nep-fmk New Economics Papers
on Financial Markets
Issue of 2017‒10‒15
three papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Term Structure Analysis with Big Data By Andreasen, Martin M.; Christensen, Jens H. E.; Rudebusch, Glenn D.
  2. Predicting Relative Returns By Valentin Haddad; Serhiy Kozak; Shrihari Santosh
  3. Fundamentals unknown: Momentum, mean-reversion and price-to-earnings trading in an artificial stock market By Schasfoort, Joeri; Stockermans, Christopher

  1. By: Andreasen, Martin M. (Aarhus University); Christensen, Jens H. E. (Federal Reserve Bank of San Francisco); Rudebusch, Glenn D. (Federal Reserve Bank of San Francisco)
    Abstract: Analysis of the term structure of interest rates almost always takes a two-step approach. First, actual bond prices are summarized by interpolated synthetic zero-coupon yields, and second, a small set of these yields are used as the source data for further empirical examination. In contrast, we consider the advantages of a one-step approach that directly analyzes the universe of bond prices. To illustrate the feasibility and desirability of the onestep approach, we compare arbitrage-free dynamic term structure models estimated using both approaches. We also provide a simulation study showing that a one-step approach can extract the information in large panels of bond prices and avoid any arbitrary noise introduced from a first-stage interpolation of yields.
    JEL: C58 G12 G17
    Date: 2017–09–15
  2. By: Valentin Haddad; Serhiy Kozak; Shrihari Santosh
    Abstract: Across a variety of asset classes, we show that relative returns are highly predictable in the time series in and out of sample, much more so than aggregate returns. For Treasuries, slope is more predictable than level. For equities, dominant principal components of anomaly long-short strategies are more predictable than the market. For foreign exchange, a carry portfolio is more predictable than a basket of all currencies against the dollar. We show the commonly used practice to predict each individual asset is often equivalent to predicting only their first principal component, the index, which obscures the predictability of relative returns. Our findings highlight that focusing on important dimensions of the cross-section allows one to uncover additional economically relevant and statistically robust patterns of predictability.
    JEL: F31 G0 G1 G12 G17
    Date: 2017–09
  3. By: Schasfoort, Joeri; Stockermans, Christopher
    Abstract: The use of fundamentalist traders in the stock market models is problematic since fundamental values in the real world are unknown. Yet, in the literature to date, fundamentalists are often required to replicate key stylized facts. The authors present an agent-based model of the stock market in which the fundamental value of the asset is unknown. They start with a zero intelligence stock market model with a limit-order-book. Then, the authors add technical traders which switch between a simple momentum and mean reversion strategy depending on its relative profitability. Technical traders use the price to earnings ratio as a proxy for fundamentals. If price to earnings are either too high or too low, they sell or buy, respectively.
    Keywords: Agent-based modelling,financial markets,technical and fundamental analysis,asset pricing
    JEL: C63 D53 D84 G12 G17
    Date: 2017

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