Academic literature on the topic 'Volatility'

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Journal articles on the topic "Volatility"

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Colin, Simanjuntak Ronald, and Febrio Nathan Kacaribu. "Pengaruh Volatilitas Makroekonomi terhadap Alokasi Kredit Bank." Jurnal Ekonomi dan Pembangunan Indonesia 21, no. 2 (October 24, 2021): 257–76. http://dx.doi.org/10.21002/jepi.v21i2.1311.

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This study discusses the impact of macroeconomic volatility on bank credit allocation. The hypothesis built that macroeconomic volatility will influence banks to careful in issuing new loans. This study uses panel data with a sample of 10 banks using Baum model. This study uses the macroeconomic volatility as bebast variables. This study uses a generalized method of moment regression test to examine the relationship between dependent and bebast variables. The results of this study indicate negative relationship between inflation volatility and volatility in GDP growth with lending, whereas the volatility of exchange rate depreciation does not have effect on lending. ----------------------------------------------------- Penelitian ini membahas dampak volatilitas makroekonomi terhadap alokasi kredit bank. Hipotesis yang dibangun bahwa volatilitas makroekonomi akan memengaruhi bank bersikap hati-hati dalam menerbitkan kredit baru. Penelitian ini menggunakan data panel dengan sampel sepuluh bank dengan menggunakan Model Baum. Penelitian ini menggunakan volatilitas makro ekonomi sebagai variabel bebas. Penelitian ini menggunakan uji regresi generalized method of moment untuk meneliti hubungan antara variabel dependen dan bebas. Hasil dari penilitian ini menunjukkan adanya hubungan negatif antara volatilitas inflasi dan volatilitas pertumbuhan GDP dengan penyaluran kredit, sedangkan untuk volatilitas depresiasi nilai tukar tidak memiliki pengaruh terhadap penyaluran kredit.
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Astuti, Tri, Sri Ambarwati, and Myranda Shavira. "DETERMINAN VOLATILITAS HARGA SAHAM." RELEVAN : Jurnal Riset Akuntansi 1, no. 2 (May 31, 2021): 73–82. http://dx.doi.org/10.35814/relevan.v1i2.2262.

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Penelitian ini bertujuan untuk menguji secara empiris pengaruh kebijakan dividend, leverage, ukuran perusahaan, dan earning volatility terhadap volatilitas harga saham pada perusahaan manufaktur yang terdaftar di Bursa Efek Indonesia selama 2016-2018. Sampel diperoleh menggunakan metode sampel purposive sampling. Sampel yang digunakan dalam penelitian ini sebanyak 18 perusahaan manufaktur. Penelitian ini dilakukan dengan menggunakan analisis regresi linear berganda. Berdasarkan hasil uji t, kebijakan dividend dan leverage tidak berpengaruh pada volatilitas harga saham, ukuran perusahaan berpengaruh positif, dan earning volatility berpengaruh negatif terhadap volatilitas harga saham. Dari hasil uji F, secara simultan kebijakan dividend, leverage, ukuran perusahaan, dan earning volatility berpengaruh terhadap volatilitas harga saham. Hasil uji koefisien determinasi menunjukkan, variabel kebijakan dividend, leverage, ukuran perusahaan, dan earning volatility memberikan pengaruh sebesar 39,69% dan sisanya dipengaruhi oleh variabel lain di luar model penelitian ini. Kata kunci: Kebijakan Dividend, Leverage, Ukuran Perusahaan, Earning Volatility, dan Volatilitas Harga Saham
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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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Ferina, Mahmudah Wulan, and Sunarto Sunarto. "Pengaruh Kebijakan Dividen, Leverage, Volume Perdagangan Saham Terhadap Volatilitas Harga Saham." Journal of Economic, Bussines and Accounting (COSTING) 7, no. 3 (February 3, 2024): 4154–61. http://dx.doi.org/10.31539/costing.v7i3.8632.

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The difference in a company's share price over a certain period of time is known as volatility of share price. A company's volatility is a mirroring of the opportunities and dangers that investors may face. Investors need to pay attention to indicators such as number of trades, leverage, and dividend policy which can impact share price volatility. This research purposes to look at the variables that effected the level of stock price volatility. Issuers listed on the BEI LQ45 index in 2018-2022 are the research population. Purposive sampling was applied to select the research sample with 168 issuers. Hypothesis testing is calculated through multiple regression analysis. The findings of the analysis model explain that (1) Dividend policy has a important and positive effect on the company's volatility value. (2) Leverage has no influence on share price volatility. (3) Trading volume has no influence on share price volatility. This provides an grasp of the low and high levels of dividend policy variables which can have an influence on understanding the level of share price volatility.Keywords: price volatility, dividend payout ratio (DPR), debt to equity ratio (DER), and trading volume activity (TVA). ABSTRAK Perbedaan harga saham perusahaan pada kurun waktu tertentu dikenal sebagai volatilitas harga saham. Volatilitas perusahaan adalah cerminan peluang dan bahaya yang mungkin dihadapi investor. Investor perlu memperhatikan indikator-indikator seperti jumlah perdagangan, leverage, dan kebijakan dividen yang memberikan dampak akan volatilitas harga saham. Penelitian ini memiliki tujuan melihat berbagai variabel yang berpengaruh pada tingkat volatilitas harga saham. Emiten yang tercatat pada indeks LQ45 BEI pada tahun 2018-2022 menjadi populasi penelitian. Purposive sampling diaplikasikan untuk memilih sampel, yang akhirnya 168 emiten menjadi sampel penelitian. Uji hipotesis dihitung melalui analisis regresi berganda. Temuan model penelitian menjelaskan bahwasanya (1) Kebijakan dividen memberikan pengaruh secara signifikan dan positif dengan nilai volatilitas perusahaan. (2) Leverage tidak memberikan pengaruh kepada volatilitas harga saham. (3) Volume perdagangan tidak memberikan pengaruh kepada volatilitas harga saham. Hal ini memberikan pemahaman tinggi rendahnya variabel kebijakan dividen mampu memberikan pengaruh akan pemahaman tingkat volatilitas harga saham. Kata kunci : Volatilitas harga saham, Dividend Pay Ratio (DPR), Debt to Equity Ratio (DER), Trading Volume Activity (TVA)
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Danial, Rahmadiva Dianitha, and Brady Rikumahu. "PENGARUH VOLATILITAS NILAI TUKAR, IDR-USD TERHADAP RETURN SAHAM DI BURSA EFEK INDONESIA: PENERAPAN MODEL GARCH." Jurnal Riset Akuntansi dan Keuangan 14, no. 2 (July 16, 2019): 95. http://dx.doi.org/10.21460/jrak.2018.142.327.

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Penelitian ini bertujuan untuk menguji pengaruh volatilitas return nilai Kurs IDR-USD terhadap volatilitas return pasar saham di Bursa Efek Indonesia. Dari pengambilan data sekunder dari 3 Januari 2012 hingga 29 September 2017 diperoleh data time series sebanyak 1404 hari. Data dianalisis dengan model GARCH dan Uji Granger Causality. Berdasarkan hasil permodelan GARCH(1,1), volatilitas kurs mempengaruhi volatilitas IHSG. Uji Granger Causality menunjukkan bahwa volatilitas kurs dan IHSG memiliki hubungan yang kausal dua arah. Penelitian ini menunjukkan bahwa informasi kurs dapat memprediksikan kondisi harga indeks saham di pasar modal di periode hari berikutnya, begitupun sebaliknya. Prediksi tepat yang dilakukan oleh investor akan mengurangi risiko dan meningkatkan imbal hasil dalam berinvestasi jika pasar uang maupun pasar modal yang sedang bergejolak. Kata Kunci: GARCH, Volatilitas, IHSG, Nilai Tukar ABSTRACT This study aims to examine the effect of the volatility of the return on the IDR-USD exchange rate toward the volatility of stock market returns in the Indonesia Stock Exchange. From the data collection from 3 January 2012 until 29 September 2017 we obtained 1404 time series. Analyzing data, this study used GARCH modeling and Granger Causality Test. The selected GARCH (1,1) modeling result shows that the volatility of exchange rate influences the volatility of Indonesian Composite Index. Granger Causality test shows that the volatility of exchange rate and volatility of Indonesian Composite Index have two-way granger cause. This study indicates that exchange rate information can predict the condition of stock price index in capital market and movement of Indonesian Composite Index (ICI) can predict exchange rate movement in foreign exchange market. Appropriate predictions by investors will reduce the risk and increase the yield in investing if the money market and capital markets are fluctuating high. Keywords: GARCH, Volatility, ICI, Exchange Rate
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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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Blanco, Belen. "Capturing the volatility smile: parametric volatility models versus stochastic volatility models." Public and Municipal Finance 5, no. 4 (December 26, 2016): 15–22. http://dx.doi.org/10.21511/pmf.05(4).2016.02.

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Black-Scholes option pricing model (1973) assumes that all option prices on the same underlying asset with the same expiration date, but different exercise prices should have the same implied volatility. However, instead of a flat implied volatility structure, implied volatility (inverting the Black-Scholes formula) shows a smile shape across strikes and time to maturity. This paper compares parametric volatility models with stochastic volatility models in capturing this volatility smile. Results show empirical evidence in favor of parametric volatility models. Keywords: smile volatility, parametric, stochastic, Black-Scholes. JEL Classification: C14 C68 G12 G13
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Pírko, Štěpán. "Investice do volatility jako odpověď na nízké výnosy." Socio-Economic and Humanities Studies 7, no. 1 (June 3, 2018): 125–38. http://dx.doi.org/10.61357/sehs.v7i1.74.

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Pokles úrokových sazeb na historicky nejnižší úrovně se během posledních let stal klíčovým problémem řady investorů. Jednou z alternativ, jak v takové nestandardní době dosahovat výnos, je využít investiční strategie orientované na obchodování s volatilitou. Řada publikovaných studií dokládá, že ceny opcí jsou dlouhodobě vyšší, než odpovídá skutečné volatilitě podkladových aktiv, zejména akciových indexů, což vytváří prostor pro dosažení zisku využitím opcí a dalších investičních nástrojů. Závěry studií, sestrojené indexy i skutečná výkonnost portfolií založených na výše uvedeném principu prokazují, že prostor pro ziskové investiční strategie může být trvalý a je založen na ekonomických zákonitostech vyplývajících z chování investorů. Investiční strategie založené na investování do volatility tak mohou, i přes řadu rizikových faktorů, obohatit výnos portfolia tradičních cenných papírů.
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Mahatma, Yudi, and Ibnu Hadi. "Stochastic Volatility Estimation of Stock Prices using the Ensemble Kalman Filter." InPrime: Indonesian Journal of Pure and Applied Mathematics 3, no. 2 (November 10, 2021): 136–43. http://dx.doi.org/10.15408/inprime.v3i2.20256.

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AbstractVolatility plays important role in options trading. In their seminal paper published in 1973, Black and Scholes assume that the stock price volatility, which is the underlying security volatility of a call option, is constant. But thereafter, researchers found that the return volatility was not constant but conditional to the information set available at the computation time. In this research, we improve a methodology to estimate volatility and interest rate using Ensemble Kalman Filter (EnKF). The price of call and put option used in the observation and the forecasting step of the EnKF algorithm computed using the solution of Black-Scholes PDE. The state-space used in this method is the augmented state space, which consists of static variables: volatility and interest rate, and dynamic variables: call and put option price. The numerical experiment shows that the EnKF algorithm is able to estimate accurately the estimated volatility and interest rates with an RMSE value of 0.0506.Keywords: stochastic volatility; call option; put option; Ensemble Kalman Filter. AbstrakVolatilitas adalah faktor penting dalam perdagangan suatu opsi. Dalam makalahnya yang dipublikasikan tahun 1973, Black dan Scholes mengasumsikan bahwa volatilitas harga saham, yang merupakan volatilitas sekuritas yang mendasari opsi beli, adalah konstan. Akan tetapi, para peneliti menemukan bahwa volatilitas pengembalian tidaklah konstan melainkan tergantung pada kumpulan informasi yang dapat digunakan pada saat perhitungan. Pada penelitian ini dikembangkan metodologi untuk mengestimasi volatilitas dan suku bunga menggunakan metode Ensembel Kalman Filter (EnKF). Harga opsi beli dan opsi jual yang digunakan pada observasi dan pada tahap prakiraan pada algoritma EnKF dihitung menggunakan solusi persamaan Black-Scholes. Ruang keadaan yang digunakan adalah ruang keadaan yang diperluas yang terdiri dari variabel statis yaitu volatilitas dan suku bunga, dan variabel dinamis yaitu harga opsi beli dan harga opsi jual. Eksperimen numerik menunjukkan bahwa algoritma ENKF dapat secara akurat mengestimasi volatiltas dan suku bunga dengan RMSE 0.0506.Kata kunci: volatilitas stokastik; opsi beli; opsi jual; Ensembel Kalman Filter.
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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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Dissertations / Theses on the topic "Volatility"

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Hrbek, Filip. "Metody předvídání volatility." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-264689.

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In this masterthesis I have rewied basic approaches to volatility estimating. These approaches are based on classical and Bayesian statistics. I have applied the volatility models for the purpose of volatility forecasting of a different foreign exchange (EURUSD, GBPUSD and CZKEUR) in the different period (from a second period to a day period). I formulate the models EWMA, GARCH, EGARCH, IGARCH, GJRGARCH, jump diffuison with constant volatility and jump diffusion model with stochastic volatility. I also proposed an MCMC algorithm in order to estimate the Bayesian models. All the models we estimated as univariate models. I compared the models according to Mincer Zarnowitz regression. The most successfull model is the jump diffusion model with a stochastic volatility. On the second place they were the GJR- GARCH model and the jump diffusion model with a constant volatility. But the jump diffusion model with a constat volatilit provided much more overvalued results.The rest of the models were even worse. From the rest the IGARCH model is the best but provided undervalued results. All these findings correspond with R squared coefficient.
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Stolbov, Anatoly. "Volatility Smile and Delta Hedging." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-206214.

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The thesis describes and applies two parametric option pricing models which partially ease the well-known discrepancy between real world and Black-Scholes model. Stochastic volatility and jumps encompassed by Heston and SVJ models explain implied volatility smile and its heterogeneous term-structure. Both models are calibrated to market data observed for EURUSD currency options on January 23, 2015. While SVJ model provided a better fit for the market, especially for mid-term expiry smile curvature, its estimated risk-neutral parameters were unrealistic comparing with their counterparts under statistical measure. Estimations suggest zero long term price volatility and 2 jumps during the year with average magnitude of 6 \%. Both models failed to match curvature of short time to expiry smile and provided a good fit of term-structure and long-expiry smile. Analysing delta ratios adjusted for non-constant volatility as a possible alternatives the study considered minimum variance delta estimated with Heston model, delta ratio recommended by Nassim Taleb and two deltas adjusted for local volatility assuming sticky moneyness and sticky tree dynamics of implied volatility. On data set of EURUSD options from 1.1.2014 to 30.5.2015, our research did not find any alternative which would be more reliable than common Black-Scholes delta.
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Galiotos, Vassilis. "Stochastic Volatility and the Volatility Smile." Thesis, Uppsala University, Department of Mathematics, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-120151.

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Marklund, Joakim, and Olle Karlsson. "Volatility Derivatives – Variance and Volatility Swaps." Thesis, Uppsala universitet, Analys och sannolikhetsteori, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-254657.

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Gříšek, Lukáš. "Cena volatility finančních proměnných." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-113803.

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This diploma thesis describes problem of change-points in volatility of the time-series and their impact on price of nancial assets. Those change-points are estimated by using statistical methods and tests. Change-point estimation was tested on simulated datas and real world driven datas. Simulation helped to discover signi cant characteristics of change-point test, those data were simulated with using stochastic calculus. Google share prices and prices of call options were chosen to analyse impact of volatility change on those prices. Also implied volatility and its impact to call option price was analysed.
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Rossi, Luca. "Essays on volatility networks and uncertainty." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/565613.

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This thesis empirically investigates different aspects of time-varying volatility. Chapter 1 estimates a large TVP-FAVAR and recovers a dynamic directed network of connections between European stock volatilities. We propose an ad-hoc estimation methodology that is shown to outperform both standard approaches and competing models. Chapter 2 focuses on tracking dynamic connectedness between US sectoral volatilities using Generalized Forecast Error Variance Decompositions with a Bayesian model. As opposed to estimates obtained with rolling windows, we allow parameters to vary in a more flexible way. We show that there exists a stable relationship between the network structure and the volatility regimes in place at a given time. Chapter 3 estimates the unexpected time-varying volatility component of fiscal budgets in Italy. We show that periods of higher unexpected fiscal volatility are likely to be recessionary. Expansionary policies are effective only when not accompanied by increases in uncertainty.
Aquesta tesi investiga empíricament diferents aspectes de la volatilitat variable. El Capítol 1 estima un TVP-FAVAR i recupera una xarxa de connexions dinàmiques entre les volatilitats de accions europees. Proposem una metodologia d’estimació ad-hoc que es demostri que supera els enfocaments estàndard i els models competidors. El Capítol 2 es centra en el seguiment de la connectivitat dinàmica entre les volatilitats sectorials dels Estats Units mitjançant descomposicions generalitzadas de variància d’errors de previsió amb un model Bayesià. A diferència de les estimacions obtingudes amb finestres enrotllables, permetem que els paràmetres variïn de manera més flexible. Mostrem que existeix una relació estable entre l’estructura de la xarxa i els règims de volatilitat vigents en un moment determinat. El Capítol 3 estima el component variable inesperat de la volatilitat dels pressupostos fiscals a Itàlia. Mostrem que els períodes de major volatilitat fiscal inesperada probablement són recessius. Les polítiques expansives només són efectives quan no s’acompanyen d’increments d’incertesa.
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Švehla, Pavel. "Analýza volatility akciových indexů na evropských burzách." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-81856.

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This thesis focuses on analysis and comparison of volatility on selected European stock markets. At first paper briefly introduces the reader to the specific features of financial econometrics and the importance of asset returns volatility analysis. Further chapters precisely cover the construction of linear and nonlinear conditional heteroscedasticity models as an appropriate tool for describing the volatility in financial data. The empirical part of the thesis analyze four stock exchange indices from various European regions and seek appropriate models to express volatility behavior in period before the financial crisis in 2008 and also during the crisis phase. Based on selected models, the paper tries to compare the volatility in both periods within the specific stock market index and moreover between different regions. The last section examines asymmetric effects in volatility of stock indices using their graphical representation.
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Wayne, David Hadyn. "Incomplete markets, volatility smiles and volatility trading." Thesis, Imperial College London, 2000. http://hdl.handle.net/10044/1/11267.

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Lopes, Rita Isabel Dória Gameiro. "Volatility derivatives and volatility indexes : an overview." Master's thesis, Instituto Superior de Economia e Gestão, 2014. http://hdl.handle.net/10400.5/9048.

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Mestrado em Finanças
Nas últimas décadas, os derivados financeiros têm-se revestido de grande importância, como se deduz facilmente do facto de o número de transações nos mercados financeiros envolvendo este tipo de instrumentos apresentar grande crescimento. De entre a grande variedade de derivados, destaca-se, para efeitos deste trabalho, uma classe particular, a classe dos derivados sobre volatilidade, que têm sido objeto de estudo na última década, talvez devido ao papel relativamente significativo que vêm assumindo a nível dos principais mercados. Intimamente ligados aos derivados sobre volatilidade estão os índices sobre volatilidade, também aqui objeto de análise. O presente estudo consiste essencialmente na revisão possível, dadas as restrições de espaço, da vasta literatura que já existe sobre o tema, o que se procurará fazer ao longo de todo o texto. Adicionalmente, procurará levar-se a cabo uma pesquisa do impacte da última crise financeira e económica no volume de negócios com derivados sobre volatilidade, para o que se selecionará um particular tipo de produtos. Do levantamento realizado sobre os tópicos em questão, pareceu poder concluir-se que estes não suscitaram antes o interesse de estudiosos portugueses. Nesse sentido, será então este o primeiro contributo, ainda que modesto, para preencher a lacuna.
During the last few decades, financial derivatives became extremely important, a conclusion easily derived from the fact that the number of transactions involving such instruments has greatly increased in financial markets. A specific type of these products consists of the so-called volatility derivatives, which have been quite studied during the last few years and are now of great significance, having experienced a growing role in the world financial markets. Closely related to volatility derivatives are the volatility indexes. This study is based mostly on a review of the literature on the subject of volatility derivatives and volatility indexes, which is presented all over the text. Additionally, an attempt is made to analyze the impact of the current economic and financial crises on volatility derivatives trading, specifically in reference to certain particular futures. To the best knowledge of the author the topic of volatility futures has not been addressed before in the Masters in Finance context; this thesis is, in that sense, a first (very small) contribution to fill the gap.
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Varga, Lukáš. "Effect of Implied Volatility on FX Carry Trade." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-113592.

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This thesis aims to back-test the ability of implied volatility carry trade strategies to outperform the carry trade strategies in the FX markets. Recent research has shown that the profitability of the strategies is partly attributable to the market mispricings of the forward volatility agreements and a tendency of the forward implied volatility to overestimate the future spot implied volatility. This thesis uses a similar approach to construct portfolios containing 10 developed as well as 9 emerging market currencies. Our approach is based on the assumption that Uncovered Interest rate Parity (UIP), Forward Unbiasedness Hypothesis (FUH) and Forward Volatility Unbiasedness Hypothesis (FVUH) do not hold and therefore providing investors with several opportunities to construct trading strategies taking advantage of these market mispricings. In this thesis, we show that the foreign exchange carry trade strategy composed of the specific developed and emerging country's currencies can be outperformed by portfolio consisting of the implied volatility carry trade strategies in the FX market over the analysed period. The portfolios are adjusted to the riskiness which is accounted for by the VIX and VXY-G7 index for developed and VIX and VXY-EM index for emerging economies. The strong performance of the strategies outlined in this thesis can be of significant value to FX traders and portfolio managers.
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Books on the topic "Volatility"

1

Schwartz, Robert A., John Aidan Byrne, and Antoinette Colaninno, eds. Volatility. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-1474-3.

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Sinclair, Euan. Volatility Trading. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118662724.

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Shiller, Robert J. Market volatility. Cambridge, Mass: MIT Press, 1989.

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Sinclair, Euan. Volatility Trading. New York: John Wiley & Sons, Ltd., 2008.

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G, Andersen Torben, and National Bureau of Economic Research., eds. Volatility forecasting. Cambridge, Mass: National Bureau of Economic Research, 2005.

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Takahashi, Makoto, Yasuhiro Omori, and Toshiaki Watanabe. Stochastic Volatility and Realized Stochastic Volatility Models. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0935-3.

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Gatheral, Jim. The Volatility Surface. New York: John Wiley & Sons, Ltd., 2006.

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Koren, Miklós. Volatility and development. London: Centre for Economic Performance, London School of Economics and Political Science, 2005.

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Bag, Dinabandhu. Valuation and Volatility. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-1135-3.

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Javaheri, Alireza. Inside Volatility Filtering. Hoboken, NJ, USA: John Wiley & Sons, Inc, 2015. http://dx.doi.org/10.1002/9781118949092.

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Book chapters on the topic "Volatility"

1

Sarkar, Asani, Robert Almgren, Albert J. Menkveld, and Liuren Wu. "Intraday Volatility: The Empirical Evidence." In Volatility, 1–18. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-1474-3_1.

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Francioni, Reto. "Opening Address: Reto Francioni." In Volatility, 19–28. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-1474-3_2.

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Engle, Robert. "What Is Happening With Financial Market Volatility and Why?" In Volatility, 29–45. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-1474-3_3.

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Tabb, Larry, Ian Domowitz, William Geyer, Ken Hight, Henri Waelbroeck, and Joseph Wald. "Volatility and Technology." In Volatility, 47–64. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-1474-3_4.

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Martell, Terrence, George Bodine, Brendan Doran, Brian Hyndman, Tim Mahoney, and Jim Ross. "Volatility and Market Structure." In Volatility, 65–83. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-1474-3_5.

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Bradley, Harold, Matt Moran, Richard Rosenblatt, Keith Ross, and Robert Shapiro. "Implications for Trading." In Volatility, 85–98. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-1474-3_6.

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Greifeld, Robert, and Erin Burnett. "Closing Dialog: Sandy Frucher and Erin Burnett." In Volatility, 99–110. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-1474-3_7.

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Ozenbas, Deniz, Michael S. Pagano, and Robert A. Schwartz. "Accentuated Intraday Stock Price Volatility." In Volatility, 111–26. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-1474-3_8.

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Deutsch, Hans-Peter, and Mark W. Beinker. "Volatility." In Derivatives and Internal Models, 701–29. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22899-6_30.

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Kävrestad, Joakim. "Volatility." In Fundamentals of Digital Forensics, 179–83. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96319-8_16.

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Conference papers on the topic "Volatility"

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Cheng, Jingfei, and Guibin Lu. "Volatility Forecasting Model-Free Implied Volatility." In International Conference on Education, Management, Commerce and Society. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/emcs-15.2015.101.

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He, Peng, and Stephen Shing-Toung Yau. "Forecasting Stock Market Volatility Using Implied Volatility." In 2007 American Control Conference. IEEE, 2007. http://dx.doi.org/10.1109/acc.2007.4282578.

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Tian, Yu, Zili Zhu, Fima Klebaner, and Kais Hamza. "A Hybrid Stochastic Volatility Model Incorporating Local Volatility." In 2012 Fourth International Conference on Computational and Information Sciences (ICCIS). IEEE, 2012. http://dx.doi.org/10.1109/iccis.2012.20.

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Hoque, Ariful, and Chandrasekhar Krishnamurti. "Modeling moneyness volatility in measuring exchange rate volatility." In Economics -Part Of 17273 - 2011 Ssci. IEEE, 2011. http://dx.doi.org/10.1109/cifer.2011.5953555.

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Djanga, Emmanuel, Mihai Cucuringu, and Chao Zhang. "Cryptocurrency volatility forecasting using commonality in intraday volatility." In ICAIF '23: 4th ACM International Conference on AI in Finance. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3604237.3626912.

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Cunha de Almeida, Eduardo, Gerson Sunye, Yves Le Traon, and Patrick Valduriez. "Testing Peers' Volatility." In 2008 23rd IEEE/ACM International Conference on Automated Software Engineering. IEEE, 2008. http://dx.doi.org/10.1109/ase.2008.63.

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Wing-Yi Chio, Sabrina, Yifei Li, and Rainie JingRan Yang. "Realized Volatility Prediction." In ESSE 2021: 2021 2nd European Symposium on Software Engineering. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3501774.3501793.

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"Forecasting The Chinese Stock Market Volatility with ETF Volatility Index." In 2022 2nd International Conference on Management Science and Industrial Economy Development. Clausius Scientific Press Inc., 2022. http://dx.doi.org/10.23977/msied2022.017.

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Hsu, Ai-Chi, Hsiao-Fen Hsiao, and Shih-Jui Yang. "A Grey-Artificial Neural Network Stochastic Volatility Model for Return Volatility." In 2009 International Conference on Management and Service Science (MASS). IEEE, 2009. http://dx.doi.org/10.1109/icmss.2009.5301917.

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Savine, Antoine. "A Theory of Volatility." In Proceedings of the International Conference on Mathematical Finance. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812799579_0013.

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Reports on the topic "Volatility"

1

Diebold, Francis, and Kamil Yilmaz. Macroeconomic Volatility and Stock Market Volatility, Worldwide. Cambridge, MA: National Bureau of Economic Research, August 2008. http://dx.doi.org/10.3386/w14269.

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Andersen, Torben, Tim Bollerslev, Peter Christoffersen, and Francis Diebold. Volatility Forecasting. Cambridge, MA: National Bureau of Economic Research, March 2005. http://dx.doi.org/10.3386/w11188.

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Guo, Hui, and Robert Savickas. Idiosyncratic Volatility, Stock Market Volatility, and Expected Stock Returns. Federal Reserve Bank of St. Louis, 2003. http://dx.doi.org/10.20955/wp.2003.028.

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Moreira, Alan, and Tyler Muir. Volatility Managed Portfolios. Cambridge, MA: National Bureau of Economic Research, April 2016. http://dx.doi.org/10.3386/w22208.

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Diebold, Francis, and Jose Lopez. Measuring Volatility Dynamics. Cambridge, MA: National Bureau of Economic Research, February 1995. http://dx.doi.org/10.3386/t0173.

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Palmer, D. A., J. M. Simonson, and D. B. Joyce. Volatility of copper. Office of Scientific and Technical Information (OSTI), August 1996. http://dx.doi.org/10.2172/285269.

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Dávila, Eduardo, and Cecilia Parlatore. Volatility and Informativeness. Cambridge, MA: National Bureau of Economic Research, January 2019. http://dx.doi.org/10.3386/w25433.

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Bekaert, Geert, Robert Hodrick, and Xiaoyan Zhang. Aggregate Idiosyncratic Volatility. Cambridge, MA: National Bureau of Economic Research, June 2010. http://dx.doi.org/10.3386/w16058.

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Heathcote, Jonathan, and Fabrizio Perri. Wealth and Volatility. Cambridge, MA: National Bureau of Economic Research, February 2015. http://dx.doi.org/10.3386/w20994.

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Drechsler, Itamar, Alan Moreira, and Alexi Savov. Liquidity and Volatility. Cambridge, MA: National Bureau of Economic Research, October 2020. http://dx.doi.org/10.3386/w27959.

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