nep-fmk New Economics Papers
on Financial Markets
Issue of 2023‒04‒10
nine papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. A Major Shock Makes Prices More Flexible and May Result in a Burst of Inflation or Deflation By Robert E. Hall
  2. DSE Stock Price Prediction using Hidden Markov Model By Raihan Tanvir; Md Tanvir Rouf Shawon; Md. Golam Rabiul Alam
  3. Predicting Stock Price Movement as an Image Classification Problem By Matej Steinbacher
  4. Cryptocurrencies Are Becoming Part of the World Global Financial Market By Marcin W\k{a}torek; Jaros{\l}aw Kwapie\'n; Stanis{\l}aw Dro\.zd\.z
  5. Robust portfolio selection under Recovery Average Value at Risk By Cosimo Munari; Justin Pl\"uckebaum; Stefan Weber
  6. Bayesian Optimization of ESG Financial Investments By Eduardo C. Garrido-Merch\'an; Gabriel Gonz\'alez Piris; Maria Coronado Vaca
  7. The Internationalization of China’s Equity Markets By Mr. Maria Soledad Martinez Peria; Mr. Sergio L. Schmukler; Jasmine Xiao; Juan J. Cortina
  8. Value Premium in Japanese Market: Statistical (Re)appraisa By Leonardo Cadamuro; Tokuo Iwaisako
  9. The Stock Price Relationship between Holding Companies and Subsidiaries: A Case study of Indonesia Multiholding Companies By Muhammad Aufaristama

  1. By: Robert E. Hall
    Abstract: The US and other advanced countries suffered bursts of severe inflation in 2021 and the first half of 2022, followed by declines of inflation later in 2022, in some countries. In times of high volatility of price determinants—cost and productivity—inflation can jump upward and fall downward at high speed, contrary to the uniformly sticky behavior associated with traditional Phillips curves. This paper establishes that sectors with standard New Keynesian price stickiness are vulnerable to rapid transitions from stickiness to flexibility, as sellers elect to reset their prices and abandon anchoring. The paper shows that the cross-industry volatility of price determinants grew substantially in the inflation episode accompanying the pandemic. Volatility remained elevated even in late 2022. The logic of the New Keynesian model of the Phillips curve links inflation to volatility, because a larger fraction of sellers are pushed out of their regions of inaction when volatility is elevated. The New Keynesian Phillips curve becomes much steeper in volatile times.
    JEL: E31 E42 E44
    Date: 2023–03
  2. By: Raihan Tanvir; Md Tanvir Rouf Shawon; Md. Golam Rabiul Alam
    Abstract: Stock market forecasting is a classic problem that has been thoroughly investigated using machine learning and artificial neural network based tools and techniques. Interesting aspects of this problem include its time reliance as well as its volatility and other complex relationships. To combine them, hidden markov models (HMMs) have been utilized to anticipate the price of stocks. We demonstrated the Maximum A Posteriori (MAP) HMM method for predicting stock prices for the next day based on previous data. An HMM is trained by analyzing the fractional change in the stock price as well as the intraday high and low values. It is then utilized to produce a MAP estimate across all possible stock prices for the next day. The approach demonstrated in our work is quite generalized and can be used to predict the stock price for any company, given that the HMM is trained on the dataset of that company's stocks dataset. We evaluated the accuracy of our models using some extensively used accuracy metrics for regression problems and came up with a satisfactory outcome.
    Date: 2023–01
  3. By: Matej Steinbacher
    Abstract: The paper studies intraday price movement of stocks that is considered as an image classification problem. Using a CNN-based model we make a compelling case for the high-level relationship between the first hour of trading and the close. The algorithm managed to adequately separate between the two opposing classes and investing according to the algorithm's predictions outperformed all alternative constructs but the theoretical maximum. To support the thesis, we ran several additional tests. The findings in the paper highlight the suitability of computer vision techniques for studying financial markets and in particular prediction of stock price movements.
    Date: 2023–03
  4. By: Marcin W\k{a}torek; Jaros{\l}aw Kwapie\'n; Stanis{\l}aw Dro\.zd\.z
    Abstract: In this study the cross-correlations between the cryptocurrency market represented by the two most liquid and highest-capitalized cryptocurrencies: bitcoin and ethereum, on the one side, and the instruments representing the traditional financial markets: stock indices, Forex, commodities, on the other side, are measured in the period: January 2020--October 2022. Our purpose is to address the question whether the cryptocurrency market still preserves its autonomy with respect to the traditional financial markets or it has already aligned with them in expense of its independence. We are motivated by the fact that some previous related studies gave mixed results. By calculating the $q$-dependent detrended cross-correlation coefficient based on the high frequency 10 s data in the rolling window, the dependence on various time scales, different fluctuation magnitudes, and different market periods are examined. There is a strong indication that the dynamics of the bitcoin and ethereum price changes since the March 2020 Covid-19 panic is no longer independent. Instead, it is related to the dynamics of the traditional financial markets, which is especially evident now in 2022, when the bitcoin and ethereum coupling to the US tech stocks is observed during the market bear phase. It is also worth emphasizing that the cryptocurrencies have begun to react to the economic data such as the Consumer Price Index readings in a similar way as traditional instruments. Such a spontaneous coupling of the so far independent degrees of freedom can be interpreted as a kind of phase transition that resembles the collective phenomena typical for the complex systems. Our results indicate that the cryptocurrencies cannot be considered as a safe haven for the financial investments.
    Date: 2023–02
  5. By: Cosimo Munari; Justin Pl\"uckebaum; Stefan Weber
    Abstract: We study mean-risk optimal portfolio problems where risk is measured by Recovery Average Value at Risk, a prominent example in the class of recovery risk measures. We establish existence results in the situation where the joint distribution of portfolio assets is known as well as in the situation where it is uncertain and only assumed to belong to a set of mixtures of benchmark distributions (mixture uncertainty) or to a cloud around a benchmark distribution (box uncertainty). The comparison with the classical Average Value at Risk shows that portfolio selection under its recovery version enables financial institutions to exert better control on the recovery on liabilities while still allowing for tractable computations.
    Date: 2023–03
  6. By: Eduardo C. Garrido-Merch\'an; Gabriel Gonz\'alez Piris; Maria Coronado Vaca
    Abstract: Financial experts and analysts seek to predict the variability of financial markets. In particular, the correct prediction of this variability ensures investors successful investments. However, there has been a big trend in finance in the last years, which are the ESG criteria. Concretely, ESG (Economic, Social and Governance) criteria have become more significant in finance due to the growing importance of investments being socially responsible, and because of the financial impact companies suffer when not complying with them. Consequently, creating a stock portfolio should not only take into account its performance but compliance with ESG criteria. Hence, this paper combines mathematical modelling, with ESG and finance. In more detail, we use Bayesian optimization (BO), a sequential state-of-the-art design strategy to optimize black-boxes with unknown analytical and costly-to compute expressions, to maximize the performance of a stock portfolio under the presence of ESG criteria soft constraints incorporated to the objective function. In an illustrative experiment, we use the Sharpe ratio, that takes into consideration the portfolio returns and its variance, in other words, it balances the trade-off between maximizing returns and minimizing risks. In the present work, ESG criteria have been divided into fourteen independent categories used in a linear combination to estimate a firm total ESG score. Most importantly, our presented approach would scale to alternative black-box methods of estimating the performance and ESG compliance of the stock portfolio. In particular, this research has opened the door to many new research lines, as it has proved that a portfolio can be optimized using a BO that takes into consideration financial performance and the accomplishment of ESG criteria.
    Date: 2023–02
  7. By: Mr. Maria Soledad Martinez Peria; Mr. Sergio L. Schmukler; Jasmine Xiao; Juan J. Cortina
    Abstract: China’s equity markets internationalization process started in the early 2000s but accelerated after 2012, when Chinese firms’ shares listed in Shanghai and Shenzhen gradually became available to international investors. This paper studies the effects of the post-2012 internationalization events by comparing the evolution of equity financing and investment activities for: (i) domestic listed firms relative to firms that already had access to international investors and (ii) domestic listed firms that were directly connected to international markets relative to those that were not. The paper finds large increases in financial and investment activities for domestic listed and for connected firms, with significant aggregate effects. The evidence also suggests the rise in firms’ equity issuances was primarily and initially financed by domestic investors. International investors’ portfolio holdings in Chinese equity markets and ownership in firms increased markedly only once Chinese firms’ locally issued shares became part of the MSCI Emerging Markets Index.
    Keywords: equity financing; equity market liberalization; firm investment; foreign investors; international investors; issuance activity; Stock Connect; portfolio holding; internationalization process; unconnected firm; China's equity markets; Stock markets; Stocks; Foreign corporations; Emerging and frontier financial markets; Market capitalization; Global
    Date: 2023–02–10
  8. By: Leonardo Cadamuro; Tokuo Iwaisako
    Abstract: This paper examines the recent decline of the value premium in the Japanese market since the late 2000s, and discuss similarities and differences between the Japanese and US markets. We adopt the analytical framework of Fama and French (2021) using predictive regression with the book-to-market (BM) ratio and the framework by Arnott et al. (2021) based on the return decomposition of HML returns. The level and volatility of the Japanese BM ratio significantly changed toward the end of 1990s; thus, careful consideration in splitting the sample periods is needed in examining the predicting ability of BM ratio about the portfolio returns sorted by the firm size and BM ratio. We find the predictable component of Japanese HML returns is relatively stable over time, and the recent decline in HML returns is mostly explained by the unpredictable decline in the valuation of value stocks relative to growth stocks after the Global Financial Crisis in the late 2000s. This is consistent with the results reported in existing studies on the US market. The evidence provided by the decomposition of HML returns also supports the findings of this study¡Çs analysis.
    Date: 2023–03
  9. By: Muhammad Aufaristama
    Abstract: This study aimed to examine the correlation between the stock prices of two major Indonesian holding companies, MNC Group and Elang Mahkota Teknologi (Emtek) Group, and their respective subsidiaries as case studies. The data for the analysis were collected from 2013 to 2022, and Spearman correlation was used to determine the strength and direction of the relationship between the stock prices of the holding companies and their subsidiaries. The results of the analysis revealed that there were varying degrees of correlation between the stock prices of the holding companies and their subsidiaries. The strongest positive correlation was observed between BHIT and BMTR, while the weakest correlations were found between BHIT and IPTV, and BHIT and MSIN. The correlations were also found to have changed over time, possibly due to market conditions, company-specific events, or changes in industry sectors.In the case of Emtek Group, the analysis suggested that EMTK's stock price movements had a significant impact on the stock prices of its subsidiaries, with varying strengths of relationships. The negative correlation between EMTK and SCMA over the entire period suggested an inverse relationship, while positive correlations with BUKA, AMOR, BBHI, and RSGK indicated a tendency to move in the same direction as EMTK's stock price. The correlations were found to have increased over time, possibly due to market conditions and EMTK's ownership stake in these companies. Overall, the findings of this study suggest that there is a complex interplay between the stock prices of parent companies and their subsidiaries, and that there are a variety of factors that can influence these relationships over time. These findings may be useful for investors in making informed decisions about their investment portfolios, as changes in the correlations could impact their portfolio's performance.
    Date: 2023–03

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