Momentum Investment Strategies Research Articles

Momentum Investment Strategies across Time and Trends: A Review and Preview

Background: This study provides a bibliometric analysis of momentum investment strategies, examining their historical evolution, behavioral dynamics, and the challenges faced by professionals in equity markets. It aims to explore the persistent profitability of momentum strategies amidst market fluctuations and the significant influence of behavioral biases on trading decisions. Methods: Employing a Bibliometric Analytical framework, the study systematically maps the knowledge structure of momentum investment strategies. It utilizes the Dimensions database for scholarly journal searches and examines peer-reviewed research publications spanning from 1993 to 2024. This method enables the identification of key research works, emerging trends, and an assessment of the literature's impact. Results: The research reveals the persistent profitability of momentum strategies despite market changes, highlighting the significant role of behavioral biases in trading decisions. This work contributes to both academic discourse and practical investment strategy development, offering insights into exploiting momentum's transformative potential in dynamic equity markets. Conclusion: This study contributes to both academic discourse and practical investment strategy development by offering evidence-based insights into the effectiveness of momentum strategies. It identifies research gaps, suggests new directions for future studies, and analyzes collaboration networks to enhance interdisciplinary research efforts. Novelty: The utilization of a Bibliometric Analytical framework in studying momentum investment strategies brings a novel approach to the field. This method not only offers a systematic mapping of knowledge but also facilitates the identification of influential research works and emerging trends, guiding both academic research and practical applications.

Analyzing the Efficacy of the Relative Strength Indicator of Capital Inflows and Outflows Based on Big Data Analysis in Achieving Abnormal Returns Evidence from the Chinese Stock Market

This study originates from an analysis of market microstructure and introduces a novel statistical indicator of relative strength in capital flows through the application of big data analytics. This indicator effectively captures the impact of capital movements on future stock prices by integrating variations in stock prices with the volume of transactions within a corresponding timeframe. Building upon this foundation, the research develops an innovative momentum investment strategy based on the relative strength indicator of capital inflows and outflows, extending beyond the traditional fixed holding period momentum strategy framework. Empirical analysis reveals that this new indicator significantly demonstrates momentum effects in the Chinese A-share market; notably, in portfolios of stocks with smaller market capitalizations, the momentum strategy grounded on the new indicator achieves higher excess returns compared to traditional momentum strategies. These findings not only validate the efficacy of the new indicator but also underscore the critical role of big data analytics in enhancing the analysis of financial markets and the efficiency of investment decision-making.

Combining low-volatility and momentum: recent evidence from the Nordic equities

ABSTRACT This paper investigates the profitability of combined low-volatility and momentum investment strategies in the Nordic stock markets from January 1999 to September 2022. Confirming earlier studies, our results first indicate that both the volatility and momentum effects persist as pure-play strategies. Further, we explore combined strategies using 50/50, double screening, and ranking strategies. Among the long-only portfolios, the momentum-first strategy generates the best Sharpe ratio using the double screening method−slightly outperforming the ranking method. Additionally, all long-only combination portfolios outperform the market in terms of risk-adjusted returns. Combination long-short strategies produce significantly higher risk-adjusted returns than pure-play strategies. Surprisingly, novel evidence suggests that none of the combination long-short strategies outperforms the pure momentum strategy after risk-adjusting the returns using the Fama and French five-factor model, implying that while momentum may enhance the returns from the low-volatility strategy, the reverse is not true for the Nordic stock markets.

Crafting investment models through contradictory value and momentum investment strategies by artificial intelligence

Crafting investment models through contradictory value and momentum investment strategies by artificial intelligence Professor Chien-Feng Huang discusses how Artificial Intelligence could provide innovative models and strategies to solve investment problems. Over the past decade, Professor Chien-Feng Huang has been working on several investment problems using Artificial Intelligence (AI). Big Data technology, data mining and machine learning play crucial roles in his research, where he hopes to discover niches and innovative solutions to bring about blue ocean strategies for investment. One major line of research Professor Huang has been pursuing is to combine seemingly contradictory strategies to generate emerging solutions for investment. For example, the momentum investing strategy might advise buying a stock, yet the value investment strategy advises against it. So, which one is right?

Understanding Momentum and Reversal Investing Strategies

Momentum and reversals are two phenomena to explain the past return trend. Originally introduced by Jegadeesh and Titman in 1993, momentum is now a common investment strategy when investors are trading securities. It points out the stock price may have a relationship with their past performance. A large number of researchers have been trying to find out the momentum investment effect based on empirical evidence in different markets in different investment periods, which include short term, medium term and long term. Moreover, a series of research concludes that the momentum investment strategy tends to help investors to get a higher return. In recent years, a large number of researchers have focused more on analysing financial markets in China, and they have paid more attention to improving the traditional Jegadeesh and Titman models. In addition, an increasing number of researchers also point out that noise trading is quite important in the security investment strategy, and the investors who are using a momentum investment strategy to trade their portfolios are supposed to take the noise trading strategy into consideration. Then a series of papers have been tried to explain the sources of the momentum effect, either risk-based or behavioural-based. When it assumes that the market is efficient, the past market prices could be reflected, and it is hard to get excess returns by observing the stock's past prices performance. Nevertheless, the momentum effect is likely to examine that the market is inefficient. When it tries to explain the momentum effect in risk-based sources, the abnormal price return may be derived from a risk that is undiversifiable. As for the behaviour-based explanation, several behavioural biases applied by different researchers could be used to study the momentum effect, such as cognitive errors, including the conservatism bias, the representative bias, and the emotional bias, including the loss aversion bias, the overconfidence bias and the self-attribution bias. Another possible explanation within this behavioural source is that overreaction to the news leads to the existence of price momentum.

Optimization study of momentum investment strategies under asymmetric power-law distribution of return rate

Abstract In the context that the tails of security returns obey an asymmetric power-law distribution, this paper constructs two fractal statistical measures based on fractal theory: fractal expectation and fractal variance. Subsequently, a new momentum strategy is constructed by introducing the fractal measures into the momentum strategy as measures of returns and risks to optimize the selection criterion. Finally, the empirical results show that the new momentum strategy outperforms the traditional momentum strategy and the risk-adjusted momentum strategy, confirming the effectiveness of fractal expectation and fractal variance.

Decoding momentum returns: an integrated bibliometric and content analysis approach

PurposeOver the past three decades, numerous conceptual and empirical studies have discussed momentum investment strategies’ presence, pervasiveness and persistence. However, science mapping in the field is inadequate. Hence, this study aims to comprehend and explore current dynamics, understand knowledge progression, elicit trends through thematic map analysis, synthesize knowledge structures and provide future research directions in this domain.Design/methodology/approachThe study applies bibliometric analysis on 562 Scopus indexed articles from 1986 to 2021. Biblioshiny version 3.1.4, a Web-based application included in Bibiliometrix package developed in R-language (Aria and Cuccurullo, 2017), was used to examine: the most prominent articles, journals, authors, institutions and countries and to understand the thematic evolution and to elicit trends through the synthesis of knowledge structures including conceptual, intellectual and social structures of the field.FindingsMotor themes, basic transverse, niche and emerging and declining themes were identified using (Callon, 1991) strategic thematic map. Besides, four major clusters based on a cocitation network of documents were identified: empirical evidence and drivers of momentum returns, theories explaining momentum returns and implications for asset pricing and market efficiency, avoiding momentum crashes and momentum in alternative asset classes, alternative explanations for momentum returns. The study infers that momentum research is becoming multidisciplinary given the dominance of behavioral theories and economic aspects in explaining the persistence of momentum profits and offers future research directions.Research limitations/implicationsThe study deploys bibliometric analysis, appropriate for deriving insights from the vast extant literature. However, a meta-analysis might offer deeper insights into specific dimensions of the research topic. Besides, the study’s findings are based on Scopus indexed articles analyzed using bibilioshiny; the database and software limitations might have affected the findings.Practical implicationsThe study is a ready reckoner for scholars who intend to recognize the evolution of momentum investment strategies, current dynamics and future research direction. The study offers practitioners insights into efficiently designing and deploying momentum investment strategies and ways to avoid momentum crashes.Social implicationsThe study offers insights into the irrational behavior and systematic errors committed by market participants that helps regulators and policymakers to direct investors’ educational efforts to minimize systematic behavioral errors and related adverse financial consequences.Originality/valueThis comprehensive study on momentum investment strategies evaluates research trends and current dynamics draws a thematic map, knowledge progression in the field and offers future research directions.

Do oil price shocks have any implications for stock return momentum?

The study examines the implications of structural oil price shocks on one of the most widely observed and pervasive momentum anomalies. We use a structural vector autoregression (SVAR) model to find the time-varying responses of momentum payoffs of India, Japan, the UK, and the US to different structural oil shocks—oil supply global aggregate demand shock, speculative shock, and other oil demand shocks. Structural oil shocks, particularly oil demand and speculative shocks, have important implications as conditioning information in predicting stock return momentum behavior according to the conditional asset pricing model. Overall, the results indicate that structural oil shocks have a significant impact on small cap and loser stock portfolios. Our findings have crucial implications to develop effective momentum investment strategies that consider structural oil shocks as conditioning information.

A Momentum Investment Strategy Based on Correlations: A Comparison between China and Us Stock Markets

A Momentum Investment Strategy Based on Correlations: A Comparison between China and Us Stock Markets

The 52-Week High Momentum Investment Strategies; Evidence in the Korean Stock Market

본 연구는 JT모멘텀전략, GH모멘텀전략 및 RR모멘텀전략의 유용성을 국내 주식시장에서 분석하였다. 또한 모멘텀전략의 성과에 영향을 미칠 수 있는 투자유예기간을 다양하게 고려하여 모멘텀전략의 성과를 비교하였다. 주요 연구결과는 다음과 같다. 첫째, 국내 주식시장에서는 기존의 JT모멘텀전략보다 52주 고가를 사용하는 GH모멘텀전략과 RR모멘텀전략이 유용한 것으로 나타났으며, 위험을 조정한 결과에서도 동일하게 나타났다. 둘째, 투자유예기간 없이 1개월 투자할 때 RR모멘텀전략이 JT모멘텀전략과 GH모멘텀전략보다 효과적인 모멘텀 투자전략인 것으로 나타났다. 셋째, RR모멘텀전략은 투자유예기간이 없이 투자하는 것이 가장 높은 성과를 보였다. 넷째, 투자유예기간은 모멘텀전략의 성과에 중요한 영향을 미치는 것을 확인하였다. 그리고 투자유예기간을 고려할 때 GH모멘텀전략이 가장 우수한 것으로 나타났다. 본 연구는 52주 고가를 이용한 모멘텀전략이 기존의 JT모멘텀전략보다 유용하다는 결과를 제시하였으며, Novy-Marx(2012)와 같이 투자유예기간의 시차가 포트폴리오의 성과에 영향을 미친다는 것을 실증적으로 증명하였다.

Momentum Effect in Developed and Emerging Stock Markets

The study aims to reaffirms the existence of short-term momentum effect in 13 developed and emerging stock markets where previous literature has lack of consensus. Although many studies emphasis on the existence of momentum effect, but still, there are substantial number of researchers that deny the its presence. The contradictory finding of many researchers over the existence of momentum effect, raises a serious question, to what extend our stock markets are informationally efficient and whether investor can make abnormal profits by using momentum investment strategies. This study applies momentum investment strategy, J6K6, to calculate momentum returns. Our study finds negative significant momentum effect in all 13 stock markets. Although momentum effect is present in 13 countries but Investors are not able to attain abnormal profit through momentum investing. These findings have an utmost importance for practitioners that they should not adopt momentum investment strategies in these countries as these strategies are generating lose. Moreover, stock market regulators should formulate these markets on the notion of efficient market hypothesis.

Establishing the risk denominator in a Sharpe ratio framework for share selection from a momentum investment strategy approach

Background: Based on the static mean-variance portfolio optimisation theory, investors will choose the portfolio with the highest Sharpe ratio to achieve a higher expected utility. However, the traditional Sharpe ratio only accounts for the first two moments of return distributions, which can lead to false portfolio performance diagnostics with the presence of asymmetric, highly skewed returns. Aim: With many criticising the standard deviation's applicability and with no consensus on the ascendency of which other risk denominator to consult, this study contributes to the literature by validating the importance of consulting value-at-risk as the more commendable risk denominators for the Johannesburg Stock Exchange. Method: These results were derived from a novel index approach that produces a comprehensive risk-adjusted performance evaluation score. Results: Of the 24 Sharpe ratio variations under evaluation, this study identified the value-at-risk Sharpe ratio as the better variation, which led to more profi table share selections for long-only portfolios from a one-year and five-year momentum investment strategy perspective. However, the attributes of adjusting for skewness and kurtosis exhibited more promise from a three-year momentum investment strategy perspective. Conclusion: The results highlighted the ability to outperform the market, which further emphasised the importance of active portfolio management. However, the results also conrfimed that active and more passive equity portfolio managers will have to consult different Sharpe ratio variations to enhance the ability to outperform the market and a buy-and-hold strategy.

Momentum Investment Strategy Using a Hidden Markov Model

There has been a growing demand for portfolio management using artificial intelligence (AI). To sustain a competitive advantage for portfolio management, stock market investors require a strategic investment decision that can realize better returns. In this study, we propose a momentum investment strategy that employs a hidden Markov model (HMM) to select stocks in the rising state. We construct an HMM momentum portfolio that includes 890 Korean stocks and analyze the performance of the stocks over the period of January 2000 to December 2018. By identifying states of stocks, sectors, and markets through HMM, our strategy buys shares in the rising state and proceeds with rebalancing after the holding period. The HMM momentum portfolio is determined to earn higher returns than traditional momentum portfolios and to achieve the best performance under the conditions of a short holding period (one week) and a short formation period (one month). In addition, our strategy exhibits competitive performance in market and sector index investment compared with market returns. This study implies that the momentum investment strategy using HMM is useful in the Korean stock market. Based on our HMM momentum strategy, future research can be enriched by applying the HMM to developing a new AI momentum strategy that can be utilized for other portfolios containing various types of financial assets on the global market.

An Analytical Overview of Investment Strategies

This paper inspects a bunch of investment strategies in light of past market data to assess execution and exchanging influence on the Canadian Market. In doing as such, we survey whether exchanging data enhances the adequacy of these strategies. Using variation models of four various approaches, we track serious areas of strength for down that upheld the Momentum Investment Strategy. The contention of whether the market is proficient has gone on for quite a while and it is fundamental for a financial backer to figure out what sort of investment methodology to pick confronting different market adequacy. It is significant to decide which sort of technique to use in various market stages.

Momentum Effect all over the World

This study is intended to reaffirm the existence and profitability of momentum investment strategies in 40 countries around the world during the period 1996–2018. The contradictory findings of previous research on the existence and profitability of momentum strategies have raised a pertinent question on the validity of efficient market hypothesis. We documented the momentum effect in 90% of our sample countries of which 52.5% exhibited positive momentum effect while 37.5% exhibited negative momentum effect. The findings were robust to two distinct sub-period analyses. The clear rejection of efficient market hypotheses is valuable to momentum traders and stock market regulators.

Global currency hedging with common risk factors

We develop a novel method to dynamically hedge foreign exchange exposure in international equity and bond portfolios. The method exploits the time-series predictability of currency returns, which we show emerges from exploiting a forecastable component in global factor returns. The hedging strategy outperforms leading alternative approaches to currency hedging across a large set of performance metrics. Moreover, we find that exploiting currency return predictability via an independent currency portfolio delivers a high risk-adjusted return and provides superior diversification gains to global equity and bond investors relative to currency carry, value, and momentum investment strategies.

KINERJA PORTOFOLIO SAHAM BERDASARKAN STRATEGI INVESTASI MOMENTUM PADA INDEKS KOMPAS100

The purpose of this study was to determine the performance of the stock portfolio using the momentum investment strategy on the Kompas100 index. The scope of this research area are companies incorporated in the Kompas100 Index listed in the Indonesia Stock Exchange for the period 2012-2017. The number of samples used was 53 samples. The method of data collection is done through non-participant observation and using two different test analysis techniques on average. Based on the results of data analysis it was found that the results of the two different test averages of Sharpe Index on the winner's portfolio get insignificant results and the loser portfolio gets significant results. This made no momentum but a contrarian strategy, where the loser portfolio measured by the Sharpe Index significantly decreased during the ownership period of 3, 6, 12 months and made the loser portfolio suffer prolonged losses. The results of this study reflect that contrarian strategy is a strategy used by investors to expect a reversal of stock returns at a certain time period, namely the rate of return that is initially positive or negative is expected to experience a reversal in a certain period of time.
 Keywords: stock portfolio performance, momentum investment strategy, Kompas100 index.

Some Observations on Trend Following: A Binomial Perspective

This paper uses a simple binomial framework to explore trend following. It shows (by counter example) that the existence of positive profits from trend-following strategies, on its own, provides no prima facie evidence on the efficiency or inefficiency of markets. In addition, it explores the most important feature of time series momentum investment strategies: the return shaping impact of trend following through its dynamic positioning. In a stylized efficient market setting (with no transaction costs), the paper shows that the dynamic nature of trend following shapes when profits and losses occur compared to a buy-and-hold strategy. There is, however, a conservation of “mass” in that gains and losses are shuffled across periods such that the unconditional distribution of profits is unaffected. In this sense, trend following, by construction, generates crisis alpha --- for crises where large losses occur over extended periods of time. Due to its ability to shape when profit and losses occur, trend following can provide significant portfolio diversification and hedging potential for those investors with strategic risk-on exposures.

Buzzwords build momentum: Global financial Twitter sentiment and the aggregate stock market

We examine the long-term relationship between signals derived from nine years of unstructured social media microblog text data and financial market developments in five major economic regions. Employing statistical language modeling techniques we construct directional sentiment metrics and link these to aggregate stock index returns. To address the noise in finance-related Twitter messages we identify expert users whose tweets predominantly focus on finance topics. We document that expert users are the main drivers behind an interdependence between Twitter sentiment and financial markets. The direct prediction value of expert sentiment metrics for stock index returns, however, is found to be elusive and short-lived. Yet, we detect significant predictive gains over benchmark models in times of negative market returns. In consequence, the relation between expert sentiment metrics and stock indices is sufficient to devise hypothetically profitable cross-sectional as well as time series momentum investment strategies for futures based on Twitter signals that survive basic transaction cost assumptions. In this context, our results show that expert sentiment signals can yield higher risk-adjusted returns than classical price-based signals.

VALUE AT RISK OF MOMENTUM INVESTMENT STRATEGY: INDONESIA'S LIQUID STOCKS PORTFOLIO

The capability of momentum investment strategy was explore through portfolio risk reduction by value at risk method at liquid shares in Indonesia stock exchange period 2008-2016. The purpose of this study are to analyse the value of momentum investment strategy risk reduction with the Value at Risk approach to historical-volatility approach and examine differences in risk reduction performance by winner and loser portfolios formed from a collection of liquid shares in the Indonesia stock exchange for the period 2008-2016. The stocks selection method in forming winners and losers portfolio done by Jegadesh and Titman procedure (1993) followed by calculation of risk reduction with the VaR-HisVol approach. The result show for quarterly and semester period winner portfolio has superior capacity of portfolio risk reduce than loser.
 Keywords—Investment; Strategy; Portfolio, VaR.
 Abstrak
 Kemampuan strategi investasi momentum dieksplorasi dalam teminologi pengurangan risiko portofolio dengan metode value at risk pada portofolio saham saham likuid di Bursa Efek Indonesia periode 2008-2016. Metode pemilihan saham pembentuk portofolio pemenang dan pecundang dilakukan dengan prosedur Jegadesh dan Titman (1993) dilanjutkan dengan kalkulasi pengurangan risiko dengan pendekatan VaR-HisVol. Hasil menunjukkan untuk portofolio pemenang periode triwulanan dan semester memiliki kapasitas superior mengurangi risiko portofolio daripada pecundang.
 Kata kunci— Investasi, Strategi, Portofolio, VaR