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The right kind of volatility
Is there a right kind of volatility for market makers? And how do market makers make money?
Learn this about options: Pricing is hedging
PhD Candidate at École Polytechnique Marcos Costa Santos Carriera takes a look at applying Q-Learning to option pricing, and its impact on hedging strategies.
A neural network approach to understanding implied volatility movements
Presentation by John Hull, Maple Financial Professor Of Derivatives & Risk Management, Joseph L. Rotman School of Management at University Of Toronto, from QuantMinds International 2019
How to survive the new challenges in quant finance?
The latest QuantMinds eMagazine delves into the use of machine learning, alternative data, blockchain applications, diversity, and more!
Modelling volatility, convexity, and option pricing – new approaches and challenges
How are quant finance pioneers achieving more accurate results?
Correlations in modelling energy derivatives, Part II
NYU Professor Roza Galeeva shares her approach to modelling correlations for energy derivatives.
High frequency markets’ volatility seasonality
Time is a powerful construct in our lives, but when modelling volatility, it can be “highly incessant”.
Building a deep learning neural network
B. Horvath, A. Muguruza and M. Tomas discuss the challenges of building a neural network that can tackle all arising challenges.
Correlations in modelling energy derivatives
Correlations are very important for energy derivatives, as Roza Galeeva, Professor at NYU, say, however there are almost no liquid markets in correlation. How could we model their behavior accurately and be able to calibrate parameters to the market instruments?
Assessing risk-profile of quant strategies: the convexity vs skewness
Artur Sepp explores how to analyse the convexity profile of a quantitative investment strategy and how convexity and skewness impacts it.
Volatility seasonality of Bitcoin prices
Anyone looking to invest in cryptocurrencies would have seen that their prices are highly volatile. Anton Golub and Vladimir Petrov explore how.
A soft introduction to rough volatility
Electronic markets have brought about more than just precise intraday data, how has it impacted volatility?
Obtaining one volatility smile for all asset classes
What techniques does Prof. David Gershon use to obtain one volatility smile for all asset classes.
Modelling during quantitative easing
Robert Carver explores quantitative easing and the two ingredients needed for making meta-predictions.
Volatility by jumps
Laura Ballotta, Reader of Financial Mathematics at Cass Business School, provides an overview of why models equipped with jumps outperform those based on pure diffusion.
Non-fundamental market sell-off and “volatility feedback loops”: a market impact perspective
What are the major drivers causing recent market sell-offs and how did volatility exacerbate the recent stock market crash?
How to produce sensible and robust volatility surfaces in real-time
Hear from Dr. Timothy Klassen is the CEO and founder of Vola Dynamics LLC, as he discusses how to produce sensible and robust volatility surfaces ahead of Global Derivatives USA.
Persistently low inflation is the economic factor which seems to have most perplexed policy makers. This low, but confusing, inflation theme has played a central role in keeping long term nominal yields, and by extension the VIX, in a lower for longer condition. Here, Michael Purves discusses VIX deflation, ahead of Global Derivatives USA.
Fatter tails and extreme currency market events
Brent Donnelly looks into the abnormal frequency of extreme currency market events since 2008 to determine causes and solutions.
The "Message from Markets"
Financial markets serve numerous roles, amongst them of course the uncoerced exchange of securities. However, in addition to that role, they inadvertently serve a very useful function of conveying to market observers information about the future. Ehun Ronn, Professor of Finance, looks into Crude-Oil prices and what message from the market can be observed.