Search Results for « Stock market volatility »
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ABSTRACT We show that consumption‐based asset pricing models with time‐separable preferences generate realistic amounts of stock price volatility if one allows for small deviations from rational expectations. Rational investors with subjective beliefs about price behavior optimally learn from past price …
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ABSTRACT We show that consumption‐based asset pricing models with time‐separable preferences generate realistic amounts of stock price volatility if one allows for small deviations from rational expectations. Rational investors with subjective beliefs about price behavior optimally learn from past price observations. This imparts momentum and mean reversion into stock prices. The model quantitatively accounts for the volatility of returns, the volatility and persistence of the price‐dividend ratio, and the predictability of long‐horizon returns. It passes a formal statistical test for the overall fit of a set of moments provided one excludes the equity premium.
We present a theory of excess stock market volatility, in which market movements are due to trades by very large institutional investors in relatively illiquid markets.Such trades generate significant spikes in returns and volume, even in the absence of important …
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We present a theory of excess stock market volatility, in which market movements are due to trades by very large institutional investors in relatively illiquid markets.Such trades generate significant spikes in returns and volume, even in the absence of important news about fundamentals.We derive the optimal trading behavior of these investors, which allows us to provide a unified explanation for apparently disconnected empirical regularities in returns, trading volume and investor size.
We investigate in a theoretical framework the joint role played by investors’ attention to news and learning uncertainty in determining asset prices. The model provides two main predictions. First, stock return variance and risk premia increase with both attention and …
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We investigate in a theoretical framework the joint role played by investors’ attention to news and learning uncertainty in determining asset prices. The model provides two main predictions. First, stock return variance and risk premia increase with both attention and uncertainty. Second, this increasing relationship is quadratic. We empirically test these two predictions, and we show that the data lend support to the increasing relationship. The evidence for a quadratic relationship is mixed. Overall, our study shows theoretically and empirically that both attention and uncertainty are key determinants of asset prices.
Notwithstanding its impressive contributions to empirical financial economics, there remains a significant gap in the volatility literature, namely its relative neglect of the connection between macroeconomic fundamentals and asset return volatility.We progress by analyzing a broad international cross section of …
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Notwithstanding its impressive contributions to empirical financial economics, there remains a significant gap in the volatility literature, namely its relative neglect of the connection between macroeconomic fundamentals and asset return volatility.We progress by analyzing a broad international cross section of stock markets covering approximately forty countries.We find a clear link between macroeconomic fundamentals and stock market volatilities, with volatile fundamentals translating into volatile stock markets.