Questions tagged [neural-networks]

The tag has no usage guidance.

0
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0answers
62 views

Predicting time series using Jump Diffusion model and Neural Networks

I am trying to understand the difference between using Jump diffusion model and Neural Networks or more precisely LSTM to predict time series data regardless what that data contains for example a ...
4
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1answer
128 views

Neural Networks for Estimation of Unmarked Private Asset Returns from Market Data

Let's assume it is March and my illiquid private assets portfolio is only 50% marked for 12/31, but I want to get the most accurate estimate of my final return for the quarter ended on 12/31. What is ...
8
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2answers
206 views

Defining an objective function for machine learning task of trading

A simplified example. Given: asset's price time series fixed distances to stop and target. A function of these inputs has two possible output values: $1$ if price is likely to hit the target ...
3
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1answer
181 views

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

I study on algorithmic trading for a while based on technical indicators. I started to learn about neural networks and want to use technical trading indicators in this approach. However, I am not ...
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2answers
318 views

Least-Squares-Monte-Carlo by Neural Network Estimator for pricing American Option Python [closed]

First I did the LSM (Longstaff-Schwartz) to understand how its work to price an American option. code for standard_normal ...
0
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3answers
417 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 ...
7
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1answer
708 views

Calibrating a two-factor Hull-White model using Neural Networks

So I have the following short-rate model $$dX_t = a_1X_tdt + \sigma_1dW_t$$ $$dY_t = a_2Y_tdt + \sigma_2dB_t$$ $$r_t = X_t + Y_t + f(t)$$ with $X_0 = Y_0 = 0$ where $W$ and $B$ are Brownian motions ...
10
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2answers
260 views

Reference request: Quantitative approaches to market abuse detection

have been asked to look at some financial timeseries for potential suspicious activity. These are stocks (my background fixed income hybrids trading and not forensic analyst...) and most of the ...
1
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0answers
270 views

Probability Integral Transform: Standardisation

I've been applying the probability integral transform as shown here to standardise date for input into a neural network: https://math.stackexchange.com/questions/592076/mapping-cdfs-to-each-other?...
2
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1answer
4k views

When and how to use RNN for stock analysis or trading

I am learning about neural network and created some small networks in feed forwarding network myself. I was curious about Recurrent Neural Networks (RNN) and read some papers about RNN in trading. The ...
1
vote
1answer
282 views

Design models using adjusted or unadjusted stock prices (time series prediction)?

I'm creating a predictive model for closing price of stocks (using neural network and support vector machines.). Is it appropriate to use adjusted prices or unadjusted prices for this prediction ...
7
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2answers
379 views

Research topics - neural networks and market liquidity

I am a masters student looking for some direction on using neural network on market depth data to help predict market liquidity and bid-ask spreads. Can some of the more experienced people give me ...
3
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1answer
402 views

Applying Time Delay Neural Network to financial events

I have an IT background and I would like to use data from a forex calendar like this one to predict prices. The problem is that calendar news impacts can last for days or weeks or even can effect ...
2
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0answers
34 views

Non-overlapping ranges of HCNN' observables and of state transition function

In the artcicle Forecasting and Trading the High-Low Range of Stocks and ETFs with Neural Networks HCNN is used for forecasting of nine time-series, namely: returns of the lows returns of the highs ...
1
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2answers
409 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 ...
1
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3answers
1k 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 ...
2
votes
2answers
646 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 ...
4
votes
3answers
370 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 ...
1
vote
2answers
848 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, ...
13
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1answer
6k 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 ...
3
votes
1answer
469 views

Econometric vs ANN models for forecast?

I hope this is an appropriate question for this forum... for me it is an obvious query since it intrigues me for a long time. Ok, assume there are 2 distinct classes of models: econometric (AR, MA, ...