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Rasekhschaffe, Keywan - 2019

Machine learning is an increasingly important and controversial topic in quantitative finance. A lively debate persists as to whether machine learning techniques can be practical investment tools. Although machine learning algorithms can uncover subtle, contextual and non-linear relationships,...

Persistent link: https://www.econbiz.de/10012893316

Measuring the Effectiveness of Volatility Auctions

Castro, Carlos - 2019

We propose a method for event studies based on synthetic portfolios that provides a robust data-driven approach to build a credible counterfactual. The method is used to evaluate the effectiveness of volatility auctions using intraday data from the Colombian Stock Exchange. The results indicate...

Persistent link: https://www.econbiz.de/10012897016

Quantile Spectral Beta : A Tale of Tail Risks, Investment Horizons, and Asset Prices

Baruník, Jozef - 2019

We examine how extreme market risks are priced in the cross-section of asset returns at various horizons. Based on the decomposition of covariance between indicator functions capturing fluctuations of different parts of return distributions over various frequencies, we define a \textit{quantile...

Persistent link: https://www.econbiz.de/10012899016

Empirical Asset Pricing via Machine Learning

Gu, Shihao - 2019

We perform a comparative analysis of machine learning methods for the canonical problem of empirical asset pricing: measuring asset risk premia. We demonstrate large economic gains to investors using machine learning forecasts, in some cases doubling the performance of leading regression-based...

Persistent link: https://www.econbiz.de/10012899608

Realized Stochastic Volatility Models with Generalized Gegenbauer Long Memory

Asai, Manabu - 2017

In recent years fractionally diﬀerenced processes have received a great deal of attention due to their ﬂexibility in ﬁnancial applications with long memory. In this paper, we develop a new realized stochastic volatility (RSV) model with general Gegenbauer long memory (GGLM), which...

Persistent link: https://www.econbiz.de/10012944285

Firm Characteristics and Expected Stock Returns

Han, Yufeng - 2020

We analyze the joint out-of-sample predictive ability of a comprehensive set of 299 firm characteristics for cross-sectional stock returns. We develop a cross-sectional out-of-sample R2 statistic that provides an informative measure of the accuracy of cross-sectional return forecasts in terms of...

Persistent link: https://www.econbiz.de/10012852228

The Effects of VIX Index, Exchange Rate & Oil Prices on the BIST 100 Index : A Quantile Regression Approach

Tekin, Bilgehan - 2020

The aim of this study is to investigate the effect of oil price, US Dollar rate and VIX on Borsa Istanbul by employing quantile regression model. In the literature, there are studies that examine the effect of the mentioned factors on stock market, but the number of studies in which these...

Persistent link: https://www.econbiz.de/10012854437

Testing for Stock Market Contagion : A Quantile Regression Approach

Park, Sungyong - 2015

Regarding the asymmetric and leptokurtic behavior of financial data, we propose a new contagion test in the quantile … contagion test allows us to investigate the stock market contagion at various quantiles, not only at the mean. We show that the … quantile contagion test can detect a contagion effect that is possibly ignored by correlation-based tests. A wide range of …

Persistent link: https://www.econbiz.de/10013025474

Defining Activeness : Active Share, Risk Share & Factor Share

Flint, Emlyn James - 2018

This paper tackles a core question of portfolio management: How ‘active' is an active portfolio? To answer this question holistically, we generalise the idea of Active Share by keeping the same calculation methodology but substituting in different types of portfolio and benchmark ‘weights'....

Persistent link: https://www.econbiz.de/10012931742

Does non-linear factorization of financial returns help build better and stabler portfolios?

Spilak, Bruno; Härdle, Wolfgang K. - 2022

A portfolio allocation method based on linear and non-linear latent constrained conditional factors is presented. The factor loadings are constrained to always be positive in order to obtain long-only portfolios, which is not guaranteed by classical factor analysis or PCA. In addition, the...

Persistent link: https://www.econbiz.de/10013292299