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I wonder when they're going to tackle macroeconomic forecasting? It seems like a good candidate - a complex system with too many variables for analytical models

• whimsicalism 5y ago
  Trying to compete in markets is like Goodhart's law on steroids. People use machine learning, but nothing this sophisticated. Outside of the market makers, most of the successful firms are just selection bias.
• EricE 5y ago
  >I wonder when they're going to tackle macroeconomic forecasting? That was Dark Sky's play - and it was amazingly fruitful. It would even leverage the barometer in most phones. It was a bit disappointing when Apple acquired them since it cuts non-iOS users off, but it was a great app when it was out. For iOS users as of iOS 15 Apple's weather widget is now based on Dark Sky's tech making their app redundant.
• libertine 5y ago
  Hmm, but aren't most macroeconomic big swings triggered by Blackswan events? And aren't those, per definition, virtually impossible to predict?
  • netcan 5y ago
    Swings, maybe. There's room for forecasting at larger or smaller intervals, even if swings are unforecastable. That said, I don't think most big financial events are black swan events in some sense but not others. Financial black swans don't tend to be random, real world events. We're living through a major real world event now, and the financial markets haven't collapse... though a lot of weird stuff is happening. The 2008 crisis and many others had not real world. Real world links were gradual and fairly financial in nature, an accumulation of debt/risk/leverage/lies/fragility or whatnot over time. These are more like bugs, design flaws or fail conditions, IMO. From a financial analyst's perspective they're "black swans" because they are events with a >0% likelihood that (by definition) are not priced into security prices or financial systems. From a forecasting model POV... who knows. In any case, forecasting the future of the economy is probably very very hard. If it's possible, it probably has epic sci-fi level consequences.
    • sprafa 5y ago
      Jim Simons and Bob Mercer used Ml to solve the market a decade plus ago. Good book on the topic is The Man Who Solved the Market
    • trashtester 5y ago
      > We're living through a major real world event now, and the financial markets haven't collapse... Central banks are pumping money into the economy at a record rate right now, and still not able to get unemployment down to "normal" levels. This causes supply chain problems and inflation signals that , unless they get resolved, will force the central banks to pull back most of the stimulus. THAT is when the crash will come (if at all). If that comes, central banks will have a choice. Double down on the austerity, raise taxes and try to weather the storm, or restart the money printer and risk very high inflation, if not hyperinflation. My bet is on the latter, as goverment obligations are so high right now that I doubt they have the stomach for austerity. This crisis is not over....
  • wnkrshm 5y ago
    Any arbitrary nonlinear system is not guaranteed to be predictable, it can be chaotic, i.e. it is deterministic but you need infinitely precise knowledge of the initial conditions to predict it (Edit: since small errors in the initial conditions don't necessarily result in small errors in the prediction for nonlinear systems).
• netcan 5y ago
  Careful, dragons be there. Day trading securities is a smaller problem than macroeconomic forecasting, probably... but down this path lies Asimov's psychohistory. It's basically forecasting history.
  • m12k 5y ago
    The crazy thing is that unlike a weather forecast, if people start to trust your economic forecast, then their actions will likely throw it off again, so your new forecast then needs to include the reactions to the first forecast (and other forecasts) and so on, sorta like solving coupled differential equations (or the plot of Dune, with "levels" of prescience). Hopefully you'll get some fix point at the end, e.g. via a Nash equilibrium, where a new forecast doesn't change anybody's reaction any more.
    • mckirk 5y ago
      Yep, it's interesting to wonder about the implications of that. Maybe the only reachable fix-point would be economic disaster, i.e. 'the only way to be right with certainty is to get people to panic by telling them they'll panic'. At least it's much easier to imagine a stable negative feedback-loop than a positive one.
    • twofornone 5y ago
      If and when ML agents control the bulk of transactions, it will be interesting to see the emergent oscillations in market prices. After all you'll likely have neural networks which are effectively being retrained daily, no telling what kind of patterns the system might settle on because of the tight coupling you describe.
    • wongarsu 5y ago
      Let's assume the forecast is sufficiently coarse, just economy will go up/down/stay as is. Now you can just compute the future based on the past plus the reaction to your forecast, for each of your forecasts. That gives you three pairs of (announced prediction, predicted outcome). Now choose any where announced prediction == predicted outcome. This leads you to the same Nash equilibrium that you described, with a simpler model. Of course it's now obvious that an equilibrium is far from guaranteed. If reactions were distributed like dice rolls, 12.5% of days don't contain any equilibrium. I guess at that point just choose whatever leads to the desired outcome (lots of opportunity for "insider trading" here). With a more detailed forecast you need a better approach like you described. I just found the limited case easier to reason about.
• graphLassie 5y ago
  A bigger problem though is the feedback loop between the model and policy makers in this context. For instance, the model predicts 2023 GDP to decrease so we take all out measures to cause this to not happen. Was the model wrong? How would you know? In this context, the model would need to predict the actions by the Fed but the Fed would be the ones using the model. So you would also have to predict the Feds reaction to the prediction the model made of the Fed's reaction to the model..on and on.
  • bick_nyers 5y ago
    The best alternative I can think of is the model explains why 2023 GDP decrease is better in the long run. Such a model can't exist without an solid understanding of human psychology, and that involves trust. Likely, the machine would need to understand this, and spend the first few months/years proving its worth, such as by making those in control of it rich. To make it work, the humans have to place their trust in the machine. Honestly, it's probably better to invent the machine then feed its commands to a real person that people can place their trust into, not unlike Westworld Season 3.
• sprafa 5y ago
  Renaissance Technologies, Jim Simons and Bob Mercer’s fund solved the market with ML techniques ages ago. Can’t remember off the tip off my head but they have consistent 60% annual returns which is unheard of. There’s a great book about it - The Man who Solved the Market
  • caturopath 5y ago
    Rentech has astounding success with one of their strategies, but it's extremely capacity constrained compared to what really good global macroeconomic forecasts would provide.
• 0x4d464d48 5y ago
  The problem is as soon as new predictions are made it causes the people participating in an economy to change their behavior. Thats why people working at central banks like the Federal Reserve will try to downplay risks like inflation to prevent signalling that theyll raise interest rates causing a market correction or businesses from raising prices to deal with it. I think the cats out of the bag now but they sure would love to stuff it back in the bag.
  • apbytes 5y ago
    Actually if someone had a model like that, they have all the incentives to keep it a secret. Also it would allow simulations to be ran and make "good" decisions. But we have better odds of cracking the prediction problem than it's responsible use.
    • 0x4d464d48 5y ago
      Hedge funds and HFT shops definitely do. They invest pretty heavily to make sure their edge is kept a secret.
  • bduerst 5y ago
    Only if you assume efficient market theory is correct. It's more likely that this information will be withheld by incumbents since it is a valuable pricing signal.
    • m0zg 5y ago
      See e.g. Renaissance Technologies and their fund. Market goes up, it goes up, market goes down, it goes up. And the guy who runs it keeps his cards super close to his chest and doesn't discuss the methods at all.
    • deleted 5y ago
      [deleted]
    • 0x4d464d48 5y ago
      Not necessarilly. I don't subscribe to it myself. But when you have a system that's state is dependant on the descisions and therefore actions of its participants anything that influences those decisions, i.e. signals, influences its state. Even the actions of individual actors in a market can be treated as signal. I think of it a bit like Chaos Theory. An investor saw a butterfly flap its wings in Fiji which triggered a chain of events culminating in the DOW dropping 800 points on a day.