nep-fmk New Economics Papers
on Financial Markets
Issue of 2016‒11‒13
five papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. What is the Expected Return on a Stock? By Martin, Ian; Wagner, Christian
  2. Tracking Changes in the Intensity of Financial Sector's Systemic Risk By Xisong Jin; Francisco Nadal De Simone
  3. Counterparty Risk and Counterparty Choice in the Credit Default Swap Market By Wenxin Du; Salil Gadgil; Michael B. Gordy; Clara Vega
  4. Monetary Policy and the Stock Market: Time-Series Evidence By Michael Weber; Andreas Neuhierl
  5. Use of unit root methods in early warning of financial crises By Virtanen, Timo; Tölö, Eero; Virén, Matti; Taipalus, Katja

  1. By: Martin, Ian; Wagner, Christian
    Abstract: We derive a formula that expresses the expected return on a stock in terms of the risk-neutral variance of the market and the stock's excess risk-neutral variance relative to the average stock. These components can be computed from index and stock option prices; the formula has no free parameters. We test the theory in-sample by running panel regressions of stock returns onto risk-neutral variances. The formula performs well at 6-month and 1-year forecasting horizons, and our predictors drive out beta, size, book-to-market, and momentum. Out-of-sample, we find that the formula outperforms a range of competitors in forecasting individual stock returns. Our results suggest that there is considerably more variation in expected returns, both over time and across stocks, than has previously been acknowledged.
    Keywords: expected returns; forecast; implied volatility; risk premia; risk-neutral variance
    JEL: E22 E44 G10 G12 G17 G31 G32
    Date: 2016–11
    URL: http://d.repec.org/n?u=RePEc:cpr:ceprdp:11608&r=fmk
  2. By: Xisong Jin; Francisco Nadal De Simone
    Abstract: This study provides the first available estimates of systemic risk in the financial sector comprising the banking and investment fund industries during 2009Q4­2015Q4. Systemic risk is measured in three forms: as risk common to the financial sector; as contagion within the financial sector and; as the build­up of financial sector's vulnerabilities over time, which may unravel in a disorderly manner. The methodology models the financial sector components' default dependence statistically and captures the time­varying non-linearities and feedback effects typical of financial markets. In addition, the study estimates the common components of the financial sector's default measures and by identifying the macro-financial variables most closely associated with them, it provides useful input into the formulation of macro­prudential policy. The main results suggest that: (1) interdependence in the financial sector decreased in the first three years of the sample, but rose again later coinciding with ECB's references to increased search for yield in the financial sector. (2) Investment funds are a more important source of contagion to banks than the other way round, and this is more the case for European banking groups than for Luxembourg banks. (3) For tracking the growth of vulnerabilities over time, it is better to monitor the most vulnerable part of the financial sector because the common components of systemic risk measures tend to lead these measures.
    Keywords: financial stability? macro-prudential policy? banking sector; investment funds; default probability? non-linearities? generalized dynamic factor model? dynamic copulas
    JEL: C1 E5 F3 G1
    Date: 2016–10
    URL: http://d.repec.org/n?u=RePEc:bcl:bclwop:bclwp102&r=fmk
  3. By: Wenxin Du; Salil Gadgil; Michael B. Gordy; Clara Vega
    Abstract: We investigate how market participants price and manage counterparty risk in the post-crisis period using confidential trade repository data on single-name credit default swap (CDS) transactions. We find that counterparty risk has a modest impact on the pricing of CDS contracts, but a large impact on the choice of counterparties. We show that market participants are significantly less likely to trade with counterparties whose credit risk is highly correlated with the credit risk of the reference entities and with counterparties whose credit quality is relatively low. Furthermore, we examine the impact of central clearing on CDS pricing. Contrary to the previous literature, but consistent with our main findings on pricing, we find no evidence that central clearing increases transaction spreads.
    Keywords: Counterparty credit risk ; Credit default swaps ; Central clearing
    JEL: G12 G13 G24
    Date: 2016–09–08
    URL: http://d.repec.org/n?u=RePEc:fip:fedgfe:2016-87&r=fmk
  4. By: Michael Weber (University of Chicago Booth School of Business); Andreas Neuhierl (Mendoza College of Business, University of Notre Dame)
    Abstract: We construct a slope factor from changes in federal funds futures of different horizons. Slope predicts stock returns at the weekly frequency: faster monetary policy easing positively predicts excess returns. Investors can achieve increases in weekly Sharpe ratios of 20% conditioning on the slope factor. The tone of speeches by the FOMC chair correlates with the slope factor. Slope predicts changes in future interest rates and forecast revisions of professional forecasters. Our findings show that the path of future interest rates matters for asset prices, and monetary policy affects asset prices throughout the year and not only at FOMC meetings. Â
    Keywords: Return Predictability, Policy Speeches, Expected Returns, Macro News
    JEL: E31 E43 E44 E52 E58 G12
    Date: 2016
    URL: http://d.repec.org/n?u=RePEc:bfi:wpaper:2016-26&r=fmk
  5. By: Virtanen, Timo; Tölö, Eero; Virén, Matti; Taipalus, Katja
    Abstract: Unit root methods have long been used in detection of financial bubbles in asset prices. The basic idea is that fundamental changes in the autocorrelation structure of relevant time series imply the presence of a rational price bubble. We provide cross-country evidence for performance of unit-root-based early warning systems in ex-ante prediction of financial crises in 15 EU countries over the past three decades. We then combine the identified early warning signals from multiple time series into a composite indicator. We also show that a mix of data with different frequencies may be useful in providing timely warning signals. Our results suggest and an early warning tool based on unit root methods provides be a valuable accessory in financial stability supervision.
    Keywords: financial crises, unit root, combination of forecasts
    JEL: G01 G14 G21
    Date: 2016–11–03
    URL: http://d.repec.org/n?u=RePEc:bof:bofrdp:2016_027&r=fmk

This nep-fmk issue is ©2016 by Kwang Soo Cheong. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at http://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.