New Economics Papers
on Financial Markets
Issue of 2011‒02‒19
eight papers chosen by

  1. Do Federal Reserve Bank Presidents Pursue Regional or National Interests? New Evidence Based on Speeches By Bernd Hayo; Matthias Neuenkirch
  2. The US stock market leads the Federal funds rate and Treasury bond yields By Kun Guo; Wei-Xing Zhou; Si-Wei Cheng; Didier Sornette
  3. Quantifying and Modeling Long-Range Cross-Correlations in Multiple Time Series with Applications to World Stock Indices By Duan Wang; Boris Podobnik; Davor Horvati\'c; H. Eugene Stanley
  4. An Update on EU Financial Reforms By Nicolas Veron
  5. Systemic Risk and Network Formation in the Interbank Market By Cohen-Cole, Ethan; Patacchini, Eleonora; Zenou, Yves
  6. A Copula Approach on the Dynamics of Statistical Dependencies in the US Stock Market By Michael C. M\"unnix; Rudi Sch\"afer
  7. Forecasting the term structure of the Euro Market using Principal Component Analysis By Dauwe, Alexander; Moura, Marcelo L.
  8. Performance Analysis of Brazilian Hedge Funds By Jordão, Gustavo A.; Moura, Marcelo L.

  1. By: Bernd Hayo (Philipps-University Marburg); Matthias Neuenkirch (Philipps-University Marburg)
    Abstract: In this paper, we analyze the determinants of speeches by Federal Reserve (Fed) officials over the period January 1998 to September 2009. Econometrically, we use a probit model with regional and national macroeconomic variables to explain the subjectively coded content of these speeches. Our results are, first, that Fed Governors and presidents follow a Taylor rule when expressing their opinions: a rise in expected inflation (unemployment) makes a hawkish speech more (less) likely. Second, the content of speeches by Fed presidents is affected by both regional and national macroeconomic variables. Third, speeches by nonvoting presidents are more focused on regional economic development than are those by voting presidents. Finally, voting presidents and Governors are less backward-looking in their wording than are nonvoting presidents.
    Keywords: Central Bank Communication, Disagreement, Federal Reserve Bank, Monetary Policy, Regional Representation, Speeches
    JEL: D72 E52 E58
    Date: 2011
  2. By: Kun Guo (CAS); Wei-Xing Zhou (ECUST); Si-Wei Cheng (CAS); Didier Sornette (ETH Zurich)
    Abstract: Using a recently introduced method to quantify the time varying lead-lag dependencies between pairs of economic time series (the thermal optimal path method), we test two fundamental tenets of the theory of fixed income: (i) the stock market variations and the yield changes should be anti-correlated; (ii) the change in central bank rates, as a proxy of the monetary policy of the central bank, should be a predictor of the future stock market direction. Using both monthly and weekly data, we found very similar lead-lag dependence between the S&P500 stock market index and the yields of bonds inside two groups: bond yields of short-term maturities (Federal funds rate (FFR), 3M, 6M, 1Y, 2Y, and 3Y) and bond yields of long-term maturities (5Y, 7Y, 10Y, and 20Y). In all cases, we observe the opposite of (i) and (ii). First, the stock market and yields move in the same direction. Second, the stock market leads the yields, including and especially the FFR. Moreover, we find that the short-term yields in the first group lead the long-term yields in the second group before the financial crisis that started mid-2007 and the inverse relationship holds afterwards. These results suggest that the Federal Reserve is increasingly mindful of the stock market behavior, seen at key to the recovery and health of the economy. Long-term investors seem also to have been more reactive and mindful of the signals provided by the financial stock markets than the Federal Reserve itself after the start of the financial crisis. The lead of the S&P500 stock market index over the bond yields of all maturities is confirmed by the traditional lagged cross-correlation analysis.
    Date: 2011–02
  3. By: Duan Wang; Boris Podobnik; Davor Horvati\'c; H. Eugene Stanley
    Abstract: We propose a modified time lag random matrix theory in order to study time lag cross-correlations in multiple time series. We apply the method to 48 world indices, one for each of 48 different countries. We find long-range power-law cross-correlations in the absolute values of returns that quantify risk, and find that they decay much more slowly than cross-correlations between the returns. The magnitude of the cross-correlations constitute "bad news" for international investment managers who may believe that risk is reduced by diversifying across countries. We find that when a market shock is transmitted around the world, the risk decays very slowly. We explain these time lag cross-correlations by introducing a global factor model (GFM) in which all index returns fluctuate in response to a single global factor. For each pair of individual time series of returns, the cross-correlations between returns (or magnitudes) can be modeled with the auto-correlations of the global factor returns (or magnitudes). We estimate the global factor using principal component analysis, which minimizes the variance of the residuals after removing the global trend. Using random matrix theory, a significant fraction of the world index cross-correlations can be explained by the global factor, which supports the utility of the GFM. We demonstrate applications of the GFM in forecasting risks at the world level, and in finding uncorrelated individual indices. We find 10 indices are practically uncorrelated with the global factor and with the remainder of the world indices, which is relevant information for world managers in reducing their portfolio risk. Finally, we argue that this general method can be applied to a wide range of phenomena in which time series are measured, ranging from seismology and physiology to atmospheric geophysics.
    Date: 2011–02
  4. By: Nicolas Veron (Peterson Institute for International Economics)
    Abstract: The European Union will have to put forth significant effort to develop its own financial regulation system in the absence of strong momentum towards global standards. Nicolas Véron compares US and EU regulatory responses to the global financial crisis and then breaks down the specific areas of reform in which the European Union has acted or is expected to act. The successful creation of the European Supervisory Authorities is the main achievement so far and could lead over time to a distinct European financial regulatory philosophy.
    Date: 2010–12
  5. By: Cohen-Cole, Ethan (University of Maryland); Patacchini, Eleonora (University of Roma La Sapienza); Zenou, Yves (Dept. of Economics, Stockholm University)
    Abstract: We propose a novel mechanism to facilitate understanding of systemic risk in financial markets. The literature on systemic risk has focused on two mechanisms, common shocks and domino-like sequential default. Our approach is a formal model that provides an intellectual combination of the two by looking at how shocks propagate through a network of interconnected banks. Transmission in our model is not based on default. Instead, we provide a simple microfoundation of banks’ profitability based on classic competition incentives. As competitors lending quantities change, both for closely connected ones and the whole market, banks adjust their own lending decisions as a result, generating a ‘transmission’ of shocks through the system. We provide a unique equilibrium characterization of a static model, and embed this model into a full dynamic model of network formation with n agents. Because we have an explicit characterization of equilibrium behavior, we have a tractable way to bring the model to the data. Indeed, our measures of systemic risk capture the propagation of shocks in a wide variety of contexts; that is, it can explain the pattern of behavior both in good times as well as in crisis.
    Keywords: Financial networks; interbank lending; interconnections; network centrality; spatial autoregressive models
    JEL: C21 G10
    Date: 2011–02–11
  6. By: Michael C. M\"unnix; Rudi Sch\"afer
    Abstract: We analyze the statistical dependency structure of the S&P 500 constituents in the 4-year period from 2007 to 2010 using intraday data from the New York Stock Exchange's TAQ database. With a copula-based approach, we find that the statistical dependencies are very strong in the tails of the marginal distributions. This tail dependence is higher than in a bivariate Gaussian distribution, which is implied in the calculation of many correlation coefficients. We compare the tail dependence to the market's average correlation level as a commonly used quantity and disclose an neraly linear relation.
    Date: 2011–02
  7. By: Dauwe, Alexander; Moura, Marcelo L.
    Date: 2011–10
  8. By: Jordão, Gustavo A.; Moura, Marcelo L.
    Date: 2011–10

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