nep-fmk New Economics Papers
on Financial Markets
Issue of 2019‒06‒17
seven papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Nominal Stock Price Anchors: A Global Phenomenon? By Kee-Hong Bae; Utpal Bhattacharya; Jisok Kang; S. Ghon Rhee
  2. Can ETFs contribute to systemic risk? By Pagano, Marco; Sánchez Serrano, Antonio; Zechner, Jozef
  3. Investment Ranking Challenge: Identifying the best performing stocks based on their semi-annual returns By Shanka Subhra Mondal; Sharada Prasanna Mohanty; Benjamin Harlander; Mehmet Koseoglu; Lance Rane; Kirill Romanov; Wei-Kai Liu; Pranoot Hatwar; Marcel Salathe; Joe Byrum
  4. Implied and Realized Volatility: A Study of Distributions and the Distribution of Difference By M. Dashti Moghaddam; Jiong Liu; R. A. Serota
  5. Portfolio diversification based on ratios of risk measures By Mathias Barkhagen; Brian Fleming; Sergio Garcia Quiles; Jacek Gondzio; Jens Kroeske; Sotirios Sabanis; Arne Staal
  6. Stock Market Volatility Analysis using GARCH Family Models: Evidence from Zimbabwe Stock Exchange By Bonga, Wellington Garikai
  7. The Japanese corporate board network By Raddant, Matthias; Takahashi, Hiroshi

  1. By: Kee-Hong Bae (Schulich School of Business, York University, North York, Ontario, Canada, M3J 1P3); Utpal Bhattacharya (Institute for Emerging Market Studies, Hong Kong University of Science and Technology); Jisok Kang (Cambridge Endowment for Research in Finance, Judge Business School, University of Cambridge, Cambridge, United Kingdom, CB2 1AG); S. Ghon Rhee (Financial Economics and Institutions Department, University of Hawaii at Manoa, Shidler College of Business, Honolulu, HI 96822, USA)
    Abstract: Weld, Michaely, Thaler, and Benartzi (2009) find that the average nominal U.S. stock price has been approximately $25 since the Great Depression. They report that this ânominal price fixation is primarily a U.S. or North American phenomenon.â Using a larger data set from 38 countries, we show that this nominal price fixation is a global phenomenon. We exploit the introduction of the Euro in 1999 to show that stock splits maintain these nominal stock price anchors. Generally, firms in countries with larger drops in nominal prices had fewer stock splits after stock prices are displayed in Euros.
    Date: 2019–05
  2. By: Pagano, Marco; Sánchez Serrano, Antonio; Zechner, Jozef
    Date: 2019–06
  3. By: Shanka Subhra Mondal; Sharada Prasanna Mohanty; Benjamin Harlander; Mehmet Koseoglu; Lance Rane; Kirill Romanov; Wei-Kai Liu; Pranoot Hatwar; Marcel Salathe; Joe Byrum
    Abstract: In the IEEE Investment ranking challenge 2018, participants were asked to build a model which would identify the best performing stocks based on their returns over a forward six months window. Anonymized financial predictors and semi-annual returns were provided for a group of anonymized stocks from 1996 to 2017, which were divided into 42 non-overlapping six months period. The second half of 2017 was used as an out-of-sample test of the model's performance. Metrics used were Spearman's Rank Correlation Coefficient and Normalized Discounted Cumulative Gain (NDCG) of the top 20% of a model's predicted rankings. The top six participants were invited to describe their approach. The solutions used were varied and were based on selecting a subset of data to train, combination of deep and shallow neural networks, different boosting algorithms, different models with different sets of features, linear support vector machine, combination of convoltional neural network (CNN) and Long short term memory (LSTM).
    Date: 2019–06
  4. By: M. Dashti Moghaddam; Jiong Liu; R. A. Serota
    Abstract: We study distributions of realized variance (squared realized volatility) and squared implied volatility, as represented by VIX and VXO indices. We find that Generalized Beta distribution provide the best fits. These fits are much more accurate for realized variance than for squared VIX and VXO -- possibly another indicator that the latter have deficiencies in predicting the former. We also show that there are noticeable differences between the distributions of the 1970-2017 realized variance and its 1990-2017 portion, for which VIX and VXO became available. This may be indicative of a feedback effect that implied volatility has on realized volatility. We also discuss the distribution of the difference between squared implied volatility and realized variance and show that, at the basic level, it is consistent with Pearson's correlations obtained from linear regression.
    Date: 2019–06
  5. By: Mathias Barkhagen; Brian Fleming; Sergio Garcia Quiles; Jacek Gondzio; Jens Kroeske; Sotirios Sabanis; Arne Staal
    Abstract: A new framework for portfolio diversification is introduced which goes beyond the classical mean-variance theory and other known portfolio allocation strategies such as risk parity. It is based on a novel concept called portfolio dimensionality and ultimately relies on the minimization of ratios of convex functions. The latter arises naturally due to our requirements that diversification measures should be leverage invariant and related to the tail properties of the distribution of portfolio returns. This paper introduces this new framework and its relationship to standardized higher order moments of portfolio returns. Moreover, it addresses the main drawbacks of standard diversification methodologies which are based primarily on estimates of covariance matrices. Maximizing portfolio dimensionality leads to highly non-trivial optimization problems with objective functions which are typically non-convex with potentially multiple local optima. Two complementary global optimization algorithms are thus presented. For problems of moderate size, a deterministic Branch and Bound algorithm is developed, whereas for problems of larger size a stochastic global optimization algorithm based on Gradient Langevin Dynamics is given. We demonstrate through numerical experiments that the introduced diversification measures possess desired properties as introduced in the portfolio diversification literature.
    Date: 2019–06
  6. By: Bonga, Wellington Garikai
    Abstract: Understanding the pattern of stock market volatility is important to investors as well as for investment policy. Volatility is directly associated with risks and returns, higher the volatility the more financial market is unstable. The volatility of the Zimbabwean stock market is modeled using monthly return series consisting of 109 observations from January 2010 to January 2019. ARCH effects test confirmed the use of GARCH family models. Symmetric and asymmetric models were used namely: GARCH(1,1), GARCH-M(1,1), IGARCH(1,1) and EGARCH(1,1). Post-estimation test for further ARCH effects were done for each model to confirm its efficiency for policy. EGARCH(1,1) turned to be the best model using both the AIC and SIC criterions; with the presence of asymmetry found to be significant. The study concludes that positive and negative shocks have different effects on the stock market returns series. Bad and good news will increase volatility of stock market returns in different magnitude. This simply imply that investors on the Zimbabwean stock exchange react differently to information depending be it positive or negative in making investment decisions.
    Keywords: Stock Market, Volatility, ARCH, GARCH, IGARCH, GARCH-M, EGARCH, Risk Premium, Zimbabwe
    JEL: C22 C58 D81 D82 E22 E44 E47 G02 G14 G15 N27 O16 R53
    Date: 2019–05–30
  7. By: Raddant, Matthias; Takahashi, Hiroshi
    Abstract: We analyze the dynamics of the Japanese board network from 2004 until 2013. We find that the network exhibits some clustering with visible firm conglomerates. Ties between firms are rather persistent, despite noticeable churning among directors. Ownership relations explain only a small fraction of board links. Besides densely connected conglomerates, some tendency of within-sector linkages and linkages to financial institutions can be confirmed. We further investigate the increase in the number of outside directors and find that sectoral differences as well as shareholder characteristics explain to large extend the variation in board composition. The connectivity of firms in the ownership and board network is sometimes related to firm profitability. Firms that are linked to peers with above average profitability are likely also more profitable than firms in other ownership relationships.
    Keywords: corporate board interlock,corporate governance,board composition
    JEL: L14 M12 G32
    Date: 2019

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