Bounded chaos in equity markets: Seasonality, information effects, and the SEC filings

Several branches of the finance literature motivate this research: the efficient market hypothesis, informational efficiency, dynamic systems, and behavioral finance. Analysis of seasonal regularities and fundamental information effects suggests a dynamic equity market model that incorporates the complementary aspects of these other market models: information, behavior, time, and market responses. This research focuses on the relationship between three characteristics of fundamental information, market responses, and seasonal variations.; Returns, volume, or volatility are generally used to analyze information effects. This research uses two aspects of each variable, its level and monthly percentage change. The dependent variables are: price level, returns, excess return to a centered moving average, excess returns to a capital asset pricing model, trading volume, change in trading volume, price volatility, and change in price volatility. The distinction between levels and changes is significant. Each variable exhibits significant monthly seasonality, but gives scant support to the January or turn-of-the-year effect. A seasonal regularity in volume and volatility implies seasonality in liquidity and risk.; The companies studied are associated with the S&P 500, S&P 400, and S&P 600 indexes. The independent variables are months and the information releases represented by the SEC filings: 10-K, 10-Q, 11-K, 8-K, annual report to shareholders, prospectus, and 1 proxy. The filings exhibit strong seasonality roughly corresponding to the seasonal in returns. Whether analyzed as an event study or linear model, they display information effects for all dependent variables, which vary substantially with company size and time period.; The interactions are significant between the monthly seasonal and information effects in a multivariate analysis. The 10-Q filing is associated with seasonality. The 10-K and 10-Q have opposite effects on returns. All of the SEC filings relate significantly with variable levels more than changes, indicating upper or lower boundaries. They behave like the coherent attractors described in dynamic systems models and counterbalance the chaotic, self-referral fractal characteristics of non-information periods. Investors can use seasonality, information, and their interactions to track market or companies' divergence from fundamental values, liquidity, and risk. This is also useful in evaluating the effectiveness of regulations promoting corporate disclosure.