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Munich Personal RePEc Archive

Items where Subject is "G17 - Financial Forecasting and Simulation"

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Number of items at this level: 285.

A

Abasov, Muzaffar (2018): Analyses of the impacts of U.S. macroeconomic announcements on the stock markets of a selection of countries.

Abounoori, Abbas Ali and Mohammadali, Hanieh and Gandali Alikhani, Nadiya and Naderi, Esmaeil (2012): Comparative study of static and dynamic neural network models for nonlinear time series forecasting.

Adegboro, Opeyemi Oluwole and Orekoya, Samuel and Adekunle, Wasiu (2019): An Assessment of the Stability and Diversity of the Nigerian Financial Service Sector.

Agaton, Casper (2017): Coal, Renewable, or Nuclear? A Real Options Approach to Energy Investments in the Philippines. Published in: International Journal of Sustainable Energy and Environmental Research , Vol. 6, No. 2 (18 December 2017): pp. 50-62.

Agaton, Casper (2017): Real Options Analysis of Renewable Energy Investment Scenarios in the Philippines. Published in: Renewable Energy and Sustainable Development , Vol. 3, No. 3 (30 December 2017): pp. 284-292.

Ahelegbey, Daniel Felix (2015): The Econometrics of Bayesian Graphical Models: A Review With Financial Application. Published in: Journal of Network Theory in Finance , Vol. 2, No. 2 (16 May 2016): pp. 1-33.

Ahmadov, Vugar and Huseynov, Salman and Mammadov, Fuad and Karimli, Tural (2015): Brent nefti opsiyonlarından neytral riskli ehtimal paylanmasının əldə olunması.

Akyildirim, Erdinc and Goncu, Ahmet and Hekimoglu, Alper and Nguyen, Duc Khuong and Sensoy, Ahmet (2021): Statistical arbitrage: Factor investing approach.

Al Janabi, Mazin A.M. and Arreola Hernandez, Jose and Berger, Theo and Nguyen, Duc Khuong (2016): Multivariate dependence and portfolio optimization algorithms under illiquid market scenarios. Published in: European Journal of Operational Research , Vol. 259, No. 3 (2017): pp. 1121-1131.

Al-Ansari, Khalid Ahmed and Aysan, Ahmet Faruk (2021): More than ten years of Blockchain creation: How did we use the technology and which direction is the research heading?

Alexandre, Michel and Antônio Silva Brito, Giovani and Cotrim Martins, Theo (2017): Default contagion among credit modalities: evidence from Brazilian data.

Aliyu, Shehu Usman Rano (2020): What have we learnt from modelling stock returns in Nigeria: Higgledy-piggledy? Published in: Inaugural Lecture Series , Vol. 1, No. 47 (24 June 2021): pp. 1-63.

Arayssi, Mahmoud (2013): Price Drivers and Investment Strategies of Gold. Published in: The Business Review Cambridge , Vol. 22, No. 1 (May 2014): pp. 87-92.

Asandului, Mircea and Lupu, Dan and Mursa, Gabriel Claudiu and Muşetescu, Radu (2015): Dynamic relations between CDS and stock markets in Eastern European countries. Published in: Economic Computation and Economic Cybernetics Studies and Research No. 4 (30 December 2015): pp. 151-170.

Astaiza-Gómez, José Gabriel (2022): The Effects of Investors' Information Acquisition On Sell-Side Analysts' Forecast Bias.

B

B M, Lithin and chakraborty, Suman and iyer, Vishwanathan and M N, Nikhil and ledwani, Sanket (2022): Modeling asymmetric sovereign bond yield volatility with univariate GARCH models: Evidence from India. Published in: Cogent Economics and Finance , Vol. 11, No. 1 (15 March 2023): p. 2189589.

BAYALE, Nimonka and EVLO, Kodjo and TRAORE, Fousseini (2018): Foreign aid shocks and macroeconomic adjustment mechanisms in WAEMU countries : an approach based on a computable general equilibrium model. Published in:

BEKHALED, Aicha and DADENE, Abdelghani and CHIKHI, Mohamed (2014): اختبار القدرة على التنبؤ بعوائد مؤشر سوق الدار البيضاء المالي من 2007 إلى 2011. Published in: El-Bahith Review No. 14 (2014): pp. 260-274.

BOUSALAM, Issam and HAMZAOUI, Moustapha and ZOUHAYR, Otman (2016): Forecasting Daily Stock Volatility Using GARCH-CJ Type Models with Continuous and Jump Variation.

Barnett, William and Chauvet, Marcelle and Leiva-Leon, Danilo and Su, Liting (2016): Nowcasting nominal gdp with the credit-card augmented Divisia monetary aggregates.

Barnett, William and Chauvet, Marcelle and Leiva-Leon, Danilo and Su, Liting (2016): The credit-card-services augmented Divisia monetary aggregates.

Barnett, William and Su, Liting (2016): Risk adjustment of the credit-card augmented Divisia monetary aggregates.

Basharina, Olga and Baranova, Nina and Larin, Sergey (2023): Разработка и апробация цифровой модели принятия эффективных инвестиционных решений для формирования стратегий развития экономических субъектов. Published in: Economic Analysis: Theory and Practice , Vol. 22, No. 9 (28 September 2023): pp. 1699-1724.

Basistha, Arabinda and Kurov, Alexander and Wolfe, Marketa Halova (2019): Volatility Forecasting: The Role of Internet Search Activity and Implied Volatility. Published in: Journal of Risk Model Validation , Vol. 14, (2019): pp. 43-53.

Baydalinova, Aynur and Sandybayeva, Balzhan and Stukach, Victor (2018): Financial security of Kazakhstan: gross domestic product, public debt, budget deficit. Published in: N E W S OF THE NATIONAL ACADEMY OF SCIENCES OF THE REPUBLIC OF KAZAKHSTAN , Vol. 5., No. SERIES OF SOCIAL AND HUMAN SCIENCES, №5 (May 2018): pp. 119-126.

Bazhenov, Timofey and Fantazzini, Dean (2019): Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility. Published in: Russian Journal of Industrial Economics , Vol. 1, No. 12 (2019): pp. 79-88.

Bell, Peter (2017): Example of a Rising NPV Profile for a Mining Project.

Bhattarai, Keshab (2013): Financial Deepening and Economic Growth.

Bonga-Bonga, Lumengo and Mwamba, Muteba (2015): A multivariate model for the prediction of stock returns in an emerging market: A comparison of parametric and non-parametric models.

Bos, Frits and Teulings, Coen (2013): Short and long-term forecasting by the Netherlands Bureau for Economic Policy Analysis (CPB): science, witchcraft, or practical tool for policy? Published in: OECD Journal on Budgeting , Vol. 1, No. 2013 (2013): pp. 45-56.

Bradrania, Reza and Pirayesh Neghab, Davood (2021): State-dependent asset allocation using neural networks. Published in: European Journal of Finance , Vol. 28, No. 11 (12 August 2021): pp. 1130-1156.

Brahmana, Rayenda Khresna (2022): Do Machine Learning Approaches Have the Same Accuracy in Forecasting Cryptocurrencies Volatilities?

Bucci, Andrea (2019): Cholesky-ANN models for predicting multivariate realized volatility.

Bucci, Andrea (2019): Realized Volatility Forecasting with Neural Networks.

Bukvić, Rajko and Pavlović, Radica (2023): The Cash Flow Concept in Modern Financial Analysis of Internal Sources of Companies’ Investment Financing. Published in: Current Aspects in Business, Economics and Finance Vol. 7, ed. Prof. Olusegun Felix Ayadi, Hooghly, West Bengal – London: B P International, 2023 (2023): pp. 111-132.

Bukvić, Rajko and Pavlović, Radica and Gajić, Aleksandar (2017): Static and Dynamic Indicators in the Analysis of Internal Sources of Companies’ Investments Financing. Published in: Journal of Modern Accounting and Auditing , Vol. 13, No. 3 (2017): pp. 108-120.

Buncic, Daniel and Stern, Cord (2018): Forecast ranked tailored equity portfolios.

Bunčák, Tomáš (2013): Jump Processes in Exchange Rates Modeling.

Buła, Rafał (2012): Aspekty metodyczne szacowania wymiaru fraktalnego finansowych szeregów czasowych. Published in: Młodzi Naukowcy dla Polskiej Nauki , Vol. 2, No. 9 (2012): pp. 192-200.

Buła, Rafał (2012): Wpływ kryzysu finansowego na oszacowania wykładnika Hursta - analiza fraktalna cen wybranych metali. Published in: Gospodarka rynkowa w warunkach kryzysu (2012): pp. 312-323.

Byrne, Joseph and Cao, Shuo and Korobilis, Dimitris (2015): Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty.

Byrne, Joseph and Fu, Rong (2016): Stock Return Prediction with Fully Flexible Models and Coefficients.

Byrne, Joseph P and Korobilis, Dimitris and Ribeiro, Pinho J (2014): Exchange Rate Predictability in a Changing World.

Bławat, Bogusław (2012): High Frequency Trading and the Warsaw Stock Exchange Fees' Structure - Preliminary Examination. Forthcoming in:

C

CHIKHI, Mohamed (2017): Chocs exogènes et non linéarités dans les séries boursières: Application à la modélisation non paramétrique du cours de l'action Orange.

Cakir, Murat (2001): Credit Derivatives in Managing Off Balance Sheet Risks by Banks.

Camilleri, Silvio John and Farrugia, Ritienne (2018): The Risk-Adjusted Performance of Alternative Investment Funds and UCITS: A Comparative Analysis. Published in: International Journal of Economics and Finance , Vol. 7, No. 10 (May 2018): pp. 23-37.

Cangoz, Mehmet Coskun and Sulla, Olga and Wang, ChunLan and Dychala, Christopher Benjamin (2019): A Joint Foreign Currency Risk Management Approach for Sovereign Assets and Liabilities. Published in: Policy Research Working Paper , Vol. 1, No. WPS8728 (5 February 2019)

Cao, Charles and Simin, Timothy and Xiao, Han (2019): Predicting the equity premium with the implied volatility spread. Forthcoming in: Journal of Financial Markets

Caporin, Massimiliano and Kolokolov, Aleksey and Renò, Roberto (2014): Multi-jumps.

Chen, Ying and Grith, Maria and Lai, Hannah L. H. (2023): Neural Tangent Kernel in Implied Volatility Forecasting: A Nonlinear Functional Autoregression Approach.

Chen, Shiu-Sheng (2013): Forecasting Crude Oil Price Movements with Oil-Sensitive Stocks. Forthcoming in:

Cheteni, Priviledge (2016): Stock market volatility using GARCH models: Evidence from South Africa and China stock markets. Published in: Journal of Economics and Behavioral Studies , Vol. 8, No. 6 (December 2016): pp. 237-245.

Chikhi, Mohamed and Terraza, Michel (2002): Un essai de prévision non paramétrique de l'action France Télécom. Published in: Working paper LAMETA No. 07 (December 2003): pp. 1-22.

Chong, Terence Tai-Leung and Cao, Bingqing and Wong, Wing Keung (2017): A Principal Component Approach to Measuring Investor Sentiment in Hong Kong.

Chowdhury, Tasnim and Datta, Rajib and Mohajan, Haradhan (2013): Green finance is essential for economic development and sustainability. Published in: International Journal Of Research In Commerce, Economics & Management , Vol. 3, No. 10 (3 November 2013): pp. 104-108.

D

Datta, Susanta and Hatekar, Neeraj (2022): Range Volatility Spillover across Sectoral Stock Indices during COVID-19 Pandemic: Evidence from Indian Stock Market.

Degiannakis, Stavros (2021): Stock market as a nowcasting indicator for real investment.

Degiannakis, Stavros and Dent, Pamela and Floros, Christos (2014): A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification. Published in: The Manchester School , Vol. 1, No. 82 (2014): pp. 71-102.

Degiannakis, Stavros and Filis, George (2019): Oil price volatility forecasts: What do investors need to know?

Degiannakis, Stavros and Filis, George and Siourounis, Grigorios and Trapani, Lorenzo (2019): Superkurtosis.

Degiannakis, Stavros and Filis, George and Siourounis, Grigorios and Trapani, Lorenzo (2021): Superkurtosis.

Degiannakis, Stavros and Floros, Christos (2013): Modeling CAC40 Volatility Using Ultra-high Frequency Data. Published in: Research in International Business and Finance No. 28 (2013): pp. 68-81.

Degiannakis, Stavros and Floros, Christos and Dent, Pamela (2013): Forecasting Value-at-Risk and Expected Shortfall using Fractionally Integrated Models of Conditional Volatility: International Evidence. Published in: International Review of Financial Analysis No. 27 (2013): pp. 21-33.

Degiannakis, Stavros and Livada, Alexandra (2016): Evaluation of Realized Volatility Predictions from Models with Leptokurtically and Asymmetrically Distributed Forecast Errors. Published in: Journal of Applied Statistics , Vol. 5, No. 43 (2016): pp. 871-892.

Degiannakis, Stavros and Livada, Alexandra (2013): Realized Volatility or Price Range: Evidence from a discrete simulation of the continuous time diffusion process. Published in: Economic Modelling No. 30 (2013): pp. 212-216.

Degiannakis, Stavros and Livada, Alexandra (2013): Realized Volatility or Price Range: Evidence from a discrete simulation of the continuous time diffusion process. Published in: Economic Modelling No. 30 (2013): pp. 212-216.

Degiannakis, Stavros and Potamia, Artemis (2017): Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: inter-day versus intra-day data. Published in: International Review of Financial Analysis No. 49 (2017): pp. 176-190.

Degiannakis, Stavros and Xekalaki, Evdokia (2008): SPEC Model Selection Algorithm for ARCH Models: an Options Pricing Evaluation Framework. Published in: Applied Financial Economics Letters , Vol. 6, No. 4 (2008): pp. 419-423.

Delis, Panagiotis and Degiannakis, Stavros and Giannopoulos, Kostantinos (2021): What should be taken into consideration when forecasting oil implied volatility index?

Demiralay, Sercan and Ulusoy, Veysel (2014): Value-at-risk Predictions of Precious Metals with Long Memory Volatility Models.

Dewandaru, Ginanjar and Masih, Rumi and Bacha, Obiyathulla and Masih, A. Mansur M. (2014): Combining Momentum, Value, and Quality for the Islamic Equity Portfolio: Multi-style Rotation Strategies using Augmented Black Litterman Factor Model.

Dhaoui, Abderrazak and Audi, Mohamed and Ouled Ahmed Ben Ali, Raja (2015): Revising empirical linkages between direction of Canadian stock price index movement and Oil supply and demand shocks: Artificial neural network and support vector machines approaches.

Dhaoui, Iyad (2013): What we have learnt from financial econometrics modeling? Published in: (2013)

Diamondopoulos, John (2012): To what extent are financial crises comparable and thus predictable?

Diaw, Abdou and Bacha, Obiyathulla Ismath and Lahsasna, Ahcene (2012): Incentive-Compatible Sukuk Musharakah for Private Sector Funding. Published in: ISRA International Journal of Islamic Finance , Vol. 4, No. 1 (June 2012): pp. 39-80.

Dimitris, Korobilis (2013): Forecasting with Factor Models: A Bayesian Model Averaging Perspective.

Djennad, Abdelmajid and Rigby, Robert and Stasinopoulos, Dimitrios and Voudouris, Vlasios and Eilers, Paul (2015): Beyond location and dispersion models: The Generalized Structural Time Series Model with Applications.

E

Egorova, Yana (2017): Инвестирование денежных средств в условиях экономического кризиса в 2017 году.

Ekong, Christopher N. and Onye, Kenneth U. (2017): Application of Garch Models to Estimate and Predict Financial Volatility of Daily Stock Returns in Nigeria. Published in: International Journal of Managerial Studies and Research (IJMSR) , Vol. 5, No. 8 (August 2017): pp. 18-34.

El-Khatib, Youssef and Hatemi-J, Abdulnasser (2022): On a Regime Switching Illiquid High Volatile Prediction Model for Cryptocurrencies.

Emara, Noha (2014): Predictive ability of three different estimates of “cay” to excess stock returns - A comparative study Germany & U.S -. Published in: The Journal of American Academy of Business , Vol. 19, No. 2 (2014): pp. 1-8.

Emara, Noha (2014): Predictive ability of three different estimates of “cay” to excess stock returns - A comparative study South Africa & U.S. -. Published in: European Research Studies Journal , Vol. 17, No. 1 (2014): pp. 3-17.

Estrada, Fernando (2014): Financial crisis in The Arcades Project of Walter Benjamin.

Estrada, Fernando (2014): Rescate y costos del riesgo financiero.

Ezzat, Hassan (2012): The Application of GARCH Methods in Modeling Volatility Using Sector Indices from the Egyptian Exchange. Published in: Journal of Money, Investment and Banking No. 27 (March 2013): pp. 68-85.

Ezzat, Hassan (2013): Long Memory Processes and Structural Breaks in Stock Returns and Volatility: Evidence from the Egyptian Exchange. Published in: International Research Journal of Finance and Economics No. 113 (August 2013): pp. 136-146.

elias elhannani, farah and boussalem, abou bakr and Benbouziane, Mohamed (2016): Financial development and the oil curse: Evidence from Algeria. Published in: Topics in Middle Eastern and African Economies , Vol. Vol. 1, No. Issue No. 1, May 2016 (May 2016): pp. 112-125.

F

FERROUHI, El Mehdi (2017): Determinants of bank deposits in Morocco. Published in: Maghreb Review of Economics and Management , Vol. 4, No. 1 : pp. 23-26.

FERROUHI, El Mehdi (2018): Determinants of banks’ profitability and performance: an overview. Published in: Contemporary Research in Commerce and Management , Vol. 4, (1 April 2018): pp. 61-74.

FERROUHI, El Mehdi and EZZAHID, Elhadj (2013): Trading mechanisms, return’s volatility and efficiency in the Casablanca Stock Exchange. Published in: Indonesian Capital Market Review , Vol. 5, No. 2 (July 2013): pp. 65-73.

FERROUHI, El Mehdi and LEHADIRI, Abderrassoul (2013): Liquidity Determinants of Moroccan Banking Industry. Published in: International Research Journal of Finance and Economics No. 118 (January 2014): pp. 102-112.

FERROUHI, El Mehdi and LEHADIRI, Abderrassoul (2014): Savings Determinants of Moroccan banks: A cointegration modeling approach. Published in: International Journal of Innovation and Applied Studies , Vol. 9, No. 2 (1 November 2014): pp. 968-973.

Fang, Yi and Niu, Hui and Lin, Yuen (2023): Ex-ante Valuation based on Prospect Theory.

Fantazzini, Dean (2023): Assessing the Credit Risk of Crypto-Assets Using Daily Range Volatility Models. Forthcoming in: Information

Fantazzini, Dean and Kurbatskii, Alexey and Mironenkov, Alexey and Lycheva, Maria (2022): Forecasting oil prices with penalized regressions, variance risk premia and Google data. Published in: Applied Econometrics

Fantazzini, Dean and Xiao, Yufeng (2023): Detecting Pump-and-Dumps with Crypto-Assets: Dealing with Imbalanced Datasets and Insiders’ Anticipated Purchases. Forthcoming in: Econometrics

Fantazzini, Dean (2022): Crypto Coins and Credit Risk: Modelling and Forecasting their Probability of Death. Forthcoming in: Journal of Risk and Financial Management

Fantazzini, Dean (2020): Discussing copulas with Sergey Aivazian: a memoir. Forthcoming in: Model Assisted Statistics and Applications : pp. 1-14.

Fantazzini, Dean (2016): The Oil Price Crash in 2014/15: Was There a (Negative) Financial Bubble? Forthcoming in: Energy Policy (2016)

Fantazzini, Dean (2020): Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries. Forthcoming in: Applied Econometrics (2020): 1 -20.

Fantazzini, Dean and Geraskin, Petr (2011): Everything You Always Wanted to Know about Log Periodic Power Laws for Bubble Modelling but Were Afraid to Ask. Forthcoming in: European Journal of Finance

Fantazzini, Dean and Kolodin, Nikita (2020): Does the hashrate affect the bitcoin price? Forthcoming in: Journal of Risk and Financial Management (2020)

Fantazzini, Dean and Nigmatullin, Erik and Sukhanovskaya, Vera and Ivliev, Sergey (2016): Everything you always wanted to know about bitcoin modelling but were afraid to ask. Forthcoming in: Applied Econometrics (2016)

Fantazzini, Dean and Shangina, Tamara (2019): The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades. Forthcoming in: Applied Econometrics

Fantazzini, Dean and Zimin, Stephan (2019): A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies. Forthcoming in: Journal of Industrial and Business Economics

Fung, Ka Wai Terence and Demir, Ender and Zhou, Lu (2014): Capital Asset Pricing Model and Stochastic Volatility: A Case study of India.

G

Gaete, Michael and Herrera, Rodrigo (2022): Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach.

Galy, Michel (1989): Banks exposure to market risks.

Gao, Ya and Han, Xing and Li, Youwei and Xiong, Xiong (2019): Overnight Momentum, Informational Shocks, and Late-Informed Trading in China.

Grajales Correa, Carlos Alexander and Pérez Ramírez, Fredy Ocaris and Venegas-Martínez, Francisco (2014): Análisis comparativo de modelos para estimar la distribución de la volatilidad de series financieras de rendimientos.

Grilli, Luca and Santoro, Domenico (2020): Boltzmann Entropy in Cryptocurrencies: A Statistical Ensemble Based Approach.

Grilli, Luca and Santoro, Domenico (2020): Dualism in Bitcoin Dynamics: existence of an Upper Bound in Poincaré Recurrence Theorem for Deterministic vs Stochastic Behavior.

Grilli, Luca and Santoro, Domenico (2020): Generative Adversarial Network for Market Hourly Discrimination.

Grilli, Luca and Santoro, Domenico (2020): How Boltzmann Entropy Improves Prediction with LSTM.

Grover, Vaibhav (2015): Identifying Dependence Structure among Equities in Indian Markets using Copulas.

Gusev, Maxim and Kroujiline, Dimitri and Govorkov, Boris and Sharov, Sergey V. and Ushanov, Dmitry and Zhilyaev, Maxim (2014): Predictable markets? A news-driven model of the stock market. Forthcoming in: Algorithmic Finance

H

Hiremath, Gourishankar S and Bandi, Kamaiah (2010): Long Memory in Stock Market Volatility:Evidence from India. Published in: Artha Vijnana , Vol. 52, No. 4 (2010): pp. 332-345.

Hiremath, Gourishankar S and Bandi, Kamaiah (2010): Some Further Evidence on the Behaviour of Stock Returns in India. Published in: International Journal of Economics and Finance , Vol. 2, No. 2 (May 2010): pp. 157-167.

Hiremath, Gourishankar S and Bandi, Kamaiah (2011): Testing Long Memory in Stock Returns of Emerging Markets: Some Further Evidence. Published in: Economics, Management, and Financial Markets , Vol. 6, No. 3 (2011): pp. 136-147.

Hiremath, Gourishankar S and Bandi, Kamaiah (2012): Variance ratios, structural breaks and nonrandom walk behaviour in the Indian stock returns. Published in: Journal of Business & Economic Studies , Vol. 2, No. 18 (2012): pp. 62-81.

Hu, Zongyi and Li, Chao (2015): Investor Sentiment and Irrational Speculative Bubble Model.

Huang, Huichou and MacDonald, Ronald and Zhao, Yang (2012): Global Currency Misalignments, Crash Sensitivity, and Moment Risk Premia.

J

Jamalludin, Nadia (2017): Risk and Performance of SapuraKencana Petroleum Berhad.

Jamalludin, Nadia (2017): Risk and Performance of SapuraKencana Petroleum Berhad.

Jarraya, Bilel (2013): Asset allocation and portfolio optimization problems with metaheuristics: a literature survey. Published in: Business Excellence and Management , Vol. 3, No. 4 (2013): pp. 38-56.

Jarraya, Bilel and Bouri, Abdelfettah (2013): Multiobjective optimization for the asset allocation of European nonlife insurance companies. Published in: Journal of Multi-Criteria Decision Analysis , Vol. 20, No. 3-4 (2013): pp. 97-108.

Jin, Xin and Maheu, John M (2014): Bayesian Semiparametric Modeling of Realized Covariance Matrices.

Jin, Xin and Maheu, John M and Yang, Qiao (2017): Bayesian Parametric and Semiparametric Factor Models for Large Realized Covariance Matrices.

Johansson, Bo (2012): A note on approximating bond returns allowing for both yield change and time passage.

Jones, Clive (2015): Predictability of the daily high and low of the S&P 500 index.

Jurdi, Doureige and Kim, Jae (2019): Predicting the U.S. Stock Market Return: Evidence from the Improved Augmented Regression Method.

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Kakorina, Ekaterina (2014): Forecasting conditional volatility on the RIN market using MS GARCH model.

Katsafados, Apostolos G. and Androutsopoulos, Ion and Chalkidis, Ilias and Fergadiotis, Emmanouel and Leledakis, George N. and Pyrgiotakis, Emmanouil G. (2019): Using textual analysis to identify merger participants: Evidence from the U.S. banking industry.

Kausik, B.N. (2023): Equity Premium in Efficient Markets.

Kazemi, Hossein S. and Zhai, Weili and He, Jibao and Cai, Jinghan (2013): Stock Market Volatility, Speculative Short Sellers and Weekend Effect: International Evidence. Published in: Journal of Financial Risk Management , Vol. Vol.2, No. 2013. No. 3 : pp. 47-54.

Khan, Dr. Muhammad Irfan and Syed, Muhammad Salman (2015): Comparison between Forecasted Stock Prices and Original Stock Prices in the Karachi Stock Exchange. Published in: Journal of Finance, Accounting and Management , Vol. 6, No. 2 (July 2015): pp. 51-62.

Kim, Hyeongwoo and Ko, Kyunghwan (2018): Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach.

Kim, Hyeongwoo and Shi, Wen (2018): Forecasting Financial Vulnerability in the US: A Factor Model Approach.

Kim, Hyeongwoo and Shi, Wen and Kim, Hyun Hak (2018): Forecasting Financial Stress Indices in Korea: A Factor Model Approach.

Kishor, N. Kundan (2023): Forecasting House Prices: The Role of Fundamentals, Credit Conditions, and Supply Indicators.

Kogan, Anton (2013): Финансовая инновация - миф или реальность?

Komijani, Akbar and Naderi, Esmaeil and Gandali Alikhani, Nadiya (2013): A Hybrid Approach for Forecasting of Oil Prices Volatility.

Konchitchki, Yaniv (2011): Inflation and Nominal Financial Reporting: Implications for Performance and Stock Prices. Published in: The Accounting Review , Vol. 86, No. 3 (May 2011): pp. 1045-1085.

Koop, Gary and Korobilis, Dimitris (2013): A New Index of Financial Conditions.

Kroujiline, Dimitri and Gusev, Maxim and Ushanov, Dmitry and Sharov, Sergey V. and Govorkov, Boris (2015): Forecasting stock market returns over multiple time horizons.

L

LaGarda, Guillermo and Manzano, Osmel and Prat, Jordi (2015): The Legacy of the Crisis: Policy Options in a Favorable Environment. Published in: IDB Publications (February 2015): pp. 1-62.

Le, Tuan Anh and Dao, Thi Thanh Binh (2021): Portfolio optimization under mean-CVaR simulation with copulas on the Vietnamese stock exchange. Published in: Investment Management and Financial Innovations , Vol. 18, No. 2 (2021): pp. 273-286.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2016): Forecast in Capital Markets.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2017): Investment in capital markets.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2014): On the winning virtuous strategies for ultra high frequency electronic trading in foreign currencies exchange markets.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2014): On the winning virtuous strategies for ultra high frequency electronic trading in foreign currencies exchange markets.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2013): Some thoughts on accurate characterization of stock market indexes trends in conditions of nonlinear capital flows during electronic trading at stock exchanges in global capital markets.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2014): Strategies on initial public offering of company equity at stock exchanges in imperfect highly volatile global capital markets with induced nonlinearities.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2013): Venture capital optimal investment portfolio strategies selection in diffusion - type financial systems in global capital markets with nonlinearities.

Ledenyov, Dimitri O. and Ledenyov, Viktor O. (2015): Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets.

Lee, David (2023): Default Forecasting and Credit Valuation Adjustment.

Lee, David (2023): Modeling Collateralization and Its Economic Significance.

Lee, David (2022): Generic Price Model for Commodity Derivatives.

Lee, David (2022): Pricing Cancellation Product.

Lee, David (2018): Pricing Financial Derivatives Subject to Counterparty Risk and Credit Value Adjustment.

Leung, Melvern and Li, Youwei and Pantelous, Athanasios and Vigne, Samuel (2019): Bayesian Value-at-Risk Backtesting: The Case of Annuity Pricing.

Li, Chenxing and Zhang, Zehua and Zhao, Ran (2023): Volatility or higher moments: Which is more important in return density forecasts of stochastic volatility model?

Lindblad, Annika (2017): Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility.

Liu, Chengwei and Chan, Yixiang and Alam Kazmi, Syed Hasnain and Fu, Hao (2015): Financial Fraud Detection Model Based on Random Forest. Published in: International Journal of Economics and Finance , Vol. 7, No. 7 (25 June 2015): pp. 178-188.

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Olkhov, Victor (2020): Volatility Depend on Market Trades and Macro Theory.

Olkhov, Victor (2020): Classical Option Pricing and Some Steps Further.

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