I'm a mathematician, not from finance, but this guy has other videos on how this gives you a statistical edge. Essentially: Black-Scholes fails to price assets accurately in the short term, because volatility follows a power law distribution. Also, because it's scale-free, changes at smaller scales actually _predict_ changes at larger scales. The entire system is said to have some net RG-flow. That's your statistical edge.
Hee hee - we seem to be on different pages here then. I'm not arguing but I tend to think the concept of a statistical edge is somewhat problematic (please feel free to share what you're doing) - it's easy to find trading algorithms that will work for a while, the problem is that they then don't work for while :), that's the statistical nature of markets - sometimes the market will trend in a way that works for a given system. What you are doing is looking for systematic biases in the data which an algorithm could exploit, which might exist but are probably peculiar to the market you are looking at, or to a particular time period for that market, and difficult to exploit with high-frequency trading because of the mechanics of trying to do that (e.g. fees, buy/sell spreads, getting your order filled), and there's no guarantee they will last. Someone like Jim Simons can find exploits, but I suspect they can be fleeting and you have to work really hard to find them. Not sure there is anything generic you can do because different assets or markets are different, and the drivers of the biases may be different. That's why I think people like Mandelbrot and Nassim Taleb are more interesting because they focus on the mistaken assumptions that large market players make about risk and valuations. Taleb played at exploiting that, Mandelbrot was more of an observer. But these things are useful to understand because it's almost a necessity for people to have stock market investments as part of a portfolio, and understanding better the nature of these things can only be helpful!
Do you have any reference book or learning resources of complexity theory and how it can be applied on financial data analysis? Many thanks! Also, I wonder what types of trading strategies you are using. It seems the most related type is trading volatility and I would like to ask whether it is applicable to the most popular type of strategies that trade the moving direction (up or down).
Hi there - unfortunately I don't think that book in relation to finance has been written yet!! (Though I could be wrong). I'd suggest though look at the websites for the Santa Fe Institute and the New England Complex Systems Institute. They are multidisciplinary, but should have bits and pieces that would help build understanding.
Thanks for the video and especially with the explanation of the power law. In terms of the market not following valuations, I think of if in terms of expectations of future valuation trends already being priced in. But when the valuations are wrong, and it seems the subjective expectations are much different than the objective reality then there is big volatility. This makes sense in terms of key players setting off these changes, as they are the status quo in defining the subjective valuations.
The topic of valuations is a logical argument, but the market is irrational and governed by social mood, where trends and irrational situations surpass human logic. One of the most iconic quotes from the 1929 crash perfectly represents this: "Human madness and greed are far more powerful forces in the business world than reason and moderation." I’d like to know what you think about socionomics or Elliott Wave, as they seem to relate closely to your video.
Good observation! I'm not sure exactly what socionomics is but I am a firm believer in behavioral economics :). Elliot wave - a bit of a dated concept that possibly has some broadly interesting ideas but not strictly useful for its intended purpose (i.e. I don't think it works as literally described). I'll try to talk about this in more depth at some point. Actually, I'd be more interested in YOUR thinking on Elliot waves!
Hey there - I'm struggling to think of a book that brings all those ideas together - maybe there's a market gap there, hee hee. But "Complexity" by Waldrop was where I first came across Complexity Theory, and "Simply Complexity: A Clear Guide to Complexity Theory" might provide a slightly more up-to-date and nuanced description. Mandelbrot's "(Mis)behavior of Markets" and Nassim Taleb's various books are all good for discussing how markets really behave. Hope that helps! I guess it depends on what you are looking for - let me know if these don't help.
@fractalmanhattan thank you for the reply. I did check the books you referred. It seems like they are introductory. I have read "the misbehavior of markets" and found it interesting but lacking detailed mathematical rigour. I have read all books written by prof. Aswath Damodaran. They provided me with necessary tools to approach valuing any company. I have created my own systems using these tools since I am well versed with software development. I wanted to do the same using fractals or complexity theory. Would really appreciate if you could suggest something which helps me in this. Thank you for your videos. They are really interesting.
Okay thanks @KJkayjae - I agree, they are pretty introductory, but I'm not really sure what books exist that explain these concepts at a level more like a textbook, sorry. I have a feeling this subject may have slipped between the cracks in some mainstream finance courses, because it is too esoteric. You occasionally see economists and finance people complaining about how dated finance models are, which proves Mandelbrot’s point, even though he died a while ago! I'd suggest go and see what you can find on the Santa Fe Institute, or New England Complex Systems Institute websites. Fractals and complexity theory have broad application, and a lot of the literature deals with them in other fields, like geophysics and sociology. A much more technical book on this is: The Weather and Climate - Emergent Laws and Multifractal Cascades by Shaun Lovejoy and Daniel Schertzer - though it talks about weather, it's the same tools. One of the problems is that a lot of these books and other info are pretty terribly written, partly because it is (was) a very new science when these were written, and in the meantime may have been overshadowed by other topics like Big Data, Machine Learning and AI.
The wealthiest 10% of Americans own a record 93% of US equities, according to Federal Reserve data. So, if their portfolio goes up 50%, they may not look at that as an opportunity to sell because they don't need the money and want a longer-term investment. They can already purchase anything they want. They are more worried about taxes than the average person. They may instead decide to take out low interest loans with stock as their collateral to avoid selling and paying a high tax rate. This will make a market owned by whales strangely calm and stable in long term up trends and down trends. Conversely if you look at meme stocks or cryptocurrencies that were owned by gamblers, they can be incredibly volatile because they want out as soon as they have a good profit.
@@miguelpereira9859 Maybe, but that would also be sad to see. When whales finally control all the supply it no longer has the type of decentralization that its creators had hoped it would have.
Making money in the market is trivial just pick 20 companies with a tech moat and in an industry where adoption alone will make it grow 10x then trim the position that experience optimism rally and redeploy in the positions suffering short term losses and re balance when possible.
Man you Talk 6 Minuten just to say absolute nothing. Where is the statistical Edge in knowing that? All this Knowledge means nothing in actual trading
I'm a mathematician, not from finance, but this guy has other videos on how this gives you a statistical edge.
Essentially: Black-Scholes fails to price assets accurately in the short term, because volatility follows a power law distribution. Also, because it's scale-free, changes at smaller scales actually _predict_ changes at larger scales. The entire system is said to have some net RG-flow. That's your statistical edge.
Interessting. So a Multi timeframe analysis gives you an edge when done Right
@@Eta_Carinae__ any resources on this?
Thanks @Eta_Carinae_ you are a scholar and an esteemed viewer!!
Hee hee - we seem to be on different pages here then. I'm not arguing but I tend to think the concept of a statistical edge is somewhat problematic (please feel free to share what you're doing) - it's easy to find trading algorithms that will work for a while, the problem is that they then don't work for while :), that's the statistical nature of markets - sometimes the market will trend in a way that works for a given system. What you are doing is looking for systematic biases in the data which an algorithm could exploit, which might exist but are probably peculiar to the market you are looking at, or to a particular time period for that market, and difficult to exploit with high-frequency trading because of the mechanics of trying to do that (e.g. fees, buy/sell spreads, getting your order filled), and there's no guarantee they will last. Someone like Jim Simons can find exploits, but I suspect they can be fleeting and you have to work really hard to find them. Not sure there is anything generic you can do because different assets or markets are different, and the drivers of the biases may be different. That's why I think people like Mandelbrot and Nassim Taleb are more interesting because they focus on the mistaken assumptions that large market players make about risk and valuations. Taleb played at exploiting that, Mandelbrot was more of an observer. But these things are useful to understand because it's almost a necessity for people to have stock market investments as part of a portfolio, and understanding better the nature of these things can only be helpful!
Do you have any reference book or learning resources of complexity theory and how it can be applied on financial data analysis? Many thanks!
Also, I wonder what types of trading strategies you are using. It seems the most related type is trading volatility and I would like to ask whether it is applicable to the most popular type of strategies that trade the moving direction (up or down).
Hi there - unfortunately I don't think that book in relation to finance has been written yet!! (Though I could be wrong). I'd suggest though look at the websites for the Santa Fe Institute and the New England Complex Systems Institute. They are multidisciplinary, but should have bits and pieces that would help build understanding.
Thanks for the video and especially with the explanation of the power law. In terms of the market not following valuations, I think of if in terms of expectations of future valuation trends already being priced in. But when the valuations are wrong, and it seems the subjective expectations are much different than the objective reality then there is big volatility. This makes sense in terms of key players setting off these changes, as they are the status quo in defining the subjective valuations.
Thanks and nice comment!! Nice way of putting it about the connection between valuations and volatility!
The topic of valuations is a logical argument, but the market is irrational and governed by social mood, where trends and irrational situations surpass human logic. One of the most iconic quotes from the 1929 crash perfectly represents this: "Human madness and greed are far more powerful forces in the business world than reason and moderation." I’d like to know what you think about socionomics or Elliott Wave, as they seem to relate closely to your video.
Good observation! I'm not sure exactly what socionomics is but I am a firm believer in behavioral economics :). Elliot wave - a bit of a dated concept that possibly has some broadly interesting ideas but not strictly useful for its intended purpose (i.e. I don't think it works as literally described). I'll try to talk about this in more depth at some point. Actually, I'd be more interested in YOUR thinking on Elliot waves!
very useful and interesting video ser, thanks.
And thanks again!!
Outstanding work 👏
3:12 Do you think it's possible to 'predict' vol clustering in general, or at least try to 'see' it coming ?
Thank you in advance
Thanks!! See my answer in the comments on the Random Walks video :)
Thanks FM! 💕
Glad you enjoyed it!!
Hey loved the video. Can you suggest a few good books which deals with this concept in depth?
Hey there - I'm struggling to think of a book that brings all those ideas together - maybe there's a market gap there, hee hee. But "Complexity" by Waldrop was where I first came across Complexity Theory, and "Simply Complexity: A Clear Guide to Complexity Theory" might provide a slightly more up-to-date and nuanced description. Mandelbrot's "(Mis)behavior of Markets" and Nassim Taleb's various books are all good for discussing how markets really behave. Hope that helps! I guess it depends on what you are looking for - let me know if these don't help.
@fractalmanhattan thank you for the reply. I did check the books you referred. It seems like they are introductory. I have read "the misbehavior of markets" and found it interesting but lacking detailed mathematical rigour. I have read all books written by prof. Aswath Damodaran. They provided me with necessary tools to approach valuing any company. I have created my own systems using these tools since I am well versed with software development. I wanted to do the same using fractals or complexity theory. Would really appreciate if you could suggest something which helps me in this.
Thank you for your videos. They are really interesting.
Okay thanks @KJkayjae - I agree, they are pretty introductory, but I'm not really sure what books exist that explain these concepts at a level more like a textbook, sorry. I have a feeling this subject may have slipped between the cracks in some mainstream finance courses, because it is too esoteric. You occasionally see economists and finance people complaining about how dated finance models are, which proves Mandelbrot’s point, even though he died a while ago! I'd suggest go and see what you can find on the Santa Fe Institute, or New England Complex Systems Institute websites. Fractals and complexity theory have broad application, and a lot of the literature deals with them in other fields, like geophysics and sociology. A much more technical book on this is: The Weather and Climate - Emergent Laws and Multifractal Cascades by Shaun Lovejoy and Daniel Schertzer - though it talks about weather, it's the same tools. One of the problems is that a lot of these books and other info are pretty terribly written, partly because it is (was) a very new science when these were written, and in the meantime may have been overshadowed by other topics like Big Data, Machine Learning and AI.
Great work. Thx
Thank you so much! Appreciate you watching it
Amazing video! Thank you, once again.
Thanks Brumor - really appreciate your support!!
Great video, thank you for good content, definitely will buy few books, and dig deeper!
Thank you! Hope it adds value!!
The wealthiest 10% of Americans own a record 93% of US equities, according to Federal Reserve data.
So, if their portfolio goes up 50%, they may not look at that as an opportunity to sell because they don't need the money and want a longer-term investment.
They can already purchase anything they want. They are more worried about taxes than the average person. They may instead decide to take out low interest loans with stock as their collateral to avoid selling and paying a high tax rate. This will make a market owned by whales strangely calm and stable in long term up trends and down trends.
Conversely if you look at meme stocks or cryptocurrencies that were owned by gamblers, they can be incredibly volatile because they want out as soon as they have a good profit.
Thanks for that and really interesting perspective!!
This is a big reason why Bitcoin will become less and less volatile in the coming years
@@miguelpereira9859 Maybe, but that would also be sad to see. When whales finally control all the supply it no longer has the type of decentralization that its creators had hoped it would have.
Urm - yeah - I tend to agree with @stevenlarson3316 on that - wouldn't it have less value the fewer people using it?
Making money in the market is trivial just pick 20 companies with a tech moat and in an industry where adoption alone will make it grow 10x then trim the position that experience optimism rally and redeploy in the positions suffering short term losses and re balance when possible.
Hey really nice comment!
Or just pick stocks that are going up and sell them when they get overvalued, it's so simple /s
@@chrisf1600 or buy them sell at the top and short back down
Why are you making videos?
Hee hee - thanks mate. I should though make an introductory video at some point to talk about "the why" of this channel
Look forward to it
Waking up every 14th of each month to $210,000 ,it's a blessing to I and my family......Big gratitude.