61–70 of 109 posts
Just a reminder: nobody ever wrote about their super successful trading strategy. Its just never happened. If you have the wherewithal to research and build a trading system that works, then you're smart enough to know that the moment you reveal your edge to the world - it disappears. Even if you dont discuss the innards of your strategy, but you talk about your process or the system youre strategy is built on, you'v…
Earlier quoted context omitted.
Probably not very good. Voleon does all ML-based trading and what I've seen of their returns does not give me any confidence in ML-based trading having alpha. I would estimate that at best in a good year returns would be like 5% y/y in the long term, much less than the sustained ~7% that index funds offer especially when adjusting for risk. Just speculation but there's a lot of firms with much more capital, better to…
Returns don't matter. People always compare strategies to the S&P 500's return, but it doesn't make any sense. In finance, strategies are compared on their Sharpe ratio, not on their returns. This is because leverage can be applied to make the returns better. For example, if you had a strategy that, unlevered, returned 5% with 2% volatility, that would be pretty amazing. If you wanted, you could lever up 4x and get a…
Apologies if I misinterpreted your comment, just my thoughts when reading it.
Earlier quoted context omitted.
+1 Any trading strategy based only on price is fool’s errand. The information that impacts price need to be included in the trading strategy. A lot of short term price movement is news driven, thus unstructured text processing of news, social media, relevant documents will be a key component of such trading strategies. I am not that familiar with forex market compared to equity market. But I expect forex to be impact…
No successful strategy ever has been based on price. Price isn't stationary so you can't do anything with it. You need to be looking at the log returns. Price is completely irrelevant, at least for equities.
In some markets it is necessary to put the same length of fiber-optic cable between the colocated servers, so that being closer to the exchange's cabinet doesn't translate into an advantage. So obviously we're talking about extremely low latency, high-frequency trading. This carries a huge amount of prerequisites to even get started. Not only are that, but there are many different order types besides "buy at market p…
[1] You can find a list of NYSE broker/dealers here: https://www.nyse.com/publicdocs/nyse/markets/nyse/members/NY... -- any firm where latency matters will need to be on this list to colo on the exchange.
I tried doing some forecasting with various neural network models after assembling what I thought was a good amount of forex data. The neural net (I tried various architectures) couldn't do any better than chance. After playing around with it and trying to double-check everything, that was as far as I could get. This puts me ahead of most traders, since most of them lose money, then quit. This makes me wonder what ki…
In a literal market, you can find alpha in tomato trading by: (1) monitoring other people’s tomato transactions in as much detail as possible; (2) spying on people who are about to buy tomatoes and rapidly make changes behind the scenes just before they make a purchase; or (3) pointing voice analysis at The Food Network looking out for recipes that call for fresh tomatoes, tracking tomato tankers in major sea lanes,…
Writing ai trading systems is the coding I do for fun since 2012. I'm a little under break even so far but I keep at it because find it so interesting. Since I started every single week I have learned a new way of thinking about a problem I encountered or a new approach to problems that still stand in my way. Questions like, how do you choose a stoploss? Well you can pick it statistically based on history or you can…
Exactly, this is one of the nice things about RL. You don't to do a bunch of handwaving to turn your predictions into a strategy.
Just a reminder: nobody ever wrote about their super successful trading strategy. Its just never happened. If you have the wherewithal to research and build a trading system that works, then you're smart enough to know that the moment you reveal your edge to the world - it disappears. Even if you dont discuss the innards of your strategy, but you talk about your process or the system youre strategy is built on, you'v…
Earlier quoted context omitted.
In a literal market, you can find alpha in tomato trading by: (1) monitoring other people’s tomato transactions in as much detail as possible; (2) spying on people who are about to buy tomatoes and rapidly make changes behind the scenes just before they make a purchase; or (3) pointing voice analysis at The Food Network looking out for recipes that call for fresh tomatoes, tracking tomato tankers in major sea lanes,…
Mind providing a source for what a 'literal market' means? Thanks.
For non-native speakers, market has a specific meaning in US English. In the US a “market” typically means a small shop selling the most common fruits, vegetables, snacks, and household items.
In Europe a market is a larger and more general area for autonomous small traders, usually also trading food and household goods.
The autonomy and low barrier to entry make them a good analogy to a stock market.
(They also suffer from availability and quality issues. A large business can arrange to purchase and retail all of these goods on behalf of consumers under one roof — a supermarket.)
I tried doing some forecasting with various neural network models after assembling what I thought was a good amount of forex data. The neural net (I tried various architectures) couldn't do any better than chance. After playing around with it and trying to double-check everything, that was as far as I could get. This puts me ahead of most traders, since most of them lose money, then quit. This makes me wonder what ki…
A few months ago I tried to evaluate autoregressive behavior in stock returns. To my surprise it seemed strong on some periods, but then weak on others [1], and as you said not reliable enough to rely on.
My impression is that a lot more information aggregation and processing is required to obtain a sustainable edge worth tranding on than what a single developer can achieve in his/her spare time.
Top investment shops have dedicated teams of sw engineers just to deal with the infrastructure that support their data pipelines, financial model backtesting and deployment.
[1] https://thomasvilhena.com/2020/01/likelihood-of-autoregressi...
Earlier quoted context omitted.
There are a number of persistent factors. They are well known in academia and to financial practitioners. There are structural reasons for their existence. We are talking about value, fama french size, etc. These are classic factors that everyone knows about. https://www.aqr.com/Insights/Research/Journal-Article/Bettin... https://en.wikipedia.org/wiki/Low-volatility_anomaly I think your attitude of dismissing decades…
> Also I don't think you understand what "risk-adjusted" means. You might be right; why don't you try explaining it for me? I suspect it is going to look a lot like a justification for why your strategy is fantastic even though it makes sub-par returns.
That will lead you to the reasons why it is very possible to both beat the market and be incapable of scaling it up to billions of dollars.
tl;dr: Someone who has found a way to reliably arbitrage to 25% gains year over year on an inefficiency that will only fill about $100,000 is not going to be able to cash their system in for billions of dollars. But they will be reliably beating the market (on a risk-adjusted basis: assuming the system has risk equal to or less than holding e.g. the S&P).
You will find that firms which can actually reliably beat the market do tend to make their founders wealthy. But they can't scale it beyond the capacity allowed for by the inefficiency. All successful hedge funds and prop shops eventually reach a point where they can't reinvest the returns for the same gain.