**Abstract**

We develop a behavioral model for liquidity and volatility based on empirical regularities in trading order flow in the London Stock Exchange. This can be viewed as a very simple agent based model in which all components of the model are validated against real data. Our empirical studies of order flow uncover several interesting regularities in the way trading orders are placed and cancelled. The resulting simple model of order flow is used to simulate price formation under a continuous double auction, and the statistical properties of the resulting simulated sequence of prices are compared to those of real data. The model is constructed using one stock (AZN) and tested on 24 other stocks. For low volatility, small tick size stocks (called Group I) the predictions are very good, but for stocks outside Group I they are not good. For Group I, the model predicts the correct magnitude and functional form of the distribution of the volatility and the bid-ask spread, without adjusting any parameters based on prices. This suggests that at least for Group I stocks, the volatility and heavy tails of prices are related to market microstructure effects, and supports the hypothesis that, at least on short time scales, the large fluctuations of absolute returns are well described by a power law with an exponent that varies from stock to stock.

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Attention conservation notice: A rant, running to over 6000 words, about the horrors of physicists trying to do economics, by someone who used to be more sympathetic, but has since left physics, and has no credentials in economics. Some may detect an unpleasant sour, musty odor, notentirelydue to my having begun writing in June 2006. Includes lots of amateur sociology of science, unsupported by evidence, or, again, any credentials on my part. Even if you care about these fields, wouldn't you rather read science than sciencecriticism?

**Abstract**

This paper examines finance professors' collective opinion on the efficiency of US stock markets and whether their views on the markets' efficiency influence their investing behavior. We survey close to 4,000 professors, with an 18% response rate and find that most professors tend to believe US stock markets are weak to semi-strong efficient. Interestingly, their individual views on efficiency are not related to their trading behavior. The primary driver of a finance professor's propensity to actively invest is one's confidence in his own abilities to beat the market, regardless of his opinion of the efficiency of the US stock market.

]]>**Abstract**

During the week of August 6, 2007, a number of high-profile and highly successful quantitative long/short equity hedge funds experienced unprecedented losses. Based on empirical results from TASS hedge-fund data as well as the simulated performance of a specific long/short equity strategy, we hypothesize that the losses were initiated by the rapid unwinding of one or more sizable quantitative equity market-neutral portfolios. Given the speed and price impact with which this occurred, it was likely the result of a sudden liquidation by a multi-strategy fund or proprietary-trading desk, possibly due to margin calls or a risk reduction. These initial losses then put pressure on a broader set of long/short and long-only equity portfolios, causing further losses on August 9th by triggering stop-loss and de-leveraging policies. A significant rebound of these strategies occurred on August 10th, which is also consistent with the sudden liquidation hypothesis. This hypothesis suggests that the quantitative nature of the losing strategies was incidental, and the main driver of the losses in August 2007 was the firesale liquidation of similar portfolios that happened to be quantitatively constructed. The fact that the source of dislocation in long/short equity portfolios seems to lie elsewhere--apparently in a completely unrelated set of markets and instruments--suggests that systemic risk in the hedge-fund industry may have increased in recent years.

]]>**Abstract**

Options traders use a pricing formula which they adapt by fudging and changing the tails and skewness by varying one parameter, the standard deviation of a Gaussian. Such formula is popularly called "Black-Scholes-Merton" owing to an attributed eponymous discovery (though changing the standard deviation parameter is in contradiction with it). However we have historical evidence that 1) Black, Scholes and Merton did not invent any formula, just found an argument to make a well known (and used) formula compatible with the economics establishment, by removing the "risk" parameter through "dynamic hedging", 2) Option traders use (and evidently have used since 1902) heuristics and tricks more compatible with the previous versions of the formula of Louis Bachelier and Edward O. Thorp (that allow a broad choice of probability distributions) and removed the risk parameter by using put-call parity. 3) Option traders did not use formulas after 1973 but continued their bottom-up heuristics. The Bachelier-Thorp approach is more robust (among other things) to the high impact rare event. The paper draws on historical trading methods and 19th and early 20th century references ignored by the finance literature. It is time to stop calling the formula by the wrong name.

]]>** Abstract**

Many important classes of assets are illiquid in the sense that they cannot always be traded immediately. Thus, a portfolio position in these types of illiquid investments becomes at least temporarily irreversible. We study the asset-pricing implications of illiquidity in a two-asset exchange economy with heterogeneous agents. In this market, one asset is always liquid. The other asset can be traded initially, but then not again until after a “blackout” period. Illiquidity has a dramatic effect on optimal portfolio decisions. Agents abandon diversification as a strategy and choose highly polarized portfolios instead. The value of liquidity can represent a large portion of the equilibrium price of an asset. We present examples in which a liquid asset can be worth up to 25 percent more than an illiquid asset even though both have identical cash flow dynamics. We also show that the expected return and volatility of an asset can change significantly as the asset becomes relatively more liquid.

]]>**Abstract**

Fundamental information resembles in many respects a durable good. Hence, the effects of its incorporation into stock prices depend on who is the agent controlling its flow. Like a durable goods monopolist, a monopolistic analyst selling information intertemporally competes against herself. This forces her to partially relinquish control over the information flow to traders. Conversely, an insider solves the intertemporal competition problem through vertical integration, thus exerting tighter control over the information flow. Comparing market patterns I show that a dynamic market where information is provided by an analyst is thicker and more informative than one where an insider trades.

**Keywords:** Information Sales, Analysts, Insider Trading, Durable Goods Monopolist.

**Abtsract**

I show that stock market shocks have important and lasting effects on the careers of MBAs. Stock market conditions while MBA students are in school have a large effect on whether they go directly to Wall Street upon graduation. Further, starting on Wall Street immediately upon graduation causes a person to be more likely to work there later and to earn, on average, substantially more money. The empirical results suggest that investment bankers are largely “made” by circumstance rather than “born” to work on Wall Street.

*Journal of Finance - December 2008*

**Clifford Lynch**- Next-Generation Implications of Open Access -
**Paul Ginsparg** - Web 2.0 in Science -
**Timo Hannay**

**Abstract**

This paper models transaction costs as the rents that a monopolistic market maker extracts from impatient investors who trade via limit orders. We show that limit orders are American options. The limit prices inducing immediate execution of the order are functionally equivalent to bid and ask prices, and can be solved for various transaction sizes to characterize the market makers entire supply curve. We find considerable empirical support for the model's predictions in the cross-section of NYSE …rms. The model produces unbiased, out-of-sample forecasts of abnormal returns for firms added to the S&P 500 index.

]]>**Abstract**

We use the information in CDO prices to study market expectations about how corporate defaults cluster. A three-factor portfolio credit model explains virtually all of the time-series and cross-sectional variation in an extensive data set of CDX index tranche prices. Tranches are priced as if losses of 0.4%, 6%, and 35% of the portfolio occur with expected frequencies of 1.2, 41.5, and 763 years, respectively. On average, 65% of the CDX spread is due to firm-specific default risk, 27% to clustered industry or sector default risk, and 8% to catastrophic or systemic default risk.

]]>**Abstract**

Building on Duffie and Kan (1996), we propose a new representation of affine models in which the state vector comprises infinitesimal maturity yields and their quadratic covariations. Because these variables possess unambiguous economic interpretations, they generate a representation that is globally identifiable. Further, this representation has more identifiable parameters than the “maximal” model of Dai and Singleton (2000). We implement this new representation for select three-factor models and find that model-independent estimates for the state vector can be estimated directly from yield curve data, which presents advantages for the estimation and interpretation of multi-factor models.

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