Stack Exchange Network

Stack Exchange network consists of 174 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange
Join us in building a kind, collaborative learning community via our updated Code of Conduct.

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.

1
vote
1answer
118 views

Limit and Market Order for training a ML model

Goal : Using deep learning to build a ML model which would predict the right places where a stock price will increase, decrease or stay stable. For the current question, assume the labels are well ...
0
votes
4answers
160 views

Determine the right order size with market making strategy

In a market market strategy https://web.stanford.edu/class/msande448/2017/Final/Reports/gr4.pdf, how can we determine the right order size? Assuming I use a market making strategy and on a specific ...
0
votes
1answer
76 views

Market, Limit and Cancellation orders

From the paper https://web.stanford.edu/class/msande448/2017/Final/Reports/gr4.pdf page 8, I need at least the limit and market order. I can easily find the full depth from dxfeed or algoseek, but I ...
-2
votes
1answer
63 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 ...
0
votes
0answers
15 views

Given historical performance of a financial index, how to categorise different historical periods depending on the market regime at the time?

We are trying to work on a Machine Learning application to attempt to predict market regime changes (bull, bear, stale?). Generally a ML algorithm needs well defined training data for establishing its ...
0
votes
0answers
18 views

Isolating the portion of the market indexes' returns that are independent of the other market indexes

I am trying to find a way to isolate the portion of the market indexes' returns that are independent of the other market indexes. My dataset comprises of 10 sectors (Technology, Financials, Utilities, ...
0
votes
2answers
159 views

Can someone please share examples of machine learning in quantitative finance? [closed]

There has been a lot said about the application of AI, ML and Neural Networks in trading for predictive modelling. I was unable to find any relevant examples that prove a credible output based on ...
0
votes
0answers
47 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) ...
0
votes
2answers
131 views

Seeking papers that deal with stock market analysis

I am sure there are a lot of papers that are related to stock market analysis.. but I haven't been able to find ones that fit my needs most. I want to read papers, replicate their analysis, and use ...
0
votes
0answers
44 views

Imposing qualitative views in Black -Litterman model

I'm trying to construct a ETF portfolio with various asset classes using Black Litterman model. To impose views, I'm considering only qualitative views like {strong bearish, bearish, bullish, strong ...
1
vote
1answer
45 views

How can I reproduce the experimental verification of the “False Strategy” theorem plot?

I recently came across the following blog post talking about the importance of back-testing overfitting, and a plot claiming to be an experimental verification of the False Strategy theorem. The ...
0
votes
1answer
54 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 ...
2
votes
1answer
120 views

approach on trading algorithm using machine learning [closed]

let's say I am supervising a algorithmic trading project using machine learning. I don't have involvement in the technical side but am involved in the high level planning. the style is likely ...
8
votes
0answers
215 views

Machine Learning usage in Q part of Quant Finance

Machine Learning algorithms is broadly used in trading strategies and in general when it comes to working with financial time series. The webpage Quantopian is a platform to see some of the ...
1
vote
0answers
21 views

Uniqueness of data metric [closed]

Is there a metric that calculates "uniqueness of data"? For example if i have two sets of 200 observations, DataSet 1 has 70 unique values but 4 values take up the next 130 observations. DataSet 2 ...
1
vote
1answer
334 views

Trading Strategy adapting to my trading frequency

We want to predict the direction towards which the price will change. In this work the term price is used to refer to the mid-price of a stock, which is defined as the mean between the best bid ...
0
votes
1answer
84 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 ...
0
votes
0answers
55 views

Unlabelled mid-price stock data

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 ...
0
votes
2answers
104 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 ...
0
votes
3answers
154 views

Appropriate way to normalize Bollinger Bands?

I am playing around with using neural nets to make predictions on market trends. I am currently feeding in a portfolio of historical data of many stocks, and am now implementing several technical ...
0
votes
0answers
29 views

Model selection given return and variance?

Suppose out-of-sample testing of a model yields certain values of returns and variance for each varying values of hyperparameters, then what are some methods in choosing the right hyperparameter? ...
0
votes
0answers
28 views

Measure of stock price predictor's performance?

Just started on my thesis based in using machine learning in the area of price prediction. I'm wondering what would be considered 'good' measures of predictive performance? Some papers use RMSE, but ...
0
votes
2answers
410 views

What’s the derivative of the sharpe ratio for one asset? Trying to optimize on it for a model

It seems most Sharpe ratio derivations seem to be for portfolios but I am just tracking a single asset? $SR = (r_p - r_f) / \sigma_p$ but what would I derive with respect to for an optimization/ ...
1
vote
1answer
83 views

How can I 'quantize' a time-series in 'groups' exhibiting similar patterns? [closed]

In Signal processing, there is a topic of 'Quantization' (the process of mapping input values from a large set to output values in a (countable) smaller set ('states') ). I would like to construct a ...
0
votes
1answer
52 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 ...
2
votes
1answer
189 views

Scaling (Data prep) & Feature selection for the financial Data for LSTM Models

Overview I'm training an index e.g. FTSE100, where I have 8 years of past data (daily). I also have a list of its constituents. For each stock, I have the following features: ...
0
votes
0answers
36 views

Sentiment classification - Commercial annotation services for market/trading/financial news sentiment

This question might well be off-topic (in that case I'd be grateful if someone could point me in the right direction). I'm looking for services (similar to Amazon Mechanical Turk) that could aid with ...
0
votes
0answers
49 views

How does HMM apply to Forex for example, when any imaginable state you can think of involving price is observable?

Intuitively it seems like you can add states to the transition probability matrix $A$ and use a learning process to figure out the new transitions. If that's correct then it answers my question as ...
0
votes
0answers
73 views

How can I estimate the “trending Ornstein-Uhlenbeck” parameters of some mean reverting data?

I am using trending OU process instead of normal OU process because my data is following the properties of trending OU process. So anyone can help me with this that how can i estimate the parameters ...
2
votes
1answer
407 views

CAPM and factor modeling: Machine learning

Excuse my ignorance with this I am still trying to wrap my head around the interpretation of the Fama French 1992 factor paper. I come from a computer science background but I am interested in ...
1
vote
0answers
77 views

What is a good algorithm to predict volatility in metals commodity markets? [closed]

I'm trying to create a script to predict major swings in the price of Aluminium. I am trying to implement a dynamic time warping algorithm for the same. Was wondering if this really is the best ...
2
votes
0answers
305 views

stochastic modeling and machine learning [closed]

For a little bit of background, I've been studying stochastic calc and a few of it's applications (currently I'm still at the early stages of learning applications) and have been curious as to whether ...
0
votes
1answer
116 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 ...
2
votes
0answers
186 views

Differential Sortino Ratio

I'm attempting to optimize a reinforcement learning system to maximize risk adjusted returns. I have currently defined the reward as the differential Sharpe ratio at each step: the influence of the ...
-4
votes
1answer
215 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 ...
6
votes
3answers
1k views

Determine trends of data (direction detection or turning point detection)

I'm working on a model to determine trends (direction detection or turning point detection). Suppose that we have a stock trend which is illustrated below. Blue line is real trend of stock close ...
-1
votes
1answer
417 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 ...
-1
votes
1answer
216 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 ...
2
votes
1answer
424 views

Where I can find historical earnings dates for stocks?

I'm trying to find all of the historical earnings dates (just the dates is good enough) for certain stocks ranging back to their IPOs. I'm plan to use it for my machine learning project. Yahoo and ...
0
votes
0answers
45 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 ...
-1
votes
1answer
228 views

ML classification algorithms give random profit [closed]

I use backtrader python framework to backtest ML classification algorithms to make decision ...
2
votes
0answers
187 views

Good books on predictive modeling (for alpha signal research)

In terms of books on predictive models, I find ESL (elements of statistical learning) trying to cover too much and serves more like a reference, instead of explaining and developing the theories for ...
0
votes
1answer
85 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: ...
0
votes
2answers
153 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 ...
3
votes
0answers
142 views

What are examples of boosting, bagging, stacking or subspace method in quantitative finance?

The above ensemble methods appear useful in several machine learning competitions, like Netflix prize or KDD. They work by diversifying between several model variants. Are they also useful in ...
0
votes
1answer
93 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 ...
1
vote
2answers
277 views

Use machine learning to find exercise boundary of American put option

I am working on using machine learning to obtain American Put's early exercise boundary. To train the model, I need an output label (known boundaries values). Is there a fast way to obtain the ...
2
votes
1answer
10k views

How do I use machine learning to build a credit scoring model? [closed]

There are currently a lot of ways for credit scoring. The most popular one is the FICO score, and its variants. For my masters thesis, I would like to work on making my own credit scoring system using ...
3
votes
1answer
185 views

Predict the financial markets in the fashion of a video game?

DeepMind have demonstrated amazing capabilities of a reinforcement machine learning agent to competently play Atari video games. It is most astounding that that during training nothing more than the ...
3
votes
1answer
757 views

Machine learning techniques for quantitative finance?

I am a mathematician who wants to learn about quantitative finance, in particular how machine learning can be applied to it. I assume some machine learning techniques are more applicable than others ...