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This paper reviews research on momentum in asset markets, with an emphasis on research involving momentum in commodity markets. Commodity markets are different than the markets for financial assets, such as stocks and bonds. Storage costs, inventory levels, and hedging demand by suppliers and producers influence commodity prices in ways that may not be observed in other asset classes. Research indicates that momentum profits are related to these market structure factors. The persistence of momentum in commodity markets has implications for investment products that incorporate commodities. The popularity of commodity investments among institutional investors has increased dramatically in the past decade. While some investors have allocated funds to hedge funds that incorporate momentum-based strategies, most of these investments are in indices that do not have a momentum component to the return. Research indicates that adding a momentum component to a commodity portfolio may provide strategic benefits in the form of higher risk-adjusted returns and reduced volatility.

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... In addition, the leverage of these portfolios is fixed to 2:1 1 . This strategy is particularly interesting because it is the one used to track the momentum effect in most of the literature [Jeegadeesh and Titman (1993), Rouwenhorst (1998), Chan et al. (2000), Okunev and White (2003), Kazemi et al. (2009) and Billio et al. (2009) among others]. This LSEW strategy is also the base of pair trading [Gatev et al. (1999)]. ...

... This strategy is particularly interesting because it is the one used to track the momentum effect in most of the literature [Jeegadeesh and Titman (1993), Rouwenhorst (1998), Chan et al. (2000), Okunev and White (2003), Kazemi et al. (2009) and Billio et al. (2009) among others]. This LSEW strategy is also the base of pair trading [Gatev et al. (1999)]. ...

Sharpe-like ratios have been traditionally used to measure the performances of portfolio managers. However, they suffer two intricate drawbacks (1) they are relative to a perr's performance and (2) the best score is generally assumed to correspond to a "good" portfolio allocation, with no guarantee on the goodness of this allocation. In this paper, we propose a new measure to quantify the goodness of an allocation and we show how to estimate this measure in the case of the strategy used to track the momentum effect, namely the Zero-Dollar Long/Short Equally Weighted (LSEW) investment strategy. Finally, we show how to use this measure to timely close the positions of an invested portfolio.

... This strategy has been used in many other markets. It has been shown to generate significant positive returns in most international stock markets (Rouwenhorst (1998), Chan et al. (2000)), in commodities markets (Kazemi et al. (2009)) and in currency markets (Okunev and White (2003)). For an extensive review of the research about momentum, we refer to Kazemi et al. (2009). ...

... It has been shown to generate significant positive returns in most international stock markets (Rouwenhorst (1998), Chan et al. (2000)), in commodities markets (Kazemi et al. (2009)) and in currency markets (Okunev and White (2003)). For an extensive review of the research about momentum, we refer to Kazemi et al. (2009). Currently, it seems that momentum is a behavioral feature of finance. ...

This paper presents a novel theoretical framework to model the evolution of a dynamic portfolio (i.e., a portfolio whose weights vary over time), considering a given investment policy. The framework is based on graph theory and the quantum probability. Embedding the dynamics of a portfolio into a graph, each node of the graph representing a plausible portfolio, we provide the probabilities for a dynamic portfolio to lie on different nodes of the graph, characterizing its optimality in terms of returns. The framework embeds cross-sectional phenomena, such as the momentum effect, in stochastic processes, using portfolios instead of individual stocks. We apply our methodology to an investment policy similar to the momentum strategy of Jegadeesh and Titman (1993). We find that the strategy symmetry is a source of momentum.

... It is usual to consider that the leverage of these portfolios is 2:1 2 which is the leverage used in the following. This strategy is commonly used to track the momentum effect in most of the literature [Jegadeesh and Titman (1993), Rouwenhorst (1998), Chan et al. (2000), Okunev and White (2003), Kazemi et al. (2009) and Billio et al. (2011a) among others]. ...

Classification JEL : C - Mathematical and Quantitative Methods/C5 - Econometric Modeling/C58 - Financial Econometrics
URL des Documents de travail : http://centredeconomiesorbonne.univ-paris1.fr/bandeau-haut/documents-de-travail/

... Recent works include Shen, Szakmary and Sharma (2007) and Miffre and Rallis (2007). A pro-found overview can be found in Schneeweis, Kazemi and Spurgin (2007). ...

This study investigates the performance of large speculators in 22 commodity markets over the last 15 years. We find that large speculators were profitable in many markets. Two possible sources of returns are analyzed for their relevance in these gains: The ability to forecast and the flow of risk premia. In contrast to earlier studies we use direct test procedures for both assessments. We find very little evidence of market timing ability. However, employing the theory of storage and using a volatility measure to proxy for convenience yield, we observe consistent risk premium earnings. Furthermore, momentum may be seen as a third source of returns to speculative activity.

Using a state-of-the-art Markov switching framework augmented by popular proxies of arbitrage activity and investor sentiment, we reexamine the dynamics of stock momentum returns and provide a first structured time-series analysis of commodity momentum portfolios. Our study arrives at the important finding that, in contrast to previous studies relying on restrictive static models, we cannot detect persuasive links between momentum returns and such variables in recent data. Consequently, the evolution of momentum returns remains puzzling. Furthermore, putting the behavior of extremes aside, stock and commodity momentum returns exhibit quite similar regime-switching behavior. This supports the frequent statement that the financialization of commodity futures markets has non-trivially linked stock and commodity returns.

A feasible asset allocation framework for the post 2008 financial world Asset allocation has long been a cornerstone of prudent investment management; however, traditional allocation plans failed investors miserably in 2008. Asset allocation still remains an essential part of the investment arena, and through a new approach, you'll discover how to make it work. In The New Science of Asset Allocation, authors Thomas Schneeweis, Garry Crowder, and Hossein Kazemi first explore the myths that plague this field then quickly move on to examine how the practice of asset allocation has failed in recent years. They then propose new allocation models that employ liquidity, transparency, and real risk controls across multiple asset classes. Outlines a new approach to asset allocation in a post-2008 world, where risk seems hidden The "great manager" problem is examined with solutions on how to capture manager alpha while limiting downside risk A complete case study is presented that allocates for beta and alpha Written by an experienced team of industry leaders and academic experts, The New Science of Asset Allocation explains how you can effectively apply this approach to a financial world that continues to change. © 2010 Thomas Schneeweis, Garry B. Crowder, and Hossein Kazemi. All rights reserved.

This comprehensive reference delivers a toolkit for harvesting market rewards from a wide range of investments. Written by a world-renowned industry expert, the reference discusses how to forecast returns under different parameters. Expected returns of major asset classes, investment strategies, and the effects of underlying risk factors such as growth, inflation, liquidity, and different risk perspectives, are also explained. Judging expected returns requires balancing historical returns with both theoretical considerations and current market conditions. Expected Returns provides extensive empirical evidence, surveys of risk-based and behavioral theories, and practical insights.

Following large positive returns in 2008, CTAs received increased attention and allocations from institutional investors. Subsequent performance has been below its long term average. This has occurred in a period following the largest financial crisis since the Great Depression. In this article, using almost a century of data, the authors investigate what typically happens to the core strategy pursued by these funds in global financial crises. They also examine the time series behavior of the markets traded by CTAs during these crisis periods. Their results show that in an extended period following financial crises, trend following average returns are less than half of those earned in no-crisis periods. Evidence from regional crises shows a similar pattern. They also find that futures markets do not display the strong time series return predictability prevalent in no-crisis periods, resulting in relatively weak returns for trend following strategies in the four years immediately following the start of a financial crisis.

In this article we present theoretical considerations and empirical evidence that the short-run autoregressive behavior of commodity markets is not only driven by market fundamentals but also by the trading of speculators. To empirically test this, we individually fit smooth transition autoregression models to commodity price series and find in many cases that the autoregressive behavior of price changes turns more positive as the relative size of speculative positions increases. This is especially pronounced for recent years. We propose as an explanation a growing fraction of speculators who engage in momentum trading.

This study provides an update to Szado and Schneeweis [2010]. The original study covered the period from March 1999 through May 2009. This updated study extends the period of analysis through September 2010. The credit crisis and the associated decline in equity markets rekindled new interest in option based equity collars and in protective strategies in general. In this paper we consider the performance of passive and active implementations of the collar strategy on the QQQ ETF as well as on a sample small cap equity mutual fund. As expected, the results of the analysis show that a passive collar is most effective (relative to a long underlying position) in declining markets and less effective in rising markets. This study also considers a more active implementation of the collar strategy. Rather than simply applying a set of fixed rules as for the passive collar, in the active collar adjusted strategy, we apply a set of rules which adapt the collar to varying economic and market conditions. This approach is similar to applying a set of tactical asset allocation rules to a set of investments. There are of course an unlimited number of conditioning factors that can be used to determine the strategy implementation. In this paper, for purposes of presentation, we combine three conditioning factors that have been suggested in academic literature (momentum, volatility, and a compound macroeconomic factor (unemployment and business cycle)) to generate a dynamic collar adjusted trading strategy. For the period of analysis, the active collar adjustment strategy tends to outperform the passive collar both in-sample as well as out-of-sample. Judgments as to the particular benefits of the passive and active collar strategies are, of course, dependent on the risk tolerance of the individual investor.

Sharpe-like ratios have been traditionally used to measure the performances of portfolio managers. However, they are known to suffer major drawbacks. Among them, two are intricate : (1) they are relative to a peer's performance and (2) the best score is generally assumed to correspond to a "good" portfolio allocation, with no guarantee on the goodness of this allocation. Last but no least (3) these measures suffer significant estimation errors leading to the inability to distinguish two managers' performances. In this paper, we propose a cross-sectional measure of portfolio performance dealing with these three issues. First, we define the score of a portfolio over a single period as the percentage of investable portfolios outperformed by this portfolio. This score quantifies the goodness of the allocation remedying drawbacks (1) and (2). The new information brought by the cross-sectionality of this score is then discussed through applications. Secondly, we build a performance index, as the average cross-section score over successive periods, whose estimation partially answers drawback (3). In order to assess its informativeness and using empirical data, we compare its forecasts with those of the Sharpe and Sortino ratios. The results show that our measure is the most robust and informative. It validates the utility of such cross-sectional performance measure.

This paper evaluates various explanations for the profitability of momentum strategies documented in Jegadeesh and Titman (1993). The evidence indicates that momentum profits have continued in the 1990s, suggesting that the original results were not a product of data snooping bias. The paper also examines the predictions of recent behavioral models that propose that momentum profits are due to delayed overreactions that are eventually reversed. Our evidence provides support for the behavioral models, but this support should be tempered with caution.

The building blocks of the Sharpe ratio--expected returns and volatilities--are unknown quantities that must be estimated statistically and are, therefore, subject to estimation error. This raises the natural question: How accurately are Sharpe ratios measured? To address this question, I derive explicit expressions for the statistical distribution of the Sharpe ratio using standard asymptotic theory under several sets of assumptions for the return-generating process--independently and identically distributed returns, stationary returns, and with time aggregation. I show that monthly Sharpe ratios cannot be annualized by multiplying by the square root of 12 except under very special circumstances, and I derive the correct method of conversion in the general case of stationary returns. In an illustrative empirical example of mutual funds and hedge funds, I find that the annual Sharpe ratio for a hedge fund can be overstated by as much as 65 percent because of the presence of serial correlation in monthly returns, and once this serial correlation is properly taken into account, the rankings of hedge funds based on Sharpe ratios can change dramatically.

This paper examines the profitability of momentum strategies implemented on international stock market indices. Our results indicate statiscally significant evidence of momentum profits. The momentum profits arise mainly from time-series predictability in stock market indices very little profit comes from predictability in the currency markets. We also find higher profits for momentum portfolios implemented on markets with higher volume in the previous period, indicating that return continuation is stronger following an increase in trading volume. This result confirms the informational role of volume and its applicability in technical analysis.

This paper investigates the profitability of non-traditional momentum strategies using stock futures contracts. The results lead to the conclusion that these strategies dominate those implemented using stocks. Despite this, however, no positive returns are found during the sample period after adjusting for risk and transaction costs.

Portfolio strategies that buy stocks with high returns over the previous 3–12 months and sell stocks with low returns over
this same time period perform well over the following 12 months. A recent article by Conrad and Kaul (1998) presents striking evidence suggesting that the momentum profits are attributable to cross-sectional differences in expected
returns rather than to any time-series dependence in returns. This article shows that Conrad and Kaul reach this conclusion
because they do not take into account the small sample biases in their tests and bootstrap experiments. Our unbiased empirical
tests indicate that cross-sectional differences in expected returns explain very little, if any, of the momentum profits.

Using the longest dataset publicly available (The Economist's index of industrial commodity prices), we analyze the behavior of real commodity prices over the period 1862-1999 and have two main findings. First, while there has been a downward trend in real commodity prices of about 1 percent per year over the last 140 years, little support is found for a break in the long-run trend decline in commodity prices. Second, there is evidence of a ratcheting up in the variability of price movements. The amplitude of price movements increased in the early 1900s, while the frequency of large price movements increased after the collapse of the Bretton Woods regime of fixed exchange rates in the early 1970s. Although there is a down-ward trend in real commodity prices, this is of little practical policy relevance, since it is small and completely dominated by the variability of prices.

Previous work shows that average returns on common stocks are related to firm characteristics like size, earnings/price, cash flow/price, book-to-market equity, past sales growth, long-term past return, and short-term past return. Because these patterns in average returns apparently are not explained by the CAPM, they are called anomalies. We find that, except for the continuation of short-term returns, the anomalies largely disappear in a three-factor model. Our results are consistent with rational ICAPM or APT asset pricing, but we also consider irrational pricing and data problems as possible explanations.

Investors face numerous challenges when seeking to estimate the prospective performance of a long-only investment in commodity futures. For instance, historically, the average annualized excess return of the average individual commodity futures has been approximately zero and commodity futures returns have been largely uncorrelated with one another. The prospective annualized excess return of a rebalanced portfolio of commodity futures, however, can be "equity-like." Some security characteristics (such as the term structure of futures prices) and some portfolio strategies have historically been rewarded with above-average returns. It is important to avoid naive extrapolation of historical returns and to strike a balance between dependable sources of return and possible sources of return.

ABSTRACT Two easily measured variables, size and book-to-market equity, combine to capture the cross-sectional variation in average stock returns associated with market {3, size, leverage, book-to-market equity, and earnings-price ratios. Moreover, when the tests allow for variation in {3 that is unrelated to size, the relation between market {3 and average return is flat, even when {3 is the only explanatory variable. THE ASSET-PRICING MODEL OF Sharpe (1964), Lintner (1965), and Black (1972)

Recent empirical research in finance has uncovered two families of pervasive regularities: underreaction of stock prices to news such as earnings announcements, and overreaction of stock prices to a series of good or bad news. In this paper, we present a parsimonious model of investor sentiment, or of how investors form beliefs, which is consistent with the empirical findings. The model is based on psychological evidence and produces both underreaction and overreaction for a wide range of parameter values.

Commodity futures and equity markets differ in several important respects. Nevertheless, it was found that momentum profits in commodities are highly significant for holding periods as long as 9 months, and returns to momentum strategies are roughly equal in magnitude to those that have been reported in stocks. The profits documented are too large to be subsumed by transactions costs. Although the momentum strategies appear to be quite risky, their profitability cannot be fully accounted for in the context of a market factor model. Further, it is shown that momentum profits eventually reverse if positions are maintained long enough after portfolio formation. © 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:227–256, 2007

The volatility of daily futures returns for six important commodities are found to be well described as FIGARCH, fractionally integrated processes, whereas the mean returns exhibit very small departures from the martingale difference property. Several years of high frequency intraday commodity futures returns are also found to have very similar long memory in volatility features as the daily returns. Semiparametric local Whittle estimation of the long memory parameter in absolute returns also finds very significant long memory features. Estimating the long memory parameter across many different data sampling frequencies provides consistent estimates of the long memory parameter, suggesting that the series are self-similar. The results have important implications for empirical work using commodity futures price data. © 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:643–668, 2007

We reexamine the volatility of agricultural commodity futures for evidence of fractional integration, providing new empirical results and extending the extant literature in important dimensions. First, we utilize two relatively new estimators based on wavelets, which are generally superior to, for example, the popular GPH estimator and exact MLE estimators on the basis of mean squared error. Second, we provide simulations to contrast our point estimates with those obtained by a fractionally integrated GARCH model. Third, we conduct a wavelet coefficient decomposition of futures volatility. We find that futures volatilities display the self similarity property consistent with long memory, and we confirm that futures volatilities exhibit persistent long memory with finite unconditional variance. Please see paper published in J of Futures Markets for all figures and equations.

As a consequence of optimal investment choices, a firm's assets and growth options change in predictable ways. Using a dynamic model, we show that this imparts predictability to changes in a firm's systematic risk, and its expected return. Simulations show that the model simultaneously reproduces: (i) the time-series relation between the book-to-market ratio and asset returns; (ii) the cross-sectional relation between book-to-market, market value, and return; (iii) contrarian effects at short horizons; (iv) momentum effects at longer horizons; and (v) the inverse relation between interest rates and the market risk premium.

This paper uses time series techniques to re-examine the Prebisch-Singer hypothesis that there has been a secular deterioration in primary commodity prices in terms of manufactured goods. Instead of using price indices, it considers 26 individual commodity prices over the period 1900–1983. This avoids possible aggregation and interpretation problems associated with the use of aggregate indices. The study finds that 16 of the 26 prices are trendless. Five have statistically significant negative trends; the remaining five have positive trends. It concludes that the Prebisch-Singer hypothesis should certainly not be considered a universal phenomenon or ‘stylized fact’.

Our paper re-examines the profitability of relative strength or momentum trading strategies (buying past strong performers and selling past weak performers). We find that standard relative strength strategies require frequent trading in disproportionately high cost securities such that trading costs prevent profitable strategy execution. In the cross-section, we find that those stocks that generate large momentum returns are precisely those stocks with high trading costs. We conclude that the magnitude of the abnormal returns associated with these trading strategies creates an illusion of profit opportunity when, in fact, none exists.

The article tests for the presence of short-term continuation and long-term reversal in commodity futures prices. While contrarian strategies do not work, the article identifies 13 profitable momentum strategies that generate 9.38% average return a year. A closer analysis of the constituents of the long–short portfolios reveals that the momentum strategies buy backwardated contracts and sell contangoed contracts. The correlation between the momentum returns and the returns of traditional asset classes is also found to be low, making the commodity-based relative-strength portfolios excellent candidates for inclusion in well-diversified portfolios.

This study examines momentum and reversals in international stock market indices. We find that country stock indices exhibit momentum during the first year after the portfolio formation date and reversals during the subsequent 2 years. Positive currency momentum predicts low stock index returns in the future, thereby weakening momentum and strengthening reversals in U.S. dollar-denominated stock index returns. Cross-sectional regression tests involving individual stock indices confirm the portfolio findings. Our results are consistent with a key prediction of recent behavioral theories, that initial momentum should be accompanied by subsequent reversals.

An efficient market has been described by Fama (1970) as one in which prices always fully reflect all available information. Of the three tests of efficiency discussed, the weak form test is concerned with the randomness of price movements and measures the ability to predict future price changes from past and present changes. There are two general ways to evaluate weak form efficiency: statistical tests and mechanical trading rules. Statistical methods, including serial correlation, spectral analysis and nonparametric runs tests, permit hypothesis testing, but Fama and Blume (p. 227) point out that they may be of limited value with complex or irregular price structures.

In this article we use a single unifying framework to analyze the sources of profits to a wide spectrum of return-based trading
strategies implemented in the literature. We show that less than 50% of the 120 strategies implemented in the article yield
statistically significant profits and, unconditionally, momentum and contrarian strategies are equally likely to be successful.
However, when we condition on the return horizon (short, medium, or long) of the strategy, or the time period during which
it is implemented, two patterns emerge. A momentum strategy is usually profitable at the medium (3- to 12-months) horizon,
while a contrarian strategy nets statistically significant profits at long horizons, but only during the 1926–1947 subperiod.
More importantly, our results show that the cross-sectional variation in the mean returns of individual securities included
in these strategies play an important role in their profitability. The cross-sectional variation can potentially account for
the profitability of momentum strategies and it is also responsible for attenuating the profits from price reversals to long-horizon
contrarian strategies.

We propose a theory of securities market under- and overreactions based on two well-known psychological biases: investor overconfidence about the precision of private information; and biased self-attribution, which causes asymmetric shifts in investors' confidence as a function of their investment outcomes. We show that overconfidence implies negative long-lag autocorrelations, excess volatility, and, when managerial actions are correlated with stock mispricing, public-event-based return predictability. Biased self-attribution adds positive short-lag autocorrelations ("momentum"), short-run earnings "drift," but negative correlation between future returns and long-term past stock market and accounting performance. The theory also offers several untested implications and implications for corporate financial policy. Copyright The American Finance Association 1998.

This paper uses the dynamic principal component method to estimate a dynamic factor model for stock returns and identify the source of momentum profits. We find that momentum is a systematic-return phenomenon - momentum profits are primarily due to stock return response to a small number of dynamic systematic factors, and the contribution by the idiosyncratic component of stock return is statistically insignificant. We also find that the estimated dynamic factors can be partially related to observed economic factors.