Algorithms that allow computers to evolve behaviors based on empirical data. Approaches include genetic programming, artificial neural networks, decision trees, support vector machines, and cluster analysis.

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14
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3answers
259 views

Regression model when samples are small and not correlated

I received this question during an onsite interview for a quant job and I'm still scratching my head on how to solve this problem. Any help would be appreciated. Mr Quant thinks that there is a ...
0
votes
1answer
28 views

Which close price should we use for machine learning?

I am building a machine learning model using historical prices and I am using data from yahoo finance. Currently yahoo finance data have two close prices one normal close price(close) and other ...
23
votes
3answers
6k views

What types of neural networks are most appropriate for trading?

What types of neural networks are most appropriate for forecasting returns? Can neural networks be the basis for a high-frequency trading strategy? Types of neural networks include: Support Vector ...
8
votes
2answers
1k views

How to normalize technical indicators for machine learning?

I'm using around 130 technical indicators for 100 different companies. Each company's stock price moves in a different range, see FTSE 100. In addition, each technical indicator moves in a different ...
3
votes
0answers
126 views

How quants use models for stock market prediction

I am learning machine learning to use it for stock market price forecasting. While doing that I got this question. If we take any country with stock exchange they have more than one investment assests ...
3
votes
2answers
200 views

Is it really possible to create a robust algorithmic trading strategy for intraday trading?

I'm an engineer doing academic research for my master thesis in the area of quantitative finance, basically the purpose is to study the possibility to create an intraday-trading algorithm. I've tried ...
9
votes
1answer
195 views

Which are useful applications of clustering in quantitative finance?

Several machine learning algorithms have been applied in finance/trading. Focusing on clustering (k-means, k-medoids) what are useful and successful applications in quantitative finance? What is used ...
0
votes
0answers
22 views

Guidance on machine learning approach to improve interpolation [duplicate]

I am thinking about doing a project on improving the accuracy of some stock signals. The signals are fundamentally derived scores on a per stock basis. They are updated on a weekly or monthly ...
0
votes
0answers
31 views

In what situations would cross validations scores be inaccurate?

I'm trying to fit a SVM model on times series stock return data, predicting a buy, hold, or sell signal of the stock. I'm using 10-fold cross validation (using the R package ...
1
vote
2answers
187 views

Feature Selection Effect on Deep Multi-Layer-Perceptron for Financial Applications

I am trying to build a machine learning system for financial price prediction. I am using a 3 layer MLP (a deep network) with 3 outputs (buy,hold,sell). I am using different features such as price ...
24
votes
5answers
4k views

Machine Learning vs Regression and/or Why still use the latter?

I come from a different field (Machine learning/AI/data science), but aim to ask a philosophical question with the utmost respect: Why do quantitative financial analysts (analysts/traders/etc.) prefer ...
3
votes
1answer
171 views

What is the machine learning language of choice in this industry for unsupervised learning

I was wondering from those with commercial machine learning financial experience, what the machine learning language of choice in this industry in the most general sense. Also, what would be the ...
76
votes
10answers
80k views

How can I go about applying machine learning algorithms to stock markets?

I am not very sure, if this question fits in here. I have recently begun, reading and learning about machine learning. Can someone throw some light onto how to go about it or rather can anyone share ...
1
vote
1answer
207 views

Machine learning to build top 3 price scenarios over n days

I have a time series of closing prices for a given stock. I would like to formulate possible future scenarios for the price. My intention is not to use these "likely" scenarios to take any position. ...
18
votes
8answers
8k views

How are cryptography and speech recognition technology applied to forecasting financial markets?

One of the answers to my previous question regarding the strategy of Renaissance Technologies, there was a reference to The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly ...
1
vote
1answer
550 views

Feature for Maching Learning(SVM) in High Frequecy Order Book?

I am trying to implement machine learning to predict the movement of bid and ask price but is unable to find the proper feature for training set. I am using Support Vector Machine for binary ...
0
votes
3answers
322 views

Research methodology of systematic strategies

Can someone please share your research methodology of systematic trading strategies? I feel like I am always using the a same data driven procedures over different underlyings and would like to get ...
1
vote
2answers
418 views

Using Technical Indicators for forecasting Financial time series using Machine learning models

Hi I am trying to use financial technical Indicators for forecasting, using machine learning models. The usual approach in time series cross validation is to use a moving window or growing window. ...
1
vote
0answers
268 views

What machine learning method is more suitable for prediction of financial time series? [closed]

I have some time series from a stock exchange market. For each of them, I want to answer the question that whether the price will grow at least p percent in the d coming days or NOT(and during these ...
2
votes
1answer
366 views

Analog - Pattern Recognition model using KNN

I'm building a pattern recognition model for my master thesis. The idea is to build a framework with some Macro variables (long/short term rates; rates differential; equity; fx; vix) in order to find ...
7
votes
1answer
540 views

How to better understand trading signals?

I am looking to get a better understanding of an output from a trading strategy. Basically I have a daily equity curve lets call it $Y_t$. I have defined a bunch of independent variables $X_{it}$ that ...
4
votes
3answers
298 views

selecting test data for neural networks

I have been working on a neural network based on certain technical indicators. As people familiar with neural networks would know after developing a hypothesis, the developer is also supposed to ...
4
votes
2answers
206 views

Machine learning for non optimal behaviour

I was working on the pricing of complex bermudean swaption when I noticed that the exercise is often (very) subobptimal. It seems that the clients are more sensitive to past growth or drop in rates ...
24
votes
8answers
4k views

Excellent information source on advanced machine learning / data mining based trading?

I did check the related posts, like this one here. However, given if one already has knowledge in finance, machine learning and statistics, and wants to know something more advanced on machine ...
1
vote
3answers
646 views

What Is A Good Success Rate Using Machine Learning For A Beginner?

I know this question will be quickly destroyed and my account summarily banned, but I just have to ask: For a trader using machine-learning algorithms (SVMs, ANNs, GAs, Decision Trees) for ...
6
votes
1answer
225 views

How to perform Empirical Mode Decomposition?

I am trying to use the EMD applied to EURUSD open price to train a machine learning algo (RVM). I have run only once the EMD on my training set and once on the training+test set. The results on the ...
5
votes
4answers
2k views

Usage of Random forests in Quantitative analysis of stocks

I have a question about Random forests and how they could be utilized in trading? I heard Random forests are used for classification, is that accurate? If so, could someone give an example of what ...
9
votes
1answer
3k views

Multilayer Perceptron (Neural Network) for Time Series Prediction

I have it in mind to build a Multilayer Perceptron for predicting financial time series. I understand the algorithm concepts (linear combiner, activation function, etc). But while trying to build the ...
2
votes
2answers
540 views

Machine Learning on matlab 2010

I am trying to develop a trading model. It uses certain technical and fundamental features and the model learns from the past. I have a 3-class output - bullish, neutral and bearish. On trying neural ...
0
votes
1answer
132 views

Choosing a weak learner

I want to compare different error rates of different classifiers with the error rate from a weak learner (better than random guessing). So, my question is, what are a few choices for a simple, easy to ...
2
votes
1answer
215 views

How to group mutual funds by volatility?

I want to group Mutual Funds by their volatility. Ideally, I would like to end up with the mutual funds beings attached to different groups: High volatility Medium volatility Low Volatility My ...
1
vote
2answers
349 views

Choosing attributes for SVM classification?

Let's assume I am classifying every trading day as a 1 or a 0. Exactly what I am classifying doesn't matter, but for the sake of this question let's say I am predicting direction of price change. So, ...
5
votes
2answers
1k views

How to calculate optimal standard deviation bands for trading?

I am trading with standard deviation bands (6 bands) on de-trended data. How can I find the most profitable signals with neural network or GA with standard deviation bands? Should I first find the ...
0
votes
2answers
507 views

Howto Calculate An Error's Partial Derivative in ANN

This is a follow-on question from this post I made, "Multilayer Perceptron (Neural Network) for Time Series Prediction", a few months back. I'm constructing a feed-forward artificial neural network, ...
7
votes
1answer
2k views

Optimal execution and reinforcement learning

Suppose a fairly simple problem: You have to buy (resp sell) a given number of shares V in a fixed time horizon H with the aim to minimize your capital spent (resp maximize your revenue). There are ...
4
votes
0answers
503 views

Algorithms for predicting a couple points in the future

I'm familiar with supervised learning algorithms like regression and neural networks which look at a bunch of input points and learn a function which outputs a value (the value varying depending on ...
15
votes
3answers
3k views

How to cluster stocks and construct an affinity matrix?

My goal is to find clusters of stocks. The "affinity" matrix will define the "closeness" of points. This article gives a bit more background. The ultimate purpose is to investigate the "cohesion" ...
8
votes
5answers
5k views

What are your opinions on WEKA KnowledgeFlow, Rapidminer, and other rapid development environments for machine learning?

Which is the most extensible? Which is the most efficient in terms of a minimal learning curve while providing a meaningful degree of flexibility and performance? Any of these tools really limited ...
12
votes
1answer
591 views

Has any research used Bayesian networks to estimate risk factor betas?

Is there any published research on estimating the beta of a security with respect to one or more risk factors via Bayesian networks? I'd like to see if this is a promising angle of research.
25
votes
1answer
2k views

Is my trading strategy search methodology sound?

I'm building an algorithmic trading business. I'd be grateful for informed comments and opinions on my trading strategy search methodology. Goal Develop (profitable!) fully automated intra-day ...
8
votes
2answers
645 views

Is there any research on applying state-space or dynamic linear models to forecasting equity risk premia?

Is there any research on applying state-space or dynamic linear models to forecasting equity risk premia on a security-by-security basis with a medium term horizon (say 3 month to 12 months horizon)? ...
15
votes
3answers
2k views

How to incorporate technical indicators into neural networks?

I plan to develop a neural network to trade commodities futures, but while messing around with some code, a question came up. If I understand correctly, people use various technical indicators with ...
8
votes
4answers
2k views

Statistical learning libraries

Is there a general (or specialised) FREE library to solve learning problems such that found in the book "The Elements of statistical Learning". As it is often time consuming to write all the ...
9
votes
2answers
927 views

How do I replicate John Hussman's recession forecasting methodology?

John Hussman has a recession forecasting methodology he often posts about on his blog, and I am trying to replicate it using publicly available data. I would like to assess his accuracy in predicting ...