nep-fmk New Economics Papers
on Financial Markets
Issue of 2019‒01‒14
nine papers chosen by

  1. Predicting the Stock Price of Frontier Markets Using Modified Black-Scholes Option Pricing Model and Machine Learning By Reaz Chowdhury; M. R. C. Mahdy; Tanisha Nourin Alam; Golam Dastegir Al Quaderi
  2. Multimodal deep learning for short-term stock volatility prediction By Marcelo Sardelich; Suresh Manandhar
  3. Annual report "Graphicity" and stock returns By Deng, Xiaohu; Gao, Lei;
  4. Three-Factor and Five-Factor Models: Implementation of Fama and French Model on Market Overreaction Conditions By Ferikawita M. Sembiring
  5. Are the Credit Rating Agencies Biased Against MENA Countries? By A. Talha Yalta; Yasemin Yalta
  6. Determinants of Capital Flows in the Korean Bond Market By Soohyon Kim
  7. Equity Analysis in Buying Company Shares on the Philippine Stock Exchange By Prince T. Medina
  8. Dynamic return and volatility spillovers among S&P 500, crude oil and gold By Mehmet Balcilar; Zeynel Abidin Ozdemir; Huseyin Ozdemir
  9. Time-varying Response of Treasury Yields to Monetary Policy Shocks: Evidence from the Tunisian Bond Market By Lassaâd Mbarek; Hardik A. Marfatia; Sonja Juko

  1. By: Reaz Chowdhury; M. R. C. Mahdy; Tanisha Nourin Alam; Golam Dastegir Al Quaderi
    Abstract: The Black-Scholes Option pricing model (BSOPM) has long been in use for valuation of equity options to find the prices of stocks. In this work, using BSOPM, we have come up with a comparative analytical approach and numerical technique to find the price of call option and put option and considered these two prices as buying price and selling price of stocks of frontier markets so that we can predict the stock price (close price). Changes have been made to the model to find the parameters strike price and the time of expiration for calculating stock price of frontier markets. To verify the result obtained using modified BSOPM we have used machine learning approach using the software Rapidminer, where we have adopted different algorithms like the decision tree, ensemble learning method and neural network. It has been observed that, the prediction of close price using machine learning is very similar to the one obtained using BSOPM. Machine learning approach stands out to be a better predictor over BSOPM, because Black-Scholes-Merton equation includes risk and dividend parameter, which changes continuously. We have also numerically calculated volatility. As the prices of the stocks goes high due to overpricing, volatility increases at a tremendous rate and when volatility becomes very high market tends to fall, which can be observed and determined using our modified BSOPM. The proposed modified BSOPM has also been explained based on the analogy of Schrodinger equation (and heat equation) of quantum physics.
    Date: 2018–12
  2. By: Marcelo Sardelich; Suresh Manandhar
    Abstract: Stock market volatility forecasting is a task relevant to assessing market risk. We investigate the interaction between news and prices for the one-day-ahead volatility prediction using state-of-the-art deep learning approaches. The proposed models are trained either end-to-end or using sentence encoders transfered from other tasks. We evaluate a broad range of stock market sectors, namely Consumer Staples, Energy, Utilities, Heathcare, and Financials. Our experimental results show that adding news improves the volatility forecasting as compared to the mainstream models that rely only on price data. In particular, our model outperforms the widely-recognized GARCH(1,1) model for all sectors in terms of coefficient of determination $R^2$, $MSE$ and $MAE$, achieving the best performance when training from both news and price data.
    Date: 2018–12
  3. By: Deng, Xiaohu (Tasmanian School of Business & Economics, University of Tasmania); Gao, Lei (Iowa State University, College of Business, Finance); (Tasmanian School of Business & Economics, University of Tasmania)
    Abstract: Prior literature finds information content in the text of 10-K filings. Using a large hand collected dataset, we provide the novel evidence on the additional information embedded in the designs and graphs of financial reports. We find that firms with lower accruals, larger size, and higher Fog index tend to add graphic information to the standard financial reports in addition to SEC standard 10-Ks. Interestingly, we find that firms who added graphic financial reports experienced a positive 2.7% abnormal returns after the graphic financial reports is released for 3 to 6 months. The finding remains robust after controlling for financial market constraints, investor sophistication, and information asymmetry. Further tests suggest that the new graphic information is additional soft information that the companies try to deliver, rather than “hardening” the existing numbers in the 10-Ks. This result suggests that corporate insiders try to employ better designed financial reports to deliver important soft information about their fundamentals, and it is still a challenge for the market to integrate the additional information in the graphic financial reports to stock prices timely and accurately.
    Keywords: graphic financial reports, reporting format change, soft information, anomaly
    Date: 2018
  4. By: Ferikawita M. Sembiring (Jenderal Achmad Yani University, Bandung Indonesia Author-2-Name: Author-2-Workplace-Name: Author-3-Name: Author-3-Workplace-Name: Author-4-Name: Author-4-Workplace-Name: Author-5-Name: Author-5-Workplace-Name: Author-6-Name: Author-6-Workplace-Name: Author-7-Name: Author-7-Workplace-Name: Author-8-Name: Author-8-Workplace-Name:)
    Abstract: Objective - Previous research by this author has stated that the market overreaction phenomenon occurs in the Indonesian capital market and the CAPM (Capital Asset Pricing Model) is able to explain portfolio returns. However, CAPM is still debated along with the emergence of the other asset pricing models, such as the multifactor model proposed by Fama and French. The aim of this research is to test the ability of that model to explain the returns of portfolios formed under market overreaction conditions. Methodology/Technique - The data used in this study is the same as that of the previous research, which includes winner and loser portfolio data formed in market overreaction conditions, particularly on the Indonesian Stock Exchange, between July 2005 and December 2015. The multifactor models used include a three-factor model consisting of the factors of market, firm size, firm value, and a five-factor model with the added factors of profitability and investment. To obtain more accurate results, GARCH econometric models were also used in addition to standard test models for obtaining unbiased results. Findings - This research concludes that market factors (Rm-Rf), firm size (SMB), and firm value (HML), are able to explain the winner and loser portfolio returns well. However, when the factors of profitability (RMW) and investment (CMA) are added into the three-factor model, the RMW and CMA explained the returns negatively and inconsistently when the GARCH model is implemented. Novelty – These results imply that the three-factor model is more accurate than the five-factor model, contrary to the previous findings of Fama and French.
    Keywords: Fama and French Model; Five-factor Model; Market Overreaction; Three-factor Model; Portfolio.
    JEL: G11 G12 G14
    Date: 2018–12–11
  5. By: A. Talha Yalta (TOBB University of Economics and Technology); Yasemin Yalta
    Abstract: We investigate the claims on regional biases in the sovereign credit ratings assigned by Fitch Ratings, Moody’s and Standard & Poor’s credit rating agencies (CRAs) for a group of 99 countries by using a series of econometric models that consider a wide range of macroeconomic, financial, institutional, regional and geopolitical indicators. Our empirical results based on the seemingly unrelated regressions (SUR) estimates indicate a strong home country bias towards the United States while there seems to be no special biases against individual group of countries such as the Middle East and North Africa (MENA) countries. We also demonstrate how modeling errors in the form of omitted variables can easily cause misleading results portraying the CRAs as biased towards or against different country groups.
    Date: 2018–12–19
  6. By: Soohyon Kim (Economic Research Institute, The Bank of Korea)
    Abstract: This study shows that interest rate differentials have minor impacts on overall capital flows into the Korean bond market. They are significant factors for private bank capital, however only for short-term interest rates, which takes up ignorable amounts in total capital balances. The most impressive factor is the foreign currency reserves owned by major central banks; these are particularly influential to capital flows throughout the sectors. Global and local risk indicators can also explain the variation of capital flows by sector. The underlying reasons behind these findings are as follows: changes in the proportions of sectoral capital balances after the global financial crisis, introduction of regulations on leverage ratios for international banks, risk management by investors, and increasing flows from foreign currency reserves of major central banks.
    Keywords: Capital flows, Bond market, Interest rate differentials, Foreign currency reserves
    JEL: C22 E44
    Date: 2018–12–20
  7. By: Prince T. Medina (The Graduate School, University of Santo Tomas, España Boulevard, 1015 Manila, Philippines Author-2-Name: Mary Caroline N. Castaño Author-2-Workplace-Name: Graduate School Student, University of Santo Tomas, Philippines Author-3-Name: Tomas S. Tiu Author-3-Workplace-Name: Graduate School Student, University of Santo Tomas, Philippines Author-4-Name: Author-4-Workplace-Name: Author-5-Name: Author-5-Workplace-Name: Author-6-Name: Author-6-Workplace-Name: Author-7-Name: Author-7-Workplace-Name: Author-8-Name: Author-8-Workplace-Name:)
    Abstract: Objective - Less than 1% of the population in the Philippines has invested in the stock market (PSE, 2016). The Philippine Stock Exchange (PSE) has been in operation since 1927 and is one of the oldest in the Asia Pacific. The primary objective of this research is to examine the investing techniques of online users using technical and fundamental analysis. Methodology/Technique - A chi-square test is used to determine if there is a significant difference between the expected frequencies and the observed frequencies in one or more categories. The research probes the relationship of the demographic profiles of respondents and their investment behavior using the Friedman's test. Findings - The descriptive statistics show the frequency counts of 418 observations and the corresponding chi-square test for the distribution-free data. The analysis of variance by ranks was used to reflect the Friedman test for the hierarchy of perception of the respondents per given variable. The chi-square test (?2 (df = 4, ? = 0.001) = 53.603) shows that actual observations on the relative valuation (86, 48, 130, 99, and 55) is significantly different from a uniform fit of 84 observations at 4 degrees of freedom and 5% level of significance. Novelty – Hence, the study concluded that investors prefer a relative valuation equity selection strategy using fundamental analysis. Furthermore, the study concludes that the moving average (36, 11, 80, 95 and 196) is preferred by investors using technical analysis.
    Keywords: Fundamental Analysis; Technical Analysis; Investment Behavior; Philippine Stock Exchange; Relative Valuation; Moving Average.
    JEL: G10 G14 G19
    Date: 2018–12–06
  8. By: Mehmet Balcilar (Department of Economics, Eastern Mediterranean University); Zeynel Abidin Ozdemir (Gazi University, Ankara, Turkey); Huseyin Ozdemir (Gazi University, Ankara, Turkey)
    Abstract: This paper examines the return and volatility spillover effects among S&P 500, crude oil and gold by employing the spillover index of Diebold and Yilmaz (2012). Monthly realized volatility and return series covering the period from January 1986 to August 2018 are used to examine the return and volatility spillovers. Our findings indicate a bi-directional return and volatility spillover among these assets. The full sample empirical evidence is consistent with the structure in which oil plays a central role in the information transmission mechanism. The role of oil and gold as a safe haven has changed over time in financial and non-financial economic turbulence time-span. Commodity market financialization has decreased the effectiveness of adding commodities to portfolios after 2002.
    Keywords: S&P 500 index; Oil price; Gold Price; Return spillover; Volatility spillover
    JEL: C13 C53 C58 G10 G12 G14 Q43
    Date: 2018
  9. By: Lassaâd Mbarek (Central Bank of Tunisia); Hardik A. Marfatia; Sonja Juko
    Abstract: This paper examines the Treasury bond yields response to monetary policy shocks in Tunisia under a heterogeneous economic environment. Using a traditional fixed coefficient model, we first estimate the impact of monetary policy changes on the term structure of interest rates for the whole period from January 2006 to December 2016. We then study the stability of this relationship by distinguishing two sub-periods around the revolution of January 2011. To investigate how the relationship between the monetary policy and the Treasury yield curve evolves over time, we estimate a time-varying parameter model. The results show that the impact of monetary policy is more pronounced at the short end of the yield curve relative to the longer end. Further, this impact declined significantly across all maturities following the revolution and exhibits wide time variation. This evidence supports the negative influence of high levels of uncertainty on monetary policy effectiveness and highlights the desirability of more active monetary policy especially in turbulent environment
    Date: 2018–10–23

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