The link between asset valuations and investor sentiment is the subject of considerable debate in the profession. We address this question by examining how survey data on investor sentiment relates to i) long-horizon returns, and ii) asset valuations. If excessive optimism drives prices above intrinsic values, periods of high sentiment should be followed by low returns as market prices revert to fundamental values. We find this to be the case for the overall stock market at horizons of two to three years. The relation is strongest for large-capitalization, low book-to-market (growth) portfolios. We also examine the relation between sentiment levels and deviations from intrinsic value. Using errors from an independent pricing model, we find sentiment is positively related to valuation errors using a variety of tests. All of our results are robust to the inclusion of other factors that have been shown to forecast stock returns, including past returns.

This paper proposes an autoregressive regime-switching model of stock price dynamics in which the process creates pricing bubbles in one regime while error-correction prevails in the other. In the bubble regime the stock price depends negatively on inflation. In the error-correction regime it depends on the price-dividend-ratio. We find that the probability of regime-switch depends on exogenous inflation and lagged price. The model is consistent with Shleifer and Vishny’s theoretical noise trader and arbitrageur model and Modigliani’s inflation illusion phenomenon. The results emphasize the importance of inflation and the price-dividend-ratio when assessing investment risk.

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We show that the long-term total market and average investor’s compounded stock returns are determined by GDP growth and are much less than believed because of the infeasible assumption that dividends can be fully reinvested. The long-term stock return closely approximates the return on risk-free debt, thus yielding a zero premium on a compounded per-capita basis. We demonstrate that the market earnings yield ratio (inverse P/E) is akin to a minimum nominal expected return and a direct function of inflation and a real required yield equal to long-term real GDP per capita growth, with marginal regard to risk. Our derived valuation formula is tested against the S&P 500 index and produces a 21 % mean percentage tracking error, compared to 32 % for the “Fed Model ” over the period 1954 – 2002.

This focus of this paper are the effect, implication, impact and realtionship between selected macroeconomic variables and wider US indices S&P 500 and industrial Dow Jones Industrial Average (DJIA). I Consider inflation, interest rates, money supply, producer price index, industrial production index, oil price and unemployment and their impact on selected stock indices in the USA between 1999 and 2012. The hypotesis of this paper is, that between selected macroeconomic variables, namely producer price index, industrial production index, oil price and Dow Jones index is strongly relationship than between these factors and S&P 500. The paper is organizing as follows. First section reviews the related literature. In section two are materials and methods which are use explained. Section 3 provides the empirical results and the last part presents the conclusions.