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Traders, analysts and investors are always looking for techniques to better predict price movements. Knowing whether a security will increase or decrease allows traders to make better investment decisions and manage risk more effectively. We are lucky to have Kris, Quantitative Analyst and Trader at Capula Investment Management, discuss the various frameworks and tools which can be used in an attempt to predict stock price. Kris ranked highly (top 10%) in BattleFin's Big Data Combine on Kaggle and he will use his experiences there to illustrate his approach.
Schedule
19:00 - 19:15 : Data Science Community Welcome 19:15 - 20:15 : Stock Market Prediction talk by Kris Kasidit Methajarunon, Quantitative Analyst / Trader at Capula 20:15 - 20:30 : Q & A with Kris Kasidit Methajarunon 20:30 - 21:30 : Social hour, light refreshments provided.
Speaker Bio
Kris Kasidit Methajarunon
Kris is currently working as a quant/trader at Capula, a fixed income hedge fund headquartered in London. Prior to this role, he interned with the High Frequency Trading team at Credit Suisse. He has a Bachelor’s degree in Computer Engineering and a Master’s degree in Financial Engineering.
Location
Garage Society 19F, 299 Queen’s Road Central, Hong Kong, Hong Kong
NOT 33 Des Voeux Road Central
Symbol & Key
Symbol & Key is a series of talks organised to support exchanges and foster connections in Hong Kong’s Data Science community. The talks are entry-level, but at the vanguard of the discipline, so it should be accessible to aspiring data scientists and experts alike.
Venue Sponsor
Drinks Sponsor
Terms & Conditions
As part of our sponsorship arrangement, the venue sponsor has the option to add you to their mailing list. To opt out, please let us know at contact@datascience.hk.
Do you have questions about The Science Behind Stock Price Prediction?
Contact Symbol & Key
When & Where
Garage Society, 19F,
299 Queen's Road Central,
Sheung Wan, Hong Kong
Symbol & Key is a series of talks organised to support exchanges and foster connections in Hong Kong's Data Science community. The talks are entry-level, but at the vanguard of the discipline, so it should be accessible to aspiring data scientists and experts alike.
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