Questions tagged [machine-learning]

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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1answer
76 views

Subset selection to identify independent variables that impact the market?

Given a lot of market-related features (~100 independent variables such as emerging market, developed market, s&p 500, tech sector returns, etc), I need to select a subset of them that are ideally ...
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3answers
171 views

Combining Quantitative data with fundamental data

These day, there is relatively new phenomena of combining quantitative data and fundamental data called 'Quantamentals'. In this regards, I was wondering how to combine Four Essential Types of ...
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1answer
69 views

Random Forests - Trees vs Predictors

This question relates to the use of random forests in finance and the relationship between the number of features, the observations, and the number of trees. Consider the relation between an RF, the ...
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2answers
487 views

Hedging with machine learning

I’ve been thinking about an interesting problem lately: Suppose I have a position in an exotic derivative. How can I automate the hedging process? Traditionally, one build a pricing model and ...
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1answer
107 views

Find a reasonable h

The mid-price at time $t$ is denoted by $$p_t = \frac{s_t^{a,1} + s_t^{b,1}}{2}.$$ This mid-price can evolve in minimum increments of half a tick but is almost always observed to move at ...
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1answer
79 views

How to properly classify rate of change?

I am working in a Machine Learning Model for Bitcoin Price. I am attempting to predict how much the price changes in the next day. I am approaching this as a classification problem instead of ...
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1answer
128 views

Unsupervised learning and in out of sample

Assume we are given $N$ samples, let's say small timeseries of 1 hour resolution daily exchange rates - for the sake of argument. Each sample is a $24$ element vector $x$. Then we proceed to do ...
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1answer
130 views

How to normalize various indicators into one column?

I've seen this video which talks about how to compress different indicators into a sin https://www.youtube.com/watch?v=sDu6CudKa0Q I tried to do the same by this way: ...
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2answers
231 views

Scaling the data to train, then how to scale the input data?

I'm somewhat new into the world of trading algo's, so bare with me. I've made a dataframe with 5 features say. I used preprocessing.scale to scale it. I checked the csv dump of it and it looks fine ...
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1answer
200 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 ...
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0answers
10 views

Sample uniqueness and sample weight in AFML book

Are they pointing towards to the same thing? I am confused on the term here. Thanks if anyone could help.
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0answers
27 views

Clusters evolution over time

I have a dataset of stock prices and I want to group stocks that share similar characteristics together using cluster analysis. I'm interested in following the evolution of each cluster over time, but ...
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0answers
48 views

Historical intraday data [duplicate]

I have been researching on the current APIs that I can request for the most detailed historical end of day intraday quote and trade data available in an easy to use format for research, backtesting ...
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0answers
260 views

How Machine Learning model addresses adverse action concerns -credit scorcard?

How to find the variables involved in the decision to report adverse action when the origination scorecard is developed using Machine Learning - XGBOOST with monotonic constraints (80 variables) ...
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0answers
52 views

Can Q-table learned by specific stock be applied to only that stock?

Let say I develop Q-learning strategy to predict IBM's stock price. So, it means that Q-table is created based on past IBM stock price data. In this case, this Q-table could be applied only to ...
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1answer
117 views

Markov chain downgrades in loan book modelling

I am working on a personal loan dataset. For each loan, we recorded its credit status monthly after it was drawn by the borrower. Let's say there were 6 status coded by A-F. My project is to use ...
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1answer
112 views

Separate market and limit orders from market depth/tick data

From the website https://www.algoseek.com/equities/, we can get a sample of the full depth market/tick data. From the paper https://arxiv.org/pdf/1710.03870.pdf page 8, I would like to extract the ...
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1answer
472 views

How to use exponential smoothing for trading?

I was wondering if there's a rule of thumb regarding the value of alpha used when performing exponential smoothing. I plan to use this technique to preprocess my data before feeding them into my ...
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1answer
403 views

z-score versus log standardisation of stock prices for calculating correlation; which to use (in ML clustering, distance measure)?

I need to compare (get correlation between) different financial instruments (stocks). The problem is that different stocks will have different price scales. I was thinking of using z-score ...
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1answer
292 views

python: How use the S&P 500 index to predict japan stock,namely timezone issue

I want to use American stock index, such as S&P 500 index(open, close...) to predict japan stock daily close price or other with machine learning. I found that there is timezone between japan and ...