Showing papers on "Algorithmic trading published in 1999"
TL;DR: In this paper, the authors used White's Reality Check bootstrap methodology to evaluate simple technical trading rules while quantifying the data-snooping bias and fully adjusting for its effect in the context of the full universe from which the trading rules were drawn.
Abstract: In this paper we utilize White’s Reality Check bootstrap methodology ~White ~1999!! to evaluate simple technical trading rules while quantifying the data-snooping bias and fully adjusting for its effect in the context of the full universe from which the trading rules were drawn. Hence, for the first time, the paper presents a comprehensive test of performance across all technical trading rules examined. We consider the study of Brock, Lakonishok, and LeBaron ~1992!, expand their universe of 26 trading rules, apply the rules to 100 years of daily data on the Dow Jones Industrial Average, and determine the effects of data-snooping. TECHNICAL TRADING RULES HAVE BEEN USED in financial markets for more than a century. Numerous studies have been performed to determine whether such rules can be employed to provide superior investing performance. 1 By and large, recent academic literature suggests that technical trading rules are capable of producing valuable economic signals. In perhaps the most comprehensive recent study of technical trading rules using 90 years of daily stock prices, Brock, Lakonishok, and LeBaron ~1992 !~ BLL, hereafter! find that 26 technical trading rules applied to the Dow Jones Industrial Average ~DJIA! significantly outperform a benchmark of holding cash. Their findings are especially strong because every one of the trading rules they consider is capable of beating the benchmark. When taken at face value, these results indicate either that the stock market is not efficient even in the weak form—a conclusion which, if found to be robust, will go against most researchers’ prior beliefs—or that risk premia display considerable variation even over very short periods of time ~i.e., at the daily interval!. An important issue generally encountered, but rarely directly addressed when evaluating technical trading rules, is data-snooping. Data-snooping
1,031 citations
TL;DR: The arrival of public information in the U.S. Treasury market sets off a two-stage adjustment process for prices, trading volume, and bid-ask spreads as mentioned in this paper, with a brief first stage, the release of a major macroeconomic announcement induces a sharp and nearly instantaneous price change with a reduction in trading volume.
Abstract: The arrival of public information in the U.S. Treasury market sets off a two-stage adjustment process for prices, trading volume, and bid-ask spreads. In a brief first stage, the release of a major macroeconomic announcement induces a sharp and nearly instantaneous price change with a reduction in trading volume, demonstrating that price reactions to public information do not require trading. The bid-ask spread widens dramatically at announcement, evidently driven by inventory control concerns. In a prolonged second stage, trading volume surges, price volatility persists, and bid-ask spreads remain moderately wide as investors trade to reconcile residual differences in their private views.
692 citations
TL;DR: In this paper, the authors measure the impact of these new rules on various measures of performance, including trading costs and depths, and show that quoted and effective spreads fell dramatically without adversely affecting market quality.
Abstract: The relative merits of dealer versus auction markets have been a subject of significant and sometimes contentious debate. On January 20, 1997, the Securities and Exchange Commission began implementing reforms that would permit the public to compete directly with Nasdaq dealers by submitting binding limit orders. Additionally, superior quotes placed by Nasdaq dealers in private trading venues began to be displayed in the Nasdaq market. We measure the impact of these new rules on various measures of performance, including trading costs and depths. Our results indicate that quoted and effective spreads fell dramatically without adversely affecting market quality.
332 citations
TL;DR: In this article, the authors provide a theoretical rebalancing benchmark for trading volume that delivers a connection between trading activity in individual stocks and market-wide volume, and find that average excess turnover vs. the benchmark is positively related to option availability and institutional ownership and negatively related to firm size.
Abstract: This paper provides a theoretical rebalancing benchmark for trading volume that delivers a connection between trading activity in individual stocks and market-wide volume. This model supports the empirical use of an adjustment for market-wide trading activity when filtering out normal trading volume. Data on a sample of large NYSE/AMEX firms support the usefulness of the benchmark. While 20% of the sample firms exhibit trading behavior that is consistent with the cross-sectional prediction of the rebalancing bench? mark, systematic deviations exist. An analysis of deviations from the benchmark allows a characterization of anomalous trading activity. I find that average excess turnover vs. the benchmark is positively related to option availability and institutional ownership and negatively related to firm size. The data do not yield a uniform conclusion on the effect of S&P 500 inclusion. S&P 500 inclusion does not significantly increase the trading of firms that are already trading above benchmark levels, but does result in additional trading for firms that undertrade the benchmark prior to inclusion. An investigation of individual firm market model regressions indicates that this is a useful methodology for filtering out the anomalous trading documented here.
196 citations
TL;DR: In this article, the authors analyzed the trading activity of a confessed inside trader, Ivan Boesky, in Carnation's stock just prior to Nestle's 1984 acquisition of Carnation.
Abstract: Prior studies have reported a positive correlation between insider trading and stock price changes implying that insider (i.e., informed) trades affect price discovery differently than non-insider (i.e., uninformed) trades. Based on these results, various scholars have argued for the legalization of insider trading to facilitate rapid price discovery. We analyze the trading activity of a confessed inside trader, Ivan Boesky, in Carnation's stock just prior to Nestle's 1984 acquisition of Carnation, and find that our tests are unable to distinguish the price effect of Boesky's (i.e., informed) purchases of Carnation's stock from the effect of non-insider (i.e., uninformed) purchases. Our conclusion survives extensive robustness tests and has methodological and public policy implications.
154 citations
TL;DR: This article examined the impact of competition on bid-ask spreads in the spot foreign exchange market and found that the expected level of competition is time varying, highly predictable, and displays a strong seasonal component that is induced by geographic concentration of business activity over the 24-hour trading day.
Abstract: This study examines the impact of competition on bid-ask spreads in the spot foreign exchange market. We measure competition primarily by the number of dealers active in the market and find that bid-ask spreads decrease with an increase in competition, even after controlling for the effects of volatility. The expected level of competition is time varying, highly predictable, and displays a strong seasonal component that in part is induced by geographic concentration of business activity over the 24-hour trading day. Our estimates show that the expected addition of one more competing dealer lowers the average quoted spread by 1.7%. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.
144 citations
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TL;DR: In this paper, the authors analyze trading volume around ex-dividend days and find evidence of significant abnormal volume by securities dealers that is positively related to dividend yield and negatively related to transaction costs.
Abstract: We analyze trading volume around ex-dividend days. We use NYSE audit file data to decompose total trading volume by trader type. These data permit us to directly test detailed hypotheses regarding the identity of traders around the ex-dividend day. We are able to distinguish between dividend-capture trading by taxable corporations and short-term trading by securities dealers. We find evidence of significant abnormal volume by securities dealers that is positively related to dividend yield and negatively related to transaction costs. We also document some abnormal trading volume consistent with corporate dividend-capture trading, but little evidence of tax-clientele trading.
103 citations
TL;DR: In this paper, the authors use The Wall Street Journal's "Investment Dartboard" column, which stimulates noise trading, as a natural experiment to evaluate models of the bid-ask spread and find that substantial increases in trading volume and significant but temporary abnormal returns occur when analysts recommend stocks in this column.
Abstract: How does increased noise trading affect market liquidity and trading costs? We use The Wall Street Journal’s “Investment Dartboard” column, which stimulates noise trading, as a natural experiment to evaluate models of the bid-ask spread. We find that substantial increases in trading volume and significant but temporary abnormal returns occur when analysts recommend stocks in this column, especially when recommendations come from analysts with successful contest track records. We also find an increase in liquidity and a decrease in the adverse selection component of the bid-ask spread. HOW DOES INCREASED NOISE TRADING affect market liquidity and trading costs? A common thread of the theoretical market-microstructure literature suggests that noise trading allows specialists to recoup losses from trades with better-informed investors. 1 Theory states that with lower adverse selection costs the equilibrium bid-ask spread falls and market liquidity increases. Not all bid-ask spread models arrive at this result, however. Some show increased noise trading merely providing cover for informed investors, affecting the spread either not at all or ambiguously. Though noise trading actually constitutes a fundamental component of most microstructure models, little or no empirical evidence exists to reveal the effect of noise-trading changes on liquidity. This lack of evidence is perhaps due to the difficulty of identifying sudden, large shifts in noise trading. Identifying noise trading’s pure effect on liquidity requires an environment in which exogenous noisetrading changes can be observed and the subsequent behavior of marketmakers can be measured. In this paper, we use a “natural experiment” with precisely these characteristics to study the relationship between noise trading and liquidity. Our results support theoretical models that derive a positive relationship between noise trading and liquidity.
94 citations
TL;DR: In this paper, the eAect of discount rate changes on stock market returns, volatility, and trading volume using intraday data was examined. And the results indicated that equity prices respond to announcements within the trading period/hour after the information release.
Abstract: We examine the eAect of discount rate changes on stock market returns, volatility, and trading volume using intraday data. Equity returns generally respond negatively and significantly to the unexpected announcements; however, the eAect of expected changes on equity returns is insignificant. Furthermore, our results indicate that equity prices respond to announcements within the trading period/hour after the information release. An indication of a return reversal is too small to cover the full transaction costs. Unexpected discount rate changes also contribute to higher market volatility although the volatility is short-lived. Similarly, unexpected changes in discount rates induce larger trading volume while expected changes do not. Abnormal trading volume occurs only in period t. Our results also support the notion that unexpected changes in the discount rates impact market returns irrespective of the Federal Reserve operating procedures. ” 1999 Elsevier Science B.V. All rights reserved.
81 citations
TL;DR: The authors apply stochastic dynamic programming to derive trading strategies that minimize the expected cost of executing a portfolio of securities over a fixed time period.
Abstract: The authors apply stochastic dynamic programming to derive trading strategies that minimize the expected cost of executing a portfolio of securities over a fixed time period. They test their strategies using real-world stock data.
79 citations
TL;DR: This paper illustrates how electronic commerce enables all-in-one markets, and considers the opportunities and challenges they pose for buyers, sellers, and third-party market makers.
Abstract: Electronic commerce has made possible a new form of electronic marketplace-the "all-in-one market." All-in-one markets combine multiple trading mechanisms on a common platform and organize trading so that buyers and suppliers can dynamically shift trading methods or simultaneously take advantage of the best features of open market competition and long-term supplier partnerships. Firms that effectively leverage these new platforms are likely to realize substantial benefits in their sourcing and distribution strategies. This paper illustrates how electronic commerce enables all-in-one markets, and considers the opportunities and challenges they pose for buyers, sellers, and third-party market makers.
TL;DR: In this paper, a generalized version of the Random Field Ising Model (RFIM) is introduced to describe trading behavior and a trade friction is introduced which, by responding to price movements, creates a feedback mechanism on future trading and generates volatility clustering.
Abstract: We propose a model with heterogeneous interacting traders which can explain some of the stylized facts of stock market returns. A generalized version of the Random Field Ising Model (RFIM) is introduced to describe trading behavior. Imitation effects, which induce agents to trade, can generate avalanches in trading volume and large gaps in demand and supply. A trade friction is introduced which, by responding to price movements, creates a feedback mechanism on future trading and generates volatility clustering.
TL;DR: In this paper, the authors examine intraday price leadership across the S&P 500, NYSE Composite, and MMI futures, and across the respective cash indexes, and find that, among the futures, the SP 500 exhibits price leadership over the other index futures, whereas among the cash indexes the MMI leads.
Abstract: The focus of this article is to test the trading cost hypothesis of price leadership, which predicts that the market with the lowest overall trading costs will react most quickly to new information. In an attempt to hold market microstructure effects constant and in contrast to previous studies, we examine intraday price leadership across the S&P 500, NYSE Composite, and MMI futures, and across the respective cash indexes—rather than between each futures and its associated cash index. We find that, among the futures, the S&P 500 exhibits price leadership over the other index futures, whereas among the cash indexes the MMI leads. Both findings are consistent with the trading cost hypothesis. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 475–498, 1999
TL;DR: In this article, the authors argue that alternative trading systems play a distinct role in the market and in particular solve the conflict-of-interest problem that exists between brokers and dealers, and propose a general strategy for their regulation that incorporates this economic role.
Abstract: New trading technologies are transforming securities markets, and with their rise have come important questions regarding the regulation of new and traditional trading mechanisms. This article provides a law and economics perspective on the regulation of alternative trading systems. We argue that alternative trading systems play a distinct role in the market and in particular solve the conflict‐of‐interest problem that exists between brokers and dealers. We propose a general strategy for their regulation that incorporates this economic role. We suggest a regulatory framework that permits providers of services to opt into particular regulatory frameworks as a way of fostering innovation and competition. The functional approach we outline is consistent with the Securities and Exchange Commission's regulatory objectives of fairness, efficiency, and transparency of market transactions.
01 Jan 1999
TL;DR: In this paper, the authors explore the empirical relationship among insider trading law, other legal rules and institutions, and equity markets in an international context and find that tougher insider trading laws are negatively and significantly related to the degree of ownership concentration in publicly traded companies.
Abstract: This paper explores the empirical relationship among insider trading law, other legal rules and institutions, and equity markets in an international context. In particular, using legal and economic data from a cross-section of countries, I investigate two empirical relationships: the relationship between insider trading law and ownership concentration and the relationship between insider trading law and equity market liquidity. Consistent with agency theories which predict that the ability of insiders to engage in uninhibited trading encourages concentrated share ownership, I find that tougher insider trading laws are negatively and significantly related to the degree of ownership concentration in publicly traded companies. That is, in economic regimes where insider trading is more stringently regulated, large shareholders hold a significantly lower fraction of outstanding shares. In addition, consistent with market microstructure theories of the relationship between asymmetric information and trading costs, I find that weaker insider trading regimes have, on average, less liquid equity markets. It is hoped that the findings of this paper will inform the ongoing law and economics debate over the desirability of regulating trading by corporate insiders. John M. Olin Fellow in Law and Economics, Harvard Law School; J.D., Harvard Law School, 1999; and Ph.D. candidate, Department of Economics, Harvard University.
TL;DR: In this paper, the authors examined changes in the volatility of the underlying shares in the cash market using an asymmetric exponential ARCH model and concluded that the introduction of futures trading has had very little impact on cash market volatility.
TL;DR: In this paper, the impact of commodity pool trading on futures price volatility was analyzed for the period 1 December 1988 through 31 March 1989 for 36 different futures markets, including the daily trading volume of large commodity pools.
Abstract: A major issue in recent years is the role that large, managed futures funds and pools play in futures markets Many market participants argue that managed futures trading increases price volatility due to the size of managed futures trading and reliance on positive feedback trading systems The purpose of this study is to provide new evidence on the impact of managed futures trading on futures price volatility A unique data set on managed futures trading is analyzed for the period 1 December 1988 through 31 March 1989 The data set includes the daily trading volume of large commodity pools for 36 different futures markets Regression results are unequivocal with respect to the impact of commodity pool trading on futures price volatility For the 72 estimated regressions (two for each market), the coefficient on commodity pool trading volume is significantly different from zero in only four cases These results constitute strong evidence that, at least for this sample period, commodity pool trading is not associated with increases in futures price volatility © 1999 John Wiley & Sons, Inc Jrl Fut Mark 19: 759–776, 1999
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TL;DR: In this article, the authors analyzed the dynamics of price formation for a strictly identical derivatives contract which is traded simultaneously at two competing exchanges and investigated whether the transparency of each trading system affects quote setting.
Abstract: This paper analyzes the dynamics of price formation for a strictly identical derivatives contract which is traded simultaneously at two competing exchanges. The domestic exchange is situated in the country that issues the underlying instrument. The foreign exchange offers a large international capital centre with many diversificationpossibilities. In addition, the exchanges are characterized by different trading systems. The domestic exchange operates by automated trading, the foreign exchange uses open outcry with an automated late afternoon session. We will investigate whether these differences support the trading system segmentation hypothesis. Our working hypothesis is two-fold. First, we investigate whether the transparency of each trading system affects quote setting. Second, we analyze whether the relative transparency of each market influences the lead/lag relationship between the two markets. Both hypotheses are empirically tested for the Bund futures contract as it is traded in London (LIFFE) and Frankfurt (DTB).
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01 Jan 1999TL;DR: In this paper, an analysis of the bid-ask spreads reveals that the electronic trading system is relatively less attractive for less liquid stocks and that the adverse selection component of the spread is larger.
Abstract: The last decade has witnessed a dramatic increase in both the number and the market share of screen-based trading systems. Electronic trading systems do offer lower operating costs and the possiblilty of remote access to the market. On the other hand, arguments based on the anonymity of electronic trading systems suggest that adverse selection may be a more severe problem and that, therefore, bid-ask spreads may be higher. The present paper addresses the issue of transaction costs in floor and computerized trading systems empirically. In Germany, floor and screen trading for the same stocks exist in parallel. Both markets are liquid and operate simultaneously for several hours each day. An analysis of the bid-ask spreads reveals that the electronic trading system is relatively less attractive for less liquid stocks. The market shares of the competing systems reveal a similar pattern. The market share of the electronic trading system is negatively related to the total trading volume of the stock, is positively related to the difference between spreads on the floor and in the screen trading system and is at least partially negatively related to return volatility. We further document that spreads in the electronic trading system respond more heavily to changes in return volatility and that the adverse selection component of the spread is larger. We discuss implications our results have for the design of electronic trading systems.
TL;DR: In this paper, the practical experience of the six major types of emissions trading systems, focusing on credit market development, participation and results, including transaction costs, is reviewed, with the potential contribution of the New Institutional Economics (NIE) to emissions trading.
TL;DR: In this paper, the authors examined the performance of intraday technical trading strategies selected using two methodologies, a genetic program and an optimized linear forecasting model, and found no evidence of excess returns to the trading rules derived with either methodology.
Abstract: This paper examines the out-of-sample performance of intraday technical trading strategies selected using two methodologies, a genetic program and an optimized linear forecasting model. When realistic transaction costs and trading hours are taken into account, we find no evidence of excess returns to the trading rules derived with either methodology. Thus, our results are consistent with market efficiency. We do, however, find that the trading rules discover some remarkably stable patterns in the data.
TL;DR: In this paper, the authors present methodological difficulties in using the Internet for market research and present a solution to overcome them. But, there are challenges in using this medium and there is much...
Abstract: At first sight the Internet seems to offer the perfect vehicle for the conduct of market research. However, there are challenging methodological difficulties in using this medium and there is much ...
TL;DR: In this paper, the authors developed a theoretical model to explain the permanent price impact asymmetry between buyer and seller-initiated block trades, which showed how the trading strategy of institutional portfolio managers creates a difference between the information content of buys and sells.
Abstract: This paper develops a theoretical model to explain the permanent price impact asymmetry between buyer and seller-initiated block trades (the permanent price impact of buys is larger than that of sells). The model shows how the trading strategy of institutional portfolio managers creates a difference between the information content of buys and sells. The main implication of the model is that the history of price performance influences the asymmetry: The longer the run-up in a stock's price, the less the asymmetry. The intensity of institutional trading and the frequency of information events affect the asymmetry differently depending on recent price performance.
TL;DR: In this article, the authors examined the components of the bid-ask spread on the Sydney Futures Exchange and found that screen-based traders are more sensitive to market volatility than floor traders in setting the bidask spread.
TL;DR: In this article, the authors examined the impact of opening rules on stock market efficiency and found that the use of a call market enhances market efficiency by increasing liquidity and lowering volatility at the open, and some of the benefits associated with a call accrue even when there is no trading at the call.
Abstract: This paper examines the impact of opening rules on stock market efficiency In particular, it contrasts the opening call on the Australian Stock Exchange (ASX) and the continuous open on the Jakarta Stock Exchange (JSX) The results suggest that the use of a call enhances market efficiency by increasing liquidity and lowering volatility at the open The results also indicate that some of the benefits associated with a call accrue even when there is no trading at the call These results suggest that the use of a call market at the open may add to the efficiency of the JSX and other similar markets
05 Jan 1999
TL;DR: The paper is based on a series of controlled experiments in the trading of wholesale electricity that expands substantially the scope of the research program reported previously and compares two alternative institutional arrangements for the Trading of electric power.
Abstract: The paper is based on a series of controlled experiments in the trading of wholesale electricity that expands substantially the scope of the research program reported previously (S. Backerman S. Rassenti and V. Smith, 1998; S. Backerman, M. Denton, S. Rassenti and V. Smith, 1998; M. Denton et al., 1998). The experiments employed cash motivated students and rented computer laboratory facilities of the University of Arizona. The primary objective of these experiments was to compare two alternative institutional arrangements for the trading of electric power. The first employed day-ahead sealed bid trading of energy for all periods in the subsequent day; the second employed simultaneous continuous double auctions for bilateral trading of energy up to the hour before delivery. All trading was executed on an eight-node network with limited transmission capacity. Each node was to be thought of as a control area, with one large wholesale generator company and one large distribution company resident there.
TL;DR: The research demonstrates the efficacy of using neural network methods to capitalize on discovered market inefficiencies as it is applied to trading on market indices in the "emerging" Singapore market is compared with the more established Dow Jones market index.
Abstract: Emerging capital markets may not be as efficient as the more established equity markets. Because of the possible inefficiency in these markets, various indicators that are external to the emerging capital market may provide a significant trading advantage. A preliminary analysis suggests that the Singapore market appears to be efficient. Neural network models are used to evaluate the claim that emerging equity markets, specifically the Singapore exchange, are affected by external signals and attempt to exploit any trading advantage imparted by these signals. The neural network technique as it is applied to trading on market indices in the "emerging" Singapore market is compared with the more established Dow Jones market index. Results indicate that external market signals can significantly improve forecasting on the Singapore DBS50 index but have little or no effect on forecasts for the more established Dow Jones Industrial Average index. The research demonstrates the efficacy of using neural network methods to capitalize on discovered market inefficiencies. Utilizing external market signals, a neural network forecasting model achieved a 63 percent trading prediction accuracy.
TL;DR: In this article, the authors examined the effect of the London Stock Exchange's market reforms on the trading costs of "public" investors and found that the overall gain of public investors in terms of the realised half-spread is not significantly different from zero.
Abstract: In October 1997, the London Stock Exchange removed the obligation of dealers to quote firm two-way prices for FTSE 100 index stocks, and allowed the public to compete directly with dealers in these stocks through the submission of limit orders. This article examines the effects of these market reforms on the trading costs of "public" investors, the targeted beneficiary of the reforms, and documents several interesting results. First, the duly signed average effective half-spread of public investors has decreased much more than the corresponding decrease in the absolute effective half-spread documented by Barclay et. al. (1998) for NASDAQ. This is because a sub-set of public investors trade through limit orders, and thereby earn the spread rather than pay it. Second, consistent with the change from obligatory to voluntary market making, there is a significant increase in the "positioning revenue" earned by dealers from a change in the price of a stock while they are carrying the stock in their inventory. As a result, the overall gain of public investors in terms of the realised half-spread is not significantly different from zero. Third, the cross-subsidisation across trade sizes has disappeared, leading to a significant decline in the average execution costs of small public trades and an increase for large public trades. Fourth, the market reforms have caused negative externalities for stocks not going through the new trading system. Finally, in the absence of the price stabilisation provided earlier by dealers, the inside half-spread has increased very sharply in the first hour of trading - a finding which highlights the need for special opening procedures for electronic order books.
TL;DR: The Santa Fe Artificial Stock Market consists of a central computational market and a number of artificially intelligent agents, which make their investment decisions by attempting to forecast the future return on the stock, using genetic algorithms to generate, test, and evolve predictive rules.
Abstract: The Santa Fe Artificial Stock Market consists of a central computational market and a number of artificially intelligent agents. The agents choose between investing in a stock and leaving their money in the bank, which pays a fixed interest rate. The stock pays a stochastic dividend and has a price which fluctuates according to agent demand. The agents make their investment decisions by attempting to forecast the future return on the stock, using genetic algorithms to generate, test, and evolve predictive rules. The artificial market shows two distinct regimes of behavior, depending on parameter settings and initial conditions. One regime corresponds to the theoretically predicted rational expectations behavior, with low overall trading volume, uncorrelated price series, and no possibility of technical trading. The other regime is more complex, and corresponds to realistic market behavior, with high trading volume, high intermittent volatility (including GARCH behavior), bubbles and crashes, and the presence of technical trading. One parameter that can be used to control the regime is the exploration rate, which governs how rapidly the agents explore new hypotheses with their genetic algorithms. At a low exploration rate the market settles into the rational expectations equilibrium. At a high exploration rate it falls into the more realistic complex regime. The transition is fairly sharp, but close to the boundary the outcome depends on the agents’ initial “beliefs”—if they believe in rational expectations they occur and are a local attractor; otherwise the market evolves into the complex regime.
TL;DR: In this paper, the authors assess whether some simple forms of technical analysis can predict stock price movements in the Madrid Stock Exchange and show that returns obtained from these trading rules are not consistent with several null models frequently used in finance, such as AR(1) GARCH and GARCH-M.
Abstract: In this paper we assess whether some simple forms of technical analysis can predict stock price movements in the Madrid Stock Exchange To that end, we use daily data for General Index of the Madrid Stock Exchange, covering the thirty-one-year period from January 1966-October 1997 Our results provide strong support for profitability of these technical trading rules By making use of bootstrap techniques, we show that returns obtained from these trading rules are not consistent with several null models frequently used in finance, such as AR(1) GARCH and GARCH-M