nep-fmk New Economics Papers
on Financial Markets
Issue of 2013‒05‒11
four papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Forecasting Stock Market Volatility: A Forecast Combination Approach By Nazarian, Rafik; Gandali Alikhani, Nadiya; Naderi, Esmaeil; Amiri, Ashkan
  2. Futures price volatility in commodities markets: The role of short term vs long term speculation By Matteo Manera; Marcella Nicolini; Ilaria Vignati
  3. Day-of-the-Week Effects in the Indian stock market By P., Srinivasan; M., Kalaivani
  4. Intebank liquidity crunch and the firm credit crunch: Evidence from the 2007-2009 crisis By Rajkamal Iyer; Samuel Da-Rocha-Lopes; José-Luis Peydró; Antoinette Schoar

  1. By: Nazarian, Rafik; Gandali Alikhani, Nadiya; Naderi, Esmaeil; Amiri, Ashkan
    Abstract: Recently, with the development of financial markets and due to the importance of these markets and their close relationship with other macroeconomic variables, using advanced mathematical models with complicated structures for forecasting these markets has become very popular. Besides, neural network models have gained a special position compared to other advanced models due to their high accuracy in forecasting different variables. Therefore, the main purpose of this study was to forecast the volatilities of TSE index by regressive models with long memory feature, feed forward neural network and hybrid models (based on forecast combination approach) using daily data. The results were indicative of the fact that based on the criteria for assessing forecasting error, i.e., MSE and RMSE, although forecasting errors of the feed forward neural network model were less than ARFIMA-FIGARCH model, the accuracy of the hybrid model of neural network and best GARCH was higher than each one of these models.
    Keywords: Stock Return, Long Memory, Neural Network, Hybrid Models.
    JEL: C14 C22 C45 C53
    Date: 2013–03–15
  2. By: Matteo Manera (University of Milan-Bicocca and Fondazione Eni Enrico Mattei); Marcella Nicolini (Department of Economics and Management, University of Pavia); Ilaria Vignati (Fondazione Eni Enrico Mattei)
    Abstract: This paper evaluates how different types of speculation affect the volatility of commodities’ futures prices. We adopt four indexes of speculation: Working’s T, the market share of non-commercial traders, the percentage of net long speculators over total open interest in future markets, which proxy for long term speculation, and scalping, which proxies for short term speculation. We consider four energy commodities (light sweet crude oil, heating oil, gasoline and natural gas) and seven non-energy commodities (cocoa, coffee, corn, oats, soybean oil, soybeans and wheat) over the period 1986-2010 analyzed at weekly frequency. Using GARCH models we find that speculation significantly affects volatility of returns: short term speculation has a positive and significant impact on volatility, while long term speculation generally has a negative effect. The robustness exercise shows that: i) scalping is positive and significant also at higher and lower data frequencies; ii) results remain unchanged through different model specifications (GARCH-in-mean, EGARCH, and TARCH); iii) results are robust to different specifications of the mean equation.
    Keywords: Commodities futures markets; Speculation; Scalping; Working’s T, Data frequency; GARCH models
    JEL: C32 G13 Q11 Q43
    Date: 2013–04
  3. By: P., Srinivasan; M., Kalaivani
    Abstract: This paper investigates empirically the day-of-the-week effect on stock returns and volatility of the Indian stock markets. The GARCH (1,1), EGARCH (1,1) and TGARCH (1,1) models were employed to examine the existence of daily anomalies over the period of 1st July, 1997 to 29th June, 2012. The empirical results derived from the GARCH models indicate the existence of day-of-the-week effects on stock returns and volatility of the Indian stock markets. The study reveals positive Monday and Wednesday effects in the NSE-Nifty and BSE-SENSEX market returns. The average return on Monday is significantly higher than the average return of Wednesday in the NSE-Nifty and BSE-SENSEX markets. Besides, the findings confirm the strong support of ARCH and GARCH effects persist in the returns series. Moreover, the asymmetric GARCH models show that the Indian stock market returns exhibit asymmetric (leverage) effect. Most importantly, the empirical results indicate that Tuesday effects have negative impact on volatility after controlling the persistence and asymmetric effects.
    Keywords: Day-of-the-week Effect, Weak-form Efficiency, GARCH Models, Asymmetric Effect
    JEL: C22 G14 O53
    Date: 2013–05–07
  4. By: Rajkamal Iyer; Samuel Da-Rocha-Lopes; José-Luis Peydró; Antoinette Schoar
    Abstract: We study the credit supply effects of the unexpected freeze of the European interbank market, using exhaustive Portuguese loan-level data. We find that banks that rely more on interbank borrowing before the crisis decrease their credit supply more during the crisis. The credit supply reduction is stronger for firms that are smaller, with weaker banking relationships. Small firms cannot compensate the credit crunch with other sources of debt. Furthermore, the impact of illiquidity on the credit crunch is stronger for less solvent banks. Finally, there are no overall positive effects of central bank liquidity, but higher hoarding of liquidity.
    Keywords: Credit crunch; banking crisis; interbank markets; access to credit; flight to quality; lender of last resort; liquidity hoarding.
    JEL: G01 G21 G28 G32
    Date: 2013–04

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