PORTFOLIO DECISIONS WITH INFORMATION AND INTERNATIONAL CURRENCY FRICTIONS
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Notice bibliographique
Résumé
Portfolio decision problems have been the focus of research for decades. Many investors nowadays are aware of the benefits of adding foreign assets to a portfolio. These benefits include diversification, “don't put all your eggs in one basket”, and hedging, which serves the same purpose as buying insurance. However, the empirical findings suggest that instead of holding the fully diversified portfolio suggested by financial theory, investors are tilted more heavily towards domestic asset positions. This disparity between theory and data is called the home bias puzzle. Three chapters in this dissertation investigate portfolio decisions from different angles and with distinctive concentrations, aiming at learning the mechanisms and factors at the root of the home bias puzzle. This dissertation complements existing literature by theoretically examining: the relation between portfolio decisions and international currencies; the role of information in asset trading behaviors; and quantitatively examining the welfare gain of holding additional foreign currency denominated assets. The first chapter, titled “International Portfolio in an Open Market Economy: The Role of Endogenous Nominal Exchange Rate'', allows endogenous monetary variables (inflation and nominal exchange) when modeling portfolio decisions in an open market economy. Endogenous monetary variables have not been studied in the existing portfolio decision research, however the risk characteristics of assets, especially bonds, can be better captured with them. This chapter finds the hedging features of assets which papers without endogenous monetary variables cannot obtain. Due to the hedging features of some domestic assets, under a specific set of reasonable parameter values, households exhibit home bias as buying insurance. This chapter has an innovative monetary structure that gives currency value, relates its value to economic conditions, and captures the neutrality of currency. It also sheds light on optimal asset allocation among different asset classes internationally, including bonds and equity issued by different production sectors. The second chapter, titled “International Diversification Portfolio in Noisy Rational Expectation Equilibria: The Role of Asymmetric Information”, investigates asset trading behaviors incorporating information factors in both static and dynamic trading versions. Related work often relies on assumptions regarding information problems, such as additional knowledge about an asset making it less risky to traders. This chapter adopts the “risk borne by investors” defined in fundamental financial theory and such assumptions (additional knowledge about an asset making it less risky to traders) are not needed. This chapter discovers rational traders trade for two separate purposes: speculation and investment. If rational investors have an informational advantage on domestic assets over foreign assets, then they speculate the same way but invest more aggressively in domestic assets in both static and dynamic trading, therefore home bias is expected to occur. This chapter also learns that information has a lasting impact on later trading behaviors. Asymmetric information which happened in earlier sessions can lead to home bias in later trading sessions. The third chapter, titled “Diversification Benefits of Foreign Currency Denominated Assets”, quantitatively analyzes the utility gain for the average U.S. investor from holding additional stock and/or bonds denominated in foreign currencies (U.K. and Canada). This chapter richens the existing literature by testing the ex-post welfare gain, providing a new perspective for understanding the international diversification benefits. The quantitative results show an additional portfolio with foreign government bonds brings more life-time ex-post welfare gain than the portfolio with the foreign stock index. It supports existing literature that, given the existing asset holdings of the average U.S. investor, the international diversification benefits of additional bonds outperform that of stock.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 découle