(PDF) Forex predicton with neural network: usd/eur ...

Did anyone make a neural network for predicting stock prices or forex?

I've done it and I would like to discuss it with someone who has done the same so we can share our discoveries
If you find yourself in that description please DM me
submitted by Becharac to neuralnetworks [link] [comments]

"I coded neural network for forex prediction in 24h..." by Mike Papinski Lab

submitted by aivideos to aivideos [link] [comments]

I want to know more about the theory (not coding)of deep learning,neural networks,recurrent neural networks,reinforcement learning ect. in prediction of stock/crypto prices.

Hi,i am learning python and i am still pretty much a beginner.One day if i get much better in programming i want to make a trading bot that incorporates some sort of AI.I know that it will be a bumpy road and that it won't be easy.
When i google the terms that i mentioned in the title i struggle a bit to understand the differences.Since i am pretty much a beginner i know that i wouldn't understand the code behind this things.Is there some good source that explains the theory of those subjects,but related to predicting future prices in the stock/crypto/forex market?Like with deep learning you can do this and this,with neural network you can do this and this ect.I would like to take one of those roads one day,to predict the markets...but i don't know what road would be the best for me to predict the markets.So if there was some theory behind it,maybe i would understand how different this subjects are in regards to predictiing future events.I guess you can make prediction models in all of those fields,i just don't understand their differences.
I hope i can get some help here without being overwhelmed with the new information.I need some resources that brake down this complicated things into more digestible pieces so an beginner can understand them.
Thank you
submitted by PurpleDemand to neuralnetworks [link] [comments]

Idea that needs someone that can actually program

Hello guys,
First of all, if I had this idea odds are at least 100 other people have had it too so if y'all can point me in their direction and see how they have applied it, I would be thankful. I have been getting into neural networks a lot lately, and one of my first thoughts was to use them for the forex market. The main issue I ran into, however, was how to present the data to the NN.
The thing most, if not all, examples I have read do is that they use an x number of previous candles + an indicator of some sort and maybe pairing it with another coin or some other variable to predict the next candle's closing price, or high, or low. After giving it a shot myself, it has been lackluster at best, and a complete failure at worst.
The idea I have been thinking about was the following: use the previous x candles and indicators and other pairs and whatever not to predict the next candle, but to instead predict if at some point, any point, in the future, the price will rise by a certain amount (say 100 pips), or drop by that same amount.
If we had a chart with the data for each candle (OHLC, an indicator's value, and another pair's value at that moment in time, for instance, all of which can be obtained from TradingView), and we associated with each candle a 1 if the first thing that happens at some point in the future is that it goes up by, say, 50 pips, or a 0 if the next thing that happens is that it goes down by 50 pips, then the neural network could be trained to predict based on the past if you trade on this candle, the price will go up by 50 pips in the future, in which case you enter the trade with a take-profit of 50 pips, and a SL of 50 pips, or if it will decrease by 50 pips in the future, in which case you do the opposite.
That's the idea. If anyone's done it before, I would appreciate a link to their work, and if anyone thinks this is dumb, do tell me too.
submitted by MrStealYourFrog to algotrading [link] [comments]

Binary option prediction - Start-up BAMM

Hi everyone!BAMM is a new innovative start-up which attack the stock market with powerful weapon, which is AI. Our initial product is the Binary Options Predictor which is created to predict future of exchange rates by using Neural Networks. System is built with historical and actual exchange rates and texts from whole internet classified by Neural Network responsible for choosing articles, posts, tweets etc. that affect the exchange rates (Big Data). This processes let us create system for Binary Options Prediction. #ai #neuralnetworks #binaryoption #forex #binaryoptions #trading
Visit our website, you can sign in for free. Our product Binary Option Predictor (beta version) will be available to subscribe in close future.
https://bamm-technology.com/
submitted by Bamm-technology to binaryoption [link] [comments]

Time Series Preprocessing

Time Series Preprocessing
Hey guys,
I'm working on predicting forex prices and I have time series data for several currencies for the OHLC data.
I'm aiming to try predictions using classical scikit-learn models, statsmodels(such as ARIMA) and even neural networks iteratively.
I'm not sure how I should transform the data as the raw values do not appear to be stationary using the Dickey-Fueller test.
Could you help?


ARIMA Residual Results

Green -> Forecast
submitted by astronights to learnmachinelearning [link] [comments]

How to deal with unequal length time series data

I have been reading research papers on financial time series prediction where the researchers use neural networks to forecast the closing price of some stock by using time series of various other securities as input features in the neural network.
For different types of securities, the financial time series can easily differ in length due to the number of trading days each security has. For example, crude oil (CL: WTI) as a commodity trades on a 5-day window (Monday-Friday), whereas FOREX trades on a 7-day window (Monday-Sunday).
Given that this unevenness in the trading days can lead to the input features being unequal in length and series having trading information for days other series cannot incorporate, how does one deal with such a problem, given that:
  1. The simple feed-forward neural network takes in equal-sized input vectors
  2. Sequential models such as RNN/LSTM can take advantage of padding but at the trade-off of disrupting the original time-series
submitted by clutchking_asiimov to learnmachinelearning [link] [comments]

TradeRiser Can Answer Simple and Complex Trading Questions

TradeRiser Can Answer Simple and Complex Trading Questions
Artificial Intelligence as the term is most often used today is simply put the theory and practice of building machines capable of performing tasks that seem to require intelligence. Currently, cutting-edge technologies striving to make this a reality include machine learning, artificial neural networks and deep learning. Meanwhile, blockchain is essentially a new filing system for digital information, which stores data in an encrypted, distributed ledger format. Because data is encrypted and distributed across many different computers, it enables the creation of tamper-proof, highly robust databases which can be read and updated only by those with permission.
https://preview.redd.it/lcgl0t05hid11.png?width=999&format=png&auto=webp&s=770bc5060c1d3852385a4cceb3603668b7027302

What is TradeRiser

TradeRiser is an artificially intelligent Research Assistant, that can answer simple and complex trading questions.

Market Problem

  • Motivation - Simplifying financial data analytics
  • Disrupting Human Intensive Research
  • Fewer Ideas Are Tested
  • Time-Consuming
  • Inefficiency
  • Information Overload
  • News and Events - Unstructured Data

TradeRiser Solution

  • TradeRiser's Research Assistant can immediately answer trading questions that a trader or investor has about the financial markets.
  • TradeRiser’s token mechanism will keep track and compensate financial analysts for their datasets of questions, data validation, accuracy checking, suggestions and example report creation.
  • The financial analysts can contribute in these ways to help train TradeRiser's machine learning Research Assistant, and be compensated accordingly.
  • XTI is the underlying mechanism used to facilitate this ecosystem, and provides XTI holders with direct participation in advancing our “single source of truth” questioning and answering system.

The Blockchain Features

  • Financial analysts are like freelancers or contractors, the blockchain allows TradeRiser to create smart contracts with the financial analysts for various pieces of work.
  • TradeRaiser commercial transactions and agreements will be executed automatically, it will enforce the obligations that the financial analysts have in a contract
  • It provides an automated collaborative approach for data gathering using a large diverse pool of financial analysts. The smart contract allows for the different stages of work carried out by çto be rewarded.

TradeRiser Ecosystem

https://preview.redd.it/5joo1336hid11.jpg?width=1349&format=pjpg&auto=webp&s=06df4aaf508337f91e57869423df76c5b00ffdcd

The Platform

TradeRiser has built an alpha/private beta version of the Research Assistant which focuses on:-
  • Forex
  • Commodities
  • Indices
The Platform will allow users to ask questions surrounding:-
  • The economic calendar events
  • Technical analysis
  • Correlation
  • Performance
Note:- The Current Version is alpha/private beta.
TradeRiser intends to transform this into powerful fully fledged Research Assistant that will accompany all corners of the trading and investing space. So far it has been seen by major investment banks and technology vendors, and has received a lot of positive feedback.
https://preview.redd.it/5j1p27s6hid11.jpg?width=1909&format=pjpg&auto=webp&s=f40fee3e9330b9206bf2a016a83f1c6c71f27552
https://preview.redd.it/mz6nteg7hid11.jpg?width=1918&format=pjpg&auto=webp&s=383b4812ef4aab510be15adb9997aff55233b5a7

TradeRiser Platform Features

  • Community Edition
  • Research Marketplace
  • Enterprise Edition

TradeRiser Tokens & Its Uses

A token based economy called XTI will be introduced, to incentivize researchers, for their data and contributions to the platform.
It'll be used for:-
  • Community Credibility
  • Payment Issues
  • Managing the Monetary Supply

Finally

Blockchain is best used in a distributed system where nodes are not necessarily trustworthy. Artificial Intelligence gains little from being distributed. It is best used on problems which require noticing patterns inferring rules of behavior, predicting eventual outcomes, determining underlying causes. The one use where these could come together would be in distributing the data a blockchain needs to contain.
✅Website: https://www.traderiser.com/ ✅Whitepaper: https://www.traderiser.com/sites/default/files/TradeRiser_WhitePaper.pdf
submitted by Ahmedgalal81 to CryptocurrencyICOs [link] [comments]

Little Known AI Company Makes World Debut In Front Of United Nations

Founded by William J D West around 5 years ago and developed in stealth mode since then, Invacio is a tech company unlike any other in the world and because of this, it is attracting attention from some fairly high up places. Governmental discussions are ongoing around the world to implement their technology in various ways.
But what is it exactly that invacio do that instigated the invitation to make their worldwide debut presentation (coming out if you will) in front of world leaders at the UNESCAP FDI meeting in Thailand on November the 3rd last year?
The answer to that is quite hard to formulate without going off on multiple tangents all at once, so, I will give a brief outline and then try to cover some more specifics in order that you can try to paint the picture for yourself more clearly…All I will say before launching into this is open your mind and try to see all the potential uses of this technology.
Invacio is primarily an applied artificial intelligence company that has created a multi-agent neural network that analyzes the world’s informational output, digests it, correlates the various disparate facts and ultimately delivers actionable intelligence across any sector of commerce, industry, society or government possible.
Regardless of the source of this data be it: NASAs satellite feeds, live news, digital radio, video broadcasts, social media twitterings etc or live market data from world exchanges or even historical digitized data banks like the National Library of Congress and thousands of others, they are all relentlessly probed and itemized by a system which is self learning and always hungry for more. Since the system was switched on, an ever growing number of proprietary datasets have been created well over 2 billion as this story is being written. Ok, so Invacio has a lot of information from all over the world: but what exactly is its use? And, what can Invacio do that any other information rich organisation with a decent search engine can’t?
Well, this is where it truly comes into its own you see, it doesn’t pull the information together, stick a label on it and forget about it until someone asks for it. No, Invacio actively seeks to place all the information it holds into context with all the rest so that comparisons, parallels and connections can be created. Why? Because their system is designed to understand the world and guide us where it can. An example of this which was given during the presentation to the United Nations was that of crisis management during the Californian wildfires last year – Within a second of the first tweet relating to the fires starting being sent, Jean (that is what they call the full operational system) was aware and rapidly pulling together every type of relevant information available. Everything from geographical data, historically relevant time based records of vineyards (soil composition, state of vines or ripeness of fruits), meteorological details (live conditions and historical in relation to similar events globally)…… you get the picture.
In the second second Jean would have been able to direct the emergency response and do as much as possible to limit the ongoing damage being caused by the fire by predicting the way the emergency would develop having analysed all available information and extrapolating.
As a bonus, in the 3rd second Jean could have told you whether it was worth buying wine futures or no.
That is one example,imagine the benefits of having that kind of analysing power in your sector:
Hedge funds… highly accurate predictions on shares, indices, commodities and forex (Agnes, Archimedes, Aquila and Tomahawk), Market intelligence… knowing what the world is thinking about your brand, competitor, client or product in real time (Alise), Security… maintaining secure facilities through the application of advanced facial recognition through security cameras(Sauron) or alternatively simply plug your organisation straight into Invacio API and pull out the information you need to make your world a better place.
Invacio ICO Invacio are currently undergoing an ICO (initial coin offering) in order to fund the roll out of various divisions that are underpinned by Jean. The coins sold during the sale will be directly connected to the use of Invacios raft of products. Whether they are used to pay whole subscription fees for AI fintech predictive services or to attract a discount against a corporate market intelligence monitoring account through the Alise division these coins will provide a great amount of utility within the Invacio group.
submitted by InvacioOfficial to u/InvacioOfficial [link] [comments]

Invacio versus the world

British born entrepreneur William West is set to go “toe to toe” with major institutions around the world with his, one of a kind, applied artificial intelligence organisation Invacio. Created over the last 5 years William’s brainchild is far more than your average chatbot or sentiment scraper creating tech company. In point of fact it is such a powerful system that Invacio were invited to make their inaugural presentation in front of the United Nations during a UNESCAP FDI meeting in Thailand last year.
The main elements that have made the elite sit up and take notice are Invacio’s flexibility and shere data processing capabilities. When you have a system that is plugged into thousands upon thousands of data sources with the capacity to analyse and correlate everything from historical market exchange data, and live news feeds with satellite data, and social media interactions, to formulate comprehensive reports and predictions for virtually any industry on earth, it tends to make an impact when people become aware of it.
Data crunching leviathans are ten a penny, in this day and age, so what is so unique about invacio that world leaders invite them to elaborate the details in front of them? That is the secret sauce: a multi agent deep neural network that constantly learns from the data coming in and its own self created distinct datasets. A system that is aware enough of its own data requirements that it literally sourced its own hacking software to gain access to some data it really wanted to see (that got shut down immediately and new rules were implemented “no entry means no entry”).
Wealth generation and crisis management were two of the areas explored during the initial UN presentation and since then further, more detailed, discussions have continued behind closed doors.
First off the bat the sector which is going to feel the full force of Invacio, muscling its way in, is the finance sector, initially they will be putting “Agnes” into the ring. A subscription based service which monitors 2995 stocks/shares and the main forex pairs, Agnes will provide highly accurate short term price predictions to whomever pays the fees be that professionals looking to get ahead of the game or hobbyist day traders looking to put a lump sum away for their future. With accuracy levels regularly running between 92 & 98% on any given trade, with the correct type of equity management trading might just become fun again, even during downturns.
Next up will be an onslaught to capture institutional money through the application of AI directly into the hedge fund market, Aquila, Archimedes and Tomahawk are the names given to these funds. Archimedes will be a human/AI hybrid fund that applies predictions made by Agnes and actioned by a human fund manager. In a 16 week experiment, with real money, Archimedes showed growth of 79%. Tomahawk is a long term forecasting system which looks anywhere from 6 months to 2 years into the future. Aquila will be a combination of all of these with the addition of invacio’s full market oversight (all commodities, shares, indices and forex pairs)
Other markets that will feel the wrath of Invacio are, Market intelligence, communications, social networking, data provision and Global security but they are a different story altogether.
Invacio are currently undergoing an ICO (initial coin offering) in order to fund the roll out of Their various divisions. The coins sold during the sale will be directly connected to the use of Invacios products find out more here www.invest.invacio.com
submitted by InvacioOfficial to u/InvacioOfficial [link] [comments]

INVACIO AI Company Makes World Debut In Front Of United Nations

Little Known AI Company Makes World Debut In Front Of United Nations
Founded by William J D West around 5 years ago and developed in stealth mode since then, Invacio is a tech company unlike any other in the world and because of this, it is attracting attention from some fairly high up places. Governmental discussions are ongoing around the world to implement their technology in various ways.
But what is it exactly that invacio do that instigated the invitation to make their worldwide debut presentation (coming out if you will) in front of world leaders at the UNESCAP FDI meeting in Thailand on November the 3rd last year?
The answer to that is quite hard to formulate without going off on multiple tangents all at once, so, I will give a brief outline and then try to cover some more specifics in order that you can try to paint the picture for yourself more clearly…All I will say before launching into this is open your mind and try to see all the potential uses of this technology.
Invacio is primarily an applied artificial intelligence company that has created a multi-agent neural network that analyzes the world’s informational output, digests it, correlates the various disparate facts and ultimately delivers actionable intelligence across any sector of commerce, industry, society or government possible.
Regardless of the source of this data be it: NASAs satellite feeds, live news, digital radio, video broadcasts, social media twitterings etc or live market data from world exchanges or even historical digitized data banks like the National Library of Congress and thousands of others, they are all relentlessly probed and itemized by a system which is self learning and always hungry for more. Since the system was switched on, an ever growing number of proprietary datasets have been created well over 2 billion as this story is being written. Ok, so Invacio has a lot of information from all over the world: but what exactly is its use? And, what can Invacio do that any other information rich organisation with a decent search engine can’t?
Well, this is where it truly comes into its own you see, it doesn’t pull the information together, stick a label on it and forget about it until someone asks for it. No, Invacio actively seeks to place all the information it holds into context with all the rest so that comparisons, parallels and connections can be created. Why? Because their system is designed to understand the world and guide us where it can. An example of this which was given during the presentation to the United Nations was that of crisis management during the Californian wildfires last year – Within a second of the first tweet relating to the fires starting being sent, Jean (that is what they call the full operational system) was aware and rapidly pulling together every type of relevant information available. Everything from geographical data, historically relevant time based records of vineyards (soil composition, state of vines or ripeness of fruits), meteorological details (live conditions and historical in relation to similar events globally)…… you get the picture.
In the second second Jean would have been able to direct the emergency response and do as much as possible to limit the ongoing damage being caused by the fire by predicting the way the emergency would develop having analysed all available information and extrapolating.
As a bonus, in the 3rd second Jean could have told you whether it was worth buying wine futures or no.
That is one example,imagine the benefits of having that kind of analysing power in your sector:
Hedge funds… highly accurate predictions on shares, indices, commodities and forex (Agnes, Archimedes, Aquila and Tomahawk), Market intelligence… knowing what the world is thinking about your brand, competitor, client or product in real time (Alise), Security… maintaining secure facilities through the application of advanced facial recognition through security cameras(Sauron) or alternatively simply plug your organisation straight into Invacio API and pull out the information you need to make your world a better place.
submitted by InvacioOfficial to u/InvacioOfficial [link] [comments]

Neurobiopharmacological Etudes by Dead Hippie Squadron - 'METHAMATICS' - Complex artistic-spiritual and scientific equations arising from years of practice as an urban shaman

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Machine learning and web dev project, trying to expand and need help!

Hey guys, I'm trying to find some people who can help me out with a project that involves trying to predict bitcoin and forex markets (and potentially other time series data sets in the future) using artificial neural networks. Originally the site was exclusively bitcoin, but I've been making some pretty significant changes recently. Here is what I've done so far:
http://www.btcpredictions.com
Here, you can sign up for free and see charts displaying predicted prices for bitcoin and currency pairs (only 2 pairs so far but adding more soon). You can also see how each chart performed over the past 24 hours. The charts are created using a relatively simple neural network right now, but I'm looking to get into some more complicated types of neural networks and methods of training, which I'm happy to talk about in more detail if anyone is interested.
What I need most (which might be obvious) is help with front end development. That being said, I would love to work with back end engineers too and AI guys who want to help me develop some of the additional services I'm trying to create. One example of one of these services is that I would like to create a trade simulator where people can test out trading strategies without risking real money.
Feel free to contact me at [email protected] if you are interested, and we can set up a time to discuss how we can work together!
-Kevin
submitted by K128kevin to codeprojects [link] [comments]

Next price predictor using Neural Network – indicator for MetaTrader 4 Trade Prediction based on neural networks Trade Prediction based on neural networks I coded neural network for forex prediction in 24h ... Forex Market Prediction using Neural Networks and Armax Currency rate prediction by Neural Networks in Matlab NNEA - Neural Network Trend Predictor Indicator for Metatrader

Neural networks have the ability to significantly benefit the forex market. The main reason for this is due to their accuracy and intuitive instincts. They have the ability to analyze fundamental data as well as technical data. Mechanical systems are not well-equipped to analyze this type of data. Human errors are even more common when faced with analyzing this data. This is why neural ... Neural networks can be used for prediction with various levels of success. The advantage of then includes automatic learning of dependencies only from measured data without any need to add further information (such as type of dependency like with the regression). The neural network is trained from the historical data with the hope that it will discover hidden dependencies and that it will be ... Prediction using neural networks, Forex prediction. This example is very similar to the previous one.The only difference is that it shows data for foreign exchange (forex) currency pairs. The empirical data used in the model of neural networks are related to the exchange rate USD/EUR in the period 23.04.2012-04.05.2012. The results shows that the model can be used for FOREX prediction. Forex prediction Data and functions Conclusion Other tutorials. Prediction using neural networks. This tutorial introduces the topic of prediction using artificial neural networks. In particular, prediction of time series using multi-layer feed-forward neural networks will be described. First, the topic of prediction will be described together with classification of prediction into types ... This makes neural networks a better tool for forex market as neural networks are know their ability of learning unknown processes and forecast the patterns of the process ahead. Lets get to the main point. In this thread I would describe the working of the system I have developed rather than the system itself as it is a long way to explain. The system is basically a time-series-forecasting ... Neural networks are known to be black box predictors where the data scientist does not usually know which particular input feature influenced the prediction the most. This can be rather limiting if we want to get some understanding of what the model actually learned. Having this kind of understanding may allow us to find bugs or weaknesses in our learning algorithm or in our data processing ...

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Next price predictor using Neural Network – indicator for MetaTrader 4

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