Tag Archives: Mathematics

How to Learn Advanced Math Without Going to University

How to Learn Advanced Mathematics Without Going to University

Interesting article series for those who not going to university

https://www.quantstart.com/articles/How-to-Learn-Advanced-Mathematics-Without-Heading-to-University-Part-1

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Pseudo quant mathematics: Crisis waiting to happen

Pseudo quant math: Crisis waiting to happen

Is there a danger lurking in the water of quant? Remember the ‘quant quake’ 10 years ago? Just Google that phrase if you are interested. But for modern day readers, we have this article to present.

From this article:

As the old joke says, “math is what mathematicians do.” Somehow this simple tautology is lost in the dishonest world of finance

Quantitative investing: A crisis waiting to happen

In a recent WSJ article, Jason Zweig brilliantly summarizes the unbearable hype and hubris exhibited by some self-titled “quants”:

BlackRock, the giant asset manager, recently announced it will rely more heavily on computers to pick stocks. Rob Arnott, a leading advocate of mechanical investing approaches, said this past week that it’s “actually relatively easy to beat the market” if you get the math right.

Read this article here

Quant Analytics Trading Pow Wow Intro

Remember that I have my re-introduction to our weekly ‘pow wows’ for my Quant Analytics members. We have nearly 200 which I am proud since I just rolled my former Elite into this new membership. Also, there will be a FREE introductory to these so you can get a form of the style.

Our first weekly one for all to attend. This will become a major feature of our private new

Quant Analytics members. We will talk general trading with automation programming

techniques if you are interested.

I have video on this.

There will be a ‘loose’ agenda on this which I will send within the next 2 days.

Remember, if you want to get my daily human trading call videos, you can join my Quant Analytics here.

Thanks Bryan

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Required Books on Stats & Math for Data Science

Required Books on Stats & Math for Data Science

These need to do on my many to do list

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Free Must Read Books on Statistics & Mathematics for Data Science

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A fine FREE Mathematics – Multivariable Calculus from UC Berkley Lecture 1

A fine FREE Mathematics – Multivariable Calculus from UC Berkley  Lecture 1

I am just starting this on my Khan Academy. I just people would appreciate the importance of topics like this quant trading

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Interesting speech about Some Applications of Mathematics in Quant Finance

Interesting speech about Some Applications of Mathematics in Quant Finance

Interested in learning more?

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The Handbook of Portfolio Mathematics with Formulas for Optimal Allocation and Leverage

Hi there

 
This is one of those books that could be important in the future but forecasting is the critical part. Without profit, you will never have a portfolio to optimize.
The Handbook of Portfolio Mathematics with Formulas for Optimal Allocation & Leverage: I wonder what we use for Matlab and Excel?? – See more at: https://quantlabs.net/blog/2014/04/the-handbook-of-portfolio-mathematics-with-formulas-for-optimal-allocation-leverage-i-wonder-what-we-use-for-matlab-and-excel/#sthash.K5elnJWR.dpuf
Should beginners learning all this get this kind of book?
Would you buy this successful algo quant trading strategy book all in Python? Is it enough or just for beginners – See more at: https://quantlabs.net/blog/2014/04/would-you-buy-this-successful-algo-quant-trading-strategy-book-all-in-python-is-it-enough-or-just-for-beginners/#sthash.aAVFcvzG.dpuf
Or why not become a QLN Premium Member? 
Become a premium quant to learn DotNet source code and Matlab trading models – See more at: https://quantlabs.net/blog/2014/04/become-a-premium-quant-to-learn-dotnet-source-code-and-matlab-trading-models/#sthash.tnwRuNsI.dpuf
Aha he said, learn more here
Bryan
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From the greatest mathematician who has gone HFT with Jim Simons of Rentech with Keynote Speech: Mathematics, Common Sense, and Good Luck

From the greatest mathematician who has gone HFT with Jim Simons of Rentech with Keynote Speech: Mathematics, Common Sense, and Good Luck

As always from the NYC Contact

Join my FREE newsletter to see us get to that level of inteligence (enter sarcasm here despite our lackluster spelling efforts)

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A lot of mathematics has been applied to analysing market movements; the room for technical advantage is narrowing fast

Outside looking in; have we got it right? Historically a lot of mathematics has been applied to analysing market movements; the room for technical advantage is narrowing fast…

External consultant view – is he right? – your views much appreciated.

‘Algorithmic trading’ covers a multitude of different activities.
Historically a lot of mathematics has been applied to analysing market movements from ‘Elliott waves’ to ‘Fibonacci series and banding’ really all as guides but none really being able to predict with any degree of certainty. So the switch was made to being able to trade either faster or with increasing volume based on the application of computer trading (HFT, LLT etc) helped by the US markets adopting a decimal dollar. Liquidity was immediately improved and because the algo volumes overall were not high percentages it all seemed to work well. Now though we have a high percentage of algo trading and it currently is mainly based on taking small increments out of market movement with very little or no view of any asset value. High volumes of these small trades seem to cancel each other out by competing with each other and the room for technical advantage is narrowing fast as we reach the limits of computer speed and latency. This competition without taking a real life view of an asset improves liquidity but appears to have an overall damping effect on value most of the time, but when a statistically significant trend makes the algo effects move in the same direction then it can make massive swings either up or down in the value of a stock because the trades are starting to work as one, possibly the cause of the 2010 market crash. Something else is happening that appears to offset this effect and that is that the financial news providers are now packaging their data in computer readable format (Bloomberg etc) to satisfy the need for algo trading to base some of their decisions on real life events (using neural nets, bayesian, genetic algorithms etc). So the latest systems take a digital news feed and run some algorithms on it to provide the decision point for the auto trading. This approach has been fuelled by diminishing returns in the purely speed related mathematical methods. The good thing about this is that it will start to reflect real life asset values again not just ‘skimming off the top’ so we should start to get more meaningful asset values being reflected. Because this approach is still a small percentage of overall algo trading I don’t believe the good market effects of this have been seen yet. Because of the limitations of computers in being able to handle large numbers of variables this approach is still in its infancy and it takes serious compute time to handle even a small number of variables. So this is where there is need for a ‘front end’ to this process that can look at huge numbers of variables in ‘real time’ and make very quick decisions. Clearly if everybody started to use this front end then the advantage would be reduced over time but the real winner will be the market because ALL decisions will be made on real life asset events so stocks should rise to their true values which is what I believe the SEC is currently concerned about. So I believe that if the SEC was able to skew the percentage ratio of pure algo trading to more real life algo trading then volatility should decrease, asset values and overall liquidity improve. D

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I notice also today that the 2 trillion hedge fund industry lost 5.02% in the past 3 months alone, (Hedge Fund monitor), the worst result since the third quarter of 2008. So no matter that many ultra clever people are involved in algorithmic trading, wouldn’t their time be better spent trying to track major market shifts more correctly instead?

 

 

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Quant analytics: The Role of Mathematics in Finance: Relevance, Reliance, Robustness

Quant analytics: The Role of Mathematics in Finance: Relevance, Reliance, Robustness

The Role of Mathematics in Finance: Relevance, Reliance, Robustness

Paul Wilmott

This is the recording of Paul Wilmott’s recent Paris lecture in which he enlightens, entertains and enrages in equal measure. His lecture is highly critical of quant modelling. On this occasion the specific targets of his disapproval are calibration, market completeness and how quant finance has become predictable. He ends on an example of ridiculous modelling from alternative risk transfer. Paul Wilmott is probably the quant most consistently critical of mathematical finance, and has been for 15 years. His denunciation of commonly held, but erroneous, beliefs is based on his own research, analysis of data, his experience running a hedge fund and, above all, basic common sense. But his negative comments rarely come without positive proposals for how mathematical modelling can be better used.

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