Relevant bibliographies by topics / Volatility

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Volatility'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Volatility"

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Arvian Rifki Santosa. "ANALISIS HUBUNGAN VOLATILITAS SAHAM BUKA, BRIS, KAEF, HMSP LQ45 DAN INDIKATOR PERTUMBUHAN EKONOMI NASIONAL." Jurnal Ekonomi, Bisnis dan Pendidikan 4, no. 12 (2024): 2. https://doi.org/10.17977/um066v4i122024p2.

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Penelitian ini bertujuan untuk menganalisis hubungan antara volatilitas sahamperusahaan dalam indeks LQ45 (BUKA, BRIS, KAEF, HMSP) dan indikatorpertumbuhan ekonomi nasional, seperti PDB, inflasi, suku bunga, dan nilaitukar Rupiah. Dengan menggunakan pendekatan kuantitatif dan datasekunder periode 2016–2023, penelitian ini mengevaluasi pengaruh dinamikapasar modal terhadap stabilitas ekonomi domestik. Hasil penelitianmenunjukkan bahwa saham-saham ini memiliki karakteristik volatilitas yangberbeda. Saham BRIS menunjukkan volatilitas tertinggi, sedangkan sahamBUKA memiliki volatilitas paling rend
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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 (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
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Astuti, Tri, Sri Ambarwati, and Myranda Shavira. "DETERMINAN VOLATILITAS HARGA SAHAM." RELEVAN : Jurnal Riset Akuntansi 1, no. 2 (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 berpen
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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 (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 D
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Nectar Dewa Fajar. "MENGUNGKAP KETERKAITAN VOLATILITAS INFLASI DAN FLUKTUASI HARGA SAHAM UNITED TRACTORS (UNTR) TAHUN 2009-2018." Jurnal Ekonomi, Bisnis dan Pendidikan 4, no. 5 (2024): 2. https://doi.org/10.17977/um066v4i52024p2.

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Abstrak Penelitian ini menganalisis hubungan antara volatilitas inflasi dengan volatilitas harga saham United Tractors (UNTR) selama periode 2009-2018. Dengan menggunakan metode kuantitatif, penelitian ini mengukur standar deviasi sebagai indikator volatilitas untuk kedua variabel. Uji korelasi Pearson menunjukkan bahwa terdapat hubungan positif antara volatilitas inflasi dan volatilitas harga saham UNTR, meskipun dengan tingkat hubungan yang lemah. Hasil ini menunjukkan bahwa kenaikan inflasi sebesar 1% berpotensi meningkatkan harga saham UNTR sebesar 0,311%. Temuan ini menyoroti pentingnya p
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Fordian, Dian, Mohammad Benny Alexandri, Suryanto Suryanto, and Suhal Kusairi. "PENGARUH VARIABEL MAKROEKONOMI DAN COVID-19 TERHADAP VOLATILITAS RETURN SAHAM DI BURSA EFEK INDONESIA PERIODE MARET 2017 – APRIL 2023." AdBispreneur 9, no. 1 (2025): 13–29. https://doi.org/10.24198/adbispreneur.v9i1.50743.

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Volatility in the form of fluctuations in the returns of a security or portfolio in a certain period predicts risk. Volatility prediction has an essential influence on investment decision-making. This study aims to determine and study the impact of macroeconomic variables and COVID-19 on the volatility of stock returns on the Indonesia Stock Exchange (IDX). This study used a quantitative approach. The data used is monthly data from January 2017 to April 2023. The data analysis method uses multiple linear regression. Macroeconomic variables, namely interest rates, exchange rates, inflation, and
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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 (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 is
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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 (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
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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 (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
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Keanu Damara. "GEJOLAK FLUKTUATIF SAHAM INDF PADA ERA PRA DAN PASCA COVID-19 AKIBAT INFLASI YANG MELAMBUNG TINGGI TAHUN 2019-2024." Jurnal Ekonomi, Bisnis dan Pendidikan 4, no. 6 (2024): 4. https://doi.org/10.17977/um066v4i62024p4.

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Penelitian ini bertujuan untuk menganalisis korelasi antara volatilitas hargasaham dan volatilitas inflasi. Data yang digunakan dalam penelitianmerupakan harga saham yang terdaftar dalam indeks LQ45, yaitu saham INDFserta inflasi tahun 2019 hingga 2024. Metode dalam penelitian ini merupakananalisis korelasi dengan pendekatan kuantatif. Hasil penelitian menunjukkanbahwa volatilitas harga saham dan inflasi memiliki korelasi. Nilai probabilitaskorelasi sebesar 0,0337 dengan koefisien korelasi sebesar -0.2618, sehinggadapat disimpulkan bahwa volatilitas harga saham dan volatiitas inflasimemiliki k
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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 estim
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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 s
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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 pric
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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
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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 perio
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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<br>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 so
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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 Parit
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Books on the topic "Volatility"

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

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

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Shiller, Robert J. Market volatility. MIT Press, 1989.

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

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

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

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

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

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

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

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Book chapters on the topic "Volatility"

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Sarkar, Asani, Robert Almgren, Albert J. Menkveld, and Liuren Wu. "Intraday Volatility: The Empirical Evidence." In Volatility. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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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Abarghouie, Masoud Omidvari, Sasan H. Alizadeh, and Ahmad Khademzadeh. "Cryptocurrency volatility prediction based on price, return and volatility cross-correlation using LSTM." In 2024 11th International Symposium on Telecommunications (IST). IEEE, 2024. https://doi.org/10.1109/ist64061.2024.10843571.

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Kunz, Pertami J., Stefano Frigiola, and Abdelhak M. Zoubir. "The Cyclic-Volatility Influence Function Bootstrap – A Resampling Framework for Periodic and Volatility-Driven Signals." In 2025 25th International Conference on Digital Signal Processing (DSP). IEEE, 2025. https://doi.org/10.1109/dsp65409.2025.11074840.

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Cheng, Jingfei, and Guibin Lu. "Volatility Forecasting Model-Free Implied Volatility." In International Conference on Education, Management, Commerce and Society. 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. 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. 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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Reports on the topic "Volatility"

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

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Andersen, Torben, Tim Bollerslev, Peter Christoffersen, and Francis Diebold. Volatility Forecasting. National Bureau of Economic Research, 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. National Bureau of Economic Research, 2016. http://dx.doi.org/10.3386/w22208.

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Diebold, Francis, and Jose Lopez. Measuring Volatility Dynamics. National Bureau of Economic Research, 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), 1996. http://dx.doi.org/10.2172/285269.

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

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

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

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10

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

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