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1
Ben Abdallah, Marwa, Maria Fekete Farkas, and Zoltan Lakner. "Analysis of meat price volatility and volatility spillovers in Finland." Agricultural Economics (Zemědělská ekonomika) 66, No. 2 (February 24, 2020): 84–91. http://dx.doi.org/10.17221/158/2019-agricecon.
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Unforeseen important changes in price can present a significant risk in the market. The price fluctuation of agricultural commodities has raised concern for studying the volatility of different agricultural products. A persistent volatility in prices causes continued uncertainty in the market. Higher price volatility is to be mitigated by higher management costs and the higher cost of risk mitigation is often converted into higher producer prices. The aim of this paper is to investigate the price volatility of producer and consumer meat prices and to capture the volatility spillover along the Finnish meat supply chain. The Generalised Autoregressive Conditional Heteroskedasticity – Baba, Engle, Kraft and Kroner (GARCH-BEKK) model is applied to analyse shocks and volatilities of the prices and to estimate whether the price volatility is flowing from the first price level (producer) to the second price level (consumer), using monthly price indices. An asymmetric volatility spillover effect was detected in the poultry meat and a unidirectional, volatility spillover effect, from consumer to producer, is observed for pork prices. The findings of this study could serve as a tool for forecasting meat producer and consumer prices, which could assist the Finnish government with endorsing policy options to alleviate the price volatility impact, to protect both consumers and producers from its negative effects.
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Nugrahapsari, Rizka Amalia, and Idha Widi Arsanti. "Analisis Volatilitas Harga Cabai Keriting di Indonesia dengan Pendekatan ARCH GARCH." Jurnal Agro Ekonomi 36, no. 1 (September 18, 2018): 25. http://dx.doi.org/10.21082/jae.v36n1.2018.25-37.
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<strong>English</strong><br />Chili includes a strategic commodity in Indonesia because of its high price volatility that makes it a major determinant of national inflation dynamics. The government always tries to improve its capability in implementing the chili price stabilization policy. The objective of the study is to assess the volatility of curly chili price volatility in Indonesia by using the ARCH GARCH approach with daily price data of January 2011 to December 2015. The results showed that the right model to calculate chili price volatility is ARCH (1). The price volatility was low and price movement was only influenced by the volatility in the previous day, not by the price variant, so the chili price volatility in the future will be smaller. Low volatility indicates that demand and supply characteristics were predictable. Price changes gradually and predictable. Farmers’ protection policy through import restrictions improves stability of domestic supply. The policy reduces the risk of drastic decline in prices due to imported chili, so the price volatility of chili in the period 2011–2015 was lower than the previous period. However, the seasonal price variation remains. Therefore, the policy should be supported with all season chili availability assurance.<br /><br /><br /><strong>Indonesian</strong><br />Cabai termasuk komoditas strategis di Indonesia karena harganya volatil sehingga menjadi salah satu penentu utama dinamika inflasi nasional. Untuk itu, pemerintah senantiasa berusaha meningkatkan kemampuannya dalam melaksanakan kebijakan stabilisasi harga cabai. Penelitian ini bertujuan untuk mengkaji volatilitas harga cabai keriting di Indonesia dengan pendekatan ARCH GARCH dan data harga harian cabai keriting periode Januari 2011 hingga Desember 2015. Hasil penelitian menunjukkan bahwa model yang tepat untuk menghitung volatilitas harga cabai keriting adalah ARCH(1). Hasil pendugaan model menunjukkan volatilitas harga cabai keriting rendah dan pergerakan harga hanya dipengaruhi oleh volatilitas pada satu hari sebelumnya, tidak dipengaruhi varian harga, sehingga diperkirakan volatilitas harga cabai keriting di masa datang akan semakin kecil. Volatilitas yang rendah menunjukkan karakteristik waktu permintaan dan penawaran cabai keriting dapat diprediksi. Perubahan harga terjadi bertahap dan dapat diperkirakan. Kebijakan perlindungan petani melalui pembatasan impor cabai menyebabkan penyediaan cabai di dalam negeri menjadi lebih stabil. Kebijakan ini mengurangi risiko penurunan harga secara drastis akibat masuknya cabai impor, sehingga volatilitas harga cabai pada periode 2011–2015 lebih rendah dibandingkan periode sebelumnya. Namun, masih terdapat variasi harga musiman. Oleh karena itu, kebijakan ini perlu diperkuat dengan upaya jaminan sediaan cabai sepanjang musim.
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Klepacz, Matthew. "Price Setting and Volatility: Evidence from Oil Price Volatility Shocks." International Finance Discussion Paper 2021, no. 1315 (April 30, 2021): 1–70. http://dx.doi.org/10.17016/ifdp.2021.1316.
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How do changes in aggregate volatility alter the impulse response of output to monetary policy? To analyze this question, I study whether individual prices in Producer Price Index micro data are more likely to change and to move in the same direction when aggregate volatility is high, which would increase aggregate price exibility and reduce the effectiveness of monetary policy. Taking advantage of plausibly exogenous oil price volatility shocks and heterogeneity in oil usage across industries, I find that price changes are more dispersed and less frequent, implying that prices are less likely to move in the same direction when aggregate volatility is high. This contrasts with findings in the literature about idiosyncratic volatility. I use a state-dependent pricing model to interpret my findings. Random menu costs are necessary for the model to match the positive empirical relationship between oil price volatility and price change dispersion. This is the case because random menu costs reduce the extent to which firms with prices far from their optimum all act in a coordinated fashion when volatility increases. The model implies that increases in aggregate volatility do not substantially reduce the ability of monetary policy to stimulate output.
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Ogunmola, Omotoso Oluseye, Abiodun Elijah Obayelu, and Sakiru Oladele Akinbode. "Volatility and Co‑movement: an Analysis of Food Commodity Prices in Nigeria." Agricultura Tropica et Subtropica 50, no. 3 (September 26, 2017): 129–39. http://dx.doi.org/10.1515/ats-2017-0014.
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AbstractThis study explains volatility as a measure and interaction of the possible movement in a particular economic variable. Prices change rapidly in adjustment to market circumstances. Food prices hike experienced overyears has resulted in widespread menace which led to increase in food price volatility. However, volatility and co-movement had generally been lower for the past two decades than for the previous ones. Wide price movements over a short period of time connote high volatility, rendering the producers and consumers vulnerable. Excess volatility can be subjected to sector ineffectiveness and is commodity specific. Producers and processors are mostly concerned about increased price volatility, which greatly exposed them to unpredictable risks and uncertainty associated with price changes. This study examined the volatility and co-movement of food commodity prices in Nigeria using price series data on rice, maize, sorghum, cassava and yam for the period of 1966 to 2013. The data were analysed using Vector Autoregressive Model to forecast food price volatility and to examine the food commodity prices that Granger cause food price volatility in other food commodities. The GARCH regression model is used to estimate the magnitude of volatility which revealed that, food commodity prices exhibit high volatility and there is persistent increase in prices over the period of study. The Nigerian food commodity prices have experienced high fluctuations over the period; therefore, the study recommends proper storage facilities and infrastructure for the food distribution corporations in Nigeria.
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Onour, Ibrahim. "Dynamics of Crude Oil Price Change and Global Food Commodity Prices." Finance & Economics Review 3, no. 1 (April 28, 2021): 38–50. http://dx.doi.org/10.38157/finance-economics-review.v3i1.248.
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Purpose: This study investigates the effect of crude oil price fluctuations (price change as well as volatility) on wheat, sugar, corn, and fertilizers price changes.
Methods: The study employs Markov switching dynamic regression, Dynamic Conditional Correlation (DCC), and Generalized Autoregressive Conditional Hetrosekadicity (GARCH) on monthly data covering the period from January 1988 to April 2018.
Results: The findings of the research support evidence of two states. State 1, pertains to the low volatility of crude oil price, and state 2 belong to the case of the high volatility of crude oil prices. Our results indicated that at state 1, an increase in crude oil prices leads to a decline in food commodity prices, while in state 2, an increase in crude oil price levels causes an increase in food commodity prices. Results of Dynamic Conditional Correlation (DCC) GARCH estimates indicate the coefficients of oil price levels are significant and positively associated with the conditional volatility of the four commodity prices.
Implications: The findings of the research imply that volatility in global food commodity prices is not due to oil price volatility but due to the oil price levels attained at extreme points.
Originality: The paper investigates the impact of different volatility levels of crude oil prices on global food commodity prices.
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Gilbert, C. L., and C. W. Morgan. "Food price volatility." Philosophical Transactions of the Royal Society B: Biological Sciences 365, no. 1554 (September 27, 2010): 3023–34. http://dx.doi.org/10.1098/rstb.2010.0139.
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The high food prices experienced over recent years have led to the widespread view that food price volatility has increased. However, volatility has generally been lower over the two most recent decades than previously. Variability over the most recent period has been high but, with the important exception of rice, not out of line with historical experience. There is weak evidence that grains price volatility more generally may be increasing but it is too early to say.
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Sholihah, Fathimah, and Nunung Kusnadi. "Dampak Pengembangan Biofuels terhadap Volatilitas Harga Beberapa Komoditas Pangan di Pasar Dunia." Jurnal Agro Ekonomi 37, no. 2 (April 20, 2020): 157. http://dx.doi.org/10.21082/jae.v37n2.2019.157-170.
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<strong>English</strong><br />Agricultural product based biofuels are the connecting points of the linkages between the global agricultural commodity, energy, and financial markets. Since the global energy markets and financial markets are volatile in nature, rapid expansion of biofuels industry results in increasing volatility of agricultural commodity prices, particularly food prices. The aims of this research is to review price volatility of some food commodities (wheat, corn and soybean) in in the world markets and to analyze the impact of global biofuels development on the price volatility. The price volatility is analyzed using the ARIMA and ARCH GARCH methods. The results show that prices of food commodities have been more volatile since the United States of America imposed the Renewable Fuel Standard Mandate-2 policy in 2007. The Corn and soybean price volatilities are higher than rice and wheat. The stronger are their linkages with biofuels development, the higher are their price volatilities. Increasing food price volatility and level should be considered as challenges and opportunities for accelerating food production growth through technological innovation and land expansion toward the achievement food self-sufficiency such that the national food security system is resilient against global market disturbances.<br /><br /><br /><strong>Indonesian</strong><br />Biofuels berbahan baku hasil pertanian menjadi komoditas penghubung antara pasar komoditas pertanian dengan pasar energi, dan selanjutnya dengan pasar finansial dunia. Oleh karena pasar energi dan pasar finansial dunia rentan gejolak maka pengembangan biofuel secara besar-besaran berdampak pada peningkatan volatilitas harga komoditas pertanian, utamanya komoditas pangan pokok. Penelitian bertujuan untuk meninjau volatilitas harga jagung, gandum, beras dan kedelai di pasar dunia serta untuk menganalisis dampak pengembangan biofuels terhadap volatilitas harga tersebut. Analisis volatilitas harga dilakukan dengan metode ARIMA dan ARCH GARCH. Penelitian menunjukkan bahwa harga komoditas pangan lebih volatil setelah Amerika Serikat menerapkan kebijakan Renewable Fuels Standard Mandate-2 tahun 2007. Volatilitas harga jagung dan kedelai lebih tinggi daripada beras dan gandum. Semakin besar keterkaitan komoditas dengan pengembangan biofuels maka semakin besar pula volatilitas harga komoditas tersebut. Peningkatan volatilitas dan level harga tersebut dapat dipandang sebagai tantangan dan peluang untuk memacu peningkatan produksi pangan melalui pengembangan teknologi dan ekstensifikasi lahan pertanian guna meningkatkan kemandirian pangan sehingga sistem ketahanan pangan nasional lebih tahan menghadapi gejolak pasar global.
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Chalimatusadiah, Chalimatusadiah, Donny Citra Lesmana, and Retno Budiarti. "Penentuan Harga Opsi Dengan Volatilitas Stokastik Menggunakan Metode Monte Carlo." Jambura Journal of Mathematics 3, no. 1 (April 28, 2021): 80–92. http://dx.doi.org/10.34312/jjom.v3i1.10137.
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ABSTRAKHal yang utama dalam perdagangan opsi adalah penentuan harga jual opsi yang optimal. Namun pada kenyataan sebenarnya fluktuasi harga aset yang terjadi di pasar menandakan bahwa volatilitas dari harga aset tidaklah konstan, hal ini menyebabkan investor mengalami kesulitan dalam menentukan harga opsi yang optimal. Artikel ini membahas tentang penentuan harga opsi tipe Eropa yang optimal dengan volatilitas stokastik menggunakan metode Monte Carlo dan pengaruh harga saham awal, harga strike, dan waktu jatuh tempo terhadap harga opsi Eropa. Adapun model volatilitas stokastik yang digunakan dalam penelitian ini adalah model Heston, yang mengasumsikan bahwa proses harga saham (St) mengikuti distribusi log-normal, dan proses volatilitas saham (Vt) mengikuti Proses Cox-Ingersoll-Ross. Hal pertama yang dilakukan dalam penelitian ini adalah mengestimasi parameter model Heston untuk mendapatkan harga saham dengan menggunakan metode ordinary least square dan metode numerik Euler-Maruyama. Langkah kedua adalah melakukan estimasi harga saham untuk mendapatkan harga opsi tipe Eropa menggunakan metode Monte Carlo. Hasil dari penelitian ini menunjukkan bahwa penggunaan metode Monte Carlo dalam penentuan harga opsi tipe Eropa dengan volatilitas stokastik model Heston menghasilkan solusi yang cukup baik karena memiliki nilai error yang kecil dan akan konvergen ke solusi eksaknya dengan semakin banyak simulasi. Selain itu, simulasi Monte Carlo memberikan kesimpulan bahwa parameter harga strike, harga saham awal dan waktu jatuh tempo memiliki pengaruh terhadap harga opsi yang konsisten dengan teori harga opsi. ABSTRACTWhat is important in options trading is determining the optimal selling price. However, in real market conditions, fluctuations in asset prices that occur in the market indicate that the volatility of asset prices is not constant, this causes investors to experience difficulty in determining the optimal option price. This article discusses the optimal determination of the European type option price with stochastic volatility using the Monte Carlo method and the effect of the initial stock price, strike price, and expiration date on European option prices. The stochastic volatility model used in this study is the Heston model, which assumes that the stock price process (S) follows the normal log distribution, and the stock volatility process (V) follows the Ingersoll-Ross Cox Process. The first thing to do in this study is to estimate the parameters of the Heston model to get stock prices using the ordinary least square method and the Euler-Maruyama numerical method. The second step is to estimate the share price to get the European type option price using a Monte Carlo Simulation. This study indicates that using the Monte Carlo method in determining the price of European type options with the Heston model of stochastic volatility produces a fairly good solution because it has a small error value and will converge to the exact solution with more simulations. Also, the Monte Carlo simulation concludes that the parameters of the strike price, initial stock price, and maturity date influence the option price, which is consistent with the option price theory.
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Lingesiya Kengatharan and Jeyan Suganya Dimon Ford. "Dividend Policy and Share Price Volatility: Evidence from Listed Non-Financial Firms in Sri Lanka." International Journal of Business and Society 22, no. 1 (March 24, 2021): 227–39. http://dx.doi.org/10.33736/ijbs.3172.2021.
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The prime objective of this research is to investigate the impact of dividend policy on share price volatility in Colombo Stock Exchange (CSE). A sample of 81 listed non -financial firms from CSE in Sri Lanka is examined using panel data analysis for a five years period from 2013 to 2017. Dividend policy of the firms has been measured by dividend pay-out, dividend yield and dividend per share and which are explanatory variables of the study after controlling for firm size and financial leverage. According to the random effect regression analysis, only 25% of the movements in share prices are explained by the explanatory variables considered in this study. Dividend yield shows significant positive impact on share price volatility whereas dividend per share shows the significant negative impact on share price movements. Firm size illustrates significant negative influence on share price volatility by indicating large size of companies share price volatility is high. But, dividend pay-out and financial leverage are not significantly persuaded on share price volatility in this study. Therefore, it is concluded that dividend yield, dividend per share and firm size have significant impact on price volatility in Sri Lankan context and findings of the study are in line with the dividend relevance theory. Dividend policy can be considered as the protective mechanism to maintain share price volatility in order to enhance the shareholders wealth.
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Anis Erma Wulandari, Harianto Harianto, Bustanul Arifin, and Heny K Suwarsinah. "The Impact of Futures Price Volatility to Spot Market : Case of Coffee in Indonesia." Jurnal Organisasi dan Manajemen 15, no. 1 (March 1, 2019): 1–15. http://dx.doi.org/10.33830/jom.v15i1.5.2019.
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Indonesia is the world 4th largest coffee producer after Brazil, Vietnam and Colombia with export potential and higher national consumption concluded in 2017 while the coffee production was relatively stagnant. This was led the producer to not only the production risk but also the price risk which then emphasize the importance of futures markets existence as price risk management. This study is performed to examine the impact of futures price volatility to spot market using ARCH-GARCH toward primary data of coffee futures and spot prices of 1172 trading days starting from January 2014 to June 2018. The ARCH-GARCH analysis result indicates that futures price volatility and monetary variables are impacting the volatility of spot price. Arabica spot price volatility is impacted by volatility of Arabica futures price, inflation and exchange rate while Robusta spot price is impacted by Robusta futures price volatility and exchange rate. This is confirming that futures market plays dominant role in spot price discovery. Local futures and spot prices are also found to be significantly influenced by volatility of offshore futures prices which indicates that emerging country futures market is actually influenced by offshore futures market which the price itself used as price reference.
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Sarwindah, Sarwindah, Widi Hidayat, and Siti Asiah Murni. "Covid-19 dan Volatilitas Harga Saham Melalui Peran Mediasi Harga Emas." E-Jurnal Akuntansi 32, no. 4 (April 5, 2022): 1002. http://dx.doi.org/10.24843/eja.2022.v32.i04.p13.
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This study aims to analyze the effect of Covid-19 which consists of the number of positive cases, the number of deaths, and the number of recoveries on stock price volatility through the mediating role of gold prices. The research population is a retail company listed on the Indonesia Stock Exchange with a research period from April 2020 to June 2021. The research sample was taken using purposive sampling, and analyzed using SEM PLS. The results of the analysis show that the number of positive cases has a significant negative effect on gold prices and the volatility of retail companies' stock prices. The number of deceased has a positive effect on the price of gold and the volatility of the stock price of retail companies. The number of recoveries has a positive effect on gold prices, but has no significant effect on stock price volatility. The mediating role explains that the price of gold has a mediating role on the effect of the number of positive cases and the number of deaths on stock price volatility, but does not have a mediating role on the effect of the number of recoveries on stock price volatility.
Keywords: Covid-19; Gold Prices; Stock Price Volatility; Retail Companies.
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Onour, Ibrahim. "Do Crude Oil Price Levels Or Its Volatility Matter In Global Food Commodity Price Change?" Management and Economics Research Journal 7, no. 3 (August 17, 2021): 1–8. http://dx.doi.org/10.18639/merj.2021.9900042.
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This study investigates the effect of crude oil price fluctuations on wheat, sugar, corn, and fertilizers. Results of Markov switching dynamic regression support evidence of two states. State 1, pertains to the low volatility of crude oil prices, and state 2, refers to higher volatility of crude oil prices. At state 1 higher levels of oil prices lead to a decline in food commodity prices, whereas in state 2, higher oil prices cause an increase in food commodity prices. Results of Dynamic Conditional Correlation (DCC) GARCH estimates indicate the coefficients of oil price levels are significant and positively associated with the conditional volatility of the four commodity prices, implying that fluctuations in global food commodity prices are not due to oil price volatility but due to the oil price levels attained at the extreme points.
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Jiang, Yong, Chao-Qun Ma, Xiao-Guang Yang, and Yi-Shuai Ren. "Time-Varying Volatility Feedback of Energy Prices: Evidence from Crude Oil, Petroleum Products, and Natural Gas Using a TVP-SVM Model." Sustainability 10, no. 12 (December 10, 2018): 4705. http://dx.doi.org/10.3390/su10124705.
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: In this paper, the time-varying volatility feedback of nine series of energy prices is researched by employing the time-varying parameter stochastic volatility in mean (TVP-SVM) model. The major findings and conclusions can be grouped as follows: Significant differences exist in the time-varying volatility feedback among the nine major energy productions. Specifically, crude oil and diesel’s price volatility has a remarkable positive time-varying effect on their returns. Yet the returns, for natural gas and most petroleum products are negatively affected by their price volatility over time. Furthermore, obvious structural break features exist in the time-varying volatility feedback of energy prices, which coincide with the breakpoints in the energy volatility. This indicates that some factors such as major global economic and geopolitical events that cause the sudden structural breaks in the energy volatility may also affect the volatility feedback of the energy price. Moreover, the volatility feedback in energy price will become weak and even have no impact on energy returns in some special periods when the energy price volatility is extremely high.
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Prabowo, Agung, Zulfatul Mukarromah, Lisnawati Lisnawati, and Pramono Sidi. "PENENTUAN HARGA OPSI BELI ATAS SAHAM PT. ANTAM (PERSERO) MENGGUNAKAN MODEL BINOMIAL FUZZY." Jurnal Matematika Sains dan Teknologi 19, no. 1 (March 16, 2018): 8–24. http://dx.doi.org/10.33830/jmst.v19i1.124.2018.
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Option is a financial instrument where price depends on the underlying stock price. The pricing of options, both selling options and purchase options, may use the CRR (Cox-Ross-Rubinstein) binomial model. Only two possible parameters were used that is u if the stock price rises and d when the stock price down. One of the elements that determine option prices is volatility. In the binomial model CRR volatility is constant. In fact, the financial market price of stocks fluctuates so that volatility also fluctuates. This article discusses volatility of fluctuating stock price movements by modeling it using binomial fuzzy with triangular curve representation. The analysis is carried out in relation to the existence of three interpretations of the triangular curve representation resulting in different degrees of membership. In addition to volatility, this study added the size or risk level ρ. As an illustration, this study used stock price movement data from PT. Antam (Persero) from August 2015 until July 2016. The results of one period obtained from the purchase price option for August 2016 with the largest volatility, medium and smallest respectively were Rp.143,43, Rp.95,49, and Rp.79,00. There was calculated at the risk level of ρ = 90%. The degree of membership for each option price varies depending on the interpretation of the triangle curve representation.
Opsi merupakan instrumen keuangan yang harganya tergantung pada harga saham yang mendasarinya. Penentuan harga opsi, baik opsi jual maupun opsi beli dapat menggunakan model binomial CRR (Cox-Ross-Rubinstein). Dalam model ini hanya dimungkinkan adanya dua parameter yaitu u apabila harga saham naik dan d pada saat harga saham turun. Salah satu unsur yang menentukan harga opsi adalah volatilitas. Dalam model binomial CRR digunakan volatilitas yang bersifat konstan. Padahal, pada pasar keuangan pergerakan harga saham mengalami fluktuasi sehingga volatilitas juga menjadi fluktuatif. Artikel ini membahas volatilitas pergerakan harga saham yang fluktuatif dengan memodelkannya menggunakan binomial fuzzy dengan representasi kurva segitiga. Analisis dilakukan terkait dengan adanya tiga interpretasi terhadap representasi kurva segitiga tersebut yang menghasilkan derajat keanggotaan yang berbeda. Selain volatilitas, dalam penelitian ini ditambahkan ukuran atau tingkat risiko ρ. Sebagai ilustrasi, digunakan data pergerakan harga saham PT. Antam (Persero) dari Agustus 2015 hingga Juli 2016. Hasil penelitian dengan perhitungan satu periode diperoleh hasil harga opsi beli untuk bulan Agustus 2016 dengan volatilitas terbesar, menengah, dan terkecil masing-masing adalah Rp.143,43, Rp.95,49, dan Rp.79,00 yang dihitung pada tingkat risiko ρ = 90%. Derajat keanggotaan untuk masing-masing harga opsi berbeda-beda tergantung pada interpretasi dari representasi kurva segitiga.
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Nwoko IC and Aye GC. "Crude oil price and food price volatility: A conceptual analysis." International Journal of Scientific Research Updates 4, no. 1 (August 30, 2022): 108–15. http://dx.doi.org/10.53430/ijsru.2022.4.1.0067.
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In this paper we explain the volatility of food prices, the sources and consequences of volatility. We develop a conceptual model linking oil price and food price volatility. We also attempt to assess previous empirical studies and identify any gaps in the literature that will serve as guide for future empirical studies.
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Kaulihowa, Teresia, and Katrina Kamati. "Determinants of house price volatility in Namibia." International Journal of Housing Markets and Analysis 12, no. 4 (August 5, 2019): 807–23. http://dx.doi.org/10.1108/ijhma-10-2018-0077.
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Purpose This paper aims to test the volatility and analyses the macroeconomic determinants of house price volatility in Namibia over the period 2007 Quarter 1 to 2017 Quarter 2. It further explores the causal relations between house price volatility and its determinants. Design/methodology/approach The study used autoregressive conditional heteroskedastic and generalized autoregressive conditional heteroskedastic models to test for volatility. The vector error correction model was used to analyse the determinants and causal relations. Findings The results support the hypothesis that house prices in Namibia exhibits persistent volatility. It was further established that past period volatility’ GDP and mortgage loans are the key determinants of house price volatility. Additionally’ there exists unidirectional causality from GDP and mortgage loans to house price volatility. Practical implications Policy implications emanating from the study implies that macroeconomic fundamentals should be monitored closely to mitigate the issues of house price volatility. Originality/value The study is the first of its kind in Namibia to address the pertinent issues of ever increasing housing prices.
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Ayuning Putri, Anisa Ferata. "FAKTOR-FAKTOR PENENTU VOLATILITAS HARGA SAHAM SEKTOR PERUSAHAAN PROPERTI, REAL ESTATE DAN BUILDING CONSTRUCTION." Jurnal Akuntansi dan Keuangan 8, no. 2 (September 2, 2020): 109. http://dx.doi.org/10.29103/jak.v8i2.2563.
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Abstrak : Tujuan dari riset ini adalah untuk melihat pengaruh Devidend Payout Ratio, Devidend Yield, Earning Volatility, Pertumbuhan Aset, Leverage, Ukuran Perusahaan dan Blockholders terhadap Volatilitas Harga Saham. Pada penelitian ini akan menggunakan data laporan Perusahaan Lembaga Keuangan dari Bursa Efek Indonesia (BEI) selama periode 2016-2018 dengan populasi sebanyak 201 perusahaan metode purposive sampling digunakan untuk memperoleh sampel selama 3 tahun sebayak 36 perusahaan. Data penelitian ini di analisis menggunaka analisis regresi linier berganda. Hasil analisis ditemukan bahwa Dividen Payout Ratio, Earning Volatility, Pertumbuhan Aset, Ukuran Perusahaan, Blockholdres tidak berpengaruh terhadap Volatilitas Harga Saham Sedangkan untuk variabel Dividen Yield berpengaruh terhadap Volatilitas Harga Saham.Kata kunci : Volatilitas Harga Saham, Dividen Payout Ratio, Dividen Yield, Earning Volatility, Pertumbuhan Aset, Ukuran Perusahaan, Blockholdres Abstrack : The purpose of this study is to examine the effect of Dividend Payment Ratio, Dividend Results, Productive Volatility, Estimated Assets, Leverage, Firm Size and Blockholders on Stock Price Volatility. In this study will use the report data of Financial Institution Companies from the Indonesia Stock Exchange (BEI) during the 2016-2018 period with a population of 201 companies using a purposive sampling method for a 3-year sample of 36 companies. The data of this study were analyzed using multiple linear regression analysis. The results of the analysis found that Dividend Payment Ratios, Income Volatility, Assets, Company Size, Blockholdres are not in conflict with Stock Price Volatility While for the Result Dividend variable produced on Stock Price Volatility. Keywords: Stock Price Volatility, Dividend Payout Ratio, Yield Dividend, Income Volatility, Asset Inventory, Firm Size, Blockholding
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Tan, Yanwen, and Huasheng Zeng. "Price transmission, reserve regulation and price volatility." China Agricultural Economic Review 11, no. 2 (May 7, 2019): 355–72. http://dx.doi.org/10.1108/caer-04-2017-0062.
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Purpose The purpose of this paper is to examine whether Chinese pork reserve regulation policy fulfills its function in stabilizing market prices and simultaneously to theoretically and empirically analyze the causes leading to the failure of Chinese Government’s intervention in the market, especially in the context of asymmetric pork and hog price information transmission. Design/methodology/approach A modified Reserve-Cobweb model based on the competitive storage model developed by Muth in 1961 is employed to examine the transmission effect of hog and pork prices under the setting of Chinese Government’s pork reserve regulation policy, using the data on Chinese hog and pork prices from June 2009 to June 2015. Findings While the Reserve-Cobweb model provides theoretical insights, suggesting that the implementation of the government’s reserve policy tool to control price volatility actually leads to increased price volatility, the empirical results indicate that the policy induces hypercorrection and impels greater price volatility, especially in the context of existence of asymmetric price information transmission. Social implications The Chinese Government should reduce excessive pork price intervention and instead allow the market to play its role in the hog and pork markets. Originality/value This paper develops a modified Reserve-Cobweb model based on the price transmission effect on different links within the agricultural products supply chain, which is used to empirically validate the existence of asymmetric price information transmission between pork and hog price in China.
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Sulistiowati, Susanti Evie, Ratya Anindita, and Rosihan Asmara. "PRODUCTION, CONSUMPTION AND PRICE (IMPORTS, PRODUCERS AND CONSUMER) VOLATILITY OF SHALLOT IN PROBOLINGGO REGENCY." Agricultural Social Economic Journal 21, no. 3 (July 31, 2021): 235–40. http://dx.doi.org/10.21776/ub.agrise.2021.021.3.8.
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Changes in production, consumption, and import variables cause the price of shallots to fluctuate. A high and unpredictable price fluctuation increasing the volatility problem. This phenomenon gives results in risk, uncertainty and leading to a decline in the welfare of producers and consumers. Based on the description of the problems above, it is important to analyze price, production, import, and consumption volatility to determined the level of risk and uncertainty faced by producers and consumers. This study uses monthly secondary data (time series) on production, price, imports, and consumption of shallots in Probolinggo Regency, for seven years (2013-2019). The ARCH/GARCH method is used to analyze the volatility of prices, production and consumption. The results from the analysis are the production variable has a low level of volatility, the consumption and import prices have high-level volatility, producer price has low-level volatility, while consumer prices has-high level volatility. From the results means that the risks and uncertainties faced by producers in conducting shallot cultivation are low. While for the consumer means the risks and uncertainties in consuming shallots are high.
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EL QALLI, YASSINE. "RECURSIVE BAYESIAN ESTIMATION IN FORWARD PRICE MODELS IMPLIED BY FAIR PRICING." International Journal of Theoretical and Applied Finance 13, no. 02 (March 2010): 301–33. http://dx.doi.org/10.1142/s0219024910005784.
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In this paper we describe a recursive Bayesian algorithm for the estimation of forward price models. The forward price is modeled within the benchmark framework for a forward price volatility function which includes a stochastic variable; a forward price with a liquidly traded maturity. A relationship between the bond price, the spot price and certain forward prices is stated. We set up the stochastic real world dynamics for these discretely compounded market observed forward prices. We propose a dynamic Bayesian estimation algorithm for a Monte Carlo time-discretized version of the resulting forward prices dynamics. The parameter to be estimated is a vector consisting of the forward price volatility parameters and the benchmarked bond price volatility parameters.
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Hao, Miao, Rong Chen, and Xinhong Fu. "Effect of Pig Price Volatility on Sichuan Pig Farmers’ Behavioral Response in China." Journal of Agricultural Science 6, no. 4 (March 15, 2014): 55. http://dx.doi.org/10.5539/jas.v6n4p55.
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This study aims to analyze cobweb phenomenon of pig price volatility and its effects on pig producers in Sichuan, China. Historical data showed that pig price from 2000 to 2003 pertained to Occlude Cobweb Phenomenon; while pig price from 2004 to 2012 pertained to Divergent Cobweb Phenomenon. Based on Cobweb Phenomenon this article provided a comparative analysis of pig price volatility’s effects on scattered farmers, scale farmers and pig factories via examining their basic information, response to price volatility, reasons leading to such response, and price expectation. The results indicated that scale farmers were the most sensitive to price volatility; hence their production behaviors probably boosted pig price volatility to some degree. Factory farming was the most competitive farming pattern and was bound to be the main trend in pig industry in the future.
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Yang, Tzu-Yi, Ha Thanh, and Chia-Wei Yen. "Oil threshold value between oil price and production." Panoeconomicus 66, no. 4 (2019): 487–505. http://dx.doi.org/10.2298/pan161013009y.
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This study proposes a panel smooth transition regression (PSTR) model to investigate the nonlinear relationship between crude oil prices and crude oil production in 122 countries, both OPEC and non-OPEC, from March 1994 to October 2015. The statistical test for the existence of a threshold effect indicates that the relationship between oil prices and oil production is nonlinear, with different changes over time among the oil price and transition variables. Additionally, a threshold value exists. Furthermore, crude oil price volatility exhibits asymmetric responses to production volatility by fluctuating above or below the threshold value. Finally, when crude oil price volatility with a lag of two periods exceeds the threshold value, crude oil production changes have a positive impact on crude oil price volatility. In contrast, when crude oil price volatility with a lag of two periods is less than the threshold value, crude oil production changes have a negative impact on price volatility.
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Hassan, Syed Aun. "Modeling Asymmetric Volatility In Oil Prices." Journal of Applied Business Research (JABR) 27, no. 3 (April 12, 2011): 71. http://dx.doi.org/10.19030/jabr.v27i3.4214.
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<p>Recent volatility in crude oil prices has affected economies around the world, especially the US economy, which is the largest consumer of oil. This paper focuses on how shocks to volatility of crude oil prices may affect future oil prices. The paper uses daily crude oil price data for the past 10 years to test and model the oil price volatility by fitting different variations of GARCH including a univariate asymmetric GARCH model to the series. Tests show high persistence and asymmetric behavior in oil price volatility, and reveal that negative and positive news have a different impact on oil price volatility. These results will help interested observers better understanding of the energy markets and has important consequences for the overall economy.</p>
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Teti̇k, Metin. "Forecasting of Gold Prices Volatility with Symmetric and Asymmetric Volatility Models." Journal of Corporate Governance, Insurance, and Risk Management 5, no. 2 (December 3, 2018): 1–14. http://dx.doi.org/10.56578/jcgirm050201.
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With this paper the author forecasts the out-of-sample volatility of gold price changes in Turkey. Looking at the both the symmetric and the asymmetric evaluation criteria, GJR-GARCH model is the best fitted model for forecasting gold price volatility in Turkey. The GJR-GARCH model findings reveal a negative shock asymmetry for gold prices. Thus, it shows that positive news in the market affects the volatility of gold prices in the next period more than negative news.
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Morales, L. Emilio. "The effects of international price volatility on farmer prices and marketing margins in cattle markets." International Food and Agribusiness Management Review 21, no. 3 (March 20, 2018): 335–50. http://dx.doi.org/10.22434/ifamr2017.0020.
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This study examines the effects of export price volatility in cattle markets using panel data from twelve countries between 1970 and 2013. Fixed-effects models with Driscoll and Kraay standard errors were estimated to control for cross-sectional dependence. Results indicate that price transmission depends on prices previously paid to farmers, variations in export prices and volatility of export prices, which reduces farmer prices in developed countries and it increases them in developing countries. In contrast, marketing margins are reduced by contemporaneous export price volatility and are increased by previous volatility. Exporters in developing countries take more time to transmit shocks in international prices, pay lower prices to farmers and absorb a bigger proportion of price fluctuations. These price transmission imperfections affect investments, technology adoption, production level and quality across the chain in developing countries, which negatively impact farmers, input and service providers, traders and other actors of the beef cattle chain.
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Dewi, Syanti, and Ishak Ramli. "OPSI SAHAM PADA PASAR MODAL DI INDONESIA (STUDI PASAR OPSI SAAT PASAR OPSI MASIH BERLANGSUNG DI BURSA EFEK INDONESIA)." Jurnal Muara Ilmu Ekonomi dan Bisnis 2, no. 2 (March 28, 2019): 300. http://dx.doi.org/10.24912/jmieb.v2i2.1001.
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Stock option exchange market is not working anymore in the Indonesian Stock Exchange, using the data option exchange market for the running period 2007-2008, we analyzed the effect of stock price, strike price, time to maturity, volatility and risk- free interest rate on the stock option’s price of listed stock call or put option trading at the Indonesian Stock Exchange during 2007-2008. The results found that the stock price, strike price, time to maturity, volatility and risk-free interest rate are positive significantly affecting the stock option price either the buying option price or the selling option price in Indonesia Stock Exchange 2007-2008 period. While there were no variables that significantly affected the call option during the periode 2007-2008, furthermore stock prices and strike prices significantly affected the put option prices. Time to maturity, Volatility, and risk free interest rate did not significantly affect the put option prices.That is why the stock option exchange market stop since the investor were not sure to the stock option price versus the risk of the volatility, time to maturity, and riskfree rate.
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Vahlevi, T. Muhd Redha, and Harjum Muharam. "Quantitative Easing Program and Financial Market Volatility in Indonesia." JEJAK 10, no. 1 (March 10, 2017): 80–89. http://dx.doi.org/10.15294/jejak.v10i1.9128.
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This research aims to examine the impact of the USD money supply during and before quantitative easing program towards financial market volatility in Indonesia which is proxied by variance of financial market index such as IHSG, Gold Price in IDR, and Exchange Rate IDR/USD to find out the effect of the excess USD money supply on Indonesias financial market volatility. This reseacrh has used monthly time series data of M1 of USD, IHSG, IDR/USD Exchange Rate, and Gold Price from December 2008 to December 2013. TGACRH in this research is used to find out wheter the volatility or variance at previous time affects volatility of these financial market index at present time and assymetric information is exist in the financial market index. The result showed that theres a difference between the effect of USD money supply to financial market index volatility in Indonesia during QE program and before QE program. Before and during QE program, USD money supply positively affects IDR/USD exchange rate volatiliy and IHSG volatility and negatively affects Gold Price volatility. During QE program, USD money supply negatively affects volatility of IDR/USD exchange rate and IHSG, and positively affects Gold Price volatility.
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Obi, Ben, Adeniji Sesan Oluseyi, and Olaniyi Evans. "Impact of Oil Price Shocks on Stock Market Prices Volatility in Nigeria: New Evidence from a Non-linear ARDL Cointegration." Journal of Global Economy 14, no. 3 (November 8, 2018): 173–90. http://dx.doi.org/10.1956/jge.v14i3.501.
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This study examined the impact of oil price shocks on stock market prices volatility in Nigeria using non-linear cointegration approach labelled as Non-linear Autoregressive Distributed Lag (NARDL) which represents one of the major important contribution to the literature on the subject matter. The study was carried out using a quarterly data for the period of 1986 to 2016. The oil price shocks impact was disentangled or decomposed into oil supply shocks, oil demand shocks and oil specific demand shocks and the results from the empirical analysis revealed that, there is long run relationship among the variables and positive oil price shocks in its various forms which exert positive and significant impact on the volatility of stock prices in both long run and short run except for oil supply shock that have negative impact in the long run, while negative oil price shocks exert negative impact on the volatility of stock prices in both short and long run. However, the asymmetric result using Wald test shows that, the positive impact of these shocks on volatility of stock prices differs in both short run and long run. Therefore, the findings from the study affirmed the presence of nonlinear relationship between oil price shocks and stock prices volatility in Nigeria which is an indication that positive and negative oil price shocks affect stock prices volatility differently and this must be taking into consideration when formulating policy
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Dewi, Cynthia Sari. "PENGARUH DIVIDEND YIELD, EARNING VOLATILITY DAN LEVERAGE TERHADAP STOCK PRICE VOLATILITY PADA SEKTOR PERTAMBANGAN YANG TERDAFTAR DI BURSA EFEK INDONESIA PERIODE 2015 - 2018." Ultima Management : Jurnal Ilmu Manajemen 11, no. 1 (January 15, 2020): 27–38. http://dx.doi.org/10.31937/manajemen.v11i1.1233.
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Penelitian ini bertujuan untuk mengetahui factor dominan yag mempengaruhi volatilitas harga saham pada sector pertambangan yang terdaftar di Bursa efek Indonesia. Selama periode 2015 hingga 2018. Jenis penelitian ini adalah studi kausalitas dengan menggunakan data kuantitatif. Data yang digunakan dalam penelitian ini adalah laporan keuangan yang telah diaudit dan dipublikasikan melalui situs web perusahaan. Teknik pengambilan sampel yang digunakan adalah judgemental sampling. Variable independen dalam penelitian ini adalah dividend yield (DY), earning volatility (EV) dan Leverage (LEV) sedangkan stock price volatility (SPV) adalah variable dependen. Jumlah sampel setiap tahun sebanyak 13 perusahaan. Hasil penelitian ini dividend yield (DY), earning volatility (EV) dan Leverage (LEV) secara simultan berpengaruh terhadap stock price volatility (SPV) pada level signifikasi 5%. Dividend yield (DY) berpengaruh signifikan terhadap stock price volatility (SPV), sedangkan Earning volatility (EV) dan Leverage (LEV) tidak berpengaruh signifikan terhadap stock price volatility (SPV) pada confidence level 95%. Adjusted R square menunjukkan 0,065(6,5%) artinya hanya 6,5% dari variable dependen yaitu stock price volatility (SPV) dapat dijelaskan oleh varibel independe dalam model regresi penelitian ini, sedangkan 93,5% dijelaskan oleh variable lain yang tidak termasuk dalam penelitian ini.
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Sohag, K., S. Husain, K. Chukavina, and Md Al Mamun. "Policy Uncertainty, Oil Price, Stock Market and Precious Metal Markets Volatility Spillovers in the Russian Economy." Economy of Region 18, no. 2 (2022): 383–97. http://dx.doi.org/10.17059/ekon.reg.2022-2-6.
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The Russian economy is emerging, meaning that natural resources play a dominant role in economic development. Given the considerable volatility in resource prices, we investigate the volatility spillovers among policy uncertainty, international oil prices, exchange rate, stock index and metal prices covering the period of 2 July 2008 to 15 May 2020 for the Russian economy applying Dynamic Connectedness based on Time-Varying Parameter Vector Autoregression (TVP-VAR). Our empirical investigation demonstrates that gold price, Russian policy uncertainty, oil price and stock index are net volatility contributors, whereas palladium, platinum, silver and exchange rate are net volatilities receivers. Market capitalisation and silver market are found to be the highest net contributor and net receiver, respectively. The palladium appears as a net volatility receiver initially, just after the global financial crisis. The Russian economic policy uncertainty appears to be the dominant volatility contributor from 2008 to 2014, but onward it turned to be a net volatility receiver. Over the year 2014, gold price was the prominent volatility contributor to another market when the oil price dropped significantly. The total connectivity of the markets are highly anchored with several exogenous shocks, including economic sanction, adoption of floating exchange rate, oil price plunge. Our empirical findings provide several policy implications to portfolio managers and Russian regional stakeholders.
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Ikromov, Nuriddin, and Abdullah Yavas. "Cash Flow Volatility, Prices and Price Volatility: An Experimental Study." Journal of Real Estate Finance and Economics 44, no. 1-2 (May 21, 2011): 203–29. http://dx.doi.org/10.1007/s11146-011-9320-5.
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Paulina, Paulina. "Analisis Volatilitas Variabel Makroekonomi dan Harga Saham Menggunakan Generalized Autoregressive Conditonal Heteroscedasticity (Garch Model)." Jurnal Manajemen Strategi dan Aplikasi Bisnis 5, no. 1 (June 30, 2022): 127–41. http://dx.doi.org/10.36407/jmsab.v5i1.533.
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Macroeconomic variables often have an impact on stock price volatility and this is needed especially to determine stock price policies in the future. The approach used to see the extent of the volatility of macroeconomic variables on stock prices is the ARCH/GARCH model. This study aims to analyze the nature of stock price volatility in the food and beverage industry in Indonesia using ARCH/GARCH. The data used in this study is secondary data, namely the stock prices of food and beverage industry companies during the period January 2015 to May 2021. The analysis of stock price volatility was carried out with the help of the Eviews 9 software. The results showed the characteristics of the stock price volatility of food and beverage companies based on the ARCH model. /GARCH is quite risky in the short term but not in the long term (indicated by macroeconomic variables of exchange rates, short-term interest rates), so that stock price movements can be anticipated as an early warning system of an increase or decrease in stock prices in the sector. In addition, it can be estimated that the volatility of stock prices in the future is moderate with changes in macroeconomic variables. For policy makers to anticipate changes in macroeconomic variables in certain situations, such as during the current Covid 19 pandemic.
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LUONG, CHUONG, and NIKOLAI DOKUCHAEV. "ANALYSIS OF MARKET VOLATILITY VIA A DYNAMICALLY PURIFIED OPTION PRICE PROCESS." Annals of Financial Economics 09, no. 03 (December 2014): 1450006. http://dx.doi.org/10.1142/s2010495214500067.
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The paper studies methods of dynamic estimation of volatility for financial time series. We suggest to estimate the volatility as the implied volatility inferred from some artificial "dynamically purified" price process that in theory allows to eliminate the impact of the stock price movements. The complete elimination would be possible if the option prices were available for continuous sets of strike prices and expiration times. In practice, we have to use only finite sets of available prices. We discuss the construction of this process from the available option prices using different methods. In order to overcome the incompleteness of the available option prices, we suggests several interpolation approaches, including the first order Taylor series extrapolation and quadratic interpolation. We examine the potential of the implied volatility derived from this proposed process for forecasting of the future volatility, in comparison with the traditional implied volatility process such as the volatility index VIX.
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Lawal, Adedoyin I., Russel O. C. Somoye, and Abiola A. Babajide. "Impact of Oil Price Shocks and Exchange Rate Volatility on Stock Market Behavior in Nigeria." Binus Business Review 7, no. 2 (September 28, 2016): 171. http://dx.doi.org/10.21512/bbr.v7i2.1453.
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The impact of exchange rate and oil prices fluctuation on the stock market has been a subject of hot debate among researchers. This study examined the impact of both the exchange rate volatility and oil price volatility on stock market volatility in Nigeria, so as to guide policy formulation based on the fact that the nation’s economy was foreign induced and mono-cultured with heavy dependence on oil. EGARCH estimation techniques were employed to examine if either the volatility in exchange rate, oil price volatility or both experts on stock market volatility in Nigeria. The result shows that share price volatility is induced by both the exchange rate volatility and oil price volatility. Thus, it is recommended that policymakers should pursue policies that tend to stabilize the exchange rate regime on the one hand, and guarantee the net oil exporting position for the economy, that market practitioners should formulate portfolio strategies in such a way that volatility in both exchange rates and oil price will be factored in time when investment decisions are being made.
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Etienne, Xiaoli Liao, Andrés Trujillo-Barrera, and Seth Wiggins. "Price and volatility transmissions between natural gas, fertilizer, and corn markets." Agricultural Finance Review 76, no. 1 (May 3, 2016): 151–71. http://dx.doi.org/10.1108/afr-10-2015-0044.
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Purpose – The purpose of this paper is to investigate the price and volatility transmission between natural gas, fertilizer (ammonia), and corn markets, an issue that has been traditionally ignored in the literature despite its significant importance. Design/methodology/approach – The authors jointly estimate a vector error correction model for the conditional mean equation and a multivariate generalized autoregressive heteroskedasticity model for the conditional volatility equation to investigate the interactions between natural gas, ammonia, and corn prices and their volatility. Findings – The authors find significant interplay between fertilizer and corn markets, while only a mild linkage in prices and volatility exist between those markets and natural gas during the period 1994-2014. There is not only a positive relationship between corn and ammonia prices in the short run, but both prices react to deviations from the long-run parity. Furthermore, the lagged conditional volatility of ammonia prices positively affects conditional volatility in the corn market and vice versa. This result is robust to a specification using crude oil price as an alternative to natural gas price to account for the large transportation cost built into ammonia prices. Results for the period of 2006-2014 indicate virtually no linkage between natural gas prices and those of fertilizer and corn during that period, while linkages in price level and volatility between the latter remain strong. Originality/value – This paper is the first in the literature to comprehensively examine the role of fertilizer on corn prices and volatility, and its relation to natural gas prices.
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Sydor, Tymur, and Brooks C. Mendell. "Transaction evidence analysis: stumpage prices and risk in central Georgia." Canadian Journal of Forest Research 38, no. 2 (February 2008): 239–46. http://dx.doi.org/10.1139/x07-126.
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This paper uses hedonic regression techniques to analyze timber bid transactions in central Georgia. Softwood stumpage prices from pay-as-cut transactions are regressed against timber sale and stand characteristics. We identify observable factors that are statistically associated with the volatility of pine sawtimber stumpage prices in the market. The remaining price volatility, defined as market risk, characterizes undiversifiable price volatility in the market. Isolating market risk in this way has implications for relative price risk across predefined timber markets. Applications of this these techniques suggest that analyzing market price variability with total measures alone, such as standard deviation, may provide false senses of timber price risk.
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Saadah, Siti, and Yunia Panjaitan. "The Green Shoe Option’s Effectiveness at Stabilizing the IPO’S Stock Price on the Indonesian Stock Exchange (2000-2013)." Gadjah Mada International Journal of Business 18, no. 1 (February 19, 2016): 71. http://dx.doi.org/10.22146/gamaijb.9292.
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The increased of price volatility due to positive initial returns will reduce investor confidence and impact on the overall market. Market stabilization mechanism is needed to control the price volatility. This research is intended to explore the effectiveness of Green-Shoe Option in reducing stock price volatility after IPO. This study is done through GARCH model development intended to identify the volatility of IPO shares price. This research compares the volatility price of company shares that apply Green shoe option at IPO with companies that do not apply it. The result of this research on companies that conduct IPO on 2000-2013 periods showed that the green shoe option stabilization program which was used by the issuers was effective in muffing the stock prices’ volatility. Therefore, according to researchers Green Shoe Option stabilization program can be used to prevent or ease the drop of shares price under Public offering.
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Hidayati, Nurul, and Puji Sucia Sukmaningrum. "FAKTOR YANG MEMPENGARUHI VOLATILITAS HARGA SAHAM PADA EMITEN YANG TERDAFTAR DI JAKARTA ISLAMIC INDEX." Jurnal Ekonomi Syariah Teori dan Terapan 8, no. 6 (December 5, 2021): 706. http://dx.doi.org/10.20473/vol8iss20216pp706-713.
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ABSTRAKTujuan dari penelitian ini yaitu meneliti pengaruh kebijakan dividen, volume perdagangan, volatilitas laba, ukuran perusahaan dan tingkat hutang terhadap volatilitas harga saham di emiten yang terdaftar di JII dari tahun 2015 sampai 2019. Adapun manfaat dari penelitian ini dalam eksistensi pasar finansial secara global karena dapat mengukur tingkat risiko. Penelitian ini dibantu dengan alat analisis Eviews 10. Regresi data panel dipilih dalam penelitian ini. Hasil penelitian membuktikan bahwa secara individual dividend payout ratio, volume perdagangan dan volatilitas laba secara positif memiliki pengaruh yang signifikan, ukuran perusahaan secara negatif memiliki pengaruh signifikan, dan tingkat hutang tidak memiliki pengaruh signifikan terhadap volatilitas harga saham. Secara simultan, variabel dividend payout ratio, volume perdagangan, ukuran perusahaan, volatilitas laba, dan tingkat hutang signifikan berpengaruh terhadap volatilitas harga saham. Kata Kunci: Volatilitas harga saham, emiten syariah, regresi data panel. ABSTRACTThe purpose of this study is to examine the effect of dividend policy, trading volume, earnings volatility, company size and level of debt on stock price volatility in issuers listed in JII from 2015 to 2019. The benefits of this research are in the existence of global financial markets because it can measure the level of risk. This research is assisted by the analysis tool Eviews 10. Panel data regression. selected in this study. The results showed that partially the dividend payout ratio, trading volume and earnings volatility had a positive and significant effect, company size had a negative and significant effect, and the level of debt had no significant effect on stock price volatility. Simultaneously, the variable dividend payout ratio, trading volume, company size, earnings volatility, and level of debt have a significant effect on stock price volatility. Keywords: Stock price volatility, sharia company, panel data regression. DAFTAR PUSTAKABawono, A., & Shina, A. F. I. (2018). Ekonometrika terapan untuk ekonomi dan bisnis Islam aplikasi dengan Eviews. Salatiga: Lembaga Penelitian dan Pengabdian kepada Masyarakat (LP2M) IAIN Salatiga Press.Brigham, E. F., & Houston, J. F. (2011). Dasar-dasar manajemen keuangan, buku kedua. Jakarta: Salemba Empat.Camilleri, S. J., Grima, L., & Grima, S. (2019). The effect of dividend policy on share price volatility: an analysis of Mediterranean banks’ stocks. Managerial Finance, 45(2), 348–364. https://doi.org/10.1108/MF-11-2017-0451Dewi, S., & Paramita, R. A. S. (2019). Pengaruh kebijakan dividen, volume perdagangan, earning volatility, leverage, dan firm size terhadap volatilitas harga saham perusahaan LQ45. Jurnal Ilmu Manajemen, 7(3), 761–771.Fakhruddin, H. M. (2008). Istilah pasar modal A-Z. Jakarta: Elex Media Komputindo.Gumanti, T. A. (2013). Kebijakan Dividen (Pertama). UPP STIM YKPN.Jahfer, A., & Mulafara, A. H. (2016). Dividend policy and share price volatility: Evidence from Colombo stock market. Internaltional Journal Managerial and Financial Accounting, 8(2), 97–108. DOI:10.1504/IJMFA.2016.077947Jannah, R., & Haridhi, M. (2016). Pengaruh kebijakan dividen, earning volatility, dan leverage terhadap volatilitas harga saham pada perusahaan non-financing yang terdaftar di bursa efek Indonesia tahun 2010-2014. Jurnal Ilmiah Mahasiswa Ekonomi Akuntansi, 1(1), 133–148.Mehmood, A., Ullah, M. H., & Ul Sabeeh, N. (2019). Determinants of stock price volatility: Evidence from cement industry. Accounting, 5(4), 145–152. https://doi.org/10.5267/j.ac.2019.2.002Muhamad. (2016). Manajemen keuangan syari’ah analisis fiqh & keuangan. Yogyakarta: UPP STIM YKPN.Novius, A. (2017). Analisis pengaruh kebijakan deviden ( Dividen payout ratio dan devidend yield) terhadap volatilitas harga saham (Studi empiris pada perusahaan kelompok LQ45 yang terdaftar di BEI). Jurnal Al-Iqtishad, 13(1), 67. https://doi.org/10.24014/jiq.v13i1.4389Rowena, J., & Hendra. (2017). Earnings volatility, kebijakan dividen, dan pertumbuhan asset berpengaruh terhadap volatilitas harga saham pada perusahaan manufaktur di BEI periode 2013 – 2015. Jurnal Administrasi Kantor, 5(2), 231–242.Sarmanu. (2017). Dasar metodologi penelitian. Surabaya: Airlangga University Press.Septyadi, M. A., & Bwarleling, T. H. (2020). Pengaruh volume perdagangan saham, leverage, dan kebijakan dividen terhadap volatilitas harga saham, 2, 149–162.Shah, S. A., & Noreen, U. (2016). Stock price volatility and role of dividend policy: Empirical evidence from Pakistan. International Journal of Economics and Financial Issues, 6(2), 461–472.Spence. (1973). Job market signaling. The Quarterly Journal of Economics, 87(3), 355–374. https://doi.org/10.2307/1882010Tandelilin, E. (2010). Manajemen portofolio dan investasi. Surabaya: Kanisius.Yulinda, E., Pujiastuti, T., & Haryono, S. (2020). Analisis pengaruh dividend payout ratio, leverage, firm size, volume perdagangan, earning volatility, dan inflasi terhadap volatilitas harga saham pada perusahaan yang terdaftar dalam indeks LQ45 tahun 2014-2017. Jurnal Ilmiah Indonesia Ilmiah Indonesia, 5(5), 76. DOI:10.36418/syntax-literate.v5i5.1106Zainudin, R., Mahdzan, N. S., & Yet, C. H. (2018). Dividend policy and stock price volatility of industrial products firms in Malaysia. International Journal of Emerging Markets, 13(1), 203–217. https://doi.org/10.1108/IJoEM-09-2016-0250
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Delavari, Majid, Nadiya Gandali Ali khani, and Esmaeil Naderi. "Oil and Methanol Price volatility." Australian Journal of Business and Management Research 03, no. 08 (August 10, 2013): 01–10. http://dx.doi.org/10.52283/nswrca.ajbmr.20130308a01.
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Crude oil as one of the main sources of energy is also the main source of income for members of OPEC. So, the volatility of crude oil price is one of the main economic variables in the world and analysis of the effect of its changes on key economic factors has been always considered as significant. The reason might be the high sensitivity of oil price to political, economic and cultural issues worldwide and consequently its volatility on the one hand, and the high influence of the volatile prices on macroeconomic variables. On the other hand, for different reasons such as oil price volatilities and income from oil export, economic planners and policy makers in Iran have been mainly focused on the promotion of non-oil exports especially during the last few decades. Therefore, methanol as one of the most commonly used petrochemical products has a high potential for production and export of non-oil products in Iran. For this reason, in the present study there was an attempt to examine the relationship between the prices of Iran’s crude oil and methanol using FIGARCH model and based on the weekly time series data related to the research variables. The results of the study showed that the long memory parameter is equal to 0.32 which is meaning the shocks caused by volatility of methanol market and crude oil price to the methanol price were lasting and meaningful and were revealed in the long term.
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Bagchi, Bhaskar. "Volatility spillovers between crude oil price and stock markets: evidence from BRIC countries." International Journal of Emerging Markets 12, no. 2 (April 18, 2017): 352–65. http://dx.doi.org/10.1108/ijoem-04-2015-0077.
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Purpose The purpose of this paper is to examine the dynamic relationship between crude oil price volatility and stock markets in the emerging economies like BRIC (Brazil, Russia, India and China) countries in the context of sharp continuous fall in the crude oil price in recent times. Design/methodology/approach The stock price volatility is partly explained by volatility in crude oil price. The author adopt an Asymmetric Power ARCH (APARCH) model which takes into account long memory behavior, speed of market information, asymmetries and leverage effects. Findings For Bovespa, MICEX, BSE Sensex and crude oil there is an asymmetric response of volatilities to positive and negative shocks and negative correlation exists between returns and volatility indicating that negative information will create greater volatility. However, for Shanghai Composite positive information has greater effect on stock price volatility in comparison to negative information. The study results also suggest the presence long memory behavior and persistent volatility clustering phenomenon amongst crude oil price and stock markets of the BRIC countries. Originality/value The present study makes a number of contributions to the existing literature in the following ways. First, the author have considered crude oil prices up to January 31, 2016, so that the study can reflect the impact of declining trend of crude oil prices on the stock indices which is also regarded as “new oil price shock” to measure the volatility between crude oil price and stock market indices of BRIC countries. Second, the volatility is captured by APARCH model which takes into account long memory behavior, speed of market information, asymmetries and leverage effects.
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Xie, Lin, Jiahua Liao, Haiting Chen, Xuefei Yan, and Xinyan Hu. "Is Futurization the Culprit for the Violent Fluctuation in China’s Apple Spot Price?" Agriculture 11, no. 4 (April 12, 2021): 342. http://dx.doi.org/10.3390/agriculture11040342.
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China aims to utilize the futures market to stabilize agricultural product price fluctuation by quantifying the effects of risk transfer and price discovery. However, the role of futurization has been questioned and even posited as the cause of drastic fluctuations in spot market prices. This research aims to clarify the impact of futurization on the price fluctuation of agricultural products and to provide policy reference for the development of the agricultural futures market through the research. Here, we examine the spot price data for apples and use Interrupted time-series analysis (ITSA) and GARCH models to estimate the impact of apple futures on the volatility of spot prices. Our findings demonstrate that the launch of China’s apple futures did not increase the volatility of apple spot prices; that is, futurization was not the cause of skyrocketing apple spot prices. In the long term, our results suggest that futures will help reduce the volatility of apple spot prices and that the introduction of futures will ultimately reduce the price volatility of agricultural products.
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Kohar, Abdul, Nurmala Ahmar, and Suratno Suratno. "SENSITIVITAS FAKTOR EKONOMI MAKRO DAN MIKRO DALAM MEMPREDIKSI VOLATILITAS HARGA SAHAM PERUSAHAAN SEKTOR INDUSTRI FOOD & BEVERAGES." JIAFE (Jurnal Ilmiah Akuntansi Fakultas Ekonomi) 4, no. 1 (April 4, 2019): 85–100. http://dx.doi.org/10.34204/jiafe.v4i1.1080.
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The movement of macroeconomic factors can be used to predict the movement of the stock price, but different researchers are using different macroeconomic factors because there is still no consensus among them which macroeconomic factors that have an influence on stock prices. This study aimed to analyze and test the impact of macroeconomics factors which consisting of inflation, interest rates, exchange rate, and microeconomy factors, consisting of asset growth, growth earnings and sales growth to the volatility of stock prices on food and beverages companies listed in Indonesia Stock Exchange between 2011 and 2015 period. The study measure the sensitivity of inflation and interest rates and stock price volatility by regressing each variable with a share price which will produce the sensitivity value of each variable. A total of 66 samples are tested by using the classic assumption as the precondition for regression analysis techniques (multiple regressions). The results showed that inflation is partially affect the stock price volatility, Indonesia Interest Rate (SBI) is partially effect on stock price volatility, and exchange rate and microeconomics are partially no effect on stock price volatility.
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Araoye, Felix Ebun, Akinola Michael Aruwaji, and Emmanuel OlusuyiAjayi. "Effect of Dividend Policy on Stock Price Volatility in Nigeria Stock Exchange." International Journal of Accounting and Financial Reporting 9, no. 2 (April 15, 2019): 219. http://dx.doi.org/10.5296/ijafr.v9i2.11861.
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This paper seeks to determine the effect of dividend policy and dividend payment on share price volatility in Nigeria. Several literatures have showed evidence that dividend policy vary inversely proportional with share price volatility with duration effect. The study used data from the actively trading companies listed in the Nigeria Securities Exchange for a period of ten (10) years from 2005–2014. The estimation is based on panel data analysis between dividend policy measures (dividend payout, dividend per share, earnings after tax, dividend declared and number of share) and Share price volatility. The findings from the random effects regression results showed dividend per share is the major determinants of share price volatility in NSE (β = 0.6870, ρ<0.05). Dividend payout ratio negatively affect share price volatility (β =0.612, ρ>0.05) and earnings after tax negatively affect share price volatility (β =0.038, ρ>0.05).Thus, the higher the payout ratio the less the share price volatility, and the higher the earnings after tax lower the share price volatility. In conclusion, dividend per share has positive effect and inclusive relationship with market share prices. It is recommended that firms should try and improve on their financial performance that will enable consistent increase in the dividend per share for positive impact on market value.
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Kengatharan, Lingesiya, and Jeyan Suganya Dimon Ford. "Factors determining the share price volatility: Evidence from listed companies in Sri Lanka." Indonesian Management and Accounting Research 18, no. 2 (January 17, 2021): 105–26. http://dx.doi.org/10.25105/imar.v18i2.6196.
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The objective of this study is to investigate the factors determining the share price volatility of listed companies in Colombo Stock Exchange (CSE), Sri Lanka. A sample of 72 listed non -financial firms from CSE in Sri Lanka is examined using panel data analysis for a five years period from 2013 to 2017. Dividend payout ratio, dividend yield, dividend per share, sales growth, leverage, exchange rate, firm size, earnings volatility and GDP are considered as explanatory variables. According to the fixed effect regression analysis, only 22% of the movements in share prices are explained by the explanatory variables considered in this study. Dividend yield shows significant positive impact on share price volatility whereas dividend per share shows the significant negative impact on share price movements. Exchange rate and firm size illustrate significant negative influence on share price volatility by indicating if firm size is large share price volatility will be high. But, dividend pay-out, financial leverage, earnings volatility and GDP are not significantly convince the share price volatility in this study. Therefore, it is concluded that dividend yield, dividend per share, exchange rates and firm size have significant impact on price volatility in Sri Lankan context. Dividend policy can be considered as the protective mechanism to maintain share price volatility in order to enhance the shareholders wealth.
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Nurhabibah, Nurhabibah, Firmansyah Firmansyah, Bagus Pramushinto, and Fachroerrozi Hoesni. "Analisis Peramalan Harga Daging Ayam Broiler di Pasar Tradisional Provinsi Jambi." J-MAS (Jurnal Manajemen dan Sains) 7, no. 1 (April 18, 2022): 35. http://dx.doi.org/10.33087/jmas.v7i1.356.
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This study aims to determine the volatility of broiler chicken meat prices in the modern market in Jambi Province and to compile a proper forecasting model for the price of broiler chicken meat in the modern market in Jambi Province. Broiler Chicken Meat Price Forecasting Analysis in Jambi Province uses skunder data which is weekly time series data with the period 2018 - 2021 (September). The data analyzed in this study is the price of broiler chicken meat in the modern market of Jambi Province. The analysis method used to determine the volatility and proper forecasting model for broiler chicken meat prices in the modern market of Jambi Province uses the ARCH/GARCH, ARIMA model. The study concluded that there is volatility in the price of broiler chicken meat in the modern market of Jambi Province. The volatility of broiler chicken meat prices in the modern market is with the ARCH(1) model. n addition, volatility in the modern market of Jambi Province can be seen based on CSD or conditional standard deviations and its volatility value. in the modern market it is 0.01630950. The right forecasting model to determine the price of broiler chicken meat in modern market of Jambi City is to use the ARIMA model.
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Hassan, Fatin Aminah. "Dynamic Shocks of Crude Oil Price and Exchange Rate on Food Prices in Emerging Countries of Southeast Asia: A Panel Vector Autoregression Model." Asian Journal of Economic Modelling 10, no. 2 (June 15, 2022): 108–23. http://dx.doi.org/10.55493/5009.v10i2.4517.
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This paper empirically analyzes food price responses to shocks from crude oil price and exchange rate volatility in five emerging Southeast Asian nations between 2000 and 2020 using impulse response functions and variance decomposition analysis of the dynamic panel Vector Autoregression approach. Based on the findings of the impulse response functions analysis, food prices respond positively to both oil price and exchange rate shocks. Meanwhile, the results of variance decomposition analysis show that food prices account for a significant portion of volatility in its own shock. The contribution of oil price shock to food price volatility is found to be greater than the contribution of exchange rate shock. Hence, the study recommends that policymakers in these nations should be vigilant about the impacts of oil price and exchange rate shocks on food prices since these factors may undermine price stability and exacerbate food security.
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Gruber, Joseph W., and Robert J. Vigfusson. "INTEREST RATES AND THE VOLATILITY AND CORRELATION OF COMMODITY PRICES." Macroeconomic Dynamics 22, no. 3 (November 9, 2016): 600–619. http://dx.doi.org/10.1017/s1365100516000389.
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We propose a novel explanation for the observed increase in the correlation of commodity prices over the past decade. In contrast to theories that rely on the increased influence of financial speculators, we examine the effect of interest rates on the volatility and correlation of commodity prices via a panel GARCH model. In theory, lower interest rates decrease the volatility of prices, as lower inventory costs promote the smoothing of transient shocks, and increase price correlation if common shocks are more persistent than idiosyncratic shocks. Empirically, we find that price volatility attributable to transitory shocks declines with interest rates, whereas particularly for metals prices, price correlation increases as interest rates decline.
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Potto, Otniel Syebastian Agusto, and Robiyanto Robiyanto. "THE DYNAMIC CORRELATION BETWEEN OIL PRICES AND THE INDONESIAN OIL COMPANIES’ STOCK PRICE." Image : Jurnal Riset Manajemen 10, no. 1 (July 2, 2021): 28–43. http://dx.doi.org/10.17509/image.v10i1.31283.
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This study aims to analyze the correlation between oil prices and the Indonesian oil companies’ stock price during the pandemic of COVID-19 by testing the effect of oil price changes on companies' stock return and stock volatility. Also, by considering the dynamic correlation between oil prices and the Indonesian oil companies’ stock prices. The data were collected from secondary data at www.finance.yahoo.com, Oil prices, and the Indonesian oil companies’ stock price period from January 2020 to June 2020 during the pandemic of COVID-19. Further, the data were analyzed by using a GARCH method to examine the effect of changes in oil prices for stock return and stock volatility. Also, the DCC-GARCH method was used to see the dynamic correlation between oil prices and the Indonesian oil companies’ stock price. The result showed that changes in oil prices have a significant effect on stock price volatility and the presence of a positive dynamic correlation between oil prices and the Indonesian oil companies’ stock price. This research can be used as a reference for investors for their investments by looking at the relationship between the oil price and The Indonesian oil companies’ stock price.
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Pardomuan Siregar, Ernst Tunggul, and Bangkit Nata Satria M. "The Effect of Green Finance On Stock Price Volatility." Eduvest - Journal of Universal Studies 3, no. 1 (January 20, 2023): 83–95. http://dx.doi.org/10.36418/eduvest.v3i1.719.
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This study aims to determine the effect of green finance (green accounting) on stock price volatility. Stock price volatility is the movement of up and down stock prices on the stock exchange. In this study, the sample used was mining companies listed on the Indonesia Stock Exchange for the 2013-2018 period with a total population of 46 companies. With purposive sampling technique, get 18 companies as samples. This study used the panel data regression method with a common effect model approach. The results showed that a green finance has a positive effect on stock price volatility. Information asymmetry as a moderation variable cannot amplify the influence of green finance on stock price volatility, and also the effect of quality environmental and social disclosures on stock price volatility
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Pardomuan Siregar, Ernst Tunggul, and Bangkit Nata Satria M. "The Effect of Green Finance On Stock Price Volatility." Eduvest - Journal of Universal Studies 3, no. 1 (January 20, 2023): 83–95. http://dx.doi.org/10.36418/eduvest.v3i1.734.
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This study aims to determine the effect of green finance (green accounting) on stock price volatility. Stock price volatility is the movement of up and down stock prices on the stock exchange. In this study, the sample used was mining companies listed on the Indonesia Stock Exchange for the 2013-2018 period with a total population of 46 companies. With purposive sampling technique, get 18 companies as samples. This study used the panel data regression method with a common effect model approach. The results showed that a green finance has a positive effect on stock price volatility. Information asymmetry as a moderation variable cannot amplify the influence of green finance on stock price volatility, and also the effect of quality environmental and social disclosures on stock price volatility