nep-fmk New Economics Papers
on Financial Markets
Issue of 2013‒01‒07
nine papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Review Of Theories of Financial Crises By Assaf Razin; Itay Goldstein
  2. The normaly distributed daily returns in stock trading By Younes Ben-Ghabrit
  3. Non stationary multifractality in stock returns By Raffaello Morales; T. Di Matteo; Tomaso Aste
  4. The Inefficient Markets Hypothesis: Why Financial Markets Do Not Work Well in the Real World By Roger E.A. Farmer; Carine Nourry; Alain Venditti
  5. Aggregate Stock Market Illiquidity and Bond Risk Premia By Kees E. Bouwman; Elvira Sojli; Wing Wah Tham
  6. The determinants of sovereign bond yield spreads in the EMU By António Afonso; Michael G. Arghyrou; Alexandros Kontonikas
  7. U.K. cross-sectional equity data: The case for robust investability filters By Rossi, Francesco
  8. Credit-Risk Valuation in the Sovereign CDS and Bonds Markets: Evidence from the Euro Area Crisis By Óscar Arce; Sergio Mayordomo; Juan Ignacio Peña
  9. A Study of the Effect of Macroeconomic Variables on Stock Market: Indian Perspective By Chandni Makan, Chandni Makan; Avneet Kaur Ahuja, Avneet Kaur Ahuja; Saakshi Chauhan, Saakshi Chauhan

  1. By: Assaf Razin (Tel Aviv University); Itay Goldstein (University of Pennsylvania)
    Abstract: The last few years have been characterized by great turmoil in the world’s financial markets; starting from the collapse of housing prices in the US, followed by the meltdown of leading financial institutions in the US and Europe, and then the ongoing challenge to the European monetary union. These events exhibit ingredients from all types of financial crises in recent history: banking crises, currency crises, credit frictions, market freezes, and the bursting of asset bubbles. In this survey, we provide a review of the analytical underpinnings of these types of crises and the directions in which they influenced future literature and the way they explain recent events.
    Date: 2012
  2. By: Younes Ben-Ghabrit
    Abstract: In this report, we talked about a new quantitative strategy for choosing the optimal(s) stock(s) to trade. The basic notions are generally very known by the financial community. The key here is to understand 1) the standard score applied to a sample and 2) the correlation factor applied to different time series in real life. These notions are the core of our research. We are going to begin with the introduction section. In this part, we talked about variance, covariance, correlation factor, daily returns in stock trading and the Shapiro-Wilk test to test the normality of a time serie. Next to that, I talked about the core of my method (what do you do if you want to pick the optimal(s) stock(s) to trade). At the end of this report, I talked about a new idea if you want to analyze more than one stock at the time. All my work goes with a primary reflexion : forecasting a stock direction is a random walk and nobody can be 100 % sure where a stock is going. All we can do, is to pretend to have a technic with a win/loss ratio greater than 51 %.
    Date: 2012–12
  3. By: Raffaello Morales; T. Di Matteo; Tomaso Aste
    Abstract: We report evidence that empirical data show time varying multifractal properties. This is obtained by comparing empirical observations of the weighted generalised Hurst exponent (wGHE) with time series simulated via Multifractal Random Walk (MRW) by Bacry \textit{et al.} [\textit{E.Bacry, J.Delour and J.Muzy, Phys.Rev.E \,{\bf 64} 026103, 2001}]. While dynamical wGHE computed on synthetic MRW series is consistent with a scenario where multifractality is constant over time, fluctuations in the dynamical wGHE observed in empirical data fail to be in agreement with a MRW with constant intermittency parameter. This is a strong argument to claim that observed variations of multifractality in financial time series are to be ascribed to a structural breakdown in the temporal covariance structure of stock returns series. As a consequence, multi fractal models with a constant intermittency parameter may not always be satisfactory in reproducing financial market behaviour.
    Date: 2012–12
  4. By: Roger E.A. Farmer; Carine Nourry; Alain Venditti
    Abstract: Existing literature continues to be unable to offer a convincing explanation for the volatility of the stochastic discount factor in real world data. Our work provides such an explanation. We do not rely on frictions, market incompleteness or transactions costs of any kind. Instead, we modify a simple stochastic representative agent model by allowing for birth and death and by allowing for heterogeneity in agents' discount factors. We show that these two minor and realistic changes to the timeless Arrow-Debreu paradigm are sufficient to invalidate the implication that competitive financial markets efficiently allocate risk. Our work demonstrates that financial markets, by their very nature, cannot be Pareto efficient, except by chance. Although individuals in our model are rational; markets are not.
    JEL: E44 G01 G12 G14
    Date: 2012–12
  5. By: Kees E. Bouwman (Erasmus University Rotterdam); Elvira Sojli (Erasmus University Rotterdam); Wing Wah Tham (Erasmus University Rotterdam)
    Abstract: We assess the effect of aggregate stock market illiquidity on U.S. Treasury bond risk premia. We find that the stock market illiquidity variable adds to the well established Cochrane-Piazzesi and Ludvigson-Ng factors. It explains 10%, 9%, 7%, and 7% of the one-year-ahead variation in the excess return for two-, three-, four-, and ve-year bonds respectively and increases the adjusted R<SUP>2</SUP> by 3-6% across all maturities over Cochrane and Piazzesi (2005) and Ludvigson and Ng (2009) factors. The effects are highly statistically and economically significant both in and out of sample. We find that our result is robust to and is not driven by information from open interest in the futures market, long-run inflation expectations, dispersion in beliefs, and funding liquidity. We argue that stock market illiquidity is a timely variable that is related to " right-to-quality" episodes and might contain information about expected future business conditions through funding liquidity and investment channels.
    Keywords: Market liquidity; Bond risk premia; Flight-to-quality
    JEL: G10 G20 G14
    Date: 2012–12–12
  6. By: António Afonso; Michael G. Arghyrou; Alexandros Kontonikas
    Abstract: We use a panel of euro area countries to assess the determinants of long-term sovereign bond yield spreads over the period 1999.01-2010.12. We find that, unlike the period preceding the global financial crisis, European government bond yield spreads are wellexplained by macro- and fiscal fundamentals over the crisis period. We also find that the menu of macro and fiscal risks priced by markets has been significantly enriched since March 2009, including the risk of the crisis’ transmission among EMU member states, international risk and liquidity risk. Finally, we find that sovereign credit ratings are statistically significant in explaining spreads, yet compared to macro- and fiscal fundamentals their role is limited. JEL Classification: C23, E62, H50.
    Keywords: sovereign yields, government debt, panel analysis, credit ratings
    Date: 2012–10
  7. By: Rossi, Francesco
    Abstract: We propose a novel approach to cross-sectional equities sample selection, derived from best market practice in index construction and focused on investability. Using the U.K. market as a template, we first demonstrate how the popular Datastream dataset is plagued by data deficiencies that would surely invalidate statistical inferences, and that are not addressed by commonly used filters. We show the benefits and need for a supplementary data source. We then develop robust investability filters to ensure statistical results from cross-sectional analysis are economically meaningful, an issue overlooked by most studies on cross-sectional risk pricing
    Keywords: cross-sectional equities; liquidity; investability; Datastream; asset pricing; Bloomberg; sample selection; turnover; volume; U.K. equities;
    JEL: G12 G11 G15 G10 C89
    Date: 2012–11
  8. By: Óscar Arce (Directorate General Economics, Statistics and Research, Bank of Spain); Sergio Mayordomo (School of Economics and Business Administration, University of Navarra); Juan Ignacio Peña (Department of Business Administration, Universidad Carlos III de Madrid)
    Abstract: We analyse the extent to which prices in the sovereign credit default swap (CDS) and bond markets reflect the same information on credit risk in the context of the current crisis of the European Monetary Union (EMU). We first document that deviations between CDS and bond spreads are related to counterparty risk, common volatility in EMU equity markets, market illiquidity, funding costs, flight-to-quality, and the volume of debt purchases by the European Central Bank (ECB) in the secondary market. Based on this we conduct a state-dependent price-discovery analysis that reveals that the levels of the counterparty risk and the common volatility in EMU equity markets, and the banks’ agreements to accept losses on their holdings of Greek bonds impair the ability of the CDS market to lead the price discovery process. On the other hand, the funding costs, the flight-to-quality indicator and the volume of debt purchases by the ECB worsen the efficiency of the bond market.
    Keywords: sovereign credit default swaps, sovereign bonds, credit spreads, price discovery
    JEL: G10 G14 G15
    Date: 2012–12–21
  9. By: Chandni Makan, Chandni Makan; Avneet Kaur Ahuja, Avneet Kaur Ahuja; Saakshi Chauhan, Saakshi Chauhan
    Abstract: Result of this study help in exploring whether the movement of Bombay Stock Exchanges indices is the outcome of some selected macroeconomic variables or it is one of the causes of movement in those variables of the Indian economy. The study consider macroeconomic variables as Index of Industrial production (IIP), Consumer Price Index (CPI), Call Money Rate (CMR), Dollar Price (DP), Foreign Institutional Investment (FII), Crude Oil Prices (CO), Gold Price (GP) and Bombay Stock Exchanges indices in the form of SENSEX, BSE- Metals, Auto, Capital Goods, Fast Moving Consumer Goods and Consumer Durables by using monthly data that span from April, 2005 to March, 2012. More specifically, in the study we use ADF test, Correlation and Regression analysis and Granger Casually test to see the effect of macroeconomic variables on Bombay Stock Exchange Indices and vice versa (by using Granger Causality test) and found some interesting results for our study analysis.
    Keywords: Descriptive Statistics; ADF Test; Correlation Matrix; Econometric Regression Model; Granger Causality Test
    JEL: A22 C12 A2 M2 C1
    Date: 2012–11–19

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