Notice bibliographique
Résumé
ABSTRACT This study examined performance of U.S. stock market during nineties, concentrating on performance of various industry sectors. study examined quarterly rates of return earned by stocks in various industry groups and performance of stock market as measured by Standard and Poor's 500 index. data used for this study covered a period beginning first quarter of 1990 through second quarter of 2001. study focused on both returns and risk provided by various industry sectors of stock market. profitability of various sector rotation strategies was also examined in this study. optimal strategy was a rebalancing of portfolio every quarter with stocks in industries that outperformed market in prior quarter. This strategy provided a very attractive risk-return portfolio characteristic and was also able to hold on to gains when market turned at start of new millennium. INTRODUCTION In recent years, with advent of index stocks traded on AMEX and other exchanges, a strategy of sector switching combined with momentum investing suddenly has become more cost effective as a whole basket of stocks can be purchased and sold with minimal transactions costs. This study examined possibility of earning excess rates of return based on a momentum identification strategy over decade of nineties. switching strategy was based on measuring momentum of stock market rates of return of various industry sectors in United States. On other hand, contrarian approach to investing suggests that over long term, all investment returns tend to regress toward their normal risk adjusted rate of return, in which case an industry that has under-performed in a given period will likely outperform market during next period. LITERATURE REVIEW A number of studies in past have found both positive and negative serial correlation of returns over different time periods based on different rebalancing Chan, Jegadeesh and Lakonishok found that strategies based on past returns provided significant returns over a horizon from six months to one year. They believe The source of these momentum profits may be tendency of at least some investors to chase past trends. These investors may rush to buy past winners and dump past losers, resulting in temporary price drifts for these stocks. Swinkels conducted a similar study in international context. His study examined momentum effect for Europe and Japan. His findings were that there was a significant momentum effect for Europe whereas it was nonexistent for stocks in Japan. Schiereck, De Bondt and Weber examined contrarian and momentum strategies in Germany. Their study examined returns and earnings of all major German companies over a period 1961-1991. They found that --what is perhaps most surprising is how closely results for Germany match findings for United States--Maybe general traits in human behavior and psychology overcame these differences--in social, cultural, and economic environment. Rouwenhorst found that international momentum returns are correlated with those of United States. His study covered 12 countries and found an internationally diversified portfolio of past winners outperformed past losers by about one percent per month. He believes that the exposure to a common factor may drive profitability of momentum strategies. METHODOLOGY This study used United States stock market price data to test following hypotheses: H0a: It is not possible to earn an excess risk-adjusted rate of return on stocks with a sector rotation strategy based on industry momentum. H1a: It is possible to earn an excess risk-adjusted rate of return on stocks with a sector rotation strategy based on industry momentum. H0b: It is not possible to earn an excess risk-adjusted rate of return on stocks with a sector rotation strategy based on a contrarian approach to industry momentum. …
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».