068: Mikael Syding – From “Schoolyard Hippie” to European Hedge Fund Manager of the Decade (to AI Enthusiast)

068: Mikael Syding – From “Schoolyard Hippie” to European Hedge Fund Manager of the Decade (to AI Enthusiast)

For this episode, we have our very first guest from Sweden—big shout out to Sweden! I spoke with Mikael Syding; a value investor who spent 15 years in the hedge fund business, and in 2009, he was awarded European Hedge Fund Manger of the Decade before retiring shortly after. During the interview, I ask Mikael to share his three greatest lessons for traders and investors, how he spotted growth opportunities, and I also ask him how his views on money have changed over the span of his career, plus a whole lot more… All of this was great, but I have to say, my favorite part of this conversation was the last 10-15 minutes, where Mikael talks about artificial intelligence and technology becoming one with humans. It’s full on—prepare to have your mind blown! Learn more about your ad choices. Visit megaphone.fm/adchoices

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Episoder(326)

106: Turney Duff – A Wall Street Trader’s Tale of Spectacular Excess

106: Turney Duff – A Wall Street Trader’s Tale of Spectacular Excess

Turney Duff was a hedge fund trader on Wall Street who lead a truly excessive lifestyle. In 2013 he released a book about his experiences—titled, The Buy Side. And currently, Turney is a consultant on...

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105: Brendan Poots – How a Former Punter Pioneered a Premier Sports Betting Hedge Fund

105: Brendan Poots – How a Former Punter Pioneered a Premier Sports Betting Hedge Fund

Brendan Poots is the founder of sports betting hedge fund, The Priomha Group, who mainly bet on football, cricket, golf and also horse racing and tennis. Priomha setup shop in Melbourne (Australia) in...

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104: Alex, @AT09_Trader – An Appetite For Risk, and Hitting Hard When Opportunity Arises

104: Alex, @AT09_Trader – An Appetite For Risk, and Hitting Hard When Opportunity Arises

Alex (@AT09_Trader) is a 22-year old, discretionary day trader, who’s seen great results in the few years he’s been grinding away at this. He trades small caps, and he trades aggressively—as you’ll so...

22 Des 201659min

Q5: Max Margenot – Good (and Not So Good) Uses of Machine Learning in Finance

Q5: Max Margenot – Good (and Not So Good) Uses of Machine Learning in Finance

Machine learning is a hot topic right now, with a lot of people wondering how it could be used in finance and trading. Used naively, machine learning poses a great deal of risk. We’ll discuss why that...

20 Des 201656min

103: Dave Bergstrom – Escaping Randomness, and Turning to Data for an Edge

103: Dave Bergstrom – Escaping Randomness, and Turning to Data for an Edge

On this episode, I’m joined by a quant trader who works at a high frequency trading firm—though you might be surprised to hear, he started out on the same path that many retail traders do—his name is;...

15 Des 201658min

Q4: Scott Sanderson – Portfolio Optimization: Risk Preferences In, Trades Out

Q4: Scott Sanderson – Portfolio Optimization: Risk Preferences In, Trades Out

When one has a price model that they think will work well for forecasting returns, the next step is to actually trade it. This isn’t that simple for a variety of reasons. For one thing, you need to de...

12 Des 20161h 11min

102: Eugene Soltes – Unraveling a $65-Billion Ponzi Scheme and Notorious Cases of Insider Trading

102: Eugene Soltes – Unraveling a $65-Billion Ponzi Scheme and Notorious Cases of Insider Trading

Eugene Soltes is an author and finance professor at Harvard Business School. Over the past eight years, give or take, he’s spent a lot of time with many big-time executives and professionals who have ...

7 Des 20161h 29min

Q3: Jonathan Larkin – Seeking Alpha? Try MORE Alpha Factors

Q3: Jonathan Larkin – Seeking Alpha? Try MORE Alpha Factors

In practice, no one trading model will ever be that good on its own. Luckily statistics has come up with a lot of theory about how you can combine weaker models to create better overall predictions. W...

5 Des 201651min

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