nep-fmk New Economics Papers
on Financial Markets
Issue of 2019‒05‒27
eighteen papers chosen by



  1. The impact of hedge fund indices on portfolio performance By Maria Teresa Medeiros Garcia; Gonçalo Liberal
  2. Fiduciary Duty and the Market for Financial Advice By Vivek Bhattacharya; Gaston Illanes; Manisha Padi
  3. Will the Market Fix the Market? A Theory of Stock Exchange Competition and Innovation By Eric Budish; Robin S. Lee; John J. Shim
  4. Testing Sharpe ratio: luck or skill? By Eric Benhamou; David Saltiel; Beatrice Guez; Nicolas Paris
  5. Spectral risk measures and uncertainty By Mohammed Berkhouch; Ghizlane Lakhnati; Marcelo Brutti Righi
  6. Risk premium factors By Gadiy, Ludmila (Гадий, Людмила); Drobyshevskiy, Sergey (Дробышевский, Сергей); Kiyutsevskaya, Anna (Киюцевская, Анна); Trunin, Pavel (Трунин, Павел); Sherbustanova, Maria (Шербустанова, Мария)
  7. Macro-finance and factor timing: Time-varying factor risk and price of risk premiums By de Oliveira Souza, Thiago
  8. Equity Risk Premium and Time Horizon: what do the French secular data say ? By Georges Prat; David Le Bris
  9. Convolutional Feature Extraction and Neural Arithmetic Logic Units for Stock Prediction By Shangeth Rajaa; Jajati Keshari Sahoo
  10. Crypto-Assets: Implications for financial stability, monetary policy, and payments and market infrastructures By Manaa, Mehdi; Chimienti, Maria Teresa; Adachi, Mitsutoshi; Athanassiou, Phoebus; Balteanu, Irina; Calza, Alessandro; Devaney, Conall; Diaz Fernandez, Ester; Eser, Fabian; Ganoulis, Ioannis; Laot, Maxime; Philipp, Günther; Poignet, Raphael; Sauer, Stephan; Schneeberger, Doris; Stracca, Livio; Tapking, Jens; Toolin, Colm; Tyler, Carolyn; Wacket, Helmut
  11. Predicting and Forecasting the Price of Constituents and Index of Cryptocurrency Using Machine Learning By Reaz Chowdhury; M. Arifur Rahman; M. Sohel Rahman; M. R. C. Mahdy
  12. Conceptual Issues in Calibrating the Basel III Countercyclical Capital Buffer By Torsten Wezel
  13. Euro area sovereign risk spillovers before and after the ECB's OMT announcement By Niels Gilbert
  14. The Predictability of Stock Market Volatility in Emerging Economies: Relative Roles of Local, Regional and Global Business Cycles By Elie Bouri; Riza Demirer; Rangan Gupta; Xiaojin Sun
  15. The Real Effects of the Bank Lending Channel By Gabriel Jiménez; Atif Mian; José-Luis Peydró; Jesús Saurina
  16. Diagnosis and Prediction of the 2015 Chinese Stock Market Bubble By Min Shu; Wei Zhu
  17. Detection of Chinese Stock Market Bubbles with LPPLS Confidence Indicator By Min Shu; Wei Zhu
  18. Republic of Poland; Financial Sector Assessment Program-Technical Note-Stress Testing and Systemic Risk Analysis By International Monetary Fund

  1. By: Maria Teresa Medeiros Garcia; Gonçalo Liberal
    Abstract: The purpose of this paper is to assessthecombination of investable hedge funds indices with a traditional portfolio of 60% stocks and40% bonds.The S&P 500 Index,the Barclays US Aggregate Bond Index, and threeinvestable hedge fund indices,the MEBI Maximum Sharpe Ratio L1Index, the MEBI Zero Beta Strategy L1Index, and the Eurekahedge ILS Advisers Index, were considered to conduct performance comparison, using time windows of two, five and ten years, from the 1st of January,2006,to the 1st 2of February, 2016. Significant reduction of the beta of the overall portfolio is reached. The findings showed that the investable hedge fund indices under analysis can be used as an easy way to protect a portfolio during different market conditions, diversifying the risks of the traditional investment portfolios.The paper provides evidence of how investable hedge fund indices lead to an improvement in the performance results,when compared with the traditional global equity-bond portfolio alone.
    Keywords: Markowitz portfolio theory;optimal portfolios;investable hedge fund index;performance evaluation
    JEL: G11 G12
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:ise:remwps:wp0852019&r=all
  2. By: Vivek Bhattacharya; Gaston Illanes; Manisha Padi
    Abstract: Recent regulatory debate in the financial advice industry has focused on expanding fiduciary duties to broker-dealers. Proponents of this reform argue that it would improve the advice given to clients and limit losses from agency problems, while detractors counter that such regulation would increase compliance costs without directly improving consumer outcomes. This paper evaluates these claims empirically, using a transactions-level dataset for annuity sales from a major financial services provider and exploiting state-level variation in common law fiduciary duty. We find that imposing fiduciary duty on broker-dealers shifts the set of products they sell to consumers, away from variable annuities and towards fixed indexed annuities. Within variable annuities, fiduciary duty induces a shift towards lower-fee, higher-return annuities with a wider array of investment options. We develop a model that leverages the distributional changes in products sold to test the mechanism by which fiduciary duty operates. We find evidence that fiduciary duty does not solely increase the cost of doing business but that it has the intended effect of directly impacting financial advice.
    JEL: G23 G28 L51 L84
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:25861&r=all
  3. By: Eric Budish; Robin S. Lee; John J. Shim
    Abstract: Will the market adopt new market designs that address the negative aspects of high-frequency trading? This paper builds a theoretical model of stock exchange competition, shaped by institutional and regulatory details of the U.S. equities market. We show that under the status quo market design: (i) trading behavior across the many distinct exchanges is as if there is just a single “synthesized” exchange; (ii) as a result, trading fees are perfectly competitive; but (iii) exchanges capture and maintain significant economic rents from the sale of “speed technology” (i.e., proprietary data feeds and co-location)—arms for the high-frequency trading arms race. Using a variety of data, we document seven stylized empirical facts that suggest that the model captures the essential economics of how U.S. stock exchanges compete and make money in the modern era. We then use the model to examine the private and social incentives for market design innovation. We find that while the social returns to market design innovation are large, the private returns are much smaller and may be negative, especially for incumbents that derive rents in the status quo from selling speed technology.
    JEL: D02 D44 D53 D82 G1 G2 G23 L1 L13 L5 L89
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:25855&r=all
  4. By: Eric Benhamou; David Saltiel; Beatrice Guez; Nicolas Paris
    Abstract: Sharpe ratio (sometimes also referred to as information ratio) is widely used in asset management to compare and benchmark funds and asset managers. It computes the ratio of the (excess) net return over the strategy standard deviation. However, the elements to compute the Sharpe ratio, namely, the expected returns and the volatilities are unknown numbers and need to be estimated statistically. This means that the Sharpe ratio used by funds is likely to be error prone because of statistical estimation errors. In this paper, we provide various tests to measure the quality of the Sharpe ratios. By quality, we are aiming at measuring whether a manager was indeed lucky of skillful. The test assesses this through the statistical significance of the Sharpe ratio. We not only look at the traditional Sharpe ratio but also compute a modified Sharpe insensitive to used Capital. We provide various statistical tests that can be used to precisely quantify the fact that the Sharpe is statistically significant. We illustrate in particular the number of trades for a given Sharpe level that provides statistical significance as well as the impact of auto-correlation by providing reference tables that provides the minimum required Sharpe ratio for a given time period and correlation. We also provide for a Sharpe ratio of 0.5, 1.0, 1.5 and 2.0 the skill percentage given the auto-correlation level.
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1905.08042&r=all
  5. By: Mohammed Berkhouch; Ghizlane Lakhnati; Marcelo Brutti Righi
    Abstract: Risk assessment under different possible scenarios is a source of uncertainty that may lead to concerning financial losses. We address this issue, first, by adapting a robust framework to the class of spectral risk measures. Second, we propose a Deviation-based approach to quantify uncertainty. Furthermore, the theory is illustrated with a practical case study from NASDAQ index.
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1905.07716&r=all
  6. By: Gadiy, Ludmila (Гадий, Людмила) (The Russian Presidential Academy of National Economy and Public Administration); Drobyshevskiy, Sergey (Дробышевский, Сергей) (The Russian Presidential Academy of National Economy and Public Administration); Kiyutsevskaya, Anna (Киюцевская, Анна) (The Russian Presidential Academy of National Economy and Public Administration); Trunin, Pavel (Трунин, Павел) (The Russian Presidential Academy of National Economy and Public Administration); Sherbustanova, Maria (Шербустанова, Мария) (Gaidar Institute for Economic Policy)
    Abstract: While developed countries have been tightening their monetary policy, the importance of a risk premium as a factor that determins investment attractiveness of a recipient country and, accordingly, the direction of financial flows in the global economy significantly increases. In this context, the choice of an indicator allowing us to compare risk levels in different countries and segments of a financial market, and then identification of the risk premium’s determinants enable us to characterize the role of global and country-specific factors. Such a separation of these factors for the Russian economy will make it possible to determine the main directions of investment attractiveness’ increasing.
    Date: 2019–04
    URL: http://d.repec.org/n?u=RePEc:rnp:wpaper:041920&r=all
  7. By: de Oliveira Souza, Thiago (Department of Business and Economics)
    Abstract: This paper documents empirically that increases in the book-to-market spread predict larger market premiums in sample and larger size, value, and investment premiums (also) out of sample. In addition, increases in the investment (or profitability) spread exclusively predict larger investment (or profitability) premiums. This predictability generates “factor timing” strategies that deliver substantial economic gains out of sample. I argue theoretically that the book-to-market spread is a price of risk proxy, while the investment and profitability spreads are factor risk proxies. The evidence confirms standard theoretical predictions in the macro-finance literature and contradicts the hypothesis of constant factor risks.
    Keywords: Out of sample; factor timing; time-varying risk; macro-finance; Fama and French
    JEL: G11 G12 G14
    Date: 2019–05–13
    URL: http://d.repec.org/n?u=RePEc:hhs:sdueko:2019_007&r=all
  8. By: Georges Prat; David Le Bris
    Abstract: We consider a representative investor whose wealth is shared between a replica of the equity market portfolio and the riskless asset, and who maximizes the expected utility of their future wealth. For a given time-horizon, the solution of this program equalizes the required risk premium to the product of price of risk by the expected variance of stock returns. As a tentative to capture exogenous disturbing effects, the term spread of interest rates and US equity risk premia complement this relationship. Two traditional horizons are considered: the one-period-ahead horizon characterizing the ‘short-term’ investor and the infinite-time horizon characterizing the ‘long-term’ investor. For each horizon, expected returns are represented by mixing the three traditional adaptive, extrapolative and regressive process, expected variance is represented by a GARCH process, while the unobservable time-varying price of risk is estimated according to the Kalman filter methodology. Based on annual French data established by Le Bris and Hautcoeur (2010), large disparities in the dynamics of the short- and long term observed premia are evidenced from 1872 to 2018, while, due to risky arbitrage and transaction costs, the observed premia appeared to gradually converge towards their required values. Overall, although the French market had experienced very strong historical shocks, our model provides both measurements and explanations of French short- and long-term risk premia and so shed some additional light on the existence of a time-varying term structure of equity risk premia. Despite differences, results on the French market are rather in accordance with those by Prat (2013) based on US secular data.
    Keywords: equity risk premium, time horizon, France
    JEL: D81 D84 E44 G11 G12
    Date: 2019
    URL: http://d.repec.org/n?u=RePEc:drm:wpaper:2019-8&r=all
  9. By: Shangeth Rajaa; Jajati Keshari Sahoo
    Abstract: Stock prediction is a topic undergoing intense study for many years. Finance experts and mathematicians have been working on a way to predict the future stock price so as to decide to buy the stock or sell it to make profit. Stock experts or economists, usually analyze on the previous stock values using technical indicators, sentiment analysis etc to predict the future stock price. In recent years, many researches have extensively used machine learning for predicting the stock behaviour. In this paper we propose data driven deep learning approach to predict the future stock value with the previous price with the feature extraction property of convolutional neural network and to use Neural Arithmetic Logic Units with it.
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1905.07581&r=all
  10. By: Manaa, Mehdi; Chimienti, Maria Teresa; Adachi, Mitsutoshi; Athanassiou, Phoebus; Balteanu, Irina; Calza, Alessandro; Devaney, Conall; Diaz Fernandez, Ester; Eser, Fabian; Ganoulis, Ioannis; Laot, Maxime; Philipp, Günther; Poignet, Raphael; Sauer, Stephan; Schneeberger, Doris; Stracca, Livio; Tapking, Jens; Toolin, Colm; Tyler, Carolyn; Wacket, Helmut
    Abstract: This paper summarises the outcomes of the analysis of the ECB Crypto-Assets Task Force. First, it proposes a characterisation of crypto-assets in the absence of a common definition and as a basis for the consistent analysis of this phenomenon. Second, it analyses recent developments in the crypto-assets market and unfolding links with financial markets and the economy. Finally, it assesses the potential impact of crypto-assets on monetary policy, payments and market infrastructures, and financial stability. The analysis shows that, in the current market, crypto-assets’ risks or potential implications are limited and/or manageable on the basis of the existing regulatory and oversight frameworks. However, this assessment is subject to change and should not prevent the ECB from continuing to monitor crypto-assets, raise awareness and develop preparedness. JEL Classification: E42, G21, G23, O33
    Keywords: characterisation, crypto-assets, crypto-assets risks, monitoring
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:ecb:ecbops:2019223&r=all
  11. By: Reaz Chowdhury; M. Arifur Rahman; M. Sohel Rahman; M. R. C. Mahdy
    Abstract: At present, cryptocurrencies have become a global phenomenon in financial sectors as it is one of the most traded financial instruments worldwide. Cryptocurrency is not only one of the most complicated and abstruse fields among financial instruments, but it is also deemed as a perplexing problem in finance due to its high volatility. This paper makes an attempt to apply machine learning techniques on the index and constituents of cryptocurrency with a goal to predict and forecast prices thereof. In particular, the purpose of this paper is to predict and forecast the close (closing) price of the cryptocurrency index 30 and nine constituents of cryptocurrencies using machine learning algorithms and models so that, it becomes easier for people to trade these currencies. We have used several machine learning techniques and algorithms and compared the models with each other to get the best output. We believe that our work will help reduce the challenges and difficulties faced by people, who invest in cryptocurrencies. Moreover, the obtained results can play a major role in cryptocurrency portfolio management and in observing the fluctuations in the prices of constituents of cryptocurrency market. We have also compared our approach with similar state of the art works from the literature, where machine learning approaches are considered for predicting and forecasting the prices of these currencies. In the sequel, we have found that our best approach presents better and competitive results than the best works from the literature thereby advancing the state of the art. Using such prediction and forecasting methods, people can easily understand the trend and it would be even easier for them to trade in a difficult and challenging financial instrument like cryptocurrency.
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1905.08444&r=all
  12. By: Torsten Wezel
    Abstract: This paper discusses issues in calibrating the countercyclical capital buffer (CCB) based on a sample of EU countries. It argues that the main indicator for buffer decisions under the Basel III framework, the credit-to-GDP gap, does not always work best in terms of covering bank loan losses that go beyond what could be expected from economic downturns. Instead, in the case of countries with short financial cycles and/or low financial deepening such as transition and developing economies, the Basel gap is shown to work best when computed with a low, smoothing factor and adjusted for the degree of financial deepening. The paper also analyzes issues in calibrating an appropriate size of the CCB and, using a loss function approach, points to a tradeoff between stability of the buffer size and cost efficiency considerations.
    Date: 2019–05–01
    URL: http://d.repec.org/n?u=RePEc:imf:imfwpa:19/86&r=all
  13. By: Niels Gilbert
    Abstract: We study the dynamics of sovereign risk spillovers from (and between) Spain and Italy, before and after the ECB's announcement of the OMT program. We identify domestic Italian and Spanish sovereign risk shocks through an intraday event study. The shocks are used as external instruments in bilateral, daily, local projection regressions. Prior to the announcement of the OMT, changes in the Spanish and, to a lesser extent, Italian spread spilled over to many other euro area member states, and also affected the euro-dollar exchange rate. Peak effects generally materialized after 2-3 days. Since the OMT announcement, spillovers to non-crisis, non-safe haven countries have disappeared. Some spillovers among crisis countries persist, but are smaller and shorter-lived than before. Overall, our results are consistent with the view that the OMT, through eliminating equilibrium multiplicity, has largely stopped contagion.
    Keywords: Sovereign risk; contagion; narrative identification; local projections; OMT
    JEL: C53 E44 F36 G01 G15
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:dnb:dnbwpp:636&r=all
  14. By: Elie Bouri (USEK Business School, Holy Spirit University of Kaslik, Jounieh, Lebanon); Riza Demirer (Department of Economics and Finance, Southern Illinois University Edwardsville, Edwardsville, IL 62026-1102, USA); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa); Xiaojin Sun (Department of Economics and Finance, University of Texas at El Paso, El Paso, TX 79968, USA)
    Abstract: This paper explores the role of business cycle proxies, measured by the output gap at the global, regional and local levels, as potential predictors of stock market volatility in the emerging BRICS nations. We observe that the emerging BRICS nations display a rather heterogeneous pattern when it comes to the relative role of idiosyncratic factors as a predictor of stock market volatility. While domestic output gap is found to capture significant predictive information for India and China particularly, the business cycles associated with emerging economies and the world in general are strongly important for the BRIC countries and weakly for South Africa, especially in the post-global financial crisis era. The findings suggest that despite the increase in the financial integration of world capital markets, emerging economies can still bear significant exposures to idiosyncratic risk factors, an issue of high importance for the profitability of global diversification strategies.
    Keywords: Stock Market Volatility, Business Cycles, BRICS, Forecasting
    JEL: C22 C53 E32 G10
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:pre:wpaper:201938&r=all
  15. By: Gabriel Jiménez; Atif Mian; José-Luis Peydró; Jesús Saurina
    Abstract: We study bank credit booms, exploiting the Spanish matched credit register over 2001-2009. We extend Khwaja and Mian (2008)’s loan-level estimator by incorporating firm-level general equilibrium adjustments. Higher ex-ante bank real-estate exposure increases credit supply to non-real-estate firms, but effects are neutralized by firm-level adjustments for firms with existing banking relationships. However, higher bank real-estate exposure increases risk-taking, by relaxing standards of existing borrowers (cheaper, longer-term and less collateralized credit), and by expanding credit on the extensive margin to first-time borrowers that default substantially more. Results suggest that the mechanism at work is greater liquidity via securitization of real-estate assets.
    Keywords: bank lending channel, real effects of credit, credit supply booms, real estate, securitization
    JEL: E32 E44 G01 G21 G28
    Date: 2019–04
    URL: http://d.repec.org/n?u=RePEc:bge:wpaper:1099&r=all
  16. By: Min Shu; Wei Zhu
    Abstract: In this study, we perform a detailed analysis of the 2015 financial bubble in the Chinese stock market by calibrating the Log Periodic Power Law Singularity (LPPLS) model to two important Chinese stock indices, SSEC and SZSC, from early 2014 to June 2015. The back tests of 2015 Chinese stock market bubbles indicates that the LPPLS model can readily detect the bubble behavior of the faster-than-exponential increase corrected by the accelerating logarithm-periodic oscillations in the 2015 Chinese Stock market. The existence of log-periodicity is detected by applying the Lomb spectral analysis on the detrended residuals. The Ornstein-Uhlenbeck property and the stationarity of the LPPLS fitting residuals are confirmed by the two Unit-root tests (Philips-Perron test and Dickery-Fuller test). According to our analysis, the actual critical day t_c can be well predicted by the LPPLS model as soon as two months before the actual bubble crash. Compared to the traditional optimization method used in LPPLS model, the covariance matrix adaptation evolution strategy (CMA-ES) may have a significantly lower computation cost. The CMA-ES is recommended as an alternative algorithm in the LPPLS model. Moreover, the exponent m does not show a remarkable feature of change when the start day t1 is fixed while the end day t2 is moved towards the actual critical time t_c in the expanding windows. In the LPPLS fitting with expanding windows, the gap (tc -t2) shows a significant decrease when the end day t2 approaches the actual bubble crash time. The change rate of the gap (tc -t2) may be used as an additional indicator besides of the key indicator tc to improve the prediction of bubble burst.
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1905.09633&r=all
  17. By: Min Shu; Wei Zhu
    Abstract: This paper aims to present an advance bubble detection methodology based on LPPLS confidence indicator for the early causal identification of positive and negative bubbles in the Chinese stock market using the daily data on the Shanghai Shenzhen CSI 300 stock market index from January 2002 through April 2018. We account for the damping condition of LPPLS model in the search space and implement the stricter filter conditions for the qualification of the valid LPPLS fits by taking account of the maximum relative error, Lomb log-periodic test of the detrended residual, and unit-root tests of the logarithmic residual based on both the Phillips-Perron test and Dickey-Fuller test to improve the performance of LPPLS confidence indicator. Our analysis shows that the LPPLS detection strategy diagnoses the positive bubbles and negative bubbles corresponding to well-known historical events, implying the detection strategy based on the LPPLS confidence indicator has an outstanding performance to identify the bubbles in advance. We find that the probability density distribution of the estimated beginning time of bubbles appears to be skewed and the mass of the distribution is concentrated on the area where the bubbles start to have a super-exponentially growth. This study presents that it is possible to detect the potential positive and negative bubbles and crashes ahead of time, which provides a prerequisite for limiting the bubble sizes and eventually minimizing the damage from the bubble crash.
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1905.09640&r=all
  18. By: International Monetary Fund
    Abstract: Poland’s financial system is dominated by the banking sector, with significant state participation and foreign ownership. Commercial and cooperative banks play a leading role in financial intermediation, channeling deposits to credit to households and corporates. State-controlled and foreign-owned commercial banks account for about 60 percent of the financial sector (or 83 percent of the banking sector). While interbank and cross-sectoral exposures are relatively limited, the cooperative banks are highly interconnected with their affiliating commercial banks through the affiliating “Apex” network structure.
    Date: 2019–05–09
    URL: http://d.repec.org/n?u=RePEc:imf:imfscr:19/120&r=all

General information on the NEP project can be found at https://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.