• Environmental and Resource Economics Review
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• v.31 no.3
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• pp.393-417
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• 2022

Using hourly SMP data from 2016 to 2020, this paper measures the weekly realized volatility and investigates the main force of its determinants. To this end, we extend the Bayesian variable selection by incorporating the regime-switching model which identifies important variables among a large number of predictors by regimes. We find that the increase in coal and nuclear generation, as well as solar power, reinforce the SMP volatility in both high volatility and low volatility regime. In contrast the increase in gas generation and gas price decrease SMP volatility when SMP volatility is high. These results suggest that the expansion of renewable energy according to 2050 Carbon Neutrality or energy transition policies increases SMP volatility but the increase in the gas generation or reduction of coal generation might offset its impact.

• Asia-Pacific Journal of Business
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• v.13 no.4
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• pp.109-121
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• 2022

Purpose - This study investigates how earnings volatility influences current stock price informativeness about expectations of future earnings. Design/methodology/approach - I adopt the FERC model developed by Collins et al. (1994) and modified by Lundholm and Myers (2002) to investigate the connection between earnings volatility and future earnings reflected in current returns. I define five-year rolling standard deviations of earnings and components as earnings volatility measures and the degree of deviation of earnings from cash flows over the same five-year, which is developed by Jayaraman (2008). Finding - My results show that earnings volatility delays current stock price response to future operation expectations. They also verify that as earnings are more divergent from cash flows, current returns are less timely incorporating value-relevant future operation. Research implications or Originality This study shows that when volatile earnings deliver obscure and unreliable information about future operation expectations, they cause the market to be conflicting in understandings their implications and make it difficult in attaining correct future cashflow estimates.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.75-87
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• 2023

We designed to employ an Artificial Intelligence learning model to predict real estate prices and determine the reasons behind their changes, with the goal of using the results as a guide for policy. Numerous studies have already been conducted in an effort to develop a real estate price prediction model. The price prediction power of conventional time series analysis techniques (such as the widely-used ARIMA and VAR models for univariate time series analysis) and the more recently-discussed LSTM techniques is compared and analyzed in this study in order to forecast real estate prices. There is currently a period of rising volatility in the real estate market as a result of both internal and external factors. Predicting the movement of real estate values during times of heightened volatility is more challenging than it is during times of persistent general trends. According to the real estate market cycle, this study focuses on the three times of extreme volatility. It was established that the LSTM, VAR, and ARIMA models have strong predictive capacity by successfully forecasting the trading price index during a period of unusually high volatility. We explores potential synergies between the hybrid artificial intelligence learning model and the conventional statistical prediction model.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.409-419
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• 2022

This paper examines the post-IPO price volatility in the first trading days after the IPO of SOEs that carry out equitization, on a sample of 76 IPOs on the Hanoi Stock Exchange (Vietnam) in the period 2013-2018. Oversubscription rate, firm size, issuance size, internal equity ownership, and listing delay are all factors that influence IPO price volatility in a primitive stock market. The results showed that the average initial market-adjusted return for the first three trading days was -11.95%; -9.58% and -7.29% and the level of price volatility is related to the rate of oversubscription and company size. Issuance price, issuance size, internal equity holdings, and listing delay do not seem to contribute significantly to post-IPO share prices. Individual investors based their valuation on information released during and after the IPO. In general, the number of IPOs that yield positive and negative returns in the first trading days is about the same, indicating that the two phenomena of undervaluation and overvaluation still occur in the process of valuing shares of Vietnamese SOEs for IPOs.

• Journal of Environmental Policy
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• v.10 no.2
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• pp.45-60
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• 2011

An aim of this paper is to test four hypotheses on price volatility in the $CO_2$ emission markets focusing on European Climate Exchange(ECX) in the EU Emission Trading Schemes(EU ETS) and Chicago Climate Exchange(CCX). I expect that, due to an influx of market information, a differently designed exchange market would bring a different price volatility, and various types of emission permits in the same exchange market would result in the same effects on the price volatility. Major findings are that the price volatility is same regardless of the types of emission exchange markets and emission permits comparing the rate of returns. However, comparing the GARCH variance, the volatility between ECX EUAs and CCX-CFIs and the volatility between EUAs(CERs) futures and daily futures are different with the exception of the volatility between EUAs futures and CERs futures. In conclusion, the price volatility depends on the types of exchanges and the types of emission permits.

• Journal of applied mathematics & informatics
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• v.41 no.1
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• pp.33-50
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• 2023

Foreign exchange options are derivative financial instruments that can exchange one currency for another at a prescribed exchange rate on a specified date. In this study, we examine the analytic formulas for vulnerable foreign exchange options based on multi-scale stochastic volatility driven by two diffusion processes: a fast mean-reverting process and a slow mean-reverting process. In particular, we take advantage of the asymptotic analysis and the technique of the Mellin transform on the partial differential equation (PDE) with respect to the option price, to derive approximated prices that are combined with a leading order price and two correction term prices. To verify the price accuracy of the approximated solutions, we utilize the Monte Carlo method. Furthermore, in the numerical experiments, we investigate the behaviors of the vulnerable foreign exchange options prices in terms of model parameters and the sensitivities of the stochastic volatility factors to the option price.

• Management & Information Systems Review
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• v.33 no.2
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• pp.119-133
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• 2014

This Research focuses on the effect of the price limits change in KOSDAQ market change on the volatility. The sample period ranges from 22 May 2000 to 24 March 2010 for daily data. We construct two subsample periods for comparing with the effect of the change of the price limit. These limits were relaxed from 12% to 15% on March 25, 2005. The first subsample period is from 25 March 2000 to 24 March 2005. The second subsample period is from 25 March 2005. to 24 March 2010. We employee four different volatility, which are the range-based volatility of Parkinson(1980; PK), Garman and Klass(1980; GK) Rogers and Satchell(1991; RS), Yang and Zhang(2008; YZ). The empirical result as follows. The major findings are summarized as follows; First, the volatility of individual stocks in KOSDAQ market reduces significantly after the price limit change. Second, There is so high volatile especially when the volatility of stock prices is high. Third, There is no meaningful relationship between volatility and market capitalization. Fourth, the more volume stocks reduce the volatility. Our results show the volatility decreased the more large volume, the more trading amount and the high price stock.

• International Area Studies Review
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• v.21 no.1
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• pp.181-200
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• 2017

This study investigates the impact of exchange rate and exchange rate volatility on the stock prices of eight industries from 2006 to 2015. The first and second exchange rate exposure of these eight industries is estimated with respect to four different exchange rates, namely the US dollar, Japanese yen, European currency unit, and British pound. In exchange rate exposure, stock prices in foods-beverages, paper-wood, electricity-gas, and banks industries are negatively related to exchange rate, whereas stock prices in electrical-electronic equp. and transport-equp. industries are positively related to exchange rate as expected. However stock price in machinery industry is negatively related to exchange rate, which is opposite to the expectation. Negative relationship is found between stock price in chemicals industry and exchange rate. In exchange rate volatility exposure, stock price in paper-wood industry is found to be negatively related to exchange rate volatility. Stock price in banks industry is also negatively related to exchange rate volatility. This result is opposite as expected, because banks are supposed to get more revenue by issuing derivatives related to foreign exchange when exchange rate volatility increases.

• Korea Trade Review
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• v.47 no.4
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• pp.177-195
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• 2022

This study analyzed the volatility spillover effect between international non-ferrous metal futures markets using the BEKK-GARCH model. Statistical data are futures price data of copper (CU), aluminum (AL), nickel (NI), tin (SN) from Shanghai Futures Exchange (SHFE) and London Metal Exchange (LME) from April 1, 2015 to December 31, 2021. Combining the research results, first, in the case of copper, aluminum, and nickel, it was found that there was a two-way volatility spillover effect between the Shanghai and London markets, and the international influence of the London market was greater. Second, in the case of the tin, it was found that the Shanghai market has a volatility spillover effect on the London market from stage I, and it is strengthened in stage II. Third, in the case of nickel, it was found that there was a two-way volatility spillover effect in the first stage, but in the second stage, the London market had a unidirectional volatility spillover effect with respect to the Shanghai market. This study confirmed that China's influence in the international non-ferrous metal futures market is gradually increasing. In addition, it suggested that international investors can engage in arbitrage and hedging using China's non-ferrous metal futures market.

• 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.