nep-fmk New Economics Papers
on Financial Markets
Issue of 2018‒11‒12
six papers chosen by

  1. Asset Price Distributions and Efficient Markets By Ricardo T. Fernholz; Caleb Stroup
  2. Forecasting of Jump Arrivals in Stock Prices: New Attention-based Network Architecture using Limit Order Book Data By Milla M\"akinen; Juho Kanniainen; Moncef Gabbouj; Alexandros Iosifidis
  3. Asymmetric Information, Predictability and Momentum in the Corporate Bond Market By Galvani, Valentina; Li, Lifang
  4. "Bond risk premia and restrictions on risk prices" By Constantino Hevia; Martin Sola
  5. Bond Risk Premia and the ”Return Forecasting Factor” By Agustin Gutierrez; Constantino Hevia; Martin Sola
  6. The Momentum Effect for Canadian Corporate Bonds By Galvani, Valentina; Li, Lifang

  1. By: Ricardo T. Fernholz; Caleb Stroup
    Abstract: We explore a decomposition in which returns on a large class of portfolios relative to the market depend on a smooth non-negative drift and changes in the asset price distribution. This decomposition is obtained using general continuous semimartingale price representations, and is thus consistent with virtually any asset pricing model. Fluctuations in portfolio relative returns depend on stochastic time-varying dispersion in asset prices. Thus, our framework uncovers an asset pricing factor whose existence emerges from an accounting identity universal across different economic and financial environments, a fact that has deep implications for market efficiency. In particular, in a closed, dividend-free market in which asset price dispersion is relatively constant, a large class of portfolios must necessarily outperform the market portfolio over time. We show that price dispersion in commodity futures markets has increased only slightly, and confirm the existence of substantial excess returns that co-vary with changes in price dispersion as predicted by our theory.
    Date: 2018–10
  2. By: Milla M\"akinen; Juho Kanniainen; Moncef Gabbouj; Alexandros Iosifidis
    Abstract: The existing literature provides evidence that limit order book data can be used to predict short-term price movements in stock markets. This paper proposes a new neural network architecture for predicting return jump arrivals in equity markets with high-frequency limit order book data. This new architecture, based on Convolutional Long Short-Term Memory with Attention, is introduced to apply time series representation learning with memory and to focus the prediction attention on the most important features to improve performance. The data set consists of order book data on five liquid U.S. stocks. The use of the attention mechanism makes it possible to analyze the importance of the inclusion limit order book data and other input variables. By using this mechanism, we provide evidence that the use of limit order book data was found to improve the performance of the proposed model in jump prediction, either clearly or marginally, depending on the underlying stock. This suggests that path-dependence in limit order book markets is a stock specific feature. Moreover, we find that the proposed approach with an attention mechanism outperforms the multi-layer perceptron network as well as the convolutional neural network and Long Short-Term memory model.
    Date: 2018–10
  3. By: Galvani, Valentina (University of Alberta, Department of Economics); Li, Lifang (University of Alberta, Department of Economics)
    Abstract: We show that firm-level cross-asset predictability for bonds with a high incidence of informed trading is mostly driven by information diffusion. In contrast, the activities of uninformed investors dominate in originating predictability for the remaining bonds in the firm-level cross-section. Capitalizing on these results, we explore the role of informed and uninformed trading in determining the momentum effect. We find that gradual information diffusion is the main driver of short-term momentum. However, the effect of uninformed trading may outweigh that of information in generating large momentum returns, as it is the case for private-issuer bonds.
    Keywords: asymmetric information; informed trading; uninformed trading; predictability; momentum; corporate bonds
    JEL: G10 G14
    Date: 2018–11–01
  4. By: Constantino Hevia; Martin Sola
    Abstract: Researchers who estimate affine term structure models often impose overidentifying restrictions (restrictions on parameters beyond those necessary for identification) for a variety of reasons. While some of those restrictions seem to have minor effects on the extracted factors and some measures of risk premia, such as the forward risk premium, they may have a large impact on other measures of risk premia that is often ignored. In this paper we analyze how apparently innocuous overidentifying restrictions imposed on affine term structure models can lead to large differences in several measures of risk premiums.
    Keywords: Bond risk premia, affine term structure models, risk prices
    JEL: E43 G12
    Date: 2018–10
  5. By: Agustin Gutierrez; Constantino Hevia; Martin Sola
    Abstract: The return forecasting factor is a linear combination of forward rates that seems to predict one-year excess bond returns of bond of all maturities better than traditional measures obtained from the yield curve. If this single factor actually captures all the relevant fluctuations in bond risk premia, then it should also summarize all the economically relevant variations in excess returns considering different holding periods. We find that it does not. We conclude that including the return forecasting factor as the main driver of risk premia in a term structure model, as has been suggested, is not supported by the data.
    Keywords: : Excess returns, bond risk premia, return forecasting factor, affine term structure models.
    Date: 2018–10
  6. By: Galvani, Valentina (University of Alberta, Department of Economics); Li, Lifang (University of Alberta, Department of Economics)
    Abstract: Using bond-level data for a sample ranging from 1987 to 2016 we document that the momentum effect is significant in the Canadian market for corporate bonds. The strategy yields momentum gains that are comparable to those observed for US corporate bonds. Conditioning on the market state (UP/ DOWN) doubles the returns on the momentum portfolio for holding periods ranging from one month up to two years. Further, momentum gains are exclusive to the UP market state. The conditional analysis further reveals that the state of the market brings about sizable momentum returns also for investment grade bonds, especially in the most recent years of the sample.
    Keywords: market states; investment grade; momentum; institution investors; Canadian corporate bonds
    JEL: G11 G12 G15
    Date: 2018–11–01

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