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12 votes

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 ...
KarolisR's user avatar
  • 693
12 votes
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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 ...
Amanda G.'s user avatar
  • 361
12 votes
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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 ...
Jan Stuller's user avatar
  • 6,178
12 votes
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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 ...
amdopt's user avatar
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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 ...
Steinwolfe's user avatar
10 votes

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 ...
Dimitri Vulis's user avatar
9 votes

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. ...
madilyn's user avatar
  • 5,240
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 ...
databento's user avatar
  • 2,498
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 ...
Casey Jones's user avatar
8 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 ...
Hamish Gibson's user avatar
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 ...
Bob Jansen's user avatar
  • 8,562
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 ...
Richard at NorgateData's user avatar
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 ...
Attack68's user avatar
  • 10.7k
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). ...
Alexey Golyshev's user avatar
7 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 ...
kurtosis's user avatar
  • 2,910
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 ...
Bob Jansen's user avatar
  • 8,562
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,...
IBridgePy IBridgePy's user avatar
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) ...
Jay's user avatar
  • 382
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++...
Theodore's user avatar
  • 1,172
6 votes
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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 ...
Attack68's user avatar
  • 10.7k
6 votes

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: ...
Jan Stuller's user avatar
  • 6,178
6 votes
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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 ...
Andreas's user avatar
  • 458
6 votes
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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 ...
Sergei Rodionov's user avatar
5 votes

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/...
RockZen's user avatar
  • 51
5 votes
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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 ...
Brian from QuantRocket's user avatar
5 votes

Algorithmic Trading: Normalization and Selection of Technical Indicators for Artificial Neural Networks

This question is broad, and the normalisation strategy is going to depend on the nature of your indicator. Assuming the technical indicators are a time series, then two simple approaches for ...
Ian Ash's user avatar
  • 180
5 votes

Why Good forecasting != Good trading?

Why Good forecasting != Good trading? I am not yet familiar with the F1 score the author compares with the Sharpe ratio. But the article rightly points out at least two grounds on which good ...
Iñaki Viggers's user avatar
5 votes

Market Making Algorithm/ Strategies

Check out Avellaneda and Stoikov (2008) They model the market maker's problem in a very neat and easy to code way. Some caveats of the model, in case you do decide to use it: The price process is ...
python_enthusiast's user avatar
5 votes

Position sizing in algorithmic trading

If you already have a strategy generating potential long and short positions, you may want to check Chapter 10 of Marcos López de Prado's book Advances in Financial Machine Learning. It describes a ...
kingfischer's user avatar
5 votes
Accepted

Textbooks on algorithmic trading

Having traded algorithmically for a couple of decades and taught on the subject, I'm going to recommend four books: one practical, two theoretical (but important), and one that is light -- a "...
kurtosis's user avatar
  • 2,910

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