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Well, yes, but more nuanced. TA is essentially a form of misguided quantitative analysis. The reason it's misguided is because the courses that teach you TA are

Well, yes, but more nuanced. TA is essentially a form of misguided quantitative analysis. The reason it's misguided is because the courses that teach you TA aren't properly backtested. Renaissance Technologies seems to have a lot of black box mathematical models that they make a lot of money on. How is that different than TA? It's backtested, and analyzed in further rigorous means. TA misses rigor, that's it. The problem: rigor is hard and many people are too immature to be rigorous, myself included as in many cases it means you need mathematical maturity. It's weird, I view trading as one of the few fields where academics are more practical than being practical. I don't think the world has learned this lesson yet. I might be wrong of course, just an opinion.

vasco 5y ago
Say a companies directors are not trustworthy and you get a bad feeling from the way they speak about people around them. Later on, huge fraud is uncovered at the company. What does (rigorous or not) TA or backtesting tell you about the likelyhood of something like this happening?
- nightski 5y ago
  It doesn't need to. You don't put all your eggs in one basket. No trader expects 100% win rate, not even close.
- mettamage 5y ago
  Nightski (sibling comment) has a point. Here are a few others. Disclaimer: I'm a retail trader and investor. I'm beginning to take retail trading/investing as seriously as founding a startup as they compete very much for the same rewards in many cases [0]. I'm assuming you're talking about seeing the CEO on television or something. I'm not assuming an insider context as I don't want to think about insider trading. I find your initial premise a tough one to accept. That people can detect lies based on their intuition. This is because I have learned in psychology classes that (1) lies are extremely tough to detect and (2) intuition is only reliable when you have practiced a lot in a consistent-rule-based environment (e.g. think Chess). While there are some lie detection patterns that outperform chance level, there are few and they don't outperform on a crazy scale. Then again, I'll indulge in the premise because it's tough to make concrete premises and I think I see where you want to go with this. So let's do this. From a quant standpoint, you could probably quantify "untrustworthy" speech somehow. You can backtest that algorithm. Obviously TA doesn't do this. Then again, I know little about TA because I think it is misguided. From a trader standpoint: maybe you actually want to trade on the lies, especially when you know about them [1]. It really comes down to your form of ethics [2] and if you can make a higher return. [0] The same rewards are: Note: I'm a bit creative in this. When I was younger I wasn't, which is why I wasn't interested in trading/investing. - Money - Having freedom in your own way of working - Getting to product market fit (aka understanding a market) - Having an impact on society. I struggled how to achieve this with trading/investing for a long while, but the way to do it is to share what you know (I do that for free, I'm quite vocal in my friend group about it). Every decision in life has an "investment" component to it (what should I eat today? Should I buy a house? Should I go to uni? Should I date that person? What route should I take from A to B?). I like to take that grand view and hone it though financial markets. - In both cases, you can create an environment where hardcore academics and truth seeking can have a huge financial and societal impact. If I ever get to the stage where I'm smart enough to make a lot of money due to truth, then at one point I'll make my strategies public if they have a strong "truth seeking" component to it (and provided I can isolate it from the luck factor involved). [1] Example: look at the whole cryptocurrency space. Note: there are genuine believers, earnest hard workers (on protocols and such) and true visionairies. However, the opposite of those archetypes are also abundant in that space: hardcore cynical speculators, lazy scammers and copycats. So there are enough traders there that simply try to beat other people in a trade despite the fact that they believe it's all worth nothing and it's all bullshit. [2] My younger self would find it unacceptable, so I'd never trade on it. Nowadays I find it acceptable to trade on "unethical things" in quite a few circumstances. In both cases, I still require that I think and feel deeply about it.
  - samhw 5y ago
    > Every decision in life has an "investment" component to it (what should I eat today? Should I buy a house? Should I go to uni? Should I date that person? What route should I take from A to B?). I like to take that grand view and hone it though financial markets. This is a really nice way of thinking about it. Thanks for sharing this.
- csee 5y ago
  A valuable edge doesn't have to predict the entire space of possible outcomes. For example, an index rebalance edge has no idea about macro events, earnings, etc, but it is still a valuable edge.
csee 5y ago
Some edges can be quantified easily, and others really can't be. One canonical example of the former is the bid-offer imbalance. That's because autocorrelation is low, variability is high, the signal can be encoded easily, the distribution is bell-shaped, the heteroskedasticity is low, and we have a tremendous amount of historical data to work with. TA exists on the very opposite side of this gulf, where its profound difficulty to study using the traditional statistics/ML toolbox is conflated with no edge by many dogmatists in the industry. It's unbelievably difficult to come up with a good encoding of what's visually obvious to a human, and beyond that such encodings are very difficult to backtest because of the typical nasties (autocorrelated data and so forth). In my strong opinion, the failure of TA is more a failure of the quant industry at present. I believe they will figure out how to monetize that edge, but it's beyond the scope of their tools and capabilities at present.

vasco 5y ago

Say a companies directors are not trustworthy and you get a bad feeling from the way they speak about people around them. Later on, huge fraud is uncovered at the company. What does (rigorous or not) TA or backtesting tell you about the likelyhood of something like this happening?

nightski 5y ago
It doesn't need to. You don't put all your eggs in one basket. No trader expects 100% win rate, not even close.
mettamage 5y ago
Nightski (sibling comment) has a point. Here are a few others. Disclaimer: I'm a retail trader and investor. I'm beginning to take retail trading/investing as seriously as founding a startup as they compete very much for the same rewards in many cases [0]. I'm assuming you're talking about seeing the CEO on television or something. I'm not assuming an insider context as I don't want to think about insider trading. I find your initial premise a tough one to accept. That people can detect lies based on their intuition. This is because I have learned in psychology classes that (1) lies are extremely tough to detect and (2) intuition is only reliable when you have practiced a lot in a consistent-rule-based environment (e.g. think Chess). While there are some lie detection patterns that outperform chance level, there are few and they don't outperform on a crazy scale. Then again, I'll indulge in the premise because it's tough to make concrete premises and I think I see where you want to go with this. So let's do this. From a quant standpoint, you could probably quantify "untrustworthy" speech somehow. You can backtest that algorithm. Obviously TA doesn't do this. Then again, I know little about TA because I think it is misguided. From a trader standpoint: maybe you actually want to trade on the lies, especially when you know about them [1]. It really comes down to your form of ethics [2] and if you can make a higher return. [0] The same rewards are: Note: I'm a bit creative in this. When I was younger I wasn't, which is why I wasn't interested in trading/investing. - Money - Having freedom in your own way of working - Getting to product market fit (aka understanding a market) - Having an impact on society. I struggled how to achieve this with trading/investing for a long while, but the way to do it is to share what you know (I do that for free, I'm quite vocal in my friend group about it). Every decision in life has an "investment" component to it (what should I eat today? Should I buy a house? Should I go to uni? Should I date that person? What route should I take from A to B?). I like to take that grand view and hone it though financial markets. - In both cases, you can create an environment where hardcore academics and truth seeking can have a huge financial and societal impact. If I ever get to the stage where I'm smart enough to make a lot of money due to truth, then at one point I'll make my strategies public if they have a strong "truth seeking" component to it (and provided I can isolate it from the luck factor involved). [1] Example: look at the whole cryptocurrency space. Note: there are genuine believers, earnest hard workers (on protocols and such) and true visionairies. However, the opposite of those archetypes are also abundant in that space: hardcore cynical speculators, lazy scammers and copycats. So there are enough traders there that simply try to beat other people in a trade despite the fact that they believe it's all worth nothing and it's all bullshit. [2] My younger self would find it unacceptable, so I'd never trade on it. Nowadays I find it acceptable to trade on "unethical things" in quite a few circumstances. In both cases, I still require that I think and feel deeply about it.
- samhw 5y ago
  > Every decision in life has an "investment" component to it (what should I eat today? Should I buy a house? Should I go to uni? Should I date that person? What route should I take from A to B?). I like to take that grand view and hone it though financial markets. This is a really nice way of thinking about it. Thanks for sharing this.
csee 5y ago
A valuable edge doesn't have to predict the entire space of possible outcomes. For example, an index rebalance edge has no idea about macro events, earnings, etc, but it is still a valuable edge.

csee 5y ago

Some edges can be quantified easily, and others really can't be. One canonical example of the former is the bid-offer imbalance. That's because autocorrelation is low, variability is high, the signal can be encoded easily, the distribution is bell-shaped, the heteroskedasticity is low, and we have a tremendous amount of historical data to work with. TA exists on the very opposite side of this gulf, where its profound difficulty to study using the traditional statistics/ML toolbox is conflated with no edge by many dogmatists in the industry. It's unbelievably difficult to come up with a good encoding of what's visually obvious to a human, and beyond that such encodings are very difficult to backtest because of the typical nasties (autocorrelated data and so forth). In my strong opinion, the failure of TA is more a failure of the quant industry at present. I believe they will figure out how to monetize that edge, but it's beyond the scope of their tools and capabilities at present.