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This paper analyzes the choice between taxes and cap and trade systems (also referred to here as a permit system or a quantity restriction) as methods of controlling greenhouse gas emissions. It argues that in the domestic context, with proper design, the two instruments are essentially the same. Commonly discussed differences in the two instruments are due to unjustified assumptions about design. In the climate change context and within a single country there is sufficient design flexibility that these differences can be substantially eliminated. To the extent that there are remaining differences, there should be a modest preference for taxes, but the benefits of taxes are swamped by the benefits of good design; even though the very best tax might be better than the very best quantity restriction, the first order of business is getting the design right. In the international context, however, taxes dominate more strongly. The design flexibility available within a single country is reduced in the international context because of the problems of coordinating systems across countries and minimizing holdouts. Moreover, the incentives to cheat and the effects of cheating are not equivalent for the two instruments in the international setting. Because climate change will require a global system for emissions, these considerations mean we should favor taxes for controlling greenhouse gas emissions.

We compare price-to-earnings ratios and dividend yields, which are indirect measures of sentiment, with the bullish sentiment index, which is a direct measure. We find that the sentiment index does better as a market-timing tool than do P/E ratios and dividend yields, but none is very reliable. We do not argue that market timing is impossible. Rather, we observe that stock prices reflect both sentiment and value, both of which are difficult to measure and neither of which is perfectly known in foresight. Successful market timing requires insights into future sentiment and value, insights beyond those that are reflected in widely available measures. JEL Classification: G11, G14 I. Market Timing in Regressions and Reality Value and sentiment are the two drivers of security prices in Shefrin and Statman’s (1994) behavioral capital asset pricing theory. Prices equal value in markets where only information traders trade and changes in value are the only driver of prices. However, noise traders join information traders in real-world markets and their sentiment, bullish or bearish, is the second driver of prices. Sentiment drives prices away from value. One implication of the two-driver framework is that stock prices are predictable if sentiment, bullish or bearish, fades over time on a predictable path. Market timers with reliable measures of sentiment can accumulate more than buyand-hold investors by switching from stocks to cash when sentiment is bullish and switching back to stocks when sentiment is bearish. But are there reliable measures of sentiment? And does sentiment fade on a predictable path?

This paper develops and tests a model of how organizational structure influences organizational performance. Organizational structure, conceptualized as the decision-making structure among a group of individuals, is shown to affect the number of initiatives pursued by organizations, and the omission and commission errors (Type I and II errors, respectively) made by organizations. The empirical setting are over 150,000 stock-picking decisions made by 609 mutual funds. Mutual funds offer an ideal and rare setting to test the theory, as detailed records exist on the projects they face, the decisions they make, and the outcomes of these decisions. The independent variable of the study, organizational structure, is coded from fund management descriptions made by Morningstar, and the estimates of the omission and commission errors are computed by a novel technique that uses bootstrapping to create measures which are comparable across funds. The findings suggest that organizational structure has relevant and predictable effects on a wide range of

In recent years financial economists have increasingly questioned the efficient market hypothesis. But surely if market prices were often irrational and if market returns were as predictable as some critics have claimed, then professionally managed investment funds should easily be able to outdistance a passive index fund. This paper shows that professional investment managers, both in The U.S. and abroad, do not outperform their index benchmarks and provides evidence that by and large market prices do seem to reflect all available information.

Abstract. In this note we investigate the ability of a mean-field model distilled from a heterogeneous agent model to simulate stylized facts of financial times series.

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Technical papers in this series are preliminary and are circulated to stimulate discussion and critical comment. These papers are not subject to CBO’s formal review and editing processes. The analysis and conclusions expressed in them are those of the authors and should not be interpreted as those of the Congressional Budget Office. References in publications should be cleared with the authors. Papers in this series can be obtained at The effect upon future Social Security benefits resulting from the introduction of individual accounts depends on both the potential risks and returns of private equities, yet the historical evidence about determinants of stock market risks and returns is mixed. In particular, correlations between equity returns and market fundamentals (such as the dividend price ratio) are weak at annual frequencies, which has led some to conclude that a random returns (fixed mean and variance) model is the preferred specification for simulating the future path of equity returns. Although choosing between random returns model and models based on market fundamentals do equally well for explaining variation of equity returns in the short run, the distinction is important when projecting equity returns over longer periods, as shown here in the context of a Monte Carlo simulation of Social Security reform. If equity returns are even weakly correlated with market fundamentals then (1) the expected future average return may be a function of the starting values for market fundamentals, and (2) the overall range of cumulative outcomes is more narrow than the random returns model suggests

The main contribution of this study is the finding that round numbers can act as price barriers for individual stocks. In addition, a first step is made to explain this and the related phenomena of round number clustering by testing two competing hypotheses, using data from the Dutch stock market during 1990-2001. After January 1, 1999 stock prices were listed in euros, while guilders were still the currency of daily life until 2002. According to the aspiration level hypothesis investors will have target prices for the stocks they own. This hypothesis predicts that round number effects in guilders will only slowly disappear. The odd price hypothesis originates from cognitive psychology and marketing. Humans have to tendency to compare numbers digit by digit from left to right, and therefore consider an odd price of 19.90 as considerable less than 20.00. This hypothesis predicts an abrupt change in round number effects after January 1, 1999. The results reject the aspiration level hypothesis and are in line with the odd price hypothesis.

We investigate whether fractal markets hypothesis and its focus on liquidity and investment horizons give reasonable predictions about dynamics of the financial markets during the turbulences such as the Global Financial Crisis of late 2000s. Compared to the mainstream efficient markets hypothesis, fractal markets hypothesis considers financial markets as complex systems consisting of many heterogenous agents, which are distinguishable mainly with respect to their investment horizon. In the paper, several novel measures of trading activity at different investment horizons are introduced through scaling of variance of the underlying processes. On the three most liquid US indices – DJI, NASDAQ and S&P500 – we show that predictions of fractal markets hypothesis actually fit the observed behavior quite well.