18 votes

Except Zipline, are there any other Pythonic algorithmic trading library I can choose?

Edit (2016-06-21): Now with live data/trading integration with Interactive Brokers. It has taken a while but it has finally arrived. Edit (2017-09-20): live data/trading includes Visual Chart and ...
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  • 618
16 votes

Regime-Switching Model for detecting market shifts

Windham Capital Management is using hidden markov models for their Risk Regime Strategies. Mark Kritzman, who is also CEO, has published an article about the general outline of the strategy (with ...
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  • 26.9k
12 votes
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Orderbook Arbitrage

A public order book gives traders information not only on the current price of a security, but also the volume and structure of the entire supply and demand schedule. Such information can be used for ...
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  • 286
12 votes
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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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  • 26.9k
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 ...
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  • 693
12 votes
Accepted

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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  • 5,096
11 votes
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Build a customizable trading engine in python

Firstly, you'll probably be directed to consider Zipline. It's worth a look but I don't think that it's a good starting point, since: Quantopian's developers don't have a financial background and it ...
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  • 5,052
11 votes

Quantitative Finance Programming Language

I think you might find this answer in The future language of quant programming? useful. People get this problem wrong because they always end up discussing the theoretical advantages of these ...
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  • 5,052
11 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 ...
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11 votes
Accepted

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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  • 3,735
10 votes

Orderbook Arbitrage

I am not sure Dark Pools (DP) have been created to avoid "market manipulation". They have been created by firms because they found an advantage to create them (see Market Microstructure in Practice, L ...
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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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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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  • 26.9k
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. ...
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  • 5,052
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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  • 1,626
8 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 ...
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  • 181
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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  • 7,652
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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  • 1,252
7 votes

Except Zipline, are there any other Pythonic algorithmic trading library I can choose?

possible update: http://pmorissette.github.io/bt/ based on http://pmorissette.github.io/ffn/ both were easily installed and somewhat usable for a novice. would love some examples other that ...
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  • 181
7 votes

Algorithm to detect the aggressor side of a trade

The most commonly-known approach to this is described in Inferring trade direction from intraday data (1991) by Lee and Ready. You will find that the non-trivial part has to do with classifying trades ...
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  • 5,052
7 votes
Accepted

What kind of front end/ gui is used with trading applications?

If I was in your position I would start to research how I can create a web server is C++ and expose calls to create a REST service. In other words, can you make your code status output to HTTP? From ...
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7 votes

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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  • 1,021
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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  • 5,052
7 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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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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  • 8,037
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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  • 357
6 votes

Except Zipline, are there any other Pythonic algorithmic trading library I can choose?

There is a module called visualize-wealth that provides: Documentation auto-generation capability with sphinx Portfolio construction methodologies in 3 ways (trade ...
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6 votes

Please advise on the choice of an automated trading framework

To be honest you're not likely to get a very satisfying answer to your question. Not because its a bad question, but because "regular people" can't just go hooking their home grown trading systems up ...
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  • 1,349
6 votes
Accepted

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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  • 8,037
6 votes
Accepted

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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