This research paper focuses on the implementation and evaluation of Minervini's momentum analysis techniques in an algorithmic approach. The study aimed to assess the limitations and challenges associated with executing Minervini's strategy in an algorithmic trading system. Several technical restrictions, practical application problems, and the exclusion of fundamental and catalyst aspects contribute to the implementation of a primitive variant of Minervini's strategy. The challenges included the subjective nature of base patterns making bases difficult to identify and limitations in risk and position sizing. However, despite the challenges, the algorithmic approach offers advantages such as the ability to analyze a large number of stocks rapidly. It is suggested to use the algorithm as a tool for stock exclusion rather than fully automating the buying and selling decisions. The research investigates the possibility of generating excess returns in Sweden, Denmark, and Finland using the implemented algorithm over different time periods from 2008 to 2023. Hundreds of stocks were divided up into 18 stock portfolios based on market capitalization size calculations for a given year. These portfolios were traded using both the momentum strategy and an index strategy. The empirical results indicate that small-cap portfolios exhibited consistent excess returns compared to mid-cap and large-cap portfolios, particularly during high volatility periods. However, the research did not account for transaction costs, which are essential to evaluate the strategy's net returns in real-world scenarios. Despite the exclusion of transaction costs in the study, the significant excess returns observed in small-cap portfolios indicate that the implemented momentum strategy performs notably better for small-cap stocks compared to mid-cap and large-cap stocks. This finding contradicts the efficient market hypothesis, assuming equal transaction costs across different market capitalizations. Further research should consider incorporating transaction costs to gain a more comprehensive understanding of the strategy's overall performance and its practical implications for various market segments. Future research should consider incorporating transaction costs and optimizing the stop-loss and profit-taking levels, and exploring a weekly-based approach instead of a daily-based approach. Additionally, volume analysis, data handling improvements, and a more detailed analysis of buy and sell decisions are recommended to optimize the algorithm's performance for future research. To summarize, while the implemented algorithm does not fully mimic Minervini's strategy, it offers valuable insights and potential value, especially in small-cap stocks. Further research and optimization are required to enhance its effectiveness and address the identified limitations.

Background: Buying past winners and selling past losers has historically generated both profits and losses. The momentum strategy has been researched with risk measures and portfolio creation as fundamental components. While no definitive framework exists, prior research has explored industry segmentation within portfolio construction but has yet to reach a clear conclusion. Purpose: The purpose is to determine if there is a significant momentum effect in industry-portfolios, and if some industries are more prone to momentum strategy than others. Method: The research followed a positivistic paradigm with deductive reasoning using a quantitative approach. Secondary data of industry returns for 30 industries from the American stock market is collected from Kenneth R French database. The portfolios are analyzed from a statistical perspective to draw conclusions of the market anomaly. Findings: Three hypotheses were formed to address the research question and purpose. The winner-portfolio yielded significant raw returns in 14 of 16 tests for various periods, while loser and winner-loser portfolios showed negative raw returns. Accounting for systematic risk generated significant profits for all the winner portfolios. Further, industry-specific momentum was examined, revealing no momentum in some industries and momentum in others.   Conclusion: We find evidence that the industry portfolio can generate significant excess return over the market for 3–12-month periods, that can't be explained by the assets systematic risks. The study concludes that while industry-specific momentum is a viable strategy for diversification and capturing winners, its effectiveness varies across industries and has shown diminishing excess returns over the past two decades.

This thesis extends the 52-week high momentum literature, which was first published by George and Hwang in 2004, by stressing the parameters of the trading strategy to investigate its robustness. George and Hwang, in their seminal paper, find that the ratio of a stock’s close price to its 52-week high price is a good predictor of future returns. The thesis stresses various parameters of the strategy - such as the percent of total stocks bought and sold each period – and applies the strategy over different time periods – such as bull and bear markets. The study finds that the strategy is more profitable over the later half of the data set due to underperformance in bear markets such as the 1929 market crash and subsequent Great Depression. The results also show a significant difference in profitability between bull and bear market periods. The second half of the thesis looks at a new area in momentum, the absolute 52-week high. The strategy buys stocks whose price has increased over the previous six months, and who also close to their 52-week high price. Stocks are only bought (sold) if their price has increased (decreased) over the past six months and is close to (far from) the 52-week high price. The aim is to cut out stocks that are considered to be underperforming in the 52-week high momentum strategy, leaving only true winner and loser stocks. This strategy was found to increase the strength of the 52-week high momentum strategy, and the results show that there is no longer a significant difference between bull and bear market returns.

The thesis examines the strategy of country momentum and is evaluated with 30 different country exchange-traded funds (ETFs) for the period 1996-2018. The empirical evaluation is designed to apply different formation- and holding periods with overlapping portfolios. The results show positive momentum returns in various periods and a few portfolios present a higher average return than the market. However, none of the portfolios is presenting any significant positive returns or alphas, meaning that the three hypotheses cannot be rejected. On the other hand, some portfolios have higher Sharpe ratios and Morningstar value than the market. Thus, meaning that the individual investor could prefer the momentum portfolio over the market despite the insignificant returns.

本研究以台灣證券交易所1995年2月至2008年所有上市公司的資料為樣本，比較Jegadeesh and Titman (1993)提出的價格動能策略、Moskowitz and Grinblatt (1999)提出的產業動能策略以及George and Hwang (2004)的52週高價動能策略之間的獲利能力。研究分別進行了月平均報酬比較、元月效果檢視、配對比較、迴歸分析以及加入定錨效果的強韌性檢視。 / 結果發現，在持有期為6個月下，只有52週高價動能策略的獲利能力為顯著且報酬率最佳，月平均報酬率達1.12%，且其對報酬率的解釋能力無法被價格動能策略或產業動能策略給替代，然而52週高價動能策略卻能部分替代價格及產業動能策略的解釋能力，顯示52週高價動能策略相較於價格及產業動能策略而言有優勢性。本研究也發現動能策略投資組合的報酬率存在元月效應，無論是哪一種動能策略的贏家或輸家，在一月份的報酬皆大幅顯著的高於其他11個月份，顯示元月效應的確存在且會影響分析的結果。 / 而最後在迴歸分析裡，結果顯示在控制了公司市值、前一期報酬率、各動能投資策略的影響後，無論是全樣本或一月份除外，依然只有52週高價動能策略的獲利能力是顯著的。然而在經過F-F三因子模型風險調整後，各動能策略投資組合的報酬率皆下降，其中價格動能策略投資組合有顯著的負報酬率，而產業動能策略與52週動能策略投資組合則有不顯著的負報酬率，顯示動能投資策略可能暴露在市場風險下，投資人在採用動能投資策略進行投資決策時應謹慎對待。而強韌性的結果顯示加入定錨效果指標後，其對本研究之結果無顯著的改變。

Thesis (MScEng (Industrial Engineering))--University of Stellenbosch, 2010. / ENGLISH ABSTRACT: Several studies have shown that abnormal returns can be generated simply by buying past winning stocks and selling past losing stocks. Being able to predict future price behaviour by past price movements represents a direct challenge to the Efficient Market Hypothesis, a centrepiece of contemporary finance. Fund managers have attempted to exploit this effect, but reliable footage of the performance of such funds is very limited. Several academic studies have documented the presence of the momentum effect across different markets and between different periods. These studies employ trading rules that might be helpful to establish whether the momentum effect is present in a market or not, but have limited practical value as they ignore several practical constraints. The number of shares in the portfolios formed by academic studies is often impractical. Some studies (e.g. Conrad & Kaul, 1998) require holding a certain percentage of every share in the selection universe, resulting in an extremely large number of shares in the portfolios. Others create portfolios with as little as three shares (e.g. Rey & Schmid, 2005) resulting in portfolios that are insufficiently diversified. All academic studies implicitly require extremely high portfolio turnover rates that could cause transaction costs to dissipate momentum profits and lead the returns of such strategies to be taxed at an investor’s income tax rate rather than her capital gains tax rate. Depending on the tax jurisdiction within which the investor resides these tax ramifications could represent a tax difference of more than 10 percent, an amount that is unlikely to be recovered by any investment strategy. Critics of studies documenting positive alpha argue that momentum returns may be due to statistical biases such as data mining or due to risk factors not effectively captured by the standard CAPM. The empirical tests conducted in this study were therefore carefully designed to avoid every factor that could compromise the results and hinder a meaningful interpretation of the results. For example, small-caps were excluded to avoid the small firm effect from influencing the results and the tests were conducted on two different samples to avoid data mining from being a possible driver. Previous momentum studies generally used long/short strategies. It was found, however, that momentum strategies generally picked short positions in volatile and illiquid stocks, making it difficult to effectively estimate the transaction costs involved with holding such positions. For this reason it was chosen to test a long-only strategy. Three different strategies were tested on a sample of JSE mid-and large-caps on a replicated S&P500 index between January 2000 and September 2009. All strategies yielded positive abnormal returns and the null hypothesis that feasible momentum strategies cannot generate statistically significant abnormal returns could be rejected at the 5 percent level of significance for all three strategies on the JSE sample. However, further analysis showed that the momentum profits were far more pronounced in “up” markets than in “down” markets, leaving macroeconomic risk as a possible explanation for the vast returns generated by the strategy. There was ample evidence for the January anomaly being a possible driver behind the momentum returns derived from the S&P500 sample. / AFRIKAANSE OPSOMMING: Verskillende studies het gewys dat abnormale winste geskep kan word deur eenvoudig voormalige wenner aandele te koop en voormalige verloorder aandele te verkoop. Die moontlikheid om toekomstige prysgedrag te voorspel deur na prysbewegings uit die verlede te kyk is ‘n direkte uitdaging teen die “Efficient Market Hypothesis”, wat ’n kernstuk van hedendaagse finansies is. Fondsbestuurders het gepoog om hierdie effek te benut, maar akademiese ondersteuning vir die gedrag van sulke fondse is uiters beperk. Verskeie akademiese studies het die teenwoordigheid van die momentum effek in verskillende markte en oor verskillende periodes uitgewys. Hierdie akademiese studies benut handelsreëls wat gebruik kan word om te bepaal of die momentum effek wel in die mark teenwordig is al dan nie, maar is van beperkte waarde aangesien hulle verskeie praktiese beperkings ignoreer. Sommige studies (Conrad & Kaul, 1998) vereis dat 'n sekere persentasie van elke aandeel in die seleksie-universum gehou moet word, wat in oormatige groot aantal aandele in die portefeulle tot gevolg het. Ander skep portefeuljes met so min as drie aandele (Rey & Schmid, 2005), wat resulteer in onvoldoende gediversifiseerde portefeuljes. Die hooftekortkoming van alle akademiese studies is dat hulle portefeulleomsetverhoudings van hoër as 100% vereis wat daartoe sal lei dat winste uit sulke strategieë teen die belegger se inkomstebelastingskoers belas sal word in plaas van haar kapitaalaanwinskoers. Afhangende van die belastingsjurisdiksie waaronder die belegger val, kan hierdie belastingseffek meer as 10% beloop, wat nie maklik deur enige belegginsstrategie herwin kan word nie. Kritici van studies wat abnormale winste dokumenteer beweer dat sulke winste ‘n gevolg kan wees van statistiese bevooroordeling soos die myn van data, of as gevolg van risikofaktore wat nie effektief deur die standaard CAPM bepaal word nie. Die empiriese toetse is dus sorgvuldig ontwerp om enige faktor uit te skakel wat die resultate van hierdie studie sal kan bevraagteken en ‘n betekenisvolle interpretasie van die resultate kan verhinder. Die toetse sluit byvoorbeeld sogenaamde “small-caps” uit om die klein firma effek uit te skakel, en die toetse is verder op twee verskillende monsters uitgevoer om myn van data as ‘n moontlke dryfveer vir die resultate uit te skakel. Normaalweg toets akademiese studies lang/ kort nulkostestrategieë. Dit is gevind dat momentum strategieë oor die algemeen kort posisies kies in vlugtige en nie-likiede aandele, wat dit moeilik maak om die geassosieerde transaksiekoste effektief te bepaal. Daar is dus besluit om ’n “lang-alleenlik” strategie te toets. Drie verskillende strategieë is getoets op ‘n steekproef van JSE “mid-caps” en “large-caps” en op ‘n gerepliseerde S&P500 index tussen Januarie 2000 en September 2009. Alle strategieë het positiewe abnormale winste opgelewer, en die nul hipotese dat momentum strategieë geen statisties beduidende abnormale winste kan oplewer kon op die 5% vlak van beduidendheid vir al drie strategieë van die JSE monster verwerp word. Verdere analiese het wel getoon dat momentumwinste baie meer opvallend vertoon het in opwaartse markte as in afwaartse markte, wat tot die gevolgtrekking kan lei dat makro-ekonomiese risiko ‘n moontlike verklaring kan wees. Daar was genoegsaam bewyse vir die Januarie effek as ‘n moontlike dryfveer agter die momentum-winste in die S&P500 monster.

本研究對1985/1至2016/10期間，37種貨幣的超額報酬與國家風險進行實證分析，以The PRS Group發佈的ICRG綜合風險評級做為國家風險的衡量指標。各國貨幣分別進行時間序列分析的結果顯示，單一國家的國家風險與該國貨幣的匯率走勢及超額報酬並不存在顯著的關聯。 投資組合分析的結果，對高國家風險貨幣與低國家風險貨幣分別執行利差交易，結果顯示兩者的超額報酬並沒有顯著差異。而動能策略在高國家風險貨幣則可以獲得顯著較高的超額報酬。 Fama-Macbeth二步驟迴歸分析結果顯示，高國家風險的投資組合確實擁有較高的因子負載量，然而國家風險因子的市場價格，也就是承受一單位 β_CRISK獲得的國家風險溢酬太低不顯著，因此國家風險無法幫助解釋貨幣報酬。 / We empirically investigate the relation between currency excess returns and country risk, as measured by the ICRG comprehensive risk rating issued by The PRS Group, of 37 currencies during 1985/1 to 2016/10. The result of the single currency time series analysis shows that there is no significant correlation between the country risk and the exchange rate movement, also the currency excess return. As a result of the portfolio analysis, there is no significant difference in excess returns when we execute carry trade respectively on high country risk currencies and low country risk currencies. While the momentum strategy in the high country risk currencies can generate significantly higher excess return. The results of the Fama-Macbeth two-step regression show that the high-risk portfolios do have a higher factor loading, whereas the country risk factor's market price, that is, the country risk premium received by a unit of β_CRISK, is too low. Therefore, country risk cannot help explain currency excess return.

This thesis explores the implementation of three quantitative investment strategies – the dividend yield strategy, the EV/EBITDA strategy, and the momentum strategy – within the Swedish stock market using Equal-Weighted Portfolios (EWP) and Value-Weighted Portfolios(VWP). The analysis is based on backtesting during the periods 2009 − 2022, 2001 − 2022, and 1992 − 2022, for each strategy respectively. The research aims to assess the risk-adjusted returns of these strategies and compare the performance of the EWP and the VWP. The results indicate that all the tested quantitative investment strategies beat the market. Moreover, the VWP achieve higher annual returns compared to the EWP. However, when considering risk-adjusted returns, the EWP generally demonstrate superior performance. Specifically, the EWP incorporating momentum monthly rebalancing exhibit the largest risk-adjusted returns.

在國人愈來愈重視投資理財的今日，股票已成為全民熱烈參與的運動。國外的研究中發現，股票市場中常會存在追高殺低的情況，也就是報酬好的股票可能會有持續良好的表現。然而，此種報酬的持續現象是否也同樣存在於國內，這正是本研究所探討的主題之一。 　　此外，與盈餘相關訊息（如非預期盈餘、盈餘發佈日前後數日的異常報酬及分析師對盈餘預測的修正程度等）對未來股票報酬的影響程度究竟如何，則是本研究的另一個主題。 　　研究樣本取樣自民國82年至86年底之台灣上市公司股價及盈餘相關資訊進行實證分析。實證結果如下： 1. 在股票報酬持續效果研究上，股價有過度反應的現象，因而在六個月 後的報酬情況有回歸平均的情形，也就是說前六個月的報酬較佳的股票在六個月後的報酬將會較低。然而，一年後乃至於三年後過去報酬較好的股價仍然能有較好的報酬。可見在台股中股價仍然存在有延續的現象。 2. 有關非預期盈餘對未來報酬影響情況的研究部份，此一訊息的延續效果大約有二年期間，隨著各項與盈餘有關訊息的發佈，將使得非預期盈餘的幅度愈來愈小，終至不具影響力。 3. 盈餘發佈日前後的異常報酬因為僅以四天的股價異常報酬做為盈餘的替代指標，所含資訊內容有限，因而使得其影響效果存續期間非常地短暫。實證結果發現在六個月內具有持續效果，超過六個月後，這項訊息將不再具有影響能力。 4. 至於分析師對國內上市公司盈餘預測的實證研究中，我們發現如果分析師對於某一家公司的盈餘預測修正幅度愈大，其未來的股價報酬將愈不理想。 5. 綜合來說，股價的持續效果比盈餘訊息對股價報酬的影響效果更為明顯；而非預期盈餘是一項不錯的選股指標。結合過去六個月的股價報酬及非預期盈餘來選擇一、二年期的投資標的是一項很有效的選股方式。 目 錄 第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的與重要性 2 第三節 研究架構 3 第二章 相關文獻探討 5 第一節 投資報酬之影響因素 5 第二節 價格的持續效果 6 第三節 盈餘對股價影響效果的持續性 8 第三章 研究方法 12 第一節 研究假設 12 第二節 研究期間、對象與資料來源 12 第三節 研究設計 13 第四節 研究流程 21 第四章 實證結果與分析 22 第一節 過去六個月報酬影響未來報酬程度分析 22 第二節 非預期盈餘的高低對未來報酬影響情況分析 28 第三節 累計異常報酬對未來報酬的影響效果分析 33 第四節 分析師修正盈餘預測幅度對股票未來報酬的影響研究 39 第五節 價格持續效果及盈餘持續效果比較分析 44 第五章 結論與建議 46 第一節 研究結論 46 第二節 後續研究建議 47 參考文獻 49 / Nowadays, people in Taiwan lay more emphases on investment and financing. They take part in investing in the stock market passionately. Research from overseas studies find that there is a phenomenon, “momentum effect” exists in the stock market. That is the reason why good-performance stocks could keep performing well. Whether the phenomenon exists in Taiwan, too? This is one of the topics of this research. 　　Moreover, how does the information about earnings, such as unexpected earnings, abcdrmal return around the earnings announcement and the changes of analysts’ forecasts on earnings, influence stock performance in the future? This is the other topic of this paper. 　　Samples from published corporate stock prices and information about earnings during 1993 to 1997 was used in this paper to do the research. The followings are five positive outcomes. 1. In the research of price momentum effect, the stock price had overreacted. It means that the mean-reversion condition existed in six months. However, the stock with good performance in the past six months would still have better return in one to three years. Therefore, we find that price momentum does exist in Taiwan stock market. 2. How did the effect of unexpected earnings on future return? We find that the effect of standardized unexpected earning would last for two years approximately. As the information of earnings was declared, the effect of unexpected earnings would drop. 3. The information was limited because of using abcdrmal return around announcement as the substitution of earnings. So, the effect of it would last for the short time. The positive outcome found that the abcdrmal return around earnings announcement did have influence in six mouths, but it took seldom effect over six months. 4. The last research was about the changes on analysts’ forecasts. We found that if the analyst made more correction on earnings forecast, the stock price would have poor performance in the future. 5. In general, the price momentum effect tends to be stronger and longer-lived than the earnings momentum effect. It would be an effective way to choose good-performance stocks in one to two years by the past-six-months performance and standardized unexpected earnings.

大型股過去一直被認為平均報酬率低於小型股，但如果從個股來看，不少大型股的績效並不會比指數差。考慮到一般非專業投資人在投資股票時，選擇大型股還是比小型股容易，本論文試圖建構一套在實務上較可行的大型個股選股策略—選擇市值第二大的股票，並定期調整個股。我們以美股標準普爾500指數中前兩大市值的股票，分為兩種投資組合做比較，結果發現，市值最大的股票不容易創造超額報酬，市值第二大的股票，反而締造極佳的超額報酬，此現象在過去3年、5年、10年，尤其較過去20年更為明顯。原因在於市值排名第二的股票，多半屬於排名仍在持續上升的成長股，這些個股基本面尚未到達頂點，故股價還會反應一段時間的基本面利多，採取類似動能策略(Momentum Strategy)的方法，報酬率容易超越指數；市值最大者則因為基本面普遍伴隨市值排名已經到頂，加上投資人對於排名第一的股票，多半易產生定錨效應(Anchoring Effect)，即認為股價可能已經反應其該有的價值，較難創造超額報酬，傾向賣出。故同樣投資大型股，選擇市值第二名的股票會優於第一名。 / According to The Size Effect Theory, small cap securities generally generate greater returns than those of large cap companies. However, this trend has involved into the difficulties of stock picking due to the large number of small caps. In this paper I propose a strategy against the size effect theory, “Second is Better”, to pick the second largest market value security as the single stock investment. I examine the performances of the No.1 and the No.2 largest market cap stocks in the S&P500 and apply a 6-month rebalance to construct two different portfolios, which is similar to the concept of Momentum Strategy that buy the past winners and sell the past losers. I find the No.2 stock outperforms than No.1 stock and generate amazing excess returns in the near mid-to-long-term periods. Because No.1 stocks are more likely to experience Momentum Crash than No.2 stocks due to investor’s anchoring bias as they believe the No.1 stock might have been peaked. No.2 stocks are usually in the growing stages that many investors believe the 2nd largest caps still yet to peak during market value expansion.