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It seems like this hedge fund was run by people who didn't understand finance in the first place. This is how many quant funds work: 1.You develop an alpha fac

by mruts 7y ago

It seems like this hedge fund was run by people who didn't understand finance in the first place. This is how many quant funds work: 1.You develop an alpha factor that you believe is associated with out performance. 2. You control risk factors such as beta, volatility, Fama French 3 factor, etc. 3. Now you create a neutral L/S portfolio that only has exposure to your alpha factor while also negating the risk factors like beta and volatility. 4. Backtest it, run a paper portfolio for awhile, etc. 5. Combine your new alpha factor with a bunch of other factors that you have already developed. The idea being that layering these alpha factors on top of each other will negate some of the noise inherent to each factor. 6. Make money and cycle out and in alpha factors for as long as they work/don't work. It seems like this "hedge fund" was solely trading based on sentiment without creating a L/S market neutral portfolio or layering on any other factors. This is a very bad idea. The quote from the guy who made the software is pretty damning: "The signals we have been provided have a strong scientific foundation. I think we did a pretty decent job. I know I can detect sentiment. I’m not a trader." This is a big red flag. A lot of AI/ML people have this arrogance that trading is easy and that you don't need any financial knowledge to make money. Maybe that was true in the 1980's, but at this point, it requires an incredible level of expertise to generate and implement profitable quant trading strategies. But all of this is off-topic, to get to the point: the Bloomberg article is garbage click-bait. You sue the General Partners, and I don't think anyone is confused about this.

pbhjpbhj 7y ago
>Maybe that was true in the 1980's, but at this point, it requires an incredible level of expertise to generate and implement profitable quant trading strategies. // Are you saying there is no luck in the market any more? Doesn't that mean it's deterministic; and doesn't that mean that market trading is unnecessary as we can allocate needs perfectly?
- nradov 7y ago
  It's not deterministic. When it comes to achieving high returns luck is more important than ever! The public markets have become more efficient and so it's now harder to win based on skill. Most of the funds which have reported high returns are actually just rolling the dice and hitting a lucky streak; the ones that lose big get shut down quickly and you never hear about them. Active traders are trying to find mis-priced securities (market inefficiencies). That used to be relatively easy for smart people who could think up a few key insights. But now there are so many quant funds deploying fast computers and legions of mathematicians that most new strategies stop working quickly. The act of making those trades drives out inefficiencies. Market trading is still necessary for liquidity to minimize the cost of capital.
IceWreck 7y ago
I am not a trader (and have zero knowledge about it) and what I'm about to say might be utter garbage, but hear me out and correct me where I'm wrong. > This is a big red flag. A lot of AI/ML people have this arrogance that trading is easy and that you don't need any financial knowledge to make money. Maybe that was true in the 1980's, but at this point, it requires an incredible level of expertise to generate and implement profitable quant trading strategies. If they were making the trading bot via training it on past data and what they call 'sentiment signals' generated from social media reaction, etc, do they need experience with trading? Is there something else that a human trader knows that the bot (which has been trained on past data and accounts for live reactions) doesn't?
- elliekelly 7y ago
  Something that stood out to me from the article was that the bot "generated a single trade in the morning." Unless they're trying to realize a quick gain by exploiting the "dumb money" most knowledgeable investors specifically avoid trading at market open because the volume/volatility typically comes from Charles Schwab et al. executing trades from regular Joes & Janes. It's noise, not signal. Since the bot wasn't implementing a day-trading strategy it's pretty clear the programmers didn't know much about how the markets work. I would guess the training data reflected that knowledge gap. As the saying goes, you don't know what you don't know.
- marcosdumay 7y ago
  I'm not a trader either, but I have non-zero knowledge about it... > do they need experience with trading? That's a yes. You don't get to put a lot of money onto an investment without some experience on how it's done. This is true for all forms of investment, not only trading. How do you even evaluate to robot if you don't know the market? What do you do if the robot breaks? What do you do if the market breaks (happens once in a while)? How much money you leave under its supervision?
- mruts 7y ago
  Absolutely. You wouldn't know how/when to back test, you wouldn't know how to reduce turnover in your portfolio, you wouldn't know how to measure the volatility of your portfolio, you wouldn't understand why you were making or losing money, you wouldn't realize a regime change in the market, you wouldn't be able to efficiently allocate trades to reduce slippage, you wouldn't know how to optimize your portfolio to achieve a better Sharpe ratio, etc etc etc. The list goes on and on and on. I worked as a quant, and the finance knowledge you need is very deep.

by mruts 7y ago

pbhjpbhj 7y ago

>Maybe that was true in the 1980's, but at this point, it requires an incredible level of expertise to generate and implement profitable quant trading strategies. // Are you saying there is no luck in the market any more? Doesn't that mean it's deterministic; and doesn't that mean that market trading is unnecessary as we can allocate needs perfectly?

nradov 7y ago
It's not deterministic. When it comes to achieving high returns luck is more important than ever! The public markets have become more efficient and so it's now harder to win based on skill. Most of the funds which have reported high returns are actually just rolling the dice and hitting a lucky streak; the ones that lose big get shut down quickly and you never hear about them. Active traders are trying to find mis-priced securities (market inefficiencies). That used to be relatively easy for smart people who could think up a few key insights. But now there are so many quant funds deploying fast computers and legions of mathematicians that most new strategies stop working quickly. The act of making those trades drives out inefficiencies. Market trading is still necessary for liquidity to minimize the cost of capital.

IceWreck 7y ago

I am not a trader (and have zero knowledge about it) and what I'm about to say might be utter garbage, but hear me out and correct me where I'm wrong. > This is a big red flag. A lot of AI/ML people have this arrogance that trading is easy and that you don't need any financial knowledge to make money. Maybe that was true in the 1980's, but at this point, it requires an incredible level of expertise to generate and implement profitable quant trading strategies. If they were making the trading bot via training it on past data and what they call 'sentiment signals' generated from social media reaction, etc, do they need experience with trading? Is there something else that a human trader knows that the bot (which has been trained on past data and accounts for live reactions) doesn't?

elliekelly 7y ago
Something that stood out to me from the article was that the bot "generated a single trade in the morning." Unless they're trying to realize a quick gain by exploiting the "dumb money" most knowledgeable investors specifically avoid trading at market open because the volume/volatility typically comes from Charles Schwab et al. executing trades from regular Joes & Janes. It's noise, not signal. Since the bot wasn't implementing a day-trading strategy it's pretty clear the programmers didn't know much about how the markets work. I would guess the training data reflected that knowledge gap. As the saying goes, you don't know what you don't know.
marcosdumay 7y ago
I'm not a trader either, but I have non-zero knowledge about it... > do they need experience with trading? That's a yes. You don't get to put a lot of money onto an investment without some experience on how it's done. This is true for all forms of investment, not only trading. How do you even evaluate to robot if you don't know the market? What do you do if the robot breaks? What do you do if the market breaks (happens once in a while)? How much money you leave under its supervision?
mruts 7y ago
Absolutely. You wouldn't know how/when to back test, you wouldn't know how to reduce turnover in your portfolio, you wouldn't know how to measure the volatility of your portfolio, you wouldn't understand why you were making or losing money, you wouldn't realize a regime change in the market, you wouldn't be able to efficiently allocate trades to reduce slippage, you wouldn't know how to optimize your portfolio to achieve a better Sharpe ratio, etc etc etc. The list goes on and on and on. I worked as a quant, and the finance knowledge you need is very deep.