Today we look at the Optiver Realized Volatility Kaggle Challenge and the role of market makers in financial markets. On this channel, over the next two months we will be completing this competition and attempting to provide an accurate methodology for predicting realized volatility over a 10-minute trading window.
In this first video, first we look at some advice from Robbert Pullen (an Optiver Trainer) with regards to financial markets and marker making. The complete video link is provided below the video timeline, this was created by @Optiver Europe.
We will then consider how we can place option prices in the marketplace into perspective, are they high or are they low? One visual method of considering our option price marketplace is to create a graph of a Historical Volatility Cone and compare this to Implied Volatility in financial markets (offered by Market Makers). I have used the same methodology as provided by a link in StackExchange (link below), and have replicated this for the ASX200 index.
Full code available on my website: [ Ссылка ]
00:00 Intro
01:06 Optiver – what are Market Makers?
05:51 Market Makers Profitability
07:43 Cheap or Expensive Options?
08:22 ASX200 Index || Creating the Historical Volatility Cone
12:10 ASX200 Index || Adding Implied Volatility of Call/Put Bid & Asks
15:40 Where does realized volatility come into it?
Quantitative Finance StackExchange Question: [ Ссылка ]
Introduction to financial markets and instruments - Kaggle edition: [ Ссылка ]
Optiver Realized Volatility Kaggle Challenge: [ Ссылка ]
★ ★ QuantPy GitHub ★ ★
Collection of resources used on QuantPy YouTube channel. [ Ссылка ]
★ ★ Discord Community ★ ★
Join a small niche community of like-minded quants on discord. [ Ссылка ]
★ ★ Support our Patreon Community ★ ★
Get access to Jupyter Notebooks that can run in the browser without downloading python.
[ Ссылка ]
★ ★ ThetaData API ★ ★
ThetaData's API provides both realtime and historical options data for end-of-day, and intraday trades and quotes. Use coupon 'QPY1' to receive 20% off on your first month.
[ Ссылка ]
★ ★ Online Quant Tutorials ★ ★
WEBSITE: [ Ссылка ]
★ ★ Contact Us ★ ★
EMAIL: pythonforquants@gmail.com
Disclaimer: All ideas, opinions, recommendations and/or forecasts, expressed or implied in this content, are for informational and educational purposes only and should not be construed as financial product advice or an inducement or instruction to invest, trade, and/or speculate in the markets. Any action or refraining from action; investments, trades, and/or speculations made in light of the ideas, opinions, and/or forecasts, expressed or implied in this content, are committed at your own risk an consequence, financial or otherwise. As an affiliate of ThetaData, QuantPy Pty Ltd is compensated for any purchases made through the link provided in this description.
