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Stochastic Interest Rates for Local Volatility Hybrid Models: Wilmott Magazine Article
E. Benhamou, A. Gruz and A. Rivoira 64 Views

This paper studies the impact of stochastic interest rates for local volatility hybrids. We first show that we can explicitly determine the bias between the local volatility of a model with stochastic interest rates and the local volatility of the same model but with deterministic interest rates as a function between the correlation of the stochastic interest rates and the digital at the local strike.

The Korn-Kreer-Lenssen Model as an Alternative for Option Pricing: Wilmott Magazine Article
Xiong Chen 2539 Views

The first purpose of this paper is to illustrate how the Korn-Kreer-Lenssen model can be implemented in pricing European vanilla options and to analyze the accuracy of this model. The Korn-Kreer-Lenssen model assumes that the underlying stock price follows a linear birth-death process rather than a geometric Brownian motion. The second purpose of this paper is to derive two closed-form solutions for pricing American digital options in the Korn Kreer-Lenssen's framework, by using the birth-death process theory, as well as the probability distribution of the first passage time of the underlying stock process.

Automated Trading with Python [WEBINAR]
In our constant endeavour to include new research and value in Algorithmic Trading domain, QuantInsti is conducting a webinar on Automated Trading with Python with speaker as Dr. Yves J. Hilpisch.

We would like to take this opportunity to invite all the forum members to this webinar and a chance to connect with the leading expert. Read on to get more information about the webinar.

Automated Trading with Python [WEBINAR]

About the Webinar:

This webinar will illustrate how easy it is to implement typical steps of automated trading:

    Historical data scraping
    Backtesting of trading strategies
    Working with streaming data
    Automated trading in real-time

All examples will be based on the platform and API of Background information about Python and the libraries used can be found in the O?Reilly book Hilpisch, Yves (2014): ?Python for Finance ? Analyze Big Financial Data?.

Date: 10th February 2016
Time: 6 P.M. IST (tentatively) / 12:30 PM / 8:30 PM
Venue: Online

About the Speaker:
Yves J. Hilpisch is founder and managing partner of The Python Quants GmbH, Germany, as well as co-founder of The Python Quants LLC., New York City. The group provides Python-based financial and derivatives analytics software as well as consulting, development and training services related to Python, Open Source and Finance. Yves is also author of the book ?Derivatives Analytics with Python? (Wiley Finance, 2015). As a graduate in Business Administration with a Dr.rer.pol. in Mathematical Finance, he lectures on Computational Finance at the CQF Program.

Without any further ado please register on the following link -

QuantInsti is one of Asia?s pioneer Algorithmic Trading Research and Training Institute focused on preparing financial market professionals for the contemporary field of Algorithmic and High Frequency Trading. As the financial markets in emerging markets are rapidly evolving like developed markets; we foresee a disruptive change in the emerging markets landscape wherein exchange volumes to the tune of 70% and above will be generated by Algorithmic Trading.

QuantInsti institute developed the curriculum for the Asia?s first Executive Programme in Algorithmic Trading (EPAT) in 2009. As an initiative by financial markets professionals with stellar academic and professional credentials, the program aims to fulfil the pressing demands for highly specialized skill sets of a potentially lucrative domain of Algorithmic Trading. QuantInsti opened the doors to global participants in 2012 by introducing virtual classrooms for its flagship EPAT course and have seen participation from all inhabited continents since then.
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