دانلود مقاله ISI انگلیسی شماره 13497
عنوان فارسی مقاله

الگوهایی در نقدینگی بازار متقابل

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
13497 2008 9 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
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عنوان انگلیسی
Patterns in cross market liquidity
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Finance Research Letters, Volume 5, Issue 1, March 2008, Pages 2–10

کلمات کلیدی
نقدینگی بازار متقابل - آب پرتقال - تحقیقات علمی - تئوری فراگیر
پیش نمایش مقاله
پیش نمایش مقاله الگوهایی در نقدینگی بازار متقابل

چکیده انگلیسی

Academic research on liquidity has generally focused on explaining what can be called within market liquidity. That is it seeks to explain things like why one stock is more liquid than another. But there has been considerably less attention to cross market liquidity: the issue of why some securities are more liquid than others. For example, stocks are apparently far more liquid than high yield bonds. Why? Why do some markets exist (orange juice for example) while others do not (potatoes for example)? This article lays out the current academic evidence regarding liquidity across assets and explains why current theories have trouble with one item or another. The challenge then is to produce an overarching theory that offers predictions that are closer to what the data seems to imply about cross market liquidity.

نتیجه گیری انگلیسی

Liquidity appears to vary enormously across markets. Overall, the current academic literature implies that in order from most to least liquid one has: government on the run bonds, government off the run bonds, large capitalization stocks, A rated corporate bonds, small capitalization stocks, lower rated corporate bonds, real estate, and then at the very bottom commodities and events for which no market even exists. Other commodities, derivatives, and event contracts would seem to range across the entire liquidity spectrum. Explaining why some asset markets are more liquid than others is not an easy task. Our current theories all have problems with one pattern or another. Perhaps there is no “single” answer. Still, it would be helpful to have an overarching set of principles that supplied predictions at least roughly consistent with the market data we have.

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