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The Man Who Solved the Market Paperback – January 1, 2019
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SOME INTERESTING POINTS:
• Simons is a true mathematician. He loves the elegance of math, the way theorems reveal truth, bringing order to chaos. When he was thirty-seven, he was awarded the top prize in geometry for his academic work.
• In 1964 Simons left his teaching job at Harvard to break codes for the Institute for Defense Analyses. His experience there was KEY to his later success. First, his approach to investing would be like that for code-breaking: apply math to find hidden structure in chaotic data. Second, he was impressed with the way the Institute hired people. It didn’t look to fill specific skills; it looked for the smartest and most creative people it could find.
• After code-breaking, Simons was hired to lead the struggling SUNY Stony Brook math department. In that job, he learned how to recruit and motivate superstar math professors. By the time he left academia to take on the challenge of investing, he had built a powerhouse department. And some of that talent would later join him and earn millions.
• Simons didn’t allow researchers to work in silos. There was one combined trading system, and everyone could see the code. Simons thought it was vital for scientists to interact, debate, and share ideas.
• Renaissance Technologies was not an overnight success. It took Simons ten years to put together the team and process that would go on to make so much money.
• By 2002 the Medallion Fund was so successful that Simons, concerned that performance would fall if the fund grew too big, raised investor fees to 44% of profits.
You don’t need to be a mathematician to read this book. It is simply a good tale. There are no formulas. And along with the story about Jim Simons, Zuckerman tells the history of the radical change in the investment world: “MBAs once scoffed at the thought of relying on a scientific and systematic approach to investing, confident they could hire coders if they were ever needed. Today, coders say the same thing about MBAs, if they think about them at all.”
+ fascinating tale about how quants think and build their models, emphasizing how difficult is to make money on the markets
- more about Rentech than Simons
- don’t expect to find trade secrets here
Top international reviews
The key insight of the book is that Jim Simons and his colleagues realised that markets were not efficient, in contrast to the mainstream view of market efficiency, and that the inefficiency could be exploited for profit. Lots of it. And they were right.
So this book is well worth reading. It’s well written and it skips along at a relatively decent pace. I don’t think it’s a five star book on my scale, and I doubt it will quite make the top step in the FT Business Book of the Year, but it is still a book you probably do want to read sometime soon if you work in and around trading financial markets.
What I liked - Useful biographies of key team players that advanced the success of Jim Simons's Medallion hedge fund and the Renaissance technologies founder. Good index enabling links and cross reference of hedge fund events - Global Alpha Cliff Asness and the Quant quake (refer Greg Smith's why I left Goldman Sachs). Capital and VC involvement described from David Sussman's refusal to GAM's agreement.
What is missing - Old style hold strategy with long event lines was robbable by the quant funds whose techniques was to reduce the event time lines and increase the number of trades. Profitability per trade would diminish but the task was to increase exponentially the number of trades in managed pattern moves - page 223 Medallion was trading up to 300,000 contracts a day. Simplification graphics would help to better grasp essential features of machine managed control like event line time reduction: page 101 halts long term trades, page 113 reduction from 1 week and 1/2 to 1 day and 1/2, page 190 trades average hold 2 days, page 271 hold time 1 or 2 days increases to 1 or 2 weeks. Sorting the Sharpe ratio and evidencing its shape change through a year eventually pushes the ratio out to 7.5 needs illuminating.
The future - investor nervousness. Retrenchment trades and fake chaff news leading to daily 100 point volatility swings in the Dow, Nikkei, Dax, are good for quant funds but negative for investor confidence and micro second entry and exit decisions - IPO management becomes precarious and issues are pulled.
I didn't know Jim Simons smoked heavily; which will be why his voice resonates the way it does and his laugh is often followed by a cough. And Bob Mercer whistles a lot, maybe more than he talks, and was one of the main financial contributors to the 2016 Trump campaign. And how this connects with Brexit and goodness knows what else is quite eye opening.
As with all worthwhile stories the book is about people, and how they relate to each other and their world.
What made the Renaissance Medallion Fund work was obviously in part the shrewd harnessing of the various individuals exceptional intellectual abilities, and the exponential growth of computers processing power. Creative and curious minds meet mathematical modelling and data analysis on a massive scale.
The real success of the company seems to come from the ability and willingness of a handful of principal players to work together, despite extraordinarily different social, political and personal alliances. Motivated by money, for sure, but the theme that much more was intrinsically involved is a strong thread which I think makes the book a 4 star read. Most pleasing of all was throughout there were no goodies or baddies!
Investors like Soros have given up a lot more of their methods - in part because their strategies relied on directional views of macroeconomic factors are harder to replicate in the future. You would assume that if you had knowledge of the code used at Renissance today you could rack up some pretty mean trading profits - since that is exactly what they are doing!
Still I think this is a must for any mathematician, and offers insight to one (of many) ways that mathematics can be applied to the world we live in.
Personal highlight? The joke at the start of Ch 2:
Q: What's the difference between a PhD in mathematics and a large pizza?
A: A large pizza feeds a family of 4.
Furthermore, the main character, Jim Simons stays quite elusive in this story and really just pops in and out of the narrative. Again, this is mainly due to his reluctance to talk much to the author.
So you are left with a slightly strange overview, with some characters probably given more prominence than they were due, probably because they were willing to talk.
It's a light read but you'll come out of it really feeling none the wiser about the man or the company
Das Buch zeigt sehr schön, dass Quantitative Investing sehr erfolgreich sein kann und ihre Bedeutung an den Finanzmärkten weiter zunehmen wird. Eine kleine Gruppe von Mathematikern und Physikern hat an den Märkten mehr erreicht als ein BWLer sich auch nur im Traum hätte vorstellen können. Investieren nach Buy & Hold oder KGV oder Dividenden bla bla .... das hat ausgedient! Rendite wird erwirtschaftet, indem große Datenmengen analysiert und ausgewertet werden, indem mathematische Modelle entworfen und verfeinert werden, indem mathematische Stringenz und Logik auf Kreativität und Programmierkenntnisse treffen.
Lesenswert für alle, die sich für die Börse und die Finanzmärkte interessieren und eine Ahnung davon bekommen wollen wer die wirklich dominanten und erfolgreichen Player dort sind.