scholarly journals SPILLOVER EFFECT INFLASI DAGING SAPI ANTAR KOTA: APLIKASI METODE BEKK-GARCH UNTUK JAKARTA, SALATIGA, DAN SURABAYA

2020 ◽  
Vol 13 (1) ◽  
pp. 80-91
Author(s):  
Ribut Nurul Tri Wahyuni ◽  
Nasrudin Nasrudin
Keyword(s):  
Spillover Effect ◽  
Garch Model ◽  
Internal Factors ◽  
Price Fluctuation ◽  
News Effects

Beef consumption in Indonesia tends to increase and its price fluctuates. In addition to internal factors, the volatility of beef inflation can also be influenced by other regions (spillover effect). Using BEKK-GARCH model, we try to show spillover effect the volatility of beef inflation in Jakarta, Salatiga, and Surabaya. The transmissions of news effects occur from Jakarta and Surabaya to Salatiga and from Jakarta and Salatiga to Surabaya. Transmission of two-way volatility occurs between Jakarta and Surabaya. Furthermore, the transmission of one-way volatility occurrs from Jakarta to Salatiga. Price fluctuation in consumer areas will be followed by price fluctuation in other consumer areas and producer areas. Therefore, controlling beef inflation should be began from consumer areas.

ANALISIS PENGARUH ERUBAHAN TINGKAT SUKU BUNGA SBI DAN PERUBAHAN KURS US$ TERHADAP HARGA PASAR SAHAM SEMEN GRESIK, TBK PERIODE JANUARI 2002 – DESEMBER 2006

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Oktafalia Marisa ◽  
Maya Syafriana
Keyword(s):  
Monetary Policy ◽  
Exchange Rate ◽  
Cash Flow ◽  
Stock Price ◽  
External Factors ◽  
Investment Climate ◽  
Internal Factors ◽  
Price Fluctuation ◽  
Two Factors ◽  
Investment Behaviour

<p class="Pendahuluan">Investment climate has begun to rise since a few years ago. Stock price fluctuations keep stable and move to the positive position. Stock price fluctuation affected by two factors, internal factors and external factors. Internal factors consist of company’s cash flow, dividend and investment behaviour. External factors consist of monetary policy, exchange rate, interest volatility, globalization, companies’ competition, and technology. This research, try to find out the effects of SBI rate and exchanged rate (USD/Rp) to PT. Semen Gresik’s stock price.</p><p class="Pendahuluan"> </p><p class="Pendahuluan">Keywords : Investment, stock price, SBI’s rate, and Exchanged rate.</p>

scholarly journals Multi-Time Scale Spillover Effect of International Oil Price Fluctuation on China’s Stock Markets

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4641
Author(s):  
Jingran Zhu ◽  
Qinghua Song ◽  
Dalia Streimikiene
Keyword(s):  
Crude Oil ◽  
Time Scale ◽  
Stock Markets ◽  
Spillover Effect ◽  
Oil Price ◽  
Time Varying ◽  
Price Fluctuation ◽  
The Impact ◽  
Oil Price Fluctuation

With the continuous increase of China’s foreign-trade dependence on crude oil and the accelerating integration of the international crude oil market and the Chinese finance market, the spillover effect of international oil price fluctuation on China’s stock markets increasingly attracts the attention of the public. In order to explore the impact of international oil price fluctuation on China’s stock markets and the time-varying spillover differences of industry sectors, this study proposes three research hypotheses and constructs a multi-time scale analysis framework based on wavelet analysis and a time-varying t-Copula model. In this paper, we use the Shanghai Composite Index as the representative of a general trend of the stock market, and we use the stock index of the China Securities Industry as the counterpart of industrial sectors. Based on the data from 5 January 2005 to 31 May 2020, this paper measures and analyzes the spillover effect of international oil price fluctuation on China’s stock markets, under different volatility periods. The results show that, firstly, the spillover effect of international oil price fluctuation on the Chinese stock markets is different. In the short and medium volatility period, the changes in international oil price are ahead of the changes in the Chinese stock markets, while the latter is ahead of the former under long-term fluctuations. Secondly, the spillover effect of international oil price fluctuation on China’s industry stock indexes is persistent. As the time scale increases, the tail dependency will increase. Finally, the impact of risk events aggravates the volatility of the stock markets in the short-term, while the mid- to long-term impact mainly affects the volatility trend. Investment risk control can make overall arrangement on the basis of the characteristics of oil price impact under different fluctuation stages.

scholarly journals Research on the Price Fluctuation and Risk Formation Mechanism of Carbon Emission Rights in China Based on a GARCH Model

2020 ◽  
Vol 12 (10) ◽  
pp. 4249 ◽  
Author(s):  
Jilin Zhang ◽  
Yukun Xu
Keyword(s):  
Carbon Emission ◽  
Garch Model ◽  
Statistical Characteristics ◽  
Mature Stage ◽  
Formation Mechanisms ◽  
Economic Downturn ◽  
Conditional Heteroskedasticity ◽  
Price Fluctuation ◽  
Price Series ◽  
Emission Rights

This paper examines the price of carbon emission rights published by the China Emissions Exchange (Shenzhen), analyzes the statistical characteristics of the price series and uses a generalized autoregressive conditional heteroskedasticity (GARCH) model to describe the price fluctuation of carbon emission rights and risk formation mechanisms. The study shows the following results: since 2013, China’s carbon emission rights prices have become more stable. The fluctuation of yield has gradually decreased and the market has approached a more mature stage. However, after 2018, due to factors such as the economic downturn and insufficient market information, the amplitude of price fluctuations has started to rise while frequency is increasing, which shows an asymmetry trend. The market trading risk is accumulating constantly.

Study on the Price Fluctuation and Dynamic Relationship between Log and Sawn Timber

2019 ◽  
Vol 69 (1) ◽  
pp. 34-41
Author(s):  
Rong Zhao ◽  
Gang Diao ◽  
Shaozhi Chen
Keyword(s):  
Statistical Significance ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Timber Supply ◽  
Price Fluctuation ◽  
Social Growth ◽  
Dynamic Relationship ◽  
Long Run ◽  
Sawn Timber ◽  
Timber Markets

Abstract The rapid economic and social growth of China has significantly increased its timber demand, resulting in a heavy reliance on foreign timber supply. Thus, price fluctuation in the international market poses a great risk to domestic timber production and processing enterprises. This study analyzed the dynamic conduction relationship between domestic and international logs and sawn timber markets and how to reduce risks by adjusting the structure of imported products' portfolios. In this article, the multivariate generalized autoregressive conditional heteroskedasticity model is applied to analyze the relationship between domestic and import prices of logs and sawn timber. The study found that among four markets, except one where the short-term spillover effect between domestic logs and sawn timber is large with statistical significance, spillover effects are small. In the long run, there are significant spillover effects between the four markets. Thus, changes in the international log market are very easy to transfer to the domestic log market through trade and then to the downstream domestic and international sawn timber markets. Therefore, in order to ensure timber security in China, this study uses the theory of portfolios to calculate product proportion with minimum risks. The proportion of portfolios indicates that, even though Chinese companies prefer logs, they have to import a great amount of sawn timber due to restrictions on log exports from sourcing countries, which increases the risk of timber supply.

scholarly journals Determining the Best Arch/Garch Model and Comparing JKSE with Stock Index in Developed Countries

The Winners ◽  
2015 ◽  
Vol 16 (2) ◽  
pp. 71
Author(s):  
Kharisya Ayu Effendi
Keyword(s):  
Interest Rates ◽  
Sharp Increase ◽  
Garch Model ◽  
Developed Countries ◽  
External Factors ◽  
Stock Index ◽  
Upward Trend ◽  
Internal Factors ◽  
The Us ◽  
Stock Indexes

The slow movement of Indonesia economic growth in 2014 due to several factors, in internal factors; due to the high interest rates in Indonesia and external factors from the US which will raise the fed rate this year. However, JKSE shows a sharp increase trend from the beginning of 2014 until the second quarter of 2015 although it remains fluctuate but insignificant. The purpose of this research is to determine the best ARCH/ GARCH model in JKSE and stock index in developed countries (FTSE, Nasdaq and STI) and then compare the JKSE with the stock index in developed countries (FTSE, Nasdaq and STI). The results obtained in this study is to determine the best model of ARCH / GARCH, it is obtained that JKSE is GARCH (1,2), while the FTSE obtains GARCH (2,2), NASDAQ produces the best model which is GARCH (1,1) and STI with GARCH (2,1), and the results of the comparison of JKSE with FTSE, NASDAQ and STI are that even though JKSE fluctuates with moderate levels but the trend shown upward trend. This is different with other stock indexes fluctuated highly and tends to have a downward trend.

scholarly journals The Impact of Macroeconomic News on US Interest Rates and Stock Indices Conditional on Their Volatility

2019 ◽  
Vol 4 (4) ◽  
Author(s):  
Sukriye Tuysuz ◽  
Catherine Lubochinsky
Keyword(s):  
Interest Rates ◽  
Stock Returns ◽  
Garch Model ◽  
Macroeconomic News ◽  
Economic Instability ◽  
Stock Indices ◽  
High Volatility ◽  
News Effects ◽  
The Impact ◽  
High Uncertainty

This paper investigates the impact of macroeconomic news on the dynamics of interest rates and stock returns during "low" and "high" volatility periods. These periods are determined by estimating asset dynamics using a SWARCH process. Our results suggest that securities volatility is higher during periods of financial or economic instability. We use these results to evaluate the impact of news during "low" and "high" volatility  periods using a GARCH model. News effects, especially “good” and “large” news, on interest rates are amplified during "high" uncertainty periods. The effect on stock returns is moderate. GARCH parameters differ strongly during both periods.

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