The Cost of Technical Trading Rules in the Forex Market: A Utility-based Evaluation

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We compute the opportunity cost for rational risk averse agents of using technical trading rules in the foreign exchange rate market. Our purpose is to investigate whether these rules can be interpreted as near-rational investment strategies for rational investors. We analyze four different exchange rates and find that the opportunity cost of using chartist rules tends to be prohibitively high. We also present a method to decompose this opportunity cost into parts related to investor's irrationality and misallocation of wealth. The results show that irrationality of chartist beliefs is an important component of the total opportunity cost of using technical trading rules.


M of a Kind: A Multivariate Approach at Pairs Trading

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Pairs trading is a popular trading strategy that tries to take advantage of market inefficiencies in order to obtain profit. Such approach, on its classical formulation, uses information of only two stocks (a stock and its pairs) in the formation of the trading signals. The objective of this paper is to suggest a multivariate version of pairs trading, which will try to create an artificial pair for a particular stock based on the information of m assets, instead of just one. The performance of three different versions of the multivariate approach was assessed for the Brazilian financial market using daily data from 2000 to 2006 for 57 assets. Considering realistic transaction costs, the analysis of performance was conducted with the calculation of raw and excessive returns, beta and alpha calculation, and the use of bootstrap methods for comparing performance indicators against portfolios build with random trading signals. The main conclusion of the paper is that the proposed version was able to beat the benchmark returns and random portfolios for the majority of the parameters. The performance is also found superior to the classic version of the strategy, Perlin (2006b). Another information derived from the research is that the proposed strategy picks up volatility from the data, that is, the annualized standard deviations of the returns are quite high. But, such event is paid by high positive returns at the long and short positions. This result is also supported by the positive annualized sharpe ratios presented by the strategy. Regarding systematic risk, the results showed that the proposed strategy does have a statistically significant beta, but it isn't high in value, meaning that the relationship between return and risk for the trading rules is still attractive.

The New Stock Market: Sense and Nonsense

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How stocks are traded in the United States has been totally transformed. Gone are the dealers on NASDAQ and the specialists at the NYSE. Instead, a company’s stock can now be traded on up to sixty competing venues where a computer matches incoming orders. A majority of quotes are now posted by high-frequency traders (HFTs), making them the preponderant source of liquidity in the new market.

Many practices associated with the new stock market are highly controversial, as illustrated by the public furor following the publication of Michael Lewis’s book Flash Boys. Critics say that HFTs use their speed in discovering changes in the market and in altering their orders to take advantage of other traders. Dark pools – off-exchange trading venues that promise to keep the orders sent to them secret and to restrict the parties allowed to trade – are accused of operating in ways that injure many traders. Brokers are said to mishandle customer orders in an effort to maximize the payments they receive in return for sending trading venues their customers’ orders, rather than delivering best execution.

In this paper, we set out a simple, but powerful, conceptual framework for analyzing the new stock market. The framework is built upon three basic concepts: adverse selection, the principal-agent problem, and a multi-venue trading system. We illustrate the utility of this framework by analyzing the new market’s eight most controversial practices. The effects of each practice are evaluated in terms of the multiple social goals served by equity trading markets.

We ultimately conclude that there is no emergency requiring immediate, poorly-considered action. Some reforms proposed by critics, however, are clearly desirable. Other proposed reforms involve a tradeoff between two or more valuable social goals. In these cases, whether a reform is desirable may be unclear, but a better understanding of the tradeoff involved enables a more informed choice and suggests where further empirical research would be useful. Finally, still other proposed reforms are based on misunderstandings of the market or of the social impacts of a practice and should be avoided.


Head and Shoulders: Not Just a Flaky Pattern

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This paper evaluates rigorously the predictive power of the head-and-shoulders pattern as applied to daily exchange rates. Though such visual, nonlinear chart patterns are applied frequently by technical analysts, our paper is one of the first to evaluate the predictive power of such patterns. We apply a trading rule based on the head-and-shoulders pattern to daily exchange rates of major currencies versus the dollar during the floating rate period (from March 1973 to June 1994). We identify head-and-shoulders patterns using an objective, computer-implemented algorithm based on criteria in published technical analysis manuals. The resulting profits, replicable in real-time, are then compared with the distribution of profits for 10,000 simulated series generated with the bootstrap technique under the null hypothesis of a random walk.

Day of the Week Effects in NSE Stock Returns: An Empirical Study

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The presence of the seasonal or monthly effect in stock returns has been reported in several developed and emerging stock markets. This study investigates the existence of seasonality in India's stock market, primarily trying to detect the "Day of the Week Effect" in the Stocks listed on the National Stock Exchange. It covers the post-reform period. The study uses the Daily return data of the stocks listed on National Stock Exchange and Bombay Stock Exchange Index for the period from November 1994 to September 2007 for analysis. After examining the stationarity of the return series, by applying "Kruskal Wallis" test and "One Way Anova" i.e. using both Parametric and Non Parametric Tests, we specify an Augmented Dummy Regressive model to find the Day of the week effect monthly effect in stock returns in India. Another feature of our study was that we analysed the day of the week effect in three different phases of market ie. "Consolidation" Phase, "Bearish" Phase and the "Bullish" Phase. This was carried with an intention to see whether the day of the week effect was visible in these specific market phases or not. The results confirm the existence of seasonality (in the form of Day of the Week Effect) stock returns in India for 66 Stocks spanning across various sectors that we analysed - The results of the study imply that the stock market in India is inefficient, and hence, investors can time their share investments to improve returns and make abnormal profits. However the Day of the Week effect was found to be absent in the Bullish as well as the Bearish phase, which was a departure from our previous belief of the existence of this effect in all phases of the market.

Predator-Prey: An Alternative Model of Stock Market Bubbles and the Business Cycle (Non-technical Version)

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For the last quarter of a century or so, the Real Business Cycle (or "RBC") model has stood as the dominant interpretation of the business cycle in mainstream economics, although throughout this long period a significant number of relevant empirical objections have been raised, both regarding its fit to "real" aggregate data and its consistency of its predictions regarding the expected behaviour of the financial markets throughout the process. All this suggests there is room to explore an alternative model. This paper proposes to base such a model on a predator-prey mechanism, along the lines of the classical Lotka-Volterra model for ecosystem dynamics, in which agency costs play the role of the predatory activity. The result is a system where "producers" (i.e., those in direct, hands-on contact with production) gradually gain control of the productive process when the times are good, and use this control to enhance their own well-being at the expense of the investors (thus increasing agency costs) until this depredation drives the system into a crisis that leads the investors to tighten their bureaucratic controls on the producers, which eventually brings the system back to the growth path. In this context, the introduction of the Efficient Markets Hypothesis in the model of course results in the resulting cycle being fully discounted from the future expected path by the rational investors but, as the market rate of return is assumed to be subject to a random walk perturbation, the growth rate that will most approximate the one in a time series of empirical observations (i.e., the one minimising the tracking error) is the median path, not the mean (whereas the market discounts the future impact of the cycle from the mean, i.e., the "expected" path, not the median) - hence, we should expect the cycle to appear on the observed time series even though market efficiency precludes it from the future expected path. Consistently with this, the resulting model also predicts that observed stock market valuations would present instances of bubbles and crashes more or less synchronised with the Business Cycle, without this implying any irrational behaviour on the part of the investors. Based on a preliminary analysis of the features of this model against well-known stylised facts, this paper suggests that it may be able to perform better against empirical validation than the Real Business Cycle model.

Profitability of Oscillators Used in Technical Analysis for Financial Market

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This research paper aim to examine the profitability of various kinds of oscillator used in technical analysis on market index of NSE (National Stock Exchange) S&P CNX NIFTY 50 during 2004-2014. We have selected the most commonly used three oscillators i.e., Stochastic oscillator, RSI Oscillator and Commodity Channel Index (CCI). The results clearly express that CCI outperform the remaining two oscillators in terms of profitability for S&P CNX NIFTY 50 Index.

Hedge Fund Leverage

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We investigate the leverage of hedge funds using both time-series and cross-sectional analysis. Hedge fund leverage is counter-cyclical to the leverage of listed financial intermediaries and decreases prior to the start of the financial crisis in mid-2007. Hedge fund leverage is lowest in early 2009 when the leverage of investment banks is highest. Changes in hedge fund leverage tend to be more predictable by economy-wide factors than by fund-specific characteristics. In particular, decreases in funding costs and increases in market values forecast increases in hedge fund leverage. Decreases in fund return volatilities also increase leverage.


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