nep-fmk New Economics Papers
on Financial Markets
Issue of 2021‒08‒23
eight papers chosen by



  1. The Real Explanation of Nominal Bond-Stock Puzzles By Mikhail Chernov; Lars A. Lochstoer; Dongho Song
  2. Who Owns What? A Factor Model for Direct Stock Holding By Vimal Balasubramaniam; John Y. Campbell; Tarun Ramadorai; Benjamin Ranish
  3. Combining Machine Learning Classifiers for Stock Trading with Effective Feature Extraction By A. K. M. Amanat Ullah; Fahim Imtiaz; Miftah Uddin Md Ihsan; Md. Golam Rabiul Alam; Mahbub Majumdar
  4. Currency Management by International Fixed Income Mutual Funds By Clemens Sialm; Qifei Zhu
  5. Predicting Credit Default Probabilities Using Bayesian Statistics and Monte Carlo Simulations By Dominic Joseph
  6. The Evolution from Life Insurance to Financial Engineering By Ralph S. J. Koijen; Motohiro Yogo
  7. Private equity buyouts and firm exports: evidence from UK firms By Paul Lavery; José María Serena Garralda; Marina-Eliza Spaliara
  8. Impact of Accounting Ratios on Stock Market Price of Listed companies in Colombo Stock Exchange By Larojan, Chandrasegaran

  1. By: Mikhail Chernov; Lars A. Lochstoer; Dongho Song
    Abstract: We present evidence that the mix of transitory and permanent shocks to consumption is changing over time. We study the implications of this finding for asset prices. The uncovered dynamics of consumption implies modestly upward sloping real bond and equity curves, upward sloping nominal yield curve, and sign-switching correlation between equities and bonds consistent with the stylized facts. This is achieved without relying on the nominal channel too much. That is, as in the data, the variation of inflation in the model is under 40% as a fraction of variation in nominal yields.
    JEL: E32 E43 E44 G12
    Date: 2021–07
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:29085&r=
  2. By: Vimal Balasubramaniam; John Y. Campbell; Tarun Ramadorai; Benjamin Ranish
    Abstract: We build a cross-sectional factor model for investors' direct stock holdings, by analogy with standard time-series factor models for stock returns. We estimate the model using data from almost 10 million retail accounts in the Indian stock market. We find that stock characteristics such as firm age and share price have strong investor clienteles associated with them. Similarly, account attributes such as account age, account size, and extreme underdiversification (holding a single stock) are associated with particular characteristic preferences. Coheld stocks tend to have higher return covariance, suggestive of the importance of clientele effects in the stock market.
    JEL: G11 G51
    Date: 2021–07
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:29065&r=
  3. By: A. K. M. Amanat Ullah; Fahim Imtiaz; Miftah Uddin Md Ihsan; Md. Golam Rabiul Alam; Mahbub Majumdar
    Abstract: The unpredictability and volatility of the stock market render it challenging to make a substantial profit using any generalized scheme. This paper intends to discuss our machine learning model, which can make a significant amount of profit in the US stock market by performing live trading in the Quantopian platform while using resources free of cost. Our top approach was to use ensemble learning with four classifiers: Gaussian Naive Bayes, Decision Tree, Logistic Regression with L1 regularization and Stochastic Gradient Descent, to decide whether to go long or short on a particular stock. Our best model performed daily trade between July 2011 and January 2019, generating 54.35% profit. Finally, our work showcased that mixtures of weighted classifiers perform better than any individual predictor about making trading decisions in the stock market.
    Date: 2021–07
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2107.13148&r=
  4. By: Clemens Sialm; Qifei Zhu
    Abstract: Investments in international fixed income securities are exposed to significant currency risks. We collect novel data on mutual fund currency derivatives and document that around 90% of U.S. international fixed income funds use currency forwards to manage their foreign exchange exposure. Funds' currency forward positions differ substantially based on risk management demands related to portfolio currency exposures, return-enhancement motives such as currency momentum and carry trade, and strategic considerations related to past performance and fund clienteles. Funds that hedge their currency risk exhibit lower return variability, but do not generate inferior abnormal returns.
    JEL: F21 F31 F34 G11 G12 G13 G15 G23 G32
    Date: 2021–07
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:29082&r=
  5. By: Dominic Joseph
    Abstract: Banks and financial institutions all over the world manage portfolios containing tens of thousands of customers. Not all customers are high credit-worthy, and many possess varying degrees of risk to the Bank or financial institutions that lend money to these customers. Hence assessment of credit risk is paramount in the field of credit risk management. This paper discusses the use of Bayesian principles and simulation-techniques to estimate and calibrate the default probability of credit ratings. The methodology is a two-phase approach where, in the first phase, a posterior density of default rate parameter is estimated based the default history data. In the second phase of the approach, an estimate of true default rate parameter is obtained through simulations
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2108.03389&r=
  6. By: Ralph S. J. Koijen; Motohiro Yogo
    Abstract: Since the mid-1980s, the share of household net worth intermediated by US financial institutions has shifted from defined benefit plans to life insurers and defined contribution plans. Life insurers have primarily grown through variable annuities, which are mutual funds with longevity insurance, a potential tax advantage, and minimum return guarantees. The minimum return guarantees change the primary function of life insurers from traditional insurance to financial engineering. Variable annuity insurers are exposed to interest and equity risk mismatch and suffered especially low stock returns during the COVID-19 crisis. We consider regulatory changes, such as more detailed financial disclosure and standardized stress tests, to monitor potential risk mismatch and to ensure stability of the insurance sector.
    JEL: G22 G32
    Date: 2021–07
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:29030&r=
  7. By: Paul Lavery; José María Serena Garralda; Marina-Eliza Spaliara
    Abstract: This paper examines the impact of private equity buyouts on the export activity of target firms. We exploit data on UK firms over the 2004-2017 period, and use difference-in-differences estimations on matched target versus non-target firms. Following private equity buyouts, non-exporting firms are more likely to begin exporting, and target firms are likewise more likely to increase their value of exports and their export intensity. Evidence from split-sample analysis further suggests that these patterns are consistent with private equity investors relaxing financial constraints and inducing productivity improvements.
    Keywords: private equity buyouts, exporting, financial constraints, transactions
    JEL: G34 G32
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:bis:biswps:961&r=
  8. By: Larojan, Chandrasegaran
    Abstract: This study investigates the impact of accounting ratios on stock market price of top twenty companies based on the highest market capitalization listed in the Colombo Stock Exchange (CSE). The objectives of this study were to examine the impact of Earnings per Share (EPS) on stock market price; to examine the impact of Dividend per Share (DPS) on stock market price, to examine the impact of Price Earnings ratio (PE) on stock market price and to examine the impact of Market to Book ratio (MB) on stock market price. The panel data was collected from the top twenty companies for the period of five years from 2015 to 2019. EPS, DPS, PE and MB ratios were used as the proxies for the independent variables and stock price was used as the proxy for the dependent variable for this study. In order to perform the inferential analysis Pearson correlation analysis, panel regression with fixed effect, random effect and pooled linear regression were used. Hausman test was adopted in order to choose either random effect regression or fixed effect regression. According to pooled regression analysis, EPS, DPS and PE ratios had positive significant impact on stock market price. MB ratio had a negative significant impact on stock market price. According to fixed effect regression analysis, EPS, PE and MB ratios had positive insignificant impact on stock market price whereas DPS had a positive significant impact on stock market price. This study offers an insight to the potential investors to make the rational investment decisions in the stock market.
    Date: 2021–07–11
    URL: http://d.repec.org/n?u=RePEc:osf:osfxxx:xwk7r&r=

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