Hazem Daouk

The World Price of Insider Trading

The existence and the enforcement of insider trading laws in stock markets is a phenomenon of the 1990s. A study of the 103 countries that have stock markets reveals that insider trading laws exist in 87 of them, but enforcement-as evidenced by prosecutions-has taken place in only 38 of them. Before 1990, the respective numbers were 34 and 9. We find that the cost of equity in a country, after controlling for a number of other variables, does not change after the introduction of insider trading laws, but decreases significantly after the first prosecution. Copyright The American Finance Association 2002.

Application of neural networks to an emerging financial market: forecasting and trading the Taiwan stock index

In this study, we attempt to model and predict the direction of return on market index of the Taiwan Stock Exchange, one of the fastest growing financial exchanges in developing Asian countries. Our motivation is based on the notion that trading strategies guided by forecasts of the direction of price movement may be more effective and lead to higher profits. The probabilistic neural network (PNN) is used to forecast the direction of index return after it is trained by historical data. Statistical performance of the PNN forecasts are measured and compared with that of the generalized methods of moments (GMM) with Kalman filter. Moreover, the forecasts are applied to various index trading strategies, of which the performances are compared with those generated by the buy-and-hold strategy as well as the investment strategies guided by forecasts estimated by the random walk model and the parametric GMM models. Empirical results show that the PNN-based investment strategies obtain higher returns than other investment strategies examined in this study. Influences of length of investment horizon and commission rate are also considered.

Forecasting Stock Indices: A Comparison of Classification and Level Estimation Models

Despite abundant research which focuses on estimating the level of return on stock market index, there is a lack of studies examining the predictability of the direction/sign of stock index movement. Given the notion that a prediction with little forecast error does not necessarily translate into capital gain, we evaluate the efficacy of several multivariate classification techniques relative to a group of level estimation approaches. Specifically, we conduct time series comparisons between the two types of models on the basis of forecast performance and investment return. The tested classification models, which predict direction based on probability, include linear discriminant analysis, logit, probit, and probabilistic neural network. On the other hand, the level estimation counterparts, which forecast the level, are exponential smoothing, multivariate transfer function, vector autoregression with Kalman filter, and multilayered feedforward neural network. Our comparative study also measures the relative strength of these models with respect to the trading profit generated by their forecasts. To facilitate more effective trading, we develop a set of threshold trading rules driven by the probabilities estimated by the classification models. Empirical experimentation suggests that the classification models outperform the level estimation models in terms of predicting the direction of the stock market movement and maximizing returns from investment trading. Further, investment returns are enhanced by the adoption of the threshold trading rules.

Forecasting exchange rates using general regression neural networks

Predicting currency movements has always been a problematic task as most conventional econometric models are not able to forecast exchange rates with significantly higher accuracy than a naive random walk model. For large multinational firms which conduct substantial currency transfers in the course of business, being able to accurately forecast the movements of exchange rates can result in considerable improvement in the overall profitability of the firm. In this study, we apply the General Regression Neural Network (GRNN) to predict the monthly exchange rates of three currencies, British pound, Canadian dollar, and Japanese yen. Our empirical experiment shows that the performance of GRNN is better than other neural network and econometric techniques included in this study. The results demonstrate the predictive strength of GRNN and its potential for solving financial forecasting problems.

Capital market governance: How do security laws affect market performance?

This paper examines the link between capital market governance (CMG) and several key measures of market performance. Using detailed data from individual stock exchanges, we develop a composite CMG index that captures three dimensions of security laws: the degree of earnings opacity, the enforcement of insider laws, and the effect of removing short-selling restrictions. We find that improvements in the CMG index are associated with decreases in the cost-of-equity capital (both implied and realized), increases in market liquidity (trading volume, market depth, and U.S. foreign investments), and increases in market pricing efficiency (reduced price synchronicity and IPO underpricing). The results are quite consistent across individual components of CMG and over alternative market performance measures.

A Study of Market-Wide Short-Selling Restrictions

This paper contributes empirical evidence to the on-going debate on short sales. Our examination of how market-wide short-sale restrictions affect aggregate market returns focuses on two main questions: What is the effect of short-sale restrictions on skewness, volatility, the probability of market crashes, and liquidity? What is the effect on the market expected return or cost of capital? We report new data on the history of short-selling and put option trading regulations and practices from 111 countries, and create a short-selling feasibility indicator for the analysis of stock market indices around the world. We find that when short-selling is possible, aggregate stock returns are less volatile and there is greater liquidity. When countries start to permit short-selling, aggregate stock price increases, implying lower a cost of capital. There is no evidence that short-sale restrictions affect either the level of skewness of returns or the probability of a market crash. Collectively, our empirical evidence suggests that allowing short-selling enhances market quality.

An Econometric Evaluation of a Geopolitical Theory of Oil Price Behavior

Previous work on crude oil price modeling has generally focused on two theoretical approaches, either the optimal control analysis of pricing of a depletable resource, or OPEC as a partial monopolist setting oil prices to maximize net present value. Neither has been wholly satisfactory. We consider a different perspective, a game theory based framework in which political and military factors interact with economic considerations for oil exporters and importers to define a target price zone (TPZ). We analyze several issues in this context: monthly vs. annual average prices, beginning and ending dates for TPZs, degree of stability in several price series (WTI, Brent, etc.), FOB and landed prices, real or nominal prices, OPEC behavior, and effect of the Euro exchange rate on dollar denominated oil prices. We conclude that a TPZ system was in operation from 1986 through 2003 and that OPEC acted as a political cartel exercising market power by controlling production in order to seek to maintain prices within the TPZ. The TPZ worked imperfectly but with a substantial degree of predictability for 18 years. In 2004 and 2005 the TPZ system deteriorated for several reasons, and has not yet been re-established.

Do Investors Learn About Analyst Accuracy

We study the impact of analyst forecasts on prices to determine whether investors learn about analyst accuracy. Our test market is the crude oil futures market. Prices rise when analysts forecast a decrease (increase) in crude supplies. In the 15 minutes following supply realizations, prices rise (fall) when forecasts have been too high (low). In both the initial price action relative to forecasts and in the subsequent reaction relative to realized forecast errors, the price response is stronger for more accurate analysts. These price reactions imply that investors learn about analyst accuracy and trade accordingly.

Informed Institutional Trading around Merger and Acquisition Announcements

Merger and acquisition (MA while banks, insurance companies, and mutual funds immediately reverse their positions to cash in, a behavior consistent with the early informed traders acting as “shortterm profit takers.” The author rules out the possibility of a market-wide information leak prior to the event because prices of target firms do not show any significant price run-ups. Also, the fact that institutions are net sellers in rival firms of targets before the announcement, allows us to rule out the possibility that institutional investors have better models to predict possible takeovers, rather than inside information. Finally, the author shows that the trading by institutions before M&A announcements is associated with a higher probability of informed trading, for the firms they trade.

A geopolitical theory of oil price behaviour: an econometric evaluation

Previous work on crude oil price modelling has generally focused on two theoretical approaches, either the+ optimal control analysis of pricing of a depletable resource or Organization of the Petroleum Exporting Countries (OPEC) as a partial monopolist setting oil prices to maximize net present value. Neither has been wholly satisfactory. We consider a different perspective: a cooperative framework in which political and military factors interacted with economic considerations for oil exporters and importers to define a Target Price Zone (TPZ). We analyse several issues in this context: monthly versus annual average prices, beginning and ending dates for TPZs, degree of stability in several price series (West Texas Intermediate (WTI), Brent, etc.), Free On Board (FOB) and landed prices, real or nominal prices, OPEC behaviour and effect of the Euro exchange rate on dollar denominated oil prices. We conclude that a TPZ system was in operation from 1986 through 2003. The TPZ worked imperfectly but with a substantial degree of predictability for 18 years. In 2004, the TPZ system deteriorated for several reasons and has not been re-established. Perhaps the US government supports the Saudis because it has always believed it had a two-way relation with OPEC generally and the Persian Gulf countries in particular. We give them protection and they supply oil.1 The Bush trip [1986] came as an additional incentive to restore some stability to prices … What they [the Saudis] heard was the Vice President of the United States of America saying that the price collapse was destabilizing and threatened the security of the United States … The Saudis looked to the United States for their own security; surely, they thought in the aftermath of the Bush visit, they would have to be attentive to the security needs of the United States.2 1 See Adelman (2005). Adelman qualifies this quotation by observing that ‘OPEC countries owe us nothing’. 2 See Yergin (1992). This is Yergins description of then Vice-President Bushs visit to Saudi Arabia in April 1986. In Yergins view, this explains why Saudi Arabia later that year cut production, subsequently leading to higher prices.