nep-fmk New Economics Papers
on Financial Markets
Issue of 2018‒03‒12
four papers chosen by

  1. Cross-stock market spillovers through variance risk premiums and equity flows By Hattori, Masazumi; Shim, Ilhyock; Sugihara, Yoshihiko
  2. Forecasting Methods in Finance By Timmermann, Allan G
  3. Are equity market anomalies disappearing? Evidence from the U.K. By John Cotter; Niall McGeever
  4. Spillovers between Bitcoin and other Assets during Bear and Bull Markets By Elie Bouri; Mahamitra Das; Rangan Gupta; David Roubaud

  1. By: Hattori, Masazumi; Shim, Ilhyock; Sugihara, Yoshihiko
    Abstract: We estimate variance risk premiums (VRPs) in the stock markets of major advanced economies (AEs) and emerging market economies (EMEs) over 2007–15 and decompose the VRP into variance-diffusive risk premium (DRP) and variance-jump risk premium (JRP). Daily VAR analysis reveals significant spillovers from the VRPs of the United States and eurozone’s AEs to the VRPs of other economic areas, especially during the post-Global Financial Crisis (GFC) period. We also find that during the post-GFC period, shocks to the DRPs of the United States and the eurozone’s AEs have relatively strong and long-lived positive effects on the VRPs of other economic areas whereas shocks to their JRPs have relatively weak and short-lived positive effects. In addition, we show that increases in the size of US VRP, DRP and JRP tend to significantly reduce weekly equity fund flows to all other AEs and some EMEs during the post-GFC period. Finally, US DRP plays a more important role than US JRP in the determination of equity fund flows to all other AEs and some EMEs after the GFC, while the opposite holds true for equity fund flows to all other AEs during the GFC. Such results indicate the possibility of equity fund flows working as a channel of cross-market VRP spillovers.
    Keywords: cross-stock market correlation, emerging market economy, equity fund flow, variance risk premium
    JEL: F32 G12 G15 G23
    Date: 2018–02
  2. By: Timmermann, Allan G
    Abstract: Our review highlights some of the key challenges in financial forecasting problems along with opportunities arising from the unique features of financiall data. We analyze the difficulty of establishing predictability in an environment with a low signal-to-noise ratio, persistent predictors, and instability in predictive relations arising from competitive pressures and investors' learning. We discuss approaches for forecasting the mean, variance, and probability distribution of asset returns. Finally, we cover how to evaluate financial forecasts while accounting for the possibility that numerous forecasting models may have been considered, leading to concerns of data mining.
    Date: 2018–02
  3. By: John Cotter (University College Dublin); Niall McGeever (University College Dublin)
    Abstract: We study the persistence over time of nine well-known equity market anomalies in the cross-section of U.K. stocks. We find strong evidence of diminished statistical significance for most of these anomalies including the return reversal and momentum effects. Two anomalies – firm profitability and stock turnover – remain quite robust throughout our sample period. These results hold for both portfolio sorts and Fama-MacBeth regression analyses and are robust to the use of alternative methods of risk adjustment. Our findings are consistent with improvements in market efficiency overtime with respect to well-known anomaly variables.
    Keywords: Anomalies, Asset Pricing, Market Efficiency
    JEL: G10 G12
    Date: 2018–02–19
  4. By: Elie Bouri (USEK Business School, Holy Spirit University of Kaslik (USEK), Jounieh, Lebanon); Mahamitra Das (Economic Research Unit, Indian Statistical Institute, Kolkata, India); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa); David Roubaud (Montpellier Research in Management, Montpellier Business School, Montpellier, France)
    Abstract: This paper contributes to the embryonic literature on the relations between Bitcoin and conventional investments by studying return and volatility spillovers between this largest cryptocurrency and four asset classes (equities, stocks, commodities, currencies, and bonds) in bear and bull market conditions. We conducted empirical analyses based on a smooth transition VAR GARCH-in-mean model covering daily data from July 19, 2010 to October 31, 2017. We found significant evidence that Bitcoin returns are related quite closely to those of most of the other assets studies, particularly commodities, and therefore, the Bitcoin market is not isolated completely. The significance and sign of the spillovers exhibited some differences in the two market conditions and in the direction of the spillovers, with greater evidence that Bitcoin receives more volatility than it transmits. Our findings have implications for investors and fund managers who are considering Bitcoin as part of their investment strategies and for policymakers concerned about the vulnerability that Bitcoin represents to the stability of the global financial system.
    Keywords: Bitcoin, asset classes, return and volatility spillovers, asymmetry, smooth transition, bivariate GARCH-M
    JEL: C11 G15
    Date: 2018–02

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