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The Fluke of Stochastic Volatility versus GARCH Inevitability : Which Model Creates Better Forecasts?

Lakshina, Valeria - 2014

stochastic volatility models, which were estimated based on Russian financial data. The data includes Aeroflot and Gazprom … to the conclusion that stochastic volatility models perform equally or in some cases better than GARCH models …

Persistent link: https://www.econbiz.de/10013045165

Conditional Volatility Models in Financial Markets and Its Application

Babashova, Sakina - 2021

Sudden and rapid changes in the economy leads to an increase in volatility. The fact that high volatility in financial … markets brings along an increase in risk made it necessary to model it. Modeling volatility, which is accepted as a measure of … risk, will benefit investors in their attitudes towards risk. The volatility of financial variables such as exchange rates …

Persistent link: https://www.econbiz.de/10013252186

Behaviour of Johannesburg Stock Exchange all share index returns : an asymmetric GARCH and news impact effects approach

Korkpoe, Carl H.; Owusu Junior, Peterson - In: Spoudai : journal of economics and business 68 (2018) 1, pp. 26-42

market was shown to react to news unequally. Volatility spikes sharply when unexpected adverse news reaches the market while …

Persistent link: https://www.econbiz.de/10011843965

Is intraday data the key to better volatility estimation?

Foster, Sam; Leveau, Daniel - 2023

Volatility is a central tenet of financial markets, impacting a wide range of investors’ daily activities, including … considerable time and effort on finding new ways to accurately measure and estimate volatility. Incorporating intraday data in your … data to volatility forecasts …

Persistent link: https://www.econbiz.de/10014350504

Predicting Returns on Mutual Fund : Some Indian Evidence

Panda, Pradeep Kumar - 2014

Common indicators of business and monetary conditions, the lagged mutual fund- risk premium and the market- risk premium are used to predict mutual fund returns for a time horizon of one-day. In isolation, each of the four predictors significantly forecast mutual-fund returns from April 2008 to...

Persistent link: https://www.econbiz.de/10013066504

Market Self-Learning of Signals, Impact and Optimal Trading : Invisible Hand Inference with Free Energy (Or, How We Learned to Stop Worrying and Love Bounded Rationality)

Halperin, Igor - 2018

We present a simple model of a non-equilibrium self-organizing market where asset prices are partially driven by investment decisions of a bounded-rational agent. The agent acts in a stochastic market environment driven by various exogenous "alpha" signals, agent's own actions (via market...

Persistent link: https://www.econbiz.de/10012919878

Partial sample regressions

Czasonis, Megan; Kritzman, Mark; Turkington, David - 2019 - This version: November 13, 2019

Financial analysts assume that the reliability of predictions derived from regression analysis improves with sample size. This is generally true because larger samples tend to produce less noisy results than smaller samples. But this is not always the case. Some observations are more relevant...

Persistent link: https://www.econbiz.de/10012225139

Using sentiment surveys to predict GDP growth and stock returns

Guzman, Giselle C. - Volkswirtschaftliche Fakultät, … - 2008

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

Persistent link: https://www.econbiz.de/10009647399

The case for higher frequency inflation expectations

Guzman, Giselle C. - Volkswirtschaftliche Fakultät, … - 2011

I present evidence that higher frequency measures of inflation expectations outperform lower frequency measures of inflation expectations in tests of accuracy, predictive power, and rationality. For decades, the academic literature has focused on three survey measures of expected inflation: the...

Persistent link: https://www.econbiz.de/10009650037

Residual Factor Prediction Via Time Series-based Machine Learning

Chen, Jianlin - 2023

Machine Learning algorithms have been widely used and proven effective in financial markets. In this paper, we introduced a Machine Learning model set trained on the residual factors from the Fama-French three-factor model (Fama and French, 1992) to find significant alpha factors. To include...

Persistent link: https://www.econbiz.de/10014349143