nep-fmk New Economics Papers
on Financial Markets
Issue of 2019‒07‒29
thirteen papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Deep Reinforcement Learning in Financial Markets By Souradeep Chakraborty
  2. Power generation portfolios: A parametric formulation of the efficient frontier By Juárez-Luna, David
  3. Securitization Structures and Security Design By Gauthier, Laurent
  4. Multi-Level Order-Flow Imbalance in a Limit Order Book By Ke Xu; Martin D. Gould; Sam D. Howison
  5. Is the financial system sufficiently resilient: a research programme and policy agenda By Paul Tucker
  6. 125 Years of Time-Varying Effects of Fiscal Policy on Financial Markets By Hardik A. Marfatia; Rangan Gupta; Stephen M. Miller
  7. Foreign Direct Investment as a Determinant of Cross-Country Stock~Market Comovement By Alexis Anagnostopoulos; Orhan Erem Atesagaoglu; Elisa Faraglia; Chryssi Giannitsarou
  8. Forecasting Local Currency Bond Risk Premia of Emerging Markets: The Role of Cross-Country Macro-Financial Linkages By Oguzhan Cepni; Rangan Gupta; I. Ethem Guney; M. Hasan Yilmaz
  9. Nonlinear price dynamics of S&P 100 stocks By Gunduz Caginalp; Mark DeSantis
  10. Study of the dynamic of Bitcoin's price By Julien Chevallier; Stéphane Goutte; Khaled Guesmi; Samir Saadi
  11. A Microstructure Study of Circuit Breakers in the Chinese Stock Markets By Steven Shuye Wang; Kuan Xu; Hao Zhang
  12. Volatility in the Cryptocurrency Market By Apostolos Serletis; Jinan Liu
  13. Do Stock Markets Lead or Lag Macroeconomic Variables? Evidence from Select European Countries By Silvio John, Camilleri; Nicolanne, Scicluna; Ye, Bai

  1. By: Souradeep Chakraborty
    Abstract: In this paper we explore the usage of deep reinforcement learning algorithms to automatically generate consistently profitable, robust, uncorrelated trading signals in any general financial market. In order to do this, we present a novel Markov decision process (MDP) model to capture the financial trading markets. We review and propose various modifications to existing approaches and explore different techniques to succinctly capture the market dynamics to model the markets. We then go on to use deep reinforcement learning to enable the agent (the algorithm) to learn how to take profitable trades in any market on its own, while suggesting various methodology changes and leveraging the unique representation of the FMDP (financial MDP) to tackle the primary challenges faced in similar works. Through our experimentation results, we go on to show that our model could be easily extended to two very different financial markets and generates a positively robust performance in all conducted experiments.
    Date: 2019–07
  2. By: Juárez-Luna, David
    Abstract: The Portfolio Theory has been extensively used as a planning tool for power generation diversification. However, no one of the existing papers provide a detailed explanation on how the efficient frontier of the Power Generation Portfolio (PGP) is costructed. We provide a parametric formulation of the efficient frontier of PGP of up to 5 technologies. The analysys takes advantages of the fact that the risk of the PGP is a convex function of the shares of the different technologies. The parametric formulation of the efficient frontier of the PGP constitutes a powerfull policy tool for power generation policy-makers.
    Keywords: Portfolio, Power Generation, Efficient Frontier, Risk, NPV.
    JEL: D81 G11 Q40 Q49
    Date: 2019–07–02
  3. By: Gauthier, Laurent
    Abstract: Securitization has been a subject of interest in the security design literature, and various models have been developed in order to explain why such transactions should produce senior securities and junior securities. However securitization structures are far more complex than a simple tranching by seniority. Using a model extending the existing literature, we derive new results by considering that interest and principal should be separately contractible, and that the senior bonds in a securitization should be par-priced, both realistic constraints. This allows us to derive optimal designs closely resembling actual securitization structures. Further, we show that the resecuritization of residuals, in the form of NIMs or reremics, is optimal through a pooling effect. We also analyze the interactions between collateral characteristics and pricing, reflecting securitization execution, and issuer structure choices. With a simple numerical application, we illustrate how important resecuritization is, and also how more attractive an excess-spread structure is relative to a more standard structure, as expected collateral losses increase. According to our analysis, the apparent complexity in excess-spread structure and in resecuritizations can be explained by a valid optimal design argument.
    Keywords: Securitization, security design, excess-spread, resecuritization
    JEL: G12 G21
    Date: 2019–07–15
  4. By: Ke Xu; Martin D. Gould; Sam D. Howison
    Abstract: We study the \emph{multi-level order-flow imbalance (MLOFI)}, which measures the net flow of buy and sell orders at different price levels in a limit order book (LOB). Using a recent, high-quality data set for 6 liquid stocks on Nasdaq, we use Ridge regression to fit a simple, linear relationship between MLOFI and the contemporaneous change in mid-price. For all 6 stocks that we study, we find that the goodness-of-fit of the relationship improves with each additional price level that we include in the MLOFI vector. Our results underline how the complex order-flow activity deep into the LOB can influence the price-formation process.
    Date: 2019–07
  5. By: Paul Tucker
    Abstract: The paper discusses why the financial system is not as resilient as policymakers currently claim - despite extensive regulatory reforms from a very weak starting point.The paper discusses different policy strategies for making some of the debt of some banks "information-insensitive", so that they it would be treated as safe in all but the most stressed circumstances. For the current prudential strategy, which is centred on minimum equity requirements, the paper argues that central banks and other agencies should start publishing annual staff reports on where regulatory and supervisory policy has been surreptitiously tightened or loosened.The paper aims to spark and contribute to the debate on the second phase of stability reforms that will be needed. It sets out an alternative policy strategy based on 100% liquidity cover for the short-term debt of banks (and shadow banks), and for the creditor hierarchy of operating banks and holding companies. In this proposal, the haircut policy of central banks would become the key instrument in determining bank equity requirements and the terms on which they could borrow in secured money markets. As such, this strategy would operationalise the theoretical and empirical work of Bengt Holmström and Gary Gorton.
    Keywords: regulatory reforms, Basel III, great financial crisis
    JEL: E44 E58 G28
    Date: 2019–07
  6. By: Hardik A. Marfatia (Department of Economics, Northeastern Illinois University, BBH 344G, 5500 N. St. Louis Ave., Chicago, IL 60625, USA); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa); Stephen M. Miller (University of Nevada, Las Vegas - Department of Economics, 4505 S. Maryland Parkway, Box 456005, Las Vegas, NV 89154)
    Abstract: This paper examines the effect of fiscal policy on financial markets over a long span of 125 years. Unlike existing studies that mainly focus on monetary policy shocks and model-based identification of fiscal policy shocks, we use a time-varying model to study the effect of fiscal policy with much cleaner and direct identification of fiscal policy shocks. In addition, we extend our analysis by measuring the response volatility in these markets and separately study the effects of good and bad components of volatility. We find significant time-variation in the response of stock and bond market returns and volatility. The overall response of the stock market exceeds that of bond markets, with more pronounced effects in the pre-1950 period than in the last six decades. Fiscal consolidation generates long-term benefits that positively affect financial markets in the latter part of the 20th century, thus providing new insights into the dynamic role of fiscal policy.
    Keywords: Fiscal Policy, Time-Varying impact, Financial returns and risks
    JEL: E5 C32 G14
    Date: 2019–07
  7. By: Alexis Anagnostopoulos; Orhan Erem Atesagaoglu; Elisa Faraglia; Chryssi Giannitsarou
    Abstract: We develop a theoretical framework in order to investigate the link between two recent trends: (i) the rise in cross-country stock market correlations over the past three decades, and (ii) the increase in global foreign direct investment (FDI) positions over the same period. Our objective is twofold: first, we investigate empirically the channel through which the rise in global stock market correlations is associated with the observed increase in global FDI. Second, we develop a two-country stochastic asset pricing model with multinational firms that allows us to quantify the extent to which the recent rise in global FDI can account for the observed increase in cross-country stock market comovement. Calibrating three versions of the model (finnancial autarky, incomplete markets and complete markets) to the US and the rest-of-the-world, we find that a permanent inrcease in FDI positions, as observed from mid 1990s to mid 2000s, leads to substantial increase in cross-country stock market comovements. Increases in FDI alone can account for approximately one third of the observed increase in stock market correlations. We also discuss the role of portfolio diversification and, more generally, asset market integration.
    Date: 2019
  8. By: Oguzhan Cepni (Central Bank of the Republic of Turkey, Haci Bayram Mah. Istiklal Cad. No:10 06050 Ulus, Altndag, Ankara, Turkey); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa); I. Ethem Guney (Central Bank of the Republic of Turkey, Haci Bayram Mah. Istiklal Cad. No:10 06050 Ulus, Altndag, Ankara, Turkey); M. Hasan Yilmaz (Central Bank of the Republic of Turkey, Haci Bayram Mah. Istiklal Cad. No:10 06050 Ulus, Altndag, Ankara, Turkey)
    Abstract: In this paper, we forecast local currency debt of five major emerging market countries (Brazil, Indonesia, Mexico, South Africa, and Turkey) over the period of January 2010 to January 2019 (with an in-sample: March 2005 to December 2018). We exploit information from a large set of economic and financial time series to assess the importance of not only “own-country” factors (derived from principal component and partial least squares approach), but also create “global” predictors by combining the country-specific variables across the five emerging economies. We find that while information on own-country factors can outperform the historical average model, global factors tend to produce not only greater statistical and economic gains, but also enhances market timing ability of investors, especially when we use the target-variable (bond premium) approach under the partial least squares method to extract our factors. Our results have important implications for not only fund managers, but also policymakers.
    Keywords: Bond risk premia, Emerging markets, Factor extraction methods, Out-of-sample forecasting
    JEL: C22 C53 G12
    Date: 2019–07
  9. By: Gunduz Caginalp; Mark DeSantis
    Abstract: The methodology presented provides a quantitative way to characterize investor behavior and price dynamics within a particular asset class and time period. The methodology is applied to a data set consisting of over 250,000 data points of the S&P 100 stocks during 2004-2018. Using a two-way fixed-effects model, we uncover trader motivations including evidence of both under- and overreaction within a unified setting. A nonlinear relationship is found between return and trend suggesting a small, positive trend increases the return, while a larger one tends to decrease it. The shape parameters of the nonlinearity quantify trader motivation to buy into trends or wait for bargains. The methodology allows the testing of any behavioral finance bias or technical analysis concept.
    Date: 2019–07
  10. By: Julien Chevallier (UP8 - Université Paris 8 Vincennes-Saint-Denis); Stéphane Goutte (UP8 - Université Paris 8 Vincennes-Saint-Denis); Khaled Guesmi (IPAG Paris - IPAG Paris); Samir Saadi (École de gestion Telfer / Université d'Ottawa - Université d'Ottawa)
    Abstract: This study contributes to the existing literature on the empirical characteristics of virtual currency allowing for dynamic transition between different economic regimes and considering various crashes and rallies over the business cycle, that are captured by jumps. We combine Markov-switching models with Levy jump-diffusion offer a new model that captures the different sub-period of crises over the business cycle, that are captured by jumps. This method also enables to test the relevance of dynamic measures of regime switching with respect to independent pure-jump process, which are not frequently used in the literature. Bitcoin offer something different than a traditional currency; there is potential value of having a network that helps as a secure repository for the common knowledge of all transactions. In addition, value of bitcoin fluctuates so wildly that it may be too risky to serve as a credible store of value.
    Keywords: Bitcoin,Jump process,Markov-switching model
    Date: 2019–07–05
  11. By: Steven Shuye Wang (School of Business, Renmin University of China); Kuan Xu (Department of Economics, Dalhousie University); Hao Zhang (Gustavson School of Business, University of Victoria)
    Date: 2019–07–22
  12. By: Apostolos Serletis (University of Calgary); Jinan Liu (University of Calgary)
    Abstract: How do cryptocurrency prices evolve? Is there any interdependence among cryptocur- rency returns and/or volatilities? Are there any return spillovers and volatility spillovers between the cryptocurrency market and other financial markets? To answer these questions,we use GARCH-in-mean models to examine the relationship between volatility and returns of leading cryptocurrencies, to investigate spillovers within the cryptocurrency market, and also from the cryptocurrency market to other financial markets. Overall, we find statistically significant transmission of shocks and volatilities among the leading cryptocurrencies. We also find statistically significant spillover effects from the cryptocurrency market to other financial markets in the United States, as well as in other leading economies (Germany, theUnited Kingdom, and Japan).
    Date: 2019–07–19
  13. By: Silvio John, Camilleri; Nicolanne, Scicluna; Ye, Bai
    Abstract: This study examines the connections between stock prices and key macroeconomic indicators: inflation, industrial production, interest rates, money supply and select interactions between the latter group of variables. Such links are evaluated through vector-autoregressions (VARs) on monthly data spanning over the period 1999-2017, for Belgium, France, Germany, Netherlands and Portugal. We check whether such relations are confirmed across different sub-periods and also adopt a non-parametric approach by using a Pesaran-Timmermann test. We find different contemporaneous and lead-lag relationships between stock prices and the selected variables, although there are variations across countries. VAR models indicate that stock prices significantly lead inflation across all countries during the sample period and in most cases this relationship was positive. In addition, stock prices significantly lead industrial production in four of the sampled countries and these relationships were positive as well. Contrary to long-established finance theories, we did not find numerous significant links between interest rates and stock indices; however the interaction between interest rates and money supply was a leading indicator of stock prices in France, Germany and Portugal.
    Keywords: Stock prices, Macroeconomic indicators, Pesaran-Timmermann test, Structural breakpoint tests, Vector autoregression
    JEL: G10 G12 G15
    Date: 2019

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