nep-fmk New Economics Papers
on Financial Markets
Issue of 2019‒09‒02
thirteen papers chosen by

  1. Simpler Better Market Betas By Ivo Welch
  2. Intra-day Equity Price Prediction using Deep Learning as a Measure of Market Efficiency By David Byrd; Tucker Hybinette Balch
  3. Strategic Trading as a Response to Short Sellers By Di Maggio, Marco; Franzoni, Francesco; Massa, Massimo; Tubaldi, Roberto
  4. Swing Pricing and Fragility in Open-end Mutual Funds By Jin, Dunhong; Kacperczyk, Marcin; Kahraman, Bige; Suntheim, Felix
  5. Conditional variance forecasts for long-term stock returns By Enno Mammen; Jens Perch Nielsen; Michael Scholz; Stefan Sperlich
  6. An instantaneous market volatility estimation By Oleh Danyliv; Bruce Bland
  7. Predicting Consumer Default: A Deep Learning Approach By Albanesi, Stefania; Vamossy, Domonkos
  8. Price Gap Anomaly in the US Stock Market: The Whole Story By Alex Plastun; Xolani Sibande; Rangan Gupta; Mark E. Wohar
  9. Towards an Unstable Hook: The Evolution of Stock Market Integration Since 1913 By Cécile Bastidon; Michael Bordo; Antoine Parent; Marc Weidenmier
  10. Market concentration and bank M&As: Evidence from the European sovereign debt crisis By Leledakis, George N.; Pyrgiotakis, Emmanouil G.
  11. A European safe asset to complement national government bonds By Giudice, Gabriele; de Manuel Aramendía, Mirzha; Kontolemis, Zenon; Monteiro, Daniel P.
  12. Financial Bubbles : New Evidence from South Africa’s Stock Market By Bago, Jean-Louis; Souratié, Wamadini M.; Ouédraogo, Moussa; Ouédraogo, Ernest; Dembélé, Alou
  13. Islamic finance and herding behavior theory: a sectoral analysis for Gulf Islamic stock market By Imed Medhioub; Mustapha Chaffai

  1. By: Ivo Welch
    Abstract: This paper proposes a robust one-pass estimator that is easy to code: Justified by the market-model itself and using a prior that market-betas should not be less than –2 and more than +4, the market-model is run on daily stock rates of return that have first been winsorized at –2 and +4 times the contemporaneous market rate of return. The resulting “slope-winsorized” estimates outperform (all) other known estimators in predicting the future OLS market-beta (on R 2 metrics). Adding reasonable age decay, suggesting a half-life of about 3 to 5 months, to observations entering the market-model further improves it. The estimates outpredict the Vasicek estimates by about half as much as the Vasicek estimates outpredict the OLS estimates.
    JEL: G10 G11 G31
    Date: 2019–07
  2. By: David Byrd; Tucker Hybinette Balch
    Abstract: In finance, the weak form of the Efficient Market Hypothesis asserts that historic stock price and volume data cannot inform predictions of future prices. In this paper we show that, to the contrary, future intra-day stock prices could be predicted effectively until 2009. We demonstrate this using two different profitable machine learning-based trading strategies. However, the effectiveness of both approaches diminish over time, and neither of them are profitable after 2009. We present our implementation and results in detail for the period 2003-2017 and propose a novel idea: the use of such flexible machine learning methods as an objective measure of relative market efficiency. We conclude with a candidate explanation, comparing our returns over time with high-frequency trading volume, and suggest concrete steps for further investigation.
    Date: 2019–08
  3. By: Di Maggio, Marco; Franzoni, Francesco; Massa, Massimo; Tubaldi, Roberto
    Abstract: We study empirically informed traders' reaction to the presence of short sellers in the market. We find that investors with positive views on a stock strategically slow down their trades when short sellers are present in the same stock. Moreover, they purchase larger amounts to take advantage of the price decline induced by short sellers. Furthermore, they break up their buy trades across multiple brokers, suggesting that they wish to hide from the short sellers. This behavior may impact price discovery, as we find a sizeable reduction of positive information impounding for stocks more exposed to short selling during information sensitive periods. The evidence is confirmed exploiting exogenous variation in short interest provided by the Reg SHO Pilot Program. The findings have relevance for the regulatory debate on the market impact of short selling.
    Keywords: Informed trading; institutional investors; Market Efficiency; Short selling; Strategic traders
    JEL: G30 M41
    Date: 2019–06
  4. By: Jin, Dunhong; Kacperczyk, Marcin; Kahraman, Bige; Suntheim, Felix
    Abstract: How to prevent runs on open-end mutual funds? In recent years, markets have observed an innovation that changed the way open-end funds are priced. Alternative pricing rules (known as swing pricing) adjust funds' net asset values to pass on funds' trading costs to transacting shareholders. Using unique data on investor transactions in U.K. corporate bond funds, we show that swing pricing eliminates the first-mover advantage arising from the traditional pricing rule and significantly reduces redemptions during stress periods. The stabilizing effect is internalized particularly by institutional investors and investors with longer investment horizons. The positive impact of alternative pricing rules on fund flows reverses in calm periods when costs associated with higher tracking error dominate the pricing effect.
    Keywords: fragility; fund runs; liquidity mismatch; strategic complementarity; swing pricing
    JEL: G10 G2 G23
    Date: 2019–08
  5. By: Enno Mammen (University of Heidelberg, Germany); Jens Perch Nielsen (Cass Business School, City, University of London, UK); Michael Scholz (University of Graz, Austria); Stefan Sperlich (Universite de Geneve, Switzerland)
    Abstract: In this paper, we apply machine learning to forecast the conditional variance of long-term stock returns measured in excess of different benchmarks, including the short-term interest rate, long-term interest rate, earnings-by-price ratio, and inflation. In particular, we apply and implement in a two-step procedure a fully nonparametric smoother with the covariates and the smoothing parameters chosen via cross-validation. We find that volatility forecastability is much less important at longer horizons regardless of the chosen model and that the homoscedastic historical average of the squared return prediction errors gives an adequate approximation of the unobserved realized conditional variance for both the one-year and five-year horizon.
    Keywords: Benchmark; Cross-validation; Prediction; Stock return volatility; Long-term forecasts; Overlapping returns; Autocorrelation
    JEL: C14 C53 C58 G17 G22
    Date: 2019–08
  6. By: Oleh Danyliv; Bruce Bland
    Abstract: Working on different aspects of algorithmic trading we empirically discovered a new market invariant. It links together the volatility of the instrument with its traded volume, the average spread and the volume in the order book. The invariant has been tested on different markets and different asset classes. In all cases we did not find significant violation of the invariant. The formula for the invariant was used for the volatility estimation, which we called the instantaneous volatility. Quantitative comparison showed that it reproduces realised volatility better than one-day-ahead GARCH(1,1) prediction. Because of the short-term prediction nature, the instantaneous volatility could be used by algo developers, volatility traders and other market professionals.
    Date: 2019–08
  7. By: Albanesi, Stefania; Vamossy, Domonkos
    Abstract: We develop a model to predict consumer default based on deep learning. We show that the model consistently outperforms standard credit scoring models, even though it uses the same data. Our model is interpretable and is able to provide a score to a larger class of borrowers relative to standard credit scoring models while accurately tracking variations in systemic risk. We argue that these properties can provide valuable insights for the design of policies targeted at reducing consumer default and alleviating its burden on borrowers and lenders, as well as macroprudential regulation.
    Keywords: Consumer default; credit scores; deep learning; macroprudential policy
    JEL: C45 D1 E27 E44 G21 G24
    Date: 2019–08
  8. By: Alex Plastun (Faculty of Economics and Management, Sumy State University, Sumy, Ukraine); Xolani Sibande (Department of Economics, University of Pretoria, Pretoria, South Africa); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa); Mark E. Wohar (College of Business Administration, University of Nebraska; USA. School of Business and Economics, Loughborough University, Leicestershire, LE11 3TU, UK)
    Abstract: This paper analyses the price gap anomaly in the US stock market (comprised of the DJI, S&P 500 and NASDAQ) covering the period 1928 to 2018. This paper aims to investigate whether or not price gaps create market inefficiencies. Price gaps occur when the current day’s opening price is different from the previous day’s closing price due orders placed before the opening of the market. Several hypotheses are tested using various statistical tests (Student’s t-test, ANOVA, Mann-Whitney test), regression analysis, and special methods, that is, the modified cumulative returns and the trading simulation approaches. We find strong evidence in favour of abnormal price movements after price gaps. We observe that during a gap day prices tend to change in the direction of the gap. A trading strategy based on this anomaly was efficient in that its results were not random, indicating that this market was not efficient. The momentum effect was found to be temporary and no evidence of seasonality in price gaps was found. Lastly, our results were also contrary to the myth that price gaps tend to get filled.
    Keywords: Price Gap Anomaly, Trading Strategy, Stock Market, Momentum Effect, Efficient Market Hypothesis
    JEL: G12 C63
    Date: 2019–08
  9. By: Cécile Bastidon; Michael Bordo; Antoine Parent; Marc Weidenmier
    Abstract: We examine equity market integration for 17 countries from 1913-2018. We use network analysis to measure the evolution of global stock market integration as well as stock market integration between and across countries. The empirical results suggest that long-run stock market integration looks like an unstable hook. Equity market integration first peaked in 1913 during the first era of globalization (1870-1913) when unfettered markets ruled the day. Integration declined over the next 60 years as countries experienced the Great Depression and shunned international capital markets. The end of the Bretton Woods system in the early 1970s ushered in the second period of globalization. Our empirical analysis suggests that stock market integration in the recent period of globalization has surpassed the first era of globalization in the last 10 years and currently has the highest level of equity market integration and network instability in world history.
    JEL: C38 F36 G15 N20
    Date: 2019–08
  10. By: Leledakis, George N.; Pyrgiotakis, Emmanouil G.
    Abstract: Using a sample of 312 bank M&As announced between 1998 and 2016 in the EU-27 countries, this paper investigates the impact of market concentration and the European sovereign debt crisis on the way investors react to these corporate events. In Western European countries, we find results which contrast the conventional wisdom that acquiring banks lose around the merger announcement date. In fact, since 2009, acquiring banks shareholders gain approximately $34 million around the announcement, a $56 million improvement compared to the pre-crisis period. These documented shareholder gains are also accompanied by significant improvements in post-merger profitability. Markedly, we link this superior performance of the post-2008 acquirers with the degree of market concentration in the Western European region. Finally, results for the Eastern European countries indicate that the crisis did not have a significant impact on the quality of bank M&As in the region.
    Keywords: European sovereign debt crisis; bank mergers and acquisitions; market concentration; event study
    JEL: G01 G14 G15 G21 G34
    Date: 2019–08–26
  11. By: Giudice, Gabriele; de Manuel Aramendía, Mirzha; Kontolemis, Zenon; Monteiro, Daniel P.
    Abstract: This paper expands the growing literature on common safe assets in the context of the euro area financial system by employing credit risk simulation techniques to investigate the properties of different safe asset models and their impact on national bond markets. The paper explores in particular the E-bonds model, whereby a supranational institution would raise funds in the markets and provide bilateral senior loans to Member States corresponding to a fixed proportion of GDP, complementing the issuance of national government bonds, without risks of mutualisation. The main findings are that E-bonds could reach a volume of 15 to 30% of euro area GDP with a high degree of safety while becoming the reference safe asset for the banking sector, capital markets and monetary policy operations in the euro area. As regards the impact on remaining national bonds, such volumes would be consistent with Germany maintaining its top credit rating. The average funding costs of Member States would remain broadly stable, while marginal funding costs would tend to experience limited increases, which should enhance market discipline.
    Keywords: Safe Assets; Eurozone; EMU Deepening; E-bonds; E-bills; SBBS; ESBies; Banking Union; Capital Markets Union; International Role of the Euro; Sovereign Bonds; Eurobills; Blue Bonds; Purple Bonds; Credit Risk
    JEL: E63 F36 G12 H63
    Date: 2019–08–20
  12. By: Bago, Jean-Louis; Souratié, Wamadini M.; Ouédraogo, Moussa; Ouédraogo, Ernest; Dembélé, Alou
    Abstract: We provide new empirical evidence of bubbles timing in the stock market of South Africa. We apply the generalized sup ADF (GSADF) unit root test of Phillips et al. (2015) to monthly share prices from January 1960 to July 2019, to detect explosive behaviors. Results indicate that, overall, South Africa’s stock market has been exuberant during the period 1960-2019. We find strong evidence of three bubble episodes during the periods of April 1968 to July 1969, December 1979 to November 1980 and April 2006 to May 2008 in the stock market of South Africa. The last two bubbles correspond to the 1979 international oil crisis and the 2008 financial crisis suggesting that the south african stock market is still vulnerable to exogenous shocks.
    Keywords: Bubble, Stock market, GSADF test, South Africa
    JEL: G12
    Date: 2019–08
  13. By: Imed Medhioub (Department of Finance and Investment, College of Economics and Administrative Sciences, Imam Muhammad Ibn Saud Islamic University); Mustapha Chaffai (Department of Management, High Business School, Sfax University)
    Abstract: This study examines herding behavior in four sectors of the Gulf Islamic stock markets. Based on the methodology of Chiang and Zheng (2010) and using daily prices for the GCC Islamic sectors from September 2013 to October 2018, results showed evidence of herding among investors in banking, insurance, hotels, restaurants, and foods sectors for the GCC Islamic stock market during the falling period when we consider a quantile regression analysis. In addition, we found that conventional return dispersions have a dominant influence on the Islamic GCC stock market during both falling and rising market periods in all sectors. We also found evidence of herd around the conventional sectors during down market period only in banking, hotel, restaurant, and food sectors. There is evidence of herd around the conventional sector during up market period for insurance and industrial sectors.
    Date: 2019–08–21

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