nep-fmk New Economics Papers
on Financial Markets
Issue of 2020‒11‒23
twelve papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Stock Market Spillovers via the Global Production Network: Transmission of U.S. Monetary Policy By Julian di Giovanni; Galina Hale
  2. Connected Funds By Fricke, Daniel; Wilke, Hannes
  3. Augmenting transferred representations for stock classification By Elizabeth Fons; Paula Dawson; Xiao-jun Zeng; John Keane; Alexandros Iosifidis
  4. Price Ceiling, Market Structure, and Payout Policies By Mao Ye; Miles Zheng; Xiongshi Li
  5. Asset Classes and Portfolio Diversification: Evidence from a Stochastic Spanning Approach By Nguyen, Duc Khuong; Topaloglou, Nikolas; Walther, Thomas
  6. Time-Invariance Coefficients Tests with the Adaptive Multi-Factor Model By Liao Zhu; Robert A. Jarrow; Martin T. Wells
  7. Synthetic forwards and cost of funding in the equity derivative market By Michele Azzone; Roberto Baviera
  8. Price discovery and gains from trade in asset markets with insider trading By Brünner, Tobias; Levinsky, Rene
  9. Reinforced Deep Markov Models With Applications in Automatic Trading By Tadeu A. Ferreira
  10. Quantifying the trade-off between income stability and the number of members in a pooled annuity fund By Thomas Bernhardt; Catherine Donnelly
  11. Beyond LIBOR: Money Markets and the Illusion of Representativeness By Lilian Muchimba; Alexis Stenfors
  12. Effect of Short-Term Debt on Financial Growth of Non-Financial Firms Listed at Nairobi Securities Exchange By David Haritone Shikumo; Oluoch Oluoch; Joshua Matanda Wepukhulu

  1. By: Julian di Giovanni; Galina Hale
    Abstract: We quantify the role of global production linkages in explaining spillovers of U.S. monetary policy shocks to stock returns of fifty-four sectors in twenty-six countries. We first present a conceptual framework based on a standard open-economy production network model that delivers a spillover pattern consistent with a spatial autoregression (SAR) process. We then use the SAR model to decompose the overall impact of U.S. monetary policy on stock returns into a direct and a network effect. We find that up to 80 percent of the total impact of U.S. monetary policy shocks on average country-sector stock returns is due to the network effect of global production linkages. We further show that U.S. monetary policy shocks have a direct impact predominantly on U.S. sectors and then propagate to the rest of the world through the global production network. Our results are robust to controlling for correlates of the global financial cycle, foreign monetary policy shocks, and to changes in variable definitions and empirical specifications.
    Keywords: global production network; asset prices; monetary policy shocks
    JEL: G15 F10 F36
    Date: 2020–11–01
  2. By: Fricke, Daniel; Wilke, Hannes
    Abstract: Investment funds are highly connected with each other, but also with the broader financial system. In this paper, we quantify potential vulnerabilities arising from funds' connectedness. While previous work exclusively focused on indirect connections (overlapping asset portfolios) between investment funds, we develop a macroprudential stress test that also includes direct connections (cross-holdings of fund shares). In our application for German investment funds, we find that these direct connections are very important from a financial stability perspective. Our main result is that the German fund sector's aggregate vulnerability can be substantial and tends to increase over time, suggesting that the fund sector can amplify adverse developments in global security markets. We also highlight spillover risks to the broader financial system, since fund sector losses would be largely borne by fund investors from the financial sector. Overall, we make an important step towards a more financial-system-wide view on fund sector vulnerabilities.
    Keywords: asset management,investment funds,systemic risk,fire sales,liquidity risk,cross-holdings,spillover effects
    JEL: G10 G11 G23
    Date: 2020
  3. By: Elizabeth Fons; Paula Dawson; Xiao-jun Zeng; John Keane; Alexandros Iosifidis
    Abstract: Stock classification is a challenging task due to high levels of noise and volatility of stocks returns. In this paper we show that using transfer learning can help with this task, by pre-training a model to extract universal features on the full universe of stocks of the S$\&$P500 index and then transferring it to another model to directly learn a trading rule. Transferred models present more than double the risk-adjusted returns than their counterparts trained from zero. In addition, we propose the use of data augmentation on the feature space defined as the output of a pre-trained model (i.e. augmenting the aggregated time-series representation). We compare this augmentation approach with the standard one, i.e. augmenting the time-series in the input space. We show that augmentation methods on the feature space leads to $20\%$ increase in risk-adjusted return compared to a model trained with transfer learning but without augmentation.
    Date: 2020–10
  4. By: Mao Ye; Miles Zheng; Xiongshi Li
    Abstract: To prevent firms from manipulating prices, U.S. regulators set price ceilings for open-market share repurchases. We find that market structure reforms in the 1990s and 2000s dramatically increased share repurchases because they relaxed constraints that prevent firms from competing with other traders under price ceilings. The 2016 Tick Size Pilot, a controlled experiment that partially reversed previous reforms, significantly reduced share repurchases. Market structure frictions provide a unified explanation for two puzzles: the dividend puzzle exists because previous research has overlooked market structure frictions; share repurchases increase relative to dividends over time because market structure reforms gradually reduce these frictions.
    JEL: G18 G35
    Date: 2020–11
  5. By: Nguyen, Duc Khuong; Topaloglou, Nikolas; Walther, Thomas
    Abstract: We propose a stochastic spanning approach to assess whether a traditional portfolio of stocks and bonds spans augmented portfolios including commodities, foreign exchange, and real estate. We empirically show that in all seven portfolio combinations, the augmented portfolio is not spanned by the traditional one. Our results are further confirmed by both parametric and non-parametric tests in an out-of-sample setting. Therefore, traditional investors can generally benefit in terms of higher Sharpe ratios from augmenting their portfolio with alternative asset classes. Additional analysis demonstrates that diversification benefits can be explained by the current state of the U.S. economy and stock markets.
    Keywords: Stochastic Dominance, Stochastic Spanning, Commodities, FX, Real Estate, Diversification
    JEL: C1 C4 C6 E32 G10 G11 G12 G15
    Date: 2020–10–30
  6. By: Liao Zhu; Robert A. Jarrow; Martin T. Wells
    Abstract: The purpose of this paper is to test the multi-factor beta model implied by the generalized arbitrage pricing theory (APT) and the Adaptive Multi-Factor (AMF) model with the Groupwise Interpretable Basis Selection (GIBS) algorithm, without imposing the exogenous assumption of constant betas. The intercept (arbitrage) tests validate both the AMF and the Fama-French 5-factor (FF5) model. We do the time-invariance tests for the betas for both the AMF model and the FF5 in various time periods. We show that for nearly all time periods with length less than 6 years, the beta coefficients are time-invariant for the AMF model, but not the FF5 model. The beta coefficients are time-varying for both AMF and FF5 models for longer time periods. Therefore, using the dynamic AMF model with a decent rolling window (such as 5 years) is more powerful and stable than the FF5 model.
    Date: 2020–11
  7. By: Michele Azzone; Roberto Baviera
    Abstract: This study introduces a new technique to recover the implicit discount factor in the derivative market using only European put and call prices: this discount is grounded in actual transactions in active markets. Moreover, this study identifies the implied cost of funding, over OIS, of major market players. Does a liquid equity market allow arbitrage? The key idea is that the (unique) forward contract -- built using the put-call parity relation -- contains information about the market discount factor: by no-arbitrage conditions we identify the implicit interest rate such that the forward contract value does not depend on the strike. The procedure is applied to options on S&P 500 and EURO STOXX 50 indices. There is statistical evidence that, in the EURO STOXX 50 market, the implicit interest rate curve coincides with the EUR OIS one, while, in the S&P 500 market, a cost of funding of, on average, 34 basis points is added on top of the USD OIS curve.
    Date: 2020–11
  8. By: Brünner, Tobias; Levinsky, Rene
    Abstract: The present study contributes to the ongoing debate on possible costs and benefits of insider trading. We present a novel call auction model with insider information. Our model predicts that more insider information improves informational efficiency of prices, but this comes at the expense of reduced gains from trade. The model further implies that in the presence of insider information the call auction performs worse than continuous double auction. Testing these hypotheses in the lab we find that insider information increases informational efficiency of call auction prices but does not decrease the realized gains from trade. Contrary to the theoretical prediction, the call auction does not perform worse than the continuous double auction. In fact, when the probability of insider information is high, the call auction has the most informative prices and highest realized gains from trade. Our experiment provides new evidence, from markets with very asymmetrically dispersed information, that lends support to the decision by many stock exchanges to use call auctions when information asymmetries are severe and the need for accurate prices is large, e.g., at the open or close of the trading day.
    Keywords: call market,call auction,double auction,asymmetric information,experiment,informational efficiency
    JEL: D82 C92 G14
    Date: 2020
  9. By: Tadeu A. Ferreira
    Abstract: Inspired by the developments in deep generative models, we propose a model-based RL approach, coined Reinforced Deep Markov Model (RDMM), designed to integrate desirable properties of a reinforcement learning algorithm acting as an automatic trading system. The network architecture allows for the possibility that market dynamics are partially visible and are potentially modified by the agent's actions. The RDMM filters incomplete and noisy data, to create better-behaved input data for RL planning. The policy search optimisation also properly accounts for state uncertainty. Due to the complexity of the RKDF model architecture, we performed ablation studies to understand the contributions of individual components of the approach better. To test the financial performance of the RDMM we implement policies using variants of Q-Learning, DynaQ-ARIMA and DynaQ-LSTM algorithms. The experiments show that the RDMM is data-efficient and provides financial gains compared to the benchmarks in the optimal execution problem. The performance improvement becomes more pronounced when price dynamics are more complex, and this has been demonstrated using real data sets from the limit order book of Facebook, Intel, Vodafone and Microsoft.
    Date: 2020–11
  10. By: Thomas Bernhardt; Catherine Donnelly
    Abstract: The number of people who receive a stable income for life from a closed pooled annuity fund is studied. Income stability is defined as keeping the income within a specified tolerance of the initial income in a fixed proportion of future scenarios. The focus is on quantifying the effect of the number of members, which drives the level of idiosyncratic longevity risk in the fund, on the income stability. To do this, investment returns are held constant and systematic longevity risk is omitted. An analytical expression that closely approximates the number of fund members who receive a stable income is derived and is seen to be independent of the mortality model. An application of the result is to calculate the length of time for which the pooled annuity fund can provide the desired level of income stability
    Date: 2020–10
  11. By: Lilian Muchimba (University of Portsmouth); Alexis Stenfors (University of Portsmouth)
    Abstract: Money market benchmarks are important indicators for economic agents. They are also crucial for central banks in assessing the functioning of the interest rate channel of the monetary transmission mechanism. However, whereas the unsecured interbank money market conventionally has been seen as encompassing instruments with maturities up to one year, it appears as if it consists of two markets. The ultra-short-term money market (typically just one day) is large, liquid and traded regularly. The term money market (one, three or six months), by contrast, is small, illiquid and rarely traded. This paper explores the feasibility of creating and maintaining a money market benchmark which does not represent an underlying liquid market. From a sociological perspective, it addresses two critical aspects of financial benchmarks: i) that they are related to but separate and distinct from the objects determining them and ii) that they are measurements and as such cannot be bought or sold (Stenfors and Lindo 2018). By doing so, the paper also reflects upon the desire by financial regulators following the LIBOR manipulation scandal to replace estimation-based by transaction-based benchmarks, as well as some challenges and contradictions in conventional central banking theory.
    Keywords: Bank of Zambia, banks, benchmarks, Eurodollar market, LIBOR, monetary transmission mechanism, reference rates
    JEL: B52 E43 E52 G15 G28
    Date: 2020–11–08
  12. By: David Haritone Shikumo; Oluoch Oluoch; Joshua Matanda Wepukhulu
    Abstract: A significant number of the non-financial firms listed at Nairobi Securities Exchange (NSE) have been experiencing declining financial performance which deter investors from investing in such firms. The lenders are also not willing to lend to such firms. As such, the firms struggle to raise funds for their operations. Prudent financing decisions can lead to financial growth of the firm. The purpose of this study is to assess the effect of short-term debt on financial growth of non-financial firms listed at Nairobi Securities Exchange for a period of ten years from 2008 to 2017. Financial firms were excluded because of their specific sector characteristics and stringent regulatory framework. The study is guided by Agency Theory and Theory of Growth of the Firm. Explanatory research design was adopted. The target population of the study comprised of 45 non-financial firms listed at the NSE for a period of ten years from 2008 to 2017. The study conducted both descriptive statistics analysis and panel data analysis. The result indicates that, short term debt explains 45.99% and 25.6% of variations in financial growth as measured by growth in earnings per share and growth in market capitalization respectively. Short term debt positively and significantly influences financial growth measured using both growth in earnings per share and growth in market capitalization. The study recommends that, the management of non-financial firms listed at Nairobi Securities Exchange to employ financing means that can improve the earnings per share, market capitalization and enhance the value of the firm for the benefit of its stakeholders.
    Date: 2020–11

This nep-fmk issue is ©2020 by Kwang Soo Cheong. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
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