nep-fmk New Economics Papers
on Financial Markets
Issue of 2009‒04‒25
twelve papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Volatility and realized quadratic variation of differenced returns : A wavelet method approach By Høg, Esben
  2. A High-Low Model of Daily Stock Price Ranges By Yan-Leung Cheung; Yin-Wong Cheung; Alan T. K. Wan
  3. Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy By Cyril Caillault; Dominique Guegan
  4. Martingalized Historical approach for Option Pricing By Christophe Chorro; Dominique Guegan; Florian Ielpo
  5. "Pricing and Hedging of Long-term Futures and Forward Contracts by a Three-Factor Model" By Kenichiro Shiraya; Akihiko Takahashi
  6. Forecasting electricity spot market prices with a k-factor GIGARCH process By Abdou Kâ Diongue; Dominique Guegan; Bertrand Vignal
  7. U.S. Stock Market Crash Risk, 1926-2006 By David S. Bates
  8. Fear of Fire Sales and the Credit Freeze By Douglas W. Diamond; Raghuram G. Rajan
  9. The Impact of the US Subprime Mortgage Crisis on the World and East Asia By Shirai, Sayuri
  10. Housing Finance in the Euro Area. By Francesco Drudi; Petra Köhler-Ulbrich; Marco Protopapa; Jiri Slacalek; Christoffer Kok Sørensen; Guido Wolswijk; Ramón Gómez Salvador; Ruth Magono; Nico Valckx; Elmar Stöss; Karin Wagner; Zoltan Walko; Marie Denise Zachary; Silvia Magri; Laura Bartiloro; Paolo Mistrulli; Yannis Asimakopoulos; Vasilis Georgakopoulos; Maria Kasselaki; Jorge Martínez Pagés; Romain Weber; Christiana Argyridou; Wendy Zammit; Nuno Ribeiro; Daniel Gabrielli; Nicola Doyle; Harri Hasko; Vesna Lukovic
  11. Does Size Matter? Economies of Scale in the German Mutual Fund Industry By Raimond Maurer; Alexander Schaefer
  12. 2008 Stock Markets and the Race to the Bottom: “Stuck” in China By Tyler Rooker

  1. By: Høg, Esben (Department of Business Studies, Aarhus School of Business)
    Abstract: This paper analyzes some asymptotic results for an alternative estimator of integrated volatility in a continuous-time diffusion process of high frequency data (used in asset pricing finance). <p> The estimator, which is computationally efficient, is based on the quadratic variation of the second order log-price differences. This is contrary to the well known realized quadratic variation of intra daily returns (which is based on first order log-price differences). This latter is known as realized volatility. <p> Analytically, the asymptotics of the proposed estimator is compared to the usual realized volatility estimators. Lastly, we provide some simulation experiments to illustrate the results.
    Keywords: continuous-time methods; quadratic variation; realized volatility; second order quadratic variation
    Date: 2008–08–01
    URL: http://d.repec.org/n?u=RePEc:hhb:aarbfi:2008-06&r=fmk
  2. By: Yan-Leung Cheung (City University of Hong Kong); Yin-Wong Cheung (University of California, Santa Cruz); Alan T. K. Wan (City University of Hong Kong)
    Abstract: We observe that daily highs and lows of stock prices do not diverge over time and, hence, adopt the cointegration concept and the related vector error correction model (VECM) to model the daily high, the daily low, and the associated daily range data. The in-sample results attest the importance of incorporating high-low interactions in modeling the range variable. In evaluating the out-of-sample forecast performance using both mean-squared forecast error and direction of change criteria, it is found that the VECM-based low and high forecasts offer some advantages over some alternative forecasts. The VECM-based range forecasts, on the other hand, do not always dominate - the forecast rankings depend on the choice of evaluation criterion and the variables being forecasted.
    Keywords: Daily High, Daily Low, VECM Model, Forecast Performance, Implied Volatility
    JEL: C32 C53 G10
    Date: 2009–01
    URL: http://d.repec.org/n?u=RePEc:hkm:wpaper:032009&r=fmk
  3. By: Cyril Caillault (Fortis Investments - Fortis investments); Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)
    Abstract: Using non-parametric and parametric models, we show that the bivariate distribution of an Asian portfolio is not stable along all the period under study. We suggest several dynamic models to compute two market risk measures, the Value at Risk and the Expected Shortfall: the RiskMetrics methodology, the Multivariate GARCH models, the Multivariate Markov-Switching models, the empirical histogram and the dynamic copulas. We discuss the choice of the best method with respect to the policy management of bank supervisors. The copula approach seems to be a good compromise between all these models. It permits taking financial crises into account and obtaining a low capital requirement during the most important crises.
    Keywords: Value at Risk ; Expected Shortfall ; Copulas ; Risk management ; GARCH models ; Markov switching models
    Date: 2009–04
    URL: http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-00375765_v1&r=fmk
  4. By: Christophe Chorro (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I); Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris); Florian Ielpo (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I)
    Abstract: In a discrete time option pricing framework, we compare the empirical performance of two pricing methodologies, namely the affine stochastic discount factor and the empirical martingale correction methodologies. Using a CAC 40 options dataset, the differences are found to be small : the higher order moment correction involved in the SDF approach may not be that essential to reduce option pricing errors.
    Keywords: Generalized hyperbolic distribution, option pricing, incomplete market, CAC 40, Stochastic Discount Factor, martingale correction.
    Date: 2009–04
    URL: http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-00376756_v1&r=fmk
  5. By: Kenichiro Shiraya (Mizuho-DL Financial Technology Co., Ltd.); Akihiko Takahashi (Faculty of Economics, University of Tokyo)
    Abstract: This paper shows pricing and hedging efficiency of a three factor stochastic mean reversion Gaussian model of commodity prices using oil and copper futures and forward contracts. The model is estimated using NYMEX WTI (light sweet crude oil) and LME Copper futures prices and is shown to fit the data well. Furthermore, it shows how to hedge based on a three-factor model and confirms that using three different futures contracts to hedge long-term contract outperforms the traditional parallel hedge based on a single futures position by time series data and simulation. It also finds that the three factor model outperforms its two-factor version in replication of actual term structures and that stochastic mean reversion models outperform constant mean reversion models in Out of Sample hedges.
    Date: 2009–04
    URL: http://d.repec.org/n?u=RePEc:tky:fseres:2009cf618&r=fmk
  6. By: Abdou Kâ Diongue (UFR SAT - Université Gaston Berger - Université Gaston Berger de Saint-Louis); Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris); Bertrand Vignal (EDF - EDF - Recherche et Développement)
    Abstract: In this article, we investigate conditional mean and variance forecasts using a dynamic model following a k-factor GIGARCH process. We are particularly interested in calculating the conditional variance of the prediction error. We apply this method to electricity prices and test spot prices forecasts until one month ahead forecast. We conclude that the k-factor GIGARCH process is a suitable tool to forecast spot prices, using the classical RMSE criteria.
    Keywords: Conditional mean - conditional variance - forecast - electricity prices - GIGARCH process
    Date: 2009–04
    URL: http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-00307606_v1&r=fmk
  7. By: David S. Bates
    Abstract: This paper applies the Bates (RFS, 2006) methodology to the problem of estimating and filtering time- changed Lévy processes, using daily data on U.S. stock market excess returns over 1926-2006. In contrast to density-based filtration approaches, the methodology recursively updates the associated conditional characteristic functions of the latent variables. The paper examines how well time-changed Lévy specifications capture stochastic volatility, the “leverage†effect, and the substantial outliers occasionally observed in stock market returns. The paper also finds that the autocorrelation of stock market excess returns varies substantially over time, necessitating an additional latent variable when analyzing historical data on stock market returns. The paper explores option pricing implications, and compares the results with observed prices of options on S&P 500 futures.
    JEL: C22 C46 G1 G13
    Date: 2009–04
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:14913&r=fmk
  8. By: Douglas W. Diamond; Raghuram G. Rajan
    Abstract: In early 2009, the supply of credit markets in industrial countries appeared to be tightening substantially. Was this because credit quality had deteriorated tremendously outside or inside the financial system? Or was it because bank balance sheets were “clogged†with illiquid securities? If the latter, why did banks not attempt to sell these securities? We argue in this paper that the existence of an “overhang†of impaired banks may itself reduce the price of potentially illiquid securities sufficiently that banks have no interest in selling them. In turn, this creates high expected returns to holding cash or liquid securities across the financial system and an aversion to locking up money in term loans. We discuss what this means for policies to clean up the banking system.
    JEL: E44 G21
    Date: 2009–04
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:14925&r=fmk
  9. By: Shirai, Sayuri
    Abstract: The world economy currently suffers from a global financial and economic crisis that has become severe since the second half of 2008. This global financial situation was triggered by the advent of the subprime mortgage crisis in the United States that became apparent from the mid-2007s. Europe was the next affected, thereafter its contagion spread to the rest of the world. East Asia did not escape. The nature of the current global financial crisis is unprecedented in terms of (1) the scale of the problems in the financial sector (particularly in the United States and Europe), (2) the depth and speed of contagion worldwide (through financial sector and trade linkages), and (3) the severity of the recession (particularly in emerging market economics, small countries, and East Asia). This paper analyzes, mainly, cross-border capital movements by looking at the pre-crisis features of the United States as the crisis hypocenter and its relationships with other countries. Detailed observations are conducted with respect to cross-border investment in stocks and debt securities, as well as banking activities. The paper then sheds light on the impact of the subprime mortgage crisis on cross-border capital movements in the United States, the United Kingdom, and East Asia. Other performance indicators such as exchange rates, economic growth and international trade are also discussed in the case of East Asia. The paper examines several challenges the recent crisis poses for East Asia.
    Keywords: Subprime Mortgage; Global Economic Crisis; East Asia; Cross-border capital flows
    JEL: F3 G15
    Date: 2009–04–02
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:14722&r=fmk
  10. By: Francesco Drudi (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Petra Köhler-Ulbrich (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Marco Protopapa (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Jiri Slacalek (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Christoffer Kok Sørensen (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Guido Wolswijk (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Ramón Gómez Salvador (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Ruth Magono (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Nico Valckx (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Elmar Stöss (Deutsche Bundesbank,Taunusanlage 5, D-60329 Frankfurt am Main, Germany.); Karin Wagner (Oesterreichische Nationalbank, Otto Wagner Platz 3, A-1011 Vienna, Austria.); Zoltan Walko (Oesterreichische Nationalbank, Otto Wagner Platz 3, A-1011 Vienna, Austria.); Marie Denise Zachary (Banque Nationale de Belgique, Boulevard de Berlaimont 14, B-1000 Brussels, Belgium.); Silvia Magri (Banca d'Italia, Via Nazionale 91, I - 00184 Rome, Italy.); Laura Bartiloro (Banca d'Italia, Via Nazionale 91, I - 00184 Rome, Italy.); Paolo Mistrulli (Banca d'Italia, Via Nazionale 91, I - 00184 Rome, Italy.); Yannis Asimakopoulos (Bank of Greece, 21, E. Venizelos Avenue, P. O. Box 3105, GR-10250 Athens, Greece.); Vasilis Georgakopoulos (Bank of Greece, 21, E. Venizelos Avenue, P. O. Box 3105, GR-10250 Athens, Greece.); Maria Kasselaki (Bank of Greece, 21, E. Venizelos Avenue, P. O. Box 3105, GR-10250 Athens, Greece.); Jorge Martínez Pagés (Banco de España, Alcalá 50, E-28014 Madrid, Spain.); Romain Weber (Banque centrale du Luxembourg, 2 boulevard Royal, L - 2983 Luxembourg, Luxembourg.); Christiana Argyridou (Central Bank of Cyprus, 80, Kennedy Avenue, CY-1076 Lekosia, Cyprus.); Wendy Zammit (Bank of Malta, Castille Place, Valetta, CMR 01, Malta.); Nuno Ribeiro (Banco de Portugal, 148, Rua do Comercio, P-1101 Lisbon, Codex, Portugal.); Daniel Gabrielli (Banque de France, 39, rue Croix-des-Petits-Champs, F-75049 Paris Cedex 01, France.); Nicola Doyle (Central Bank of Ireland, Dame Street, IE Dublin 2, Ireland.); Harri Hasko (Suomen Pankki, P. O. Box 160, FIN-00101 Helsinki, FI.); Vesna Lukovic (Banka Slovenije, Slovenska 35, SL-1505 Ljubljana, SL.)
    Abstract: This report analyses the main developments in housing finance in the euro area in the decade, covering the period from 1999 to 2007. It looks at mortgage indebtedness, various characteristics of loans for house purchase, the funding of such loans and the spreads between the interest rates on loans granted by banks and the interest rates banks had to pay on their funding, or the return they made on alternative investments. In addition, the report contains a comparison of key aspects of housing finance in the euro area with those in the United Kingdom and the United States. At the end, the report briefly discusses aspects of the transmission of monetary policy to the economy. JEL Classification: D14, E44, E5, G21, R21.
    Keywords: bank competition, bank funding, bankruptcy, banks, cost of funding (of banks), cost of housing loans, debt service, ECB monetary policy, foreclosure, household debt, household survey, housing finance, insolvency, loan maturity, loan-to-value ratio, monetary policy transmission, mortgage, mortgage covered bond, mortgage equity withdrawal, mortgage interest rate spread, redemption scheme, rental market, retail deposits, securitisation, taxation, US housing market crisis.
    Date: 2009–03
    URL: http://d.repec.org/n?u=RePEc:ecb:ecbops:20090101&r=fmk
  11. By: Raimond Maurer; Alexander Schaefer
    Abstract: In this paper, we analyze economies of scale for German mutual fund complexes. Using 2002-2005 data of 41 investment management companies, we specify a hedonic translog cost function. Applying a fixed effects regression on a one-way error component model there is clear evidence of significant overall economies of scale. On the level of individual mutual fund complexes we find significant economies of scale for all of the companies in our sample. With regard to cost efficiency, we find that the average mutual fund complexes in all size quartiles deviate considerably from the best practice cost frontier.
    JEL: G2 L25
    Date: 2009–04
    URL: http://d.repec.org/n?u=RePEc:fra:franaf:201&r=fmk
  12. By: Tyler Rooker (Goldsmiths, University of London)
    Abstract: Since late 2005, China’s two stock markets, in Shanghai (SSE) and Shenzhen (SZSE), have risen over 600% only to fall by close to 60% from a peak in late 2007. The race up and down is reflected in China’s macroeconomic indicators, but the real story lies with individuals investing in the market. In contrast to past studies of China’s stock markets, this paper argues that individual investors, and especially those investing less than 100,000 USD, are a critical part of the market. One postulate is that it is precisely these “micro” investors who, despite the general consensus that China’s stock markets are “policy markets”, keep the state from regulating the market. Put warrants, literally worthless paper in the days before the end of trading, continue to become sites for speculative trading. The 2007 stock market rose 97%, while the 2008 market has fallen over 50%: the non-tradable share reform, allowing large and small holders to trade previously non-tradable shares, is the current bane of the market. Yet the culprits in abnormal trading are not “individuals”, but the companies, often owned by local governments, that are the vanguard of China’s reform. This paper reviews these developments in detail, and suggests a potential new theory of China’s securities reform.
    Date: 2008–05
    URL: http://d.repec.org/n?u=RePEc:wef:wpaper:0040&r=fmk

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