nep-fmk New Economics Papers
on Financial Markets
Issue of 2007‒04‒28
three papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Asset Pricing with Adaptive Learning By Carceles-Poveda, Eva; Giannitsarou, Chryssi
  2. On forecasting the term structure of credit spreads By C.N.V. Krishnan; Peter H. Ritchken; James B. Thomson
  3. Expected stock returns and variance risk premia By Tim Bollerslev; Hao Zhou

  1. By: Carceles-Poveda, Eva; Giannitsarou, Chryssi
    Abstract: We study the extent to which self-referential adaptive learning can explain stylized asset pricing facts in a general equilibrium framework. In particular, we analyze the effects of recursive least squares and constant gain algorithms in a production economy and a Lucas type endowment economy. We find that recursive least squares learning has almost no effects on asset price behaviour, since the algorithm converges relatively fast to rational expectations. On the other hand, constant gain learning may contribute towards explaining the stock price and return volatility as well as the predictability of excess returns in the endowment economy. In the production economy, however, the effects of constant gain learning are mitigated by the persistence induced by capital accumulation. We conclude that, contrary to popular belief, standard self-referential learning cannot fully resolve the asset pricing puzzles observed in the data.
    Keywords: Adaptive learning; Asset pricing; Excess returns; Predictability
    JEL: D83 D84 G12
    Date: 2007–04
  2. By: C.N.V. Krishnan; Peter H. Ritchken; James B. Thomson
    Abstract: Predictions of firm-by-firm term structures of credit spreads based on current spot and forward values can be improved upon by exploiting information contained in the shape of the credit-spread curve. However, the current credit-spread curve is not a sufficient statistic for predicting future credit spreads; the explanatory power can be increased further by exploiting information contained in the shape of the riskless-yield curve. In the presence of credit-spread and riskless factors, other macroeconomic, marketwide, and firm-specific risk variables do not significantly improve predictions of credit spreads. Current credit-spread and riskless-yield curves impound essentially all marketwide and firm-specific information necessary for predicting future credit spreads.
    Keywords: Corporate bond ; Rate of return
    Date: 2007
  3. By: Tim Bollerslev; Hao Zhou
    Abstract: We find that the difference between implied and realized variances, or the variance risk premium, is able to explain more than fifteen percent of the ex-post time series variation in quarterly excess returns on the market portfolio over the 1990 to 2005 sample period, with high (low) premia predicting high (low) future returns. The magnitude of the return predictability of the variance risk premium easily dominates that afforded by standard predictor variables like the P/E ratio, the dividend yield, the default spread, and the consumption-wealth ratio (CAY). Moreover, combining the variance risk premium with the P/E ratio results in an R^2 for the quarterly returns of more than twenty-five percent. The results depend crucially on the use of "model-free", as opposed to standard Black-Scholes, implied variances, and realized variances constructed from high-frequency intraday, as opposed to daily, data. Our findings suggest that temporal variation in risk and risk-aversion both play an important role in determining stock market returns.
    Date: 2007

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