/pdf/the-theory-of-industrial-organization-19bejph0ej.pdf

The Theory of Industrial Organization

This paper examines the empirical performance of jump diffusion models of stock price dynamics from joint options and stock markets data. The paper introduces a model with discontinuous correlated jumps in stock prices and stock price volatility, and with state-dependent arrival intensity. We discuss how to perform likelihoodbased inference based upon joint options/returns data and present estimates of risk premiums for jump and volatility risks. The paper finds that while complex jump specifications add little explanatory power in fitting options data, these models fare better in fitting options and returns data simultaneously. THE STATISTICAL PROPERTIES of stock returns have long been of interest to finan

/pdf/do-stock-prices-and-volatility-jump-reconciling-evidence-3v87q9zfqr.pdf

Do Stock Prices and Volatility Jump? Reconciling Evidence from Spot and Option Prices

https://www.federalreserve.gov/pubs/ifdp/2006/871/ifdp871.pdf

Real-Time Price Discovery in Global Stock, Bond and Foreign Exchange Markets

This article provides several new insights into the economic sources of skewness. First, we document the differential pricing of individual equity options versus the market index, and relate it to variations in return skewness. Second, we show how risk aversion introduces skewness in the risk-neutral density. Third, we derive laws that decompose individual return skewness into a systematic component and an idiosyncratic component. Empirical analysis of OEX options and 30 stocks demonstrates that individual risk-neutral distributions differ from that of the market index by being far less negatively skewed. This paper explains the presence and evolution of risk-neutral skewness over time and in the cross-section of individual stocks.

Stock Return Characteristics, Skew Laws, and the Differential Pricing of Individual Equity Options

This article presents a dynamic, rational expectations equilibrium model of asset prices where the drift of fundamentals (dividends) shifts between two unobservable states at random times. I show that in equilibrium, investors’ willingness to hedge against changes in their own “uncertainty” on the true state makes stock prices overreact to bad news in good times and underreact to good news in bad times. I then show that this model is better able than conventional models with no regime shifts to explain features of stock returns, including volatility clustering, “leverage effects,” excess volatility, and time-varying expected returns.

Stock Market Overreactions to Bad News in Good Times: A Rational Expectations Equilibrium Model

The average relative profitability of different firms in the economy jumps erratically. Al? though investors are unable to observe these productivity switches, they continuously update their beliefs regarding high and low productivity firms by observing the total return on each firm, which consists of the average productivity plus noise. The portfolio choices, interest rate, and stock return processes are derived in a Cox-Ingersoll-Ross (1985a) style general equilibrium model. Three stylized facts of stock market returns are addressed: negative skewness, excess kurtosis, and predictive asymmetry (excess returns and future changes in volatility are negatively correlated). To measure the last stylized fact, an EGARCH model is fitted to sample paths simulated from the model. Parameter values that permit faster learning fit the three facts better. I. Introduction This paper has three purposes. First, it presents the special properties of a filter in continuous time that characterizes the dynamics of Bayesian learning about recurrent profitability switches and their relation to fluctuating confidence. Second, the paper shows how fluctuating confidence, which arises due to this up? dating process, is reflected in the statistical properties of interest rate and stock return processes in a Cox-Ingersoll-Ross (1985a and b) (henceforth, CIR) stochas? tic production economy. Portfolio adjustments to hedge the exposure of the risk associated with these fluctuations are discussed. Finally, the paper draws some re? lationships between the speed of learning and the ability of the model to replicate three stylized facts about stock market returns. I argue that the often used Kalman filtering problem is not suitable to model fluctuating confidence and to replicate the three stylized facts.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/E3D44BA44BE71B902D62D9261CCCF8A1/S0022109000000727a.pdf/div-class-title-fluctuating-confidence-in-stock-markets-implications-for-returns-and-volatility-div.pdf

Fluctuating Confidence in Stock Markets: Implications for Returns and Volatility

Agents with heterogeneous beliefs about fundamental growth do not perfectly share risks but instead speculate with each other on the relative accuracy of their models' predictions. They face the risk that market prices move more in line with the trading models of competing agents rather than their own. Less risk averse agents speculate more aggressively and demand higher risk premiums. Our calibrated model generates countercyclical consumption volatility, earnings forecast dispersion, and cross-sectional consumption dispersion. With a risk aversion coefficient less than one, agents' speculation causes half the observed equity premium and lowers the riskless rate by one percent.

Heterogeneous Beliefs, Speculation, and the Equity Premium

Stock and Treasury bond comovement, volatilities, and their relations to their price valuations and fundamentals change stochastically over time, both in magnitude and direction. These stochastic changes are explained by a general equilibrium model in which agents learn about composite economic and inflation regimes. We estimate our model using both fundamentals and asset prices, and find that inflation news signal either positive or negative future real economic growth depending on the times, thereby affecting the direction of stock/bond comovement. The learning dynamics generate strong non-linearities between volatilities and price valuations. We find empirical support for numerous predictions of the model.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1626044_code15729.pdf?abstractid=1569064&rulid=52948&mirid=2

What Ties Return Volatilities to Price Valuations and Fundamentals

Agents with heterogeneous beliefs about fundamental growth do not share risks perfectly but instead speculate with each other on the relative accuracy of their models' predictions. They face the risk that market prices move more in line with the trading models of competing agents than with their own. Less risk-averse agents speculate more aggressively and demand higher risk premiums. My calibrated model generates countercyclical consumption volatility, earnings forecast dispersion, and cross-sectional consumption dispersion. With a risk aversion coefficient less than one, agents' speculation causes half the observed equity premium and lowers the riskless rate by about 1%. Copyright 2008 by The American Finance Association.

Stock and Treasury bond comovement, volatilities, and their relations to their price valuations and fundamentals change stochastically over time, in both magnitude and direction. These stochastic changes are explained by a general equilibrium model in which agents learn about composite economic and inflation regimes. We estimate our model using both fundamentals and asset prices and find that inflation news signal either positive or negative future real economic growth depending on the times, thereby affecting the direction of stock-bond comovement. The learning dynamics generate strong nonlinearities between volatilities and price valuations. We find empirical support for numerous predictions of the model.

https://www.jstor.org/stable/10.1086/671799

Alexander David

Papers

Fluctuating Confidence in Stock Markets: Implications for Returns and Volatility

Heterogeneous Beliefs, Speculation, and the Equity Premium

What Ties Return Volatilities to Price Valuations and Fundamentals

Heterogeneous Beliefs, Speculation, and the Equity Premium

What ties return volatilities to price valuations and fundamentals