by information inefficiency in the spot market. The data examined are daily logarithmic returns on KOSPI 200 stock price index from January 4, 1993 to December 26, 2000. To examine the existence of the asymmetric volatility in the futures market, logarithmic returns on KOSPI 200 futures are used from May 4, 1996 to December 26, 2000. We used a conditional mode of TGARCH(threshold GARCH) of Glosten, Jagannathan and Runkel(1993). Pre-futures the spot market exhibits significant asymmetric responses of volatility to news and post-futures asymmetries are significantly lower, irrespective of bear market and bull market. The results suggest that the introduction of stock index futures has an effect on the asymmetric volatility of the spot market and are inconsistent with leverage being the sole explanation of asymmetry. However, it is found that the volatility of futures is not so asymmetric as expected.

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