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Institution

J.P. Morgan & Co.

About: J.P. Morgan & Co. is a based out in . It is known for research contribution in the topics: Portfolio & Implied volatility. The organization has 328 authors who have published 436 publications receiving 14291 citations.


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TL;DR: This paper developed a structural model of intraday price formation that embodies both information shocks and microstructure effects in an internally consistent, unified setting, which allows us to better understand the observed intra-day patterns in bid-ask spreads, price volatility, transaction costs, as well as the autocorrelations of transaction returns and quote revisions.
Abstract: This paper develops a structural model of intraday price formation that embodies both information shocks and microstructure effects in an internally consistent, unified setting. The model allows us to better understand the observed intra-day patterns in bid-ask spreads, price volatility, transaction costs, as well as the autocorrelations of transaction returns and quote revisions. For example, the model simultaneously sheds light on why, over the day, (i) the variance of transaction price changes is U-shaped while the variance of ask price changes is declining, (ii) the bid-ask spread is U-shaped although information asymmetry and uncertainty over fundamentals is decreasing, and (iii) the autocorrelations of transaction price changes are large and negative, yet the autocorrelations of ask price changes are small and negative. In addition, the model s parameters also provide a natural metric of price discovery and effective trading costs, which may prove useful in future studies.

913 citations

Journal ArticleDOI
TL;DR: In this article, the authors argue that insufficient attention has so far been paid to the link between monetary policy and the perception and pricing of risk by economic agents, what might be termed the "risk-taking channel" of monetary policy.

862 citations

Journal ArticleDOI
TL;DR: The authors developed and tested a structural model of intraday price formation that embodies public information shocks and microstructure effects, and used the model to analyze intradays patterns in bid-ask spreads, price volatility, transaction costs, and return and quote autocorrelations, and construct metrics for price discovery and effective trading costs.
Abstract: This article develops and tests a structural model of intraday price formation that embodies public information shocks and microstructure effects. We use the model to analyze intraday patterns in bid-ask spreads, price volatility, transaction costs, and return and quote autocorrelations, and to construct metrics for price discovery and effective trading costs. Information asymmetry and uncertainty over fundamentals decrease over the day, although transaction costs increase. The results help explain the U-shaped pattern in intraday bid-ask spreads and volatility, and are also consistent with the intraday decline in the variance of ask price changes. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.

758 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present a model for pricing and hedging derivative securities and option portfolios in an environment where the volatility is not known precisely, but is assumed instead to lie between two extreme values σmin and σmax.
Abstract: We present a model for pricing and hedging derivative securities and option portfolios in an environment where the volatility is not known precisely, but is assumed instead to lie between two extreme values σminand σmax. These bounds could be inferred from extreme values of the implied volatilities of liquid options, or from high-low peaks in historical stock- or option-implied volatilities. They can be viewed as defining a confidence interval for future volatility values. We show that the extremal non-arbitrageable prices for the derivative asset which arise as the volatility paths vary in such a band can be described by a non-linear PDE, which we call the Black-Scholes-Barenblatt equation. In this equation, the ‘pricing’ volatility is selected dynamically from the two extreme values, σmin, σmax, according to the convexity of the value-function. A simple algorithm for solving the equation by finite-differencing or a trinomial tree is presented. We show that this model captures the importance of diversifi...

728 citations

Journal ArticleDOI
TL;DR: In this article, the authors compare eight stochastic models explaining improvements in mortality rates in England & Wales and in the US and find that an extension of the Cairns, Blake & Dowd (2006b) model that incorporates the cohort effect fits the English and Wales data best, while for US data, the Renshaw & Haberman (2006) extension to the Lee & Carter (1992) model also allows for a cohort effect provides the best fit.
Abstract: We compare quantitatively eight stochastic models explaining improvements in mortality rates in England &Wales and in the US. On the basis of the Bayes Information Criterion (BIC), we find that an extension of the Cairns, Blake & Dowd (2006b) model that incorporates the cohort effect fits the England & Wales data best, while for US data, the Renshaw & Haberman (2006) extension to the Lee & Carter (1992) model that also allows for a cohort effect provides the best fit. However, we identify problems with the robustness of parameter estimates of these models over different time periods. A different extension to the Cairns, Blake & Dowd (2006b) model that allows not only for a cohort effect, but also for a quadratic age effect, while ranking below the other models in terms of the BIC, exhibits parameter stability across different time periods for both data sets. This model also shows, for both data sets, that there have been approximately linear improvements over time in mortality rates at all ages, but that the improvements have been greater at lower ages than at higher ages, and that there are significant cohort effects.

557 citations


Authors

Showing all 328 results

NameH-indexPapersCitations
Manuela Veloso7172027543
Tucker Balch4118110577
George Deodatis361255798
Mustafa Caglayan321444027
Henrique Andrade27813387
Daniel Borrajo261682619
Haibin Zhu25434945
Paolo Pasquariello24532409
Andrew M. Abrahams21371130
Alan Nicholson19901478
Samuel Assefa19342112
Joshua D. Younger17182305
Espen Gaarder Haug171431653
Jeffrey S. Saltz1657852
Guy Coughlan15272729
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20221
202123
202050
201920
20188
201712