nep-fmk New Economics Papers
on Financial Markets
Issue of 2016‒09‒11
six papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Equity Premium Prediction: The Role of Economic and Statistical Constraints By Jiahan Li; Ilias Tsiakas
  2. Network, Market, and Book-Based Systemic Risk Rankings By Michiel C.W. van de Leur; Andre Lucas
  3. Short Selling in the Tails By Marco Valerio Geraci; Tomas Garbaravicius; David Veredas
  4. 'Herding through learning in an asset pricing model' By Michele Berardi
  5. Impact of Mergers and Acquisitions on European Insurers: Evidence from Equity Markets By Petr Jakubik; Dimitrios Zafeiris
  6. Quantitative Easing and Liquidity in the Japanese Government Bond Market By Kentaro Iwatsubo; Tomoki Taishi

  1. By: Jiahan Li (University of Notre Dame, USA); Ilias Tsiakas (Department of Economics and Finance, University of Guelph, Canada; The Rimini Centre for Economic Analysis, Italy)
    Abstract: This paper shows that the equity premium is predictable out of sample when we use a predictive regression that conditions on a large set of economic fundamentals, subject to: (i) economic constraints on the sign of coefficients and return forecasts, and (ii) statistical constraints imposed by shrinkage estimation. Equity premium predictability delivers a certainty equivalent return of about 2:7% per year over the benchmark for a mean-variance investor. Our predictive framework outperforms a large group of competing models that also condition on economic fundamentals as well as models that condition on technical indicators.
    Keywords: Equity Premium; Out-of-Sample Prediction; Economic Fundamentals; Technical Indicators; Shrinkage Estimation
    JEL: G11 G14 G17
    Date: 2016–09
    URL: http://d.repec.org/n?u=RePEc:rim:rimwps:16-25&r=fmk
  2. By: Michiel C.W. van de Leur (VU University Amsterdam, the Netherlands); Andre Lucas (VU University Amsterdam, the Netherlands)
    Abstract: We investigate the information content of stock correlation based network measures for systemic risk rankings, such as SIFIRank (based on Google's PageRank). Using European banking data, we first show that SIFIRank is empirically equivalent to a ranking based on average pairwise stock correlations. Next, we find that correlation based network measures still appear to complement currently available systemic risk ranking methods based on book or market values. A further analytical investigation, however, shows that the value-added appears to be mainly attributable to pairwise cross-sectional heterogeneity rather than to more subtle network relations and feedback loops.
    Keywords: Systemically Important Financial Institutions (SIFI); European banking sector; systemic risk rankings; network based risk measures
    JEL: G01 G21
    Date: 2016–09–08
    URL: http://d.repec.org/n?u=RePEc:tin:wpaper:20160074&r=fmk
  3. By: Marco Valerio Geraci; Tomas Garbaravicius; David Veredas
    Abstract: Short selling plays a crucial role for price discovery and liquidity purposes yetnational governing authorities decided to ban short selling in periods of extreme pricemovements, on the grounds that short selling can exacerbate price downturns. Whereasmost of the literature analyses the average relation between short selling and pricechanges, our study focuses on the relation that occurs during extreme events, usinga new paradigm that stems from the literature on tail correlations. For the largestEuropean and US banks, as well as European insurers, we uncover a very strong relationwhen both variables are in their tails. In normal times, no negative association is found,which favours the view that short sellers act as price stabilizers. But during turmoil,short selling relates with excessive price drops that can put the market under seriousstress.
    JEL: G15 G18 G28
    Date: 2016–09
    URL: http://d.repec.org/n?u=RePEc:eca:wpaper:2013/235546&r=fmk
  4. By: Michele Berardi
    Abstract: In this paper we show how uncertainty and learning can lead to a disconnection between fundamental values and prices in a simple asset pricing model. Agents use prices, besides an idiosyncratic exogenous signal, to infer fundamental values: as agents accumulate information, they put increasing weight on the public signal and in the limit they ignore completely their private information. The Bayesian equilibrium implies that agents end up relying only on prices in their signal extraction problem, an outcome that reminds the rational herding result in sequential decision making. We also consider two extensions that should mitigate this e¤ect, namely constant gain adaptive learning and Bayesian learning with an explicit probability of change in the fundamental. In both cases the problem persists, though somewhat mitigated. As a by-product, we also establish a connection between the constant gain parameter in adaptive learning and the subjective probability of exogenous changes in Bayesian learning..
    Date: 2016
    URL: http://d.repec.org/n?u=RePEc:man:cgbcrp:223&r=fmk
  5. By: Petr Jakubik (Institute of Economic Studies, Faculty of Social Sciences, Charles University in Prague, Smetanovo nabrezi 6, 111 01 Prague 1, Czech Republic; European Insurance and Occupational Pensions Authority); Dimitrios Zafeiris (Institute of Economic Studies, Faculty of Social Sciences, Charles University in Prague, Smetanovo nabrezi 6, 111 01 Prague 1, Czech Republic; European Insurance and Occupational Pensions Authority)
    Abstract: The current macro-economic and financial conditions remain extremely challenging for the European insurance sector. Under the ongoing low yield environment insurers are changing their business models and looking for new investment and business opportunities to improve their profitability and the overall solvency positions. This is also reflected in an increasing interest in mergers and acquisitions to achieve sufficient returns. However, there is no clear answer in the literature whether this strategy brings the expected positive results. This study empirically tests the effects of mergers and acquisitions (M&A) on share prices of European insurers via an event study. Our results do not confirm the positive impact of such strategies on acquirers’ share prices delivering abnormal returns for shareholders.
    Date: 2016–07
    URL: http://d.repec.org/n?u=RePEc:fau:wpaper:wp2016_12&r=fmk
  6. By: Kentaro Iwatsubo (Graduate School of Economics, Kobe University); Tomoki Taishi (Graduate School of Economics, Kobe University)
    Abstract: The gQuantitative and Qualitative Monetary Easing (QQE) h enacted immediately after the inauguration of the Bank of Japan Governor Kuroda brought violent fluctuations in the prices of government bonds and deteriorated market liquidity. Does a central bank fs government bond purchasing policy generally reduce market liquidity? Do conditions exist that can prevent the decrease? This paper analyzes how the Bank of Japan fs purchasing policy changes influenced market liquidity. The results revealed that three specific policy changes contributed significantly to improving market liquidity: 1) increased purchasing frequency; 2) a decrease in the purchase amount per transaction; and 3) a reduced variability in the purchase amounts. These policy changes facilitated investors f purchase schedule expectations and helped reduce market uncertainty. The evidence supports the theory that the effect of government bond purchasing policy on market liquidity depends on the market fs informational environment.
    Date: 2016–09
    URL: http://d.repec.org/n?u=RePEc:koe:wpaper:1623&r=fmk

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