13
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How long do algorithmic trading strategies typically remain profitable?
Is there a typical "half-life" of a strategy?
This is a really subjective question, and I don't think any singular answer will generalize well. That being said, I will give some examples ...
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12
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Which algorithms do robo-advisors use?
After having done a lot of research on the topic I found the following excellent research piece on ETF.com:
Wealthfront modifies historic asset-class returns with current market
implied expected ...
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12
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Is it really possible to create a robust algorithmic trading strategy for intraday trading?
Here's my favorite example of an intraday strategy on S&P500 futures that at least used to work:
Intraday Share Price Volatility and Leveraged ETF Rebalancing
I pull it out whenever people start ...
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Does Chan use the wrong state transition model in his Kalman filter code?
In addition to getting the right transition model for the Kalman filter, the main obstacle to optimizing filter performance is to implement an optimal initialization. I use an iterative approach to ...
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12
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What are the "sniffing" or "stalking" algorithms?
Sniffing (or stalking) algo indeed detects other algorithms. How does that work in practice?
Imagine the order book for a particular equity is: Bid 1 = 99 (size 10,000), Bid 2 = 98 (size 25,000), Bid ...
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10
votes
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Is it really possible to create a robust algorithmic trading strategy for intraday trading?
Such a complex question...
Geometric Brownian Motion (GBM) will not typically work to aid one finding strategies based on technicals, as the pursuit of the technical trader is to find market ...
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Is this how stock trading works?
In January 2020, Matteo Aquilina, Eric Budish, and Peter O’Neill from Britain's Financial Conduct Authority published this study, illustrating how "low latency" market participants can make ...
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9
votes
Why do Human traders make money?
First we have to clarify what we mean by profits: I think your question can only address the fact that some human traders beat the market (because you also make profit by just buying the market, e.g. ...
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9
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Why does algorithmic trading account for a significantly higher percentage of trades in the USA than in Europe or Asia?
Why does algorithmic trading account for a significantly higher percentage of trades in the USA than in Europe or Asia?
One of the major reasons for this is the significant fragmentation in the U.S. ...
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9
votes
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Modelling queue position
No, you have to build your model empirically with data.
Suppose $p(x)$ denotes the probability of cancel in front of you when your order is positioned $0 \leq x \leq 1$ through the queue, there are a ...
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8
votes
Programmatically detect RSI divergence
I was searching for answers to the same question and came across your question.
After some thought and research, here is the plan I have developed. I will be working in Python.
Calculate relative ...
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8
votes
Is this how stock trading works?
You would definitely have some advantage. High Frequency Trading is all about speed and the fastest traders wins. Oftentimes, winner takes all.
The blog Sniper in Mahwah & friends digs into the ...
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8
votes
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YFinance incoherent daily and hourly values
When you sample stock market data, you really need to understand what source(s) and rules are being used, and any adjustments applied to the data. Different rules might also exist for different ...
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7
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Proof that no trading system always wins
At the first glance, what you are asking for is a model admitting arbitrage, so there is a zero chance of losing money and positive chance of yielding profits. Well, many equilibrium models start with ...
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7
votes
Which features to include in an algorithmic trading dashboard?
Unfortunately, the answer is: it depends. People care about different metrics and visualizations depending on the type of strategy that they are running. It is a very bad idea to spend time creating ...
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7
votes
definition of mid price in literature
As someone who has contributed to literature, I am purposefully vague with the use of mid price. Not that I don't define it but that it is difficult to state which definition is the best in which ...
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7
votes
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Defining an objective function for machine learning task of trading
The code below is written in Wolfram Mathematica.
For example, we have some training data. And we are trying to predict: long (1) or short (0).
...
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7
votes
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Algorithmic Trading: Python vs SQL
Python has lots of excellent libraries to compute Technical indicators for you, ta and ta-lib are great. These libraries have ...
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votes
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How can we estimate new stock price after a large purchase?
There are a number of price impact models which seek to predict the bias induced on prices by trading. There are also issues with some of these models (which I will mention later).
Models
Probably the ...
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7
votes
Accepted
Formerly profitable algorithmic trading strategies?
Take a look at compilations such as 151 Trading Strategies.
I wouldn't expect this information to be widely disclosed. After all, a non-profitable strategy is a supermartingale which means there is an ...
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7
votes
If 90% of retail traders lose money, doesn’t that mean price movements are not random?
Markets might be nonrandom but retail traders losing money on average is insufficient evidence of this. Most folks lose money playing roulette despite the outcome being random. As noob2 suggests in ...
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6
votes
Sources of Machine Readable News
I ended up developing my own financial news API (real-time and historical) covering
All newswires and press releases of all US listed companies (PR Newswire, Globenewswire, BusinessWire, etc)
...
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6
votes
Except Zipline, are there any other Pythonic algorithmic trading library I can choose?
Interactive Brokers hosted a webinar on Nov. 10 2016 about Implement Algo Trading coded in Python using Interactive Brokers API. The presenter gave a good explanation on the applicability of IBridgePy,...
6
votes
Trading C++ Libraries
These are the libraries I most prominently use for C++:
QuantLib
Boost C++ Libraries
This is not specifically a library however it is extremely helpful, the Anaconda Compiler Tools.
The Armadillo C++...
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6
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approach on trading algorithm using machine learning
'Machine learning' describes a very broad spectrum of algorithms. Just briefly here are a few conceptual areas;
Neural networks
Reinforcement learning
Genetic algorithms and genetic programming
...
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6
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How can we estimate new stock price after a large purchase?
Let me try to answer: I have seen how equity trades are executed at the order book level. Let's say the price of the stock is 100 (last traded price). Let's say the order book is as follows:
Bids: ...
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6
votes
Accepted
Learning and applying Quantitative Finance successfully as an individual instead of a team
Welcome to Quant-Stackexchange Sleepy Panda, this is an interesting question and it also seems to be an interesting book.
Regarding your Question:
It depends on your goal and your definition of ...
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6
votes
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How to compare algorithmic trading strategy risk/reward performance?
As you will probably read in the documentation of many packages for algorithmic trading, there is a standard list of well known metrics outside of the ones you already mention:
Sortino Ratio: Similar ...
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5
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Which algorithms do robo-advisors use?
Well, I did some modest research on this topic, looking at peers.
Most of them use Modern Portfolio Theory, see this pic:
You can find this small survey here: https://www.linkedin.com/pulse/...
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3rd party API like IBPy for Interactive Brokers python API?
The problem with using IbPy is not only that it does not support Python 3 but even more importantly it's anchored to an older version of IB's API so it's missing a lot of features IB has added in ...
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