Author: Jonathan

Dr Jonathan Kinlay is the Head of Quantitative Trading at Systematic Strategies, LLC, a systematic hedge fund that deploys high frequency, systematic trading strategies. Dr Kinlay, was the founder and General Partner of the Caissa Capital hedge fund, whose volatility arbitrage strategies were developed by Dr Kinlay’s investment research firm, Investment Analytics. Dr Kinlay was formerly Global Head of Model Review at the US investment bank Bear Stearns. Dr Kinlay holds a PhD in economics and has held positions on the faculty at New York University Stern School of Business, Carnegie Mellon and Reading Universities.
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Introducing My Groundbreaking AI Assistants

I’m delighted to introduce my new series of custom-designed AI tools powered by cutting-edge generative technology. With just a click, you can now access a range of intelligent assistants tailored for different tasks.

These AI helpers are the product of fine-tuning powerful models called Generative Pre-trained Transformers (GPTs). I’ve carefully adjusted them to excel at everything from writing to math to coding and beyond.

To try one out, simply click the icon below for the assistant you need. A new world of AI support is now at your fingertips.

As a subscriber to ChatGPT, you can use these GPT-based assistants entirely for free.

I’ll also be expanding the collection as I develop more, so be sure to bookmark this page and sign up for my blog to receive updates and new releases.

Let my growing cast of AI experts supercharge your work and unleash your productivity. The future is here – let them help you take on any task or challenge imaginable. Just click and tell them how they can lend a hand.

Quantitative Finance

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The SABR Stochastic Volatility Model

The SABR (Stochastic Alpha, Beta, Rho) model is a stochastic volatility model, which attempts to capture the volatility smile in derivatives markets. The name stands for “Stochastic Alpha, Beta, Rho”, referring to the parameters of the model. The model was developed by Patrick Hagan, Deep Kumar, Andrew Lesniewski, and Diana Woodward.

The-SABR-Stochastic-Volatility-Model

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Seasonality in Equity Returns

To amplify Valérie Noël‘s post a little, we can use the Equities Entity Store (https://lnkd.in/epg-5wwM) to extract returns for the S&P500 index for (almost) the last century and compute the average return by month, as follows.

July is shown to be (by far) the most positive month for the index, with an average return of +1.67%, in stark contrast to the month of Sept. in which the index has experienced an average negative return of -1.15%.

Continuing the analysis a little further, we can again use the the Equities Entity Store (https://lnkd.in/epg-5wwM) to extract estimated average volatility for the S&P500 by calendar month since 1927:

As you can see, July is not only the month with highest average monthly return, but also has amongst the lowest levels of volatility, on average.

Consequently, risk-adjusted average rates of return in July far exceed other months of the year.

Conclusion: bears certainly have a case that the market is over-stretched here, but I would urge caution: hold off until end Q3 before shorting this market in significant size.

For those market analysts who prefer a little more analytical meat, we can compare the median returns for the #S&P500 Index for the months of July and September using the nonparametric MannWhitney test.

This indicates that there is only a 0.13% probability that the series of returns for the two months are generated from distributions with the same median.

Conclusion: Index performance in July really is much better than in September.

For more analysis along these lines, see my recent book, Equity Analytics: