Filter Tests In Nasdaq Stocks

This study examines the performance of filter and dual moving-average crossover trading rules applied to Nasdaq stocks. We find that trading rules conditioned on a stock's past price history perform poorly, but those based on past movements in the overall Nasdaq Index tend to earn statistically significant abnormal returns. Since there is a high level of transaction costs in this market, these abnormal returns are generally not economically significant. However, there are indications that pursuing some of these strategies can be worthwhile in carefully selected subsets of stocks.     

Global industry portfolios and short-term predictability of returns: Is it there?

This paper explores the degree of success of a large set of active trading rules that have been popularized in the literature on the short-term predictability of returns in equity and foreign exchange markets by extending the scope of research in three dimensions: global portfolios, industry portfolios, and exclusive versus inclusive portfolios. Our results show that after adjusting for (1) the impact of nonsynchronous prices in the reported closing index levels which causes spurious autocorrelations in returns, (2) data snooping bias caused by searching through a large number of possible trading strategies in order to find a few that yield superior in-sample performance, and (3) transaction costs that reduce any profits from active trading, the risk-adjusted profits generated by short-term trend chasing trading rules are generally not statistically significant and the hypothesis of no outperformance of trading rules over either buy-and-hold or risk-free benchmark return cannot be rejected in most industries. Such findings favor short-term market efficiency and are hardly comforting for active traders.     

Reexamining the Profitability of Technical Analysis with Data Snooping Checks

In this article we reexamine the profitability of technicalanalysis using White’s reality check and Hansen’sSPA test that correct the data snooping bias. Compared to previousstudies, we study a more complete "universe" of trading techniques,including not only simple rules but also complex trading strategies,and we test the profitability of these rules and strategieswith four main indices. It is found that significantly profitablesimple rules and complex trading strategies do exist in thedata from relatively "young" markets (NASDAQ Composite and Russell2000) but not in the data from relatively "mature" markets [DowJones Industrial Average (DJIA) and S&P 500]. Moreover,after taking transaction costs into account, we find that thebest rules for NASDAQ Composite and Russell 2000 outperformthe buy-and-hold strategy in most in- and out-of-sample periods.It is also found that complex trading strategies are able toimprove on the profits of simple rules and may even generatesignificant profits from unprofitable simple rules.     

Secret Reserves or Special Credits? A Reappraisal of the Reserve and Provision Accounting Policies of the Roy Mail Steam Packet Company, 1915–27

The Royal Mail case (Rex v Kylsant and another) in 1931 is generally seen as central to the appraisal of secret reserve accounting by companies in the first part of this century. Although the case shows that Royal Mail's accounts disguised the decline in their trading profits, it does not convincingly establish secret reserves as the major cause of this deception. In this paper, information contained in the company's internal records provides the basis for an alternative view, that secret reserves were established during the war years, through accelerated depreciation charges, but were not used to enhance profits after trading conditions became more difficult. Instead it is argued that the reported profits for 1922-27 were largely dependent upon a range of (undisclosed) non-trading incomes of the period.     

An analysis of commodity markets: What gain for investors?

In this paper we study whether the commodity futures market predicts the commodity spot market. Using historical daily data on four commodities—oil, gold, platinum, and silver—we find that they do. We then show how investors can use this information on the futures market to devise trading strategies and make profits. In particular, dynamic trading strategies based on a mean–variance investor framework produce somewhat different results compared with those based on technical trading rules. Dynamic trading strategies suggest that all commodities are profitable and profits are dependent on structural breaks. The most recent global financial crisis marked a period in which commodity profits were the weakest.     

Market ecologies: The effect of information on the interaction and profitability of technical trading strategies

Technical trading strategies make profits by identifying and exploiting patterns in market prices—patterns generated by the interaction of market participants. Using a model market populated by individuals using a range of trading rules we show that the presence of technical traders may be beneficial, in some cases reducing volatility and increasing price efficiency. In particular, contrarian traders who base their decisions on high frequency data have the largest positive effect. It is also found that if technical traders condition their actions using ‘real time’ information, they partially emulate arbitrageurs and make positive profits.     

Efficiency of the silver futures market: An empirical study using daily data

This paper investigates whether the silver futures market is efficient with respect to the information contained in the time series of daily price changes. An analysis of the serial correlation of returns on silver futures supports the hypothesis that successive price changes are independent. However, a series of first and second order Markov chain models built using the direction as well as the magnitude of price change, reveals some short-term dependence. This result regarding the non-independence of successive price changes is reinforced by an analysis of upward and downward cycles, and by the extraordinary profits generated by using mechanical filter rules. The conclusion of this study is that the silver futures market does not seem to be efficient even in the weak form and that astute traders and investors can make modest excess risk-adjusted returns by using appropriate trading strategies.     

The effect of public information and competition on trading volume and price volatility

In a one-period model of market making with many exogenouslyinformed traders, we first show that the variance of pricesand expected trading volume depend on the public informationreleased at the start of trading. This is accomplished by representingbeliefs with elliptically contoured distributions, for whichthe form of optimal decision rules does not depend on the specificdistribution used. Second, if the model is altered so that thedecision to become informed is made endogenous, then the decisionrules of the market-maker and informed traders depend on thepublic information. Third, in a multiperiod model with manyinformed traders and long-lived private information, recursionformulas similar to those of Kyle (1985) hold for all ellipticallycontoured distributions, trading volume is autocorrelated and,unless per period liquidity trading is bounded away from zeroas new trading periods are added, informed traders' profitsvanish.     

Forecasting annual excess stock returns via an adaptive network‐based fuzzy inference system

In this study, an adaptive network‐based fuzzy inference system (ANFIS) and a neural network were tested for the ability of these techniques to forecast the annual excess returns of three large publicly traded companies from a time series of said returns. The predictive ability of these techniques was compared with that of an autoregressive moving average (ARMA) model. The Fair–Shiller test was used in the comparisons in order to obtain results that were not subjective and so that conclusions could be made regarding the information used by the techniques in the generation of their forecasts. Since predictive ability does not translate to profitability, a simple trading strategy was used to determine the ability to generate profits from trading upon the forecasts of the respective techniques. As hypothesized, the ANFIS and neural network techniques are able to generate forecasts with significant predictive ability. However, neither technique dominates the other or the ARMA model. In tests of the ability of the techniques to generate profits from their forecasts, a simple trading strategy was used (trading on the predicted sign of the return). The ANFIS and the neural network generated profits in all of the trading scenarios. However, neither technique dominated the other, nor did they consistently outperform the traditional and naive models (strategies). The mixed results in the predictive ability tests and the profitability tests indicate that the conclusions from the study differ based upon the context in which the forecasts are used. Copyright © 2005 John Wiley & Sons, Ltd.     

Point and Figure charting: A computational methodology and trading rule performance in the S&P 500 futures market

This paper empirically contributes to the existing trading rule literature by providing a methodology for the calculation of Point and Figure charts using ultra-high-frequency data and tests trading rules using eight objective, pre-defined trading rules on S&P 500 futures contracts traded between 1990 and 1998. To assess the robustness of reported profits, a bootstrapping adjustment was conducted to determine the forecasting power of the PF trading rules. The results producing mixed statistical significance with some rules proving significant while many others were not.     

The rise and fall of technical trading rule success

The purpose of this paper is to examine the performance of an important set of momentum-based technical trading rules (TTRs) applied to all members of the Dow Jones Industrial Average (DJIA) stock index over the period 1928–2012. Using a set of econometric models that permit time-variation in risk-adjusted returns to TTR portfolios, the results reveal that profits evolve slowly over time, are confined to particular episodes primarily from the mid-1960s to mid-1980s, and rely on the ability of investors to short-sell stocks. These findings are demonstrated to be consistent with theoretical models that predict a relationship between TTR performance and market conditions.     

On market efficiency of Asian foreign exchange rates: evidence from a joint variance ratio test and technical trading rules

This study employs a joint variance ratio test and technical trading rules to examine the random walk behavior for nine Asian foreign exchange rates for the period 1988–1995. The joint variance ratio test results suggest that there is little evidence of serial correlations in the daily exchange rate series. The results also indicate that, in general, the moving average and channel trading rules do not generate significant, positive profits.     

Insider Trading and Pay‐Performance Sensitivity: An Empirical Analysis

Abstract:   We examine whether the sensitivity of pay to performance is associated with the amount of insider trading that managers undertake. Because insider trading profits represent an alternative form of compensation, we expect that firms will consider the compensation component provided by insider trading when designing remuneration contracts. Employing a proxy for insider trading that captures the degree to which managers trade on private information, we find evidence that an increased (a decreased) level of insider trading is associated with a decreased (an increased) pay‐performance sensitivity.     

An analysis of trading strategies in eleven European stock markets

Abstract

In recent years, the validity of the weak form efficient market hypothesis (EMH) has been called into question as several studies have uncovered evidence that technical trading rules have predictive ability with respect to both developed and emerging stock market indices. This study analyses the forecasting power of 2 of the most popular trading rules using index data for a selection of 11 European stock markets over the January 1991 to December 2000 period. The findings indicate that the emerging markets included in this paper are informationally inefficient; these markets displayed some degree of predictability in their share returns, although the developed markets did not. Furthermore, the results point to large differences in the performance of the rules examined; while small size filters consistently outperformed the buy-and-hold strategy in the emerging markets examined even after the consideration of transaction costs, the performance of the moving average rules was erratic and varied dramatically from market to market.     

Co‐evolved genetic programs for stock market trading

The profitability of trading rules evolved by three different optimised genetic programs, namely a single population genetic program (GP), a co‐operative co‐evolved GP, and a competitive co‐evolved GP is compared. Profitability is determined by trading thirteen listed shares on the Johannesburg Stock Exchange (JSE) over a period of April 2003 to June 2008. An empirical study presented here shows that GPs can generate profitable trading rules across a variety of industries and market conditions. The results show that the co‐operative co‐evolved GP generates trading rules perform significantly worse than a single population GP and a competitively co‐evolved GP. The results also show that a competitive co‐evolved GP and the single population GP produce similar trading rules. The profits returned by the evolved trading rules are compared to the profit returned by the buy‐and‐hold trading strategy. The evolved trading rules significantly outperform the buy‐and‐hold strategy when the market trends downwards. No significant difference is identified among the buy‐and‐hold strategy, the competitive co‐evolved GP, and single population GP when the market trends upwards.     

The Impact of Portfolio Diversification on Trading Rules Profits: Some Evidence for UK Share Portfolios

This paper demonstrates how the autocorrelation structure of UK portfolio returns is linked to dynamic interrelationships among the component securities of that portfolio. Moreover, portfolio return autocorrelation is shown to be an increasing function of the number of securities in the portfolio. Since the security interrelationships seemed to be more a product of their history of non-synchronous trading than of systematic industry-related phenomena, it should not be possible to exploit the high levels of return persistence using trading rules. We show that rules designed to exploit this portfolio autocorrelation structure do not produce economic profits.     

Do momentum-based strategies work in emerging currency markets?

Existing studies on the profitability of trading rules in the currency market focus mainly on the currencies of developed countries. The profitability of technical trading rules on the currencies of emerging economies is surprisingly understudied. This paper evaluates the profitability of technical trading rules in emerging currency markets. Similar to Okunev and White [Okunev, J. and White, D., (2003) “Do Momentum-based Strategies Still Work in Foreign Currency Markets?” Journal of Financial and Quantitative Analysis 38, 425–447.], 354 long/short moving average rules for six currencies are investigated. It is found that investing in emerging currencies can generate a considerable annual return of over 20%, even after a 5% annual transaction cost is imposed. The trading-rule profits are relatively stable across the 20 year sample period. Furthermore, the impact of financial crises on the trading-rule returns is also examined. It is found that the profitability of the trading rules is improved after the crises.     

Market Efficiency and the Returns to Simple Technical Trading Rules: New Evidence from U.S. Equity Market and Chinese Equity Markets

Numerous studies in the finance literature have investigated technical analysis to determine its validity as an investment tool. This study is an attempt to explore whether some forms of technical analysis can predict stock price movement and make excess profits based on certain trading rules in markets with different efficiency level. To avoid using arbitrarily selected 26 trading rules as did by Brock, Lakonishok and LeBaron (1992) and later by Bessembinder and Chan (1998), this paper examines predictive power and profitability of simple trading rules by expanding their universe of 26 rules to 412 rules. In order to find out the relationship between market efficiency and excess return by applying trading rules, we examine excess return over periods in U.S. markets and also compare the excess returns between U.S. market and Chinese markets. Our results found that there is no evidence at all supporting technical forecast power by these trading rules in U.S. equity index after 1975. During the 1990s break-even costs turned to be negative, –0.06%, even failing to beat a buy-holding strategyin U.S. equity market. In comparison, our results provide support for the technical strategies even in the presence of trading cost in Chinese stock markets.     

Trading performance and market efficiency: Evidence from algorithmic trading

In India, National Stock Exchange directly identifies algorithmic trading participation. Algorithmic traders possess intraday market timing skills. Results are not motivated by extreme short-term signals or transitory price trading. Magnitude of market timing performance in cross-sectional group of traders shows that they earn profit across all the cases, and maximize while providing liquidity. Volume-weighted-average-price decomposition analysis reports algorithmic traders earn profits through intraday market timing performance for five-minute and one-minute intervals, and it is higher compared to short-term market timing performance across all trader groups. Order imbalance and price delay regressions show that algorithmic trading significantly improves price efficiency.