nep-fmk New Economics Papers
on Financial Markets
Issue of 2019‒03‒04
seven papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Discovering Language of the Stocks By Marko Po\v{z}enel; Dejan Lavbi\v{c}
  2. An Economic Examination of Collateralization in Different Financial Markets By Tim Xiao
  3. How much capital does a bank need: A few points regarding the Basel accord By Nizam, Ahmed Mehedi
  4. Q-Gaussian diffusion in stock markets By Alonso-Marroquin Fernando; Arias-Calluari Karina; Harre Michael; Najafi Morteza N.; Herrmann Hans J
  5. Global Stock Market Prediction Based on Stock Chart Images Using Deep Q-Network By Jinho Lee; Raehyun Kim; Yookyung Koh; Jaewoo Kang
  6. The long and short of it: the post-crisis corporate CDS market By Boyarchenko, Nina; Costello, Anna M.; Shachar, Or
  7. Does the composition of government expenditures matter for sovereign bond spreads' evolution in developing countries? By Jean-Louis Combes; Alexandru Minea; Pegdéwendé Nestor Sawadogo

  1. By: Marko Po\v{z}enel; Dejan Lavbi\v{c}
    Abstract: Stock prediction has always been attractive area for researchers and investors since the financial gains can be substantial. However, stock prediction can be a challenging task since stocks are influenced by a multitude of factors whose influence vary rapidly through time. This paper proposes a novel approach (Word2Vec) for stock trend prediction combining NLP and Japanese candlesticks. First, we create a simple language of Japanese candlesticks from the source OHLC data. Then, sentences of words are used to train the NLP Word2Vec model where training data classification also takes into account trading commissions. Finally, the model is used to predict trading actions. The proposed approach was compared to three trading models Buy & Hold, MA and MACD according to the yield achieved. We first evaluated Word2Vec on three shares of Apple, Microsoft and Coca-Cola where it outperformed the comparative models. Next we evaluated Word2Vec on stocks from Russell Top 50 Index where our Word2Vec method was also very successful in test phase and only fall behind the Buy & Hold method in validation phase. Word2Vec achieved positive results in all scenarios while the average yields of MA and MACD were still lower compared to Word2Vec.
    Date: 2019–02
  2. By: Tim Xiao (University of Toronto)
    Abstract: This paper attempts to assess the economic significance and implications of collateralization in different financial markets, which is essentially a matter of theoretical justification and empirical verification. We present a comprehensive theoretical framework that allows for collateralization adhering to bankruptcy laws. As such, the model can back out differences in asset prices due to collateralized counterparty risk. This framework is very useful for pricing outstanding defaultable financial contracts. By using a unique data set, we are able to achieve a clean decomposition of prices into their credit risk factors. We find empirical evidence that counterparty risk is not overly important in credit-related spreads. Only the joint effects of collateralization and credit risk can sufficiently explain unsecured credit costs. This finding suggests that failure to properly account for collateralization may result in significant mispricing of financial contracts. We also analyze the difference between cleared and OTC markets. Acknowledge: The data were provided by FinPricing at Key words: unilateral/bilateral collateralization, partial/full/over collateralization, asset pricing, plumbing of the financial system, swap premium spread, OTC/cleared/listed financial markets.
    Date: 2019–02–18
  3. By: Nizam, Ahmed Mehedi
    Abstract: Basel framework for bank's capital adequacy has been criticized for its over reliance on external credit rating agencies. Moreover, implementation of Minimum Capital Requirement (MCR) under Basel-III is often linked to a decrease in economic growth as it requires banks to maintain a higher capital base which raises their cost of fund. In addition to these, here, we criticize the Basel accord for the capital requirement under this framework is not inspired by the essence of the basic accounting equation. Moreover, under Basel framework, capital requirement and liquidity parameters are discussed separately. Here, we argue that the capital requirement should arise as a by-product of the day to day liquidity management and hence both the requirements can be brought together under one umbrella which enables us to view the overall position of a bank from a more holistic point of view. Here, we attain all the above issues and provide a comprehensive framework regarding bank's capital adequacy and liquidity requirements which is claimed to settle all the aforementioned issues and reduces all the extensive paper works needed for the implementation of the Basel accord.
    Keywords: Basel; Capital Adequacy; Minimum Capital Requirement; MCR; Liquidity Ratio; LCR; NSFR; Liquidity Coverage Ratio; Net Stable Funding Ratio; Banking; Basic Accounting Equation
    JEL: E58 G0 G01 G20 G21 G28
    Date: 2019–02–22
  4. By: Alonso-Marroquin Fernando; Arias-Calluari Karina; Harre Michael; Najafi Morteza N.; Herrmann Hans J
    Abstract: We analyze the Standard & Poor's 500 stock market index from the last 22 years. The probability density function of price returns exhibits two well-distinguished regimes with self-similar structure: the first one displays strong super-diffusion together with short-time correlations, and the second one corresponds to weak super-diffusion with weak time correlations. Both regimes are well-described by q-Gaussian distributions. The porous media equation is used to derive the governing equation for these regimes, and the Black-Scholes diffusion coefficient is explicitly obtained from the governing equation.
    Date: 2019–02
  5. By: Jinho Lee; Raehyun Kim; Yookyung Koh; Jaewoo Kang
    Abstract: We applied Deep Q-Network with a Convolutional Neural Network function approximator, which takes stock chart images as input, for making global stock market predictions. Our model not only yields profit in the stock market of the country where it was trained but generally yields profit in global stock markets. We trained our model only in the US market and tested it in 31 different countries over 12 years. The portfolios constructed based on our model's output generally yield about 0.1 to 1.0 percent return per transaction prior to transaction costs in 31 countries. The results show that there are some patterns on stock chart image, that tend to predict the same future stock price movements across global stock markets. Moreover, the results show that future stock prices can be predicted even if the training and testing procedures are done in different countries. Training procedure could be done in relatively large and liquid markets (e.g., USA) and tested in small markets. This result demonstrates that artificial intelligence based stock price forecasting models can be used in relatively small markets (emerging countries) even though they do not have a sufficient amount of data for training.
    Date: 2019–02
  6. By: Boyarchenko, Nina (Federal Reserve Bank of New York); Costello, Anna M. (University of Michigan, Ross School of Business); Shachar, Or (Federal Reserve Bank of New York)
    Abstract: The 2007-09 financial crisis highlighted the vulnerability of financial institutions linked by a complex web of credit default swap (CDS) contracts, sparking a wave of regulatory changes to the structure of the market. In this paper, we provide broad evidence on the evolution of the CDS market in the post-crisis period, document the properties of participants’ exposures to corporate CDS over time, and study the differential pricing of transactions between different types of counterparties.
    Keywords: CDS positions; CDS transactions; dealer market power
    JEL: G10 G12 G19
    Date: 2019–02–01
  7. By: Jean-Louis Combes (CERDI - Centre d'Études et de Recherches sur le Développement International - Clermont Auvergne - UCA - Université Clermont Auvergne - CNRS - Centre National de la Recherche Scientifique); Alexandru Minea (CERDI - Centre d'Études et de Recherches sur le Développement International - Clermont Auvergne - UCA - Université Clermont Auvergne - CNRS - Centre National de la Recherche Scientifique); Pegdéwendé Nestor Sawadogo (CERDI - Centre d'Études et de Recherches sur le Développement International - Clermont Auvergne - UCA - Université Clermont Auvergne - CNRS - Centre National de la Recherche Scientifique)
    Abstract: This paper evaluates the effects of public expenditures on sovereign bond spreads in emerging market countries. Specifically, the paper explores empirically how country risk, as proxied by sovereign bond spreads, is influenced by the different types of government expenditures (namely current spending, public investments, spending on education, health, social protection, economic affairs and defense) and country-specific fundamentals. Using panel data from emerging market countries, we find that governments can improve their borrowing conditions in international financial markets by heightening public investment and managing their current spending. In accordance with the empirical literature on the determinants of spreads, we find that country-specific fundamentals are also important determinants of spreads. Further, we find evidence that financial markets' reaction to public expenditures depends on government effectiveness.
    Keywords: Government effectiveness,Government expenditures,Sovereign bond spreads,Emerging market
    Date: 2019–02–14

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