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Real-time-stock-market-prediction related contents

  • 007-koeffel / tokyo_stock_predictions

    Real-time-stock-market-prediction, Success in any financial market requires one to identify solid investments. When a stock or derivative is undervalued, it makes sense to buy. If it's overvalued, perhaps it's time to sell. While these finance decisions were historically made manually by professionals, technology has ushered in new opportunities for retail investors. Data scientists, specifically, may be interested to explore quantitative trading, where decisions are executed programmatically based on predictions from trained models. There are plenty of existing quantitative trading efforts used to analyze financial markets and formulate investment strategies. To create and execute such a strategy requires both historical and real-time data, which is difficult to obtain especially for retail investors. This competition will provide financial data for the Japanese market, allowing retail investors to analyze the market to the fullest extent. Japan Exchange Group, Inc. (JPX) is a holding company operating one of the largest stock exchanges in the world, Tokyo Stock Exchange (TSE), and derivatives exchanges Osaka Exchange (OSE) and Tokyo Commodity Exchange (TOCOM). JPX is hosting this competition and is supported by AI technology company AlpacaJapan Co.,Ltd. This competition will compare your models against real future returns after the training phase is complete. The competition will involve building portfolios from the stocks eligible for predictions (around 2,000 stocks). Specifically, each participant ranks the stocks from highest to lowest expected returns and is evaluated on the difference in returns between the top and bottom 200 stocks. You'll have access to financial data from the Japanese market, such as stock information and historical stock prices to train and test your model. All winning models will be made public so that other participants can learn from the outstanding models. Excellent models also may increase the interest in the market among retail investors, including those who want to practice quantitative trading. At the same time, you'll gain your own insights into programmatic investment methods and portfolio analysis―and you may even discover you have an affinity for the Japanese market.

    From user 007-koeffel

  • 767472021 / oneworld

    Real-time-stock-market-prediction, https://www.kaggle.com/c/jane-street-market-prediction/overview “Buy low, sell high.” It sounds so easy…. In reality, trading for profit has always been a difficult problem to solve, even more so in today’s fast-moving and complex financial markets. Electronic trading allows for thousands of transactions to occur within a fraction of a second, resulting in nearly unlimited opportunities to potentially find and take advantage of price differences in real time. In a perfectly efficient market, buyers and sellers would have all the agency and information needed to make rational trading decisions. As a result, products would always remain at their “fair values” and never be undervalued or overpriced. However, financial markets are not perfectly efficient in the real world. Developing trading strategies to identify and take advantage of inefficiencies is challenging. Even if a strategy is profitable now, it may not be in the future, and market volatility makes it impossible to predict the profitability of any given trade with certainty. As a result, it can be hard to distinguish good luck from having made a good trading decision. In the first three months of this challenge, you will build your own quantitative trading model to maximize returns using market data from a major global stock exchange. Next, you’ll test the predictiveness of your models against future market returns and receive feedback on the leaderboard. Your challenge will be to use the historical data, mathematical tools, and technological tools at your disposal to create a model that gets as close to certainty as possible. You will be presented with a number of potential trading opportunities, which your model must choose whether to accept or reject. In general, if one is able to generate a highly predictive model which selects the right trades to execute, they would also be playing an important role in sending the market signals that push prices closer to “fair” values. That is, a better model will mean the market will be more efficient going forward. However, developing good models will be challenging for many reasons, including a very low signal-to-noise ratio, potential redundancy, strong feature correlation, and difficulty of coming up with a proper mathematical formulation.

    From user 767472021

  • 930turbo / blastock

    Real-time-stock-market-prediction, Ready to blast off with blastock? Read and monitor stock market data in real time! Use our built in AI to gain predictions on investments by monitoring patterns on stock data.

    From user 930turbo

  • anurag-moudgil / smarpma

    Real-time-stock-market-prediction, Stock Market Prediction Models’ Analyzer: ▪ Trained and tested Machine Learning Models on Real-Time stock market data of companies (like GOOGLE, AMAZON etc.) to get the best Machine Learning model to predict the variations in price▪ Technologies Used- Python (Libraries- “BeautifulSoup”, “urllib2”, “Tkinter”) & R Programming.

    From user anurag-moudgil

  • anwarcsebd / stock-market-analysis

    Real-time-stock-market-prediction, Stock Market Analysis and Prediction is the project related to Exploratory data analysis( EDA), Data visualization and Predictive analysis using real-time financial data, provided by The Investors Exchange (IEX).

    From user anwarcsebd

  • casually-pylearner / prediction-of-stock-market-deviation-using-arima-algorithm

    Real-time-stock-market-prediction, Stock market is an ideal way to invest hard earned money as it has the potential to provide great returns. But, even with the current technology at hand, it is a risky deed due to the inability to understand sudden market changes and interpret data appropriately. To ease the process of investment and to provide better awareness, we propose ‘Prediction of stock market deviation using ARIMA algorithm’: a real-time risk prediction software that considers market interests. It is based on a parametric time series analysis technique- ARIMA (Auto Regressive Integrated Moving Average) algorithm to interpret historic data. It also makes use of Sentiment analysis to convert market trends to valuable information. Since stock market is highly influenced by information release and public acceptance, the addition of Sentiment Analysis to ARIMA boosts system performance and provides a more accurate representation of market volatility. The software provides pictorial and graphical representations and can also be used to compare the growth of two companies for the required time period. The objective is to provide short term and long term prediction capabilities to prepare for future potential investments.

    From user casually-pylearner

  • ck011 / stock-market-analysis

    Real-time-stock-market-prediction, Stock Market Analysis and Prediction is the project related to Exploratory data analysis(EDA), Data visualization and Predictive analysis using data, provided by The Investors Exchange (IEX). I looked at real-time financial data from the stock market. I have used python libraries to get stock information, visualize different aspects of it, and finally I worked at a few ways of analyzing the risk of a stock, based on its previous performance history. I have also used statistical method called Monte Carlo Method to predict future stock prices.

    From user ck011

  • daksh-intwala / s-p500-stock-analysis-and-lstm-model-prediction

    Real-time-stock-market-prediction, Detailed EDA performed in DataBricks environment wherein ETL was done through PySpark. LSTM model was trained and effective predictions were made with minimal Mean Square Error. The aim was to guide beginners in investing stock market and how S&P500 stock can be a safe heaven for the passive investors and a real-time big investment opportunity for venture capitalists.

    From user daksh-intwala

  • endeavour3 / stock-market-prediction-using-machine-learning

    Real-time-stock-market-prediction, Stock market prediction using machine learning leverages historical and real-time financial data to build predictive models. These models analyze market indicators, news sentiment, and technical data to forecast future stock prices and trends.

    From user endeavour3

  • gjepcindia / gold-sheds-war-premium-but-uncertainty-may-see-price-soar-again

    Real-time-stock-market-prediction, The Boy Who Cried Wolf’ is one of the better known stories of Aesop’s Fables. The shepherd boy who repeatedly cried ‘Wolf!’ to ease his boredom, having fun at expense of the villagers who rushed to his rescue, found out the hard way when a wolf actually came and no one responded to his alarm. Gold can now add its own version of ‘The Boy Who Cried Wolf’ in reverse. For almost the entire year, gold analysts, gold bugs, experts, analysts, chartists et al predicted a higher price for the yellow metal in 2021. Many predicted $2500-3000 per ounce to be range that the gold price could reach. LBMA gold analysts forecast an average of $1,973.8 per ounce for 2021. In reality, gold ended the year 2021 at $1,805.85 per ounce with an average gold price of $1,798.6 per ounce. It made a mockery of the price predictions made by all the analysts, etc. Ultimately, for gold, when the wolf finally made an appearance in the form of Vladamir Putin’s invasion of Ukraine on 24th February, 2022, all hell broke loose! The yellow metal which began the year at $1,809.05 per ounce made steady progress despite a couple of dips below the $1,800 per ounce mark. It was poised at $1,826 per ounce on the 11th February. Thereafter, as the winds of war began to blow it was poised just below the $1,900 per ounce mark. Then, as Russia invaded Ukraine with all its might on the 24th of February, the yellow metal rose sharply to $1,968 per ounce (am fix) on the same day. Then, after a dive to below $1,900 per ounce on the second day of the war, it rose by leaps and bounds over the next few days to scale $2,039 per ounce on the 8th of March (London pm fix). In fact, gold actually came within a whisker of crossing its all-time high of $2075 per ounce of August 6th 2020 (intra-day). The yellow metal just fell short of that mark as it fleetingly touched the $2,071 per ounce mark on 8th March 2022 (intra-day). As it neared its peak level, gold took in its stride all the negatives for gold. However, when it became apparent that instead of a T-20 match, it looked more like a timeless test match, the gold price retreated back to below the $2,000 per ounce mark. And when it became evident that neither Russia nor US-led NATO were willing to risk a WWIII, gold gradually slipped to below $1.950 per ounce levels. It even slipped below the $1,900 per ounce level (intra-day) before recovering again. Gold even discounted for the Fed rate hike of 0.25% and ended at $1,935.80 per ounce on 18th March after dipping below $1,915 per ounce levels a day earlier. It was not only gold, but the entire precious metals basket that reached higher levels after Russia invaded Ukraine. Gold rose from $1,809.05 per ounce at the start of 2022 to its peak for the year $2,071 per ounce on March 8, 2022 (up by over 14%). Silver too surged by over 14% to scale $26.17 per ounce at its peak for the year. The PGM group metals fared even better as platinum climbed by over 18% at $1,151 per ounce and palladium sky rocketed by over 61% to scale $3057 per ounce. Not only that oil rose to over $150 a barrel and the stock markets crashed spectacularly all over the global. The BSE, NSE as well as the Dow Jones fell sharply as war broke out. However, on March 18, 2022, gold shed half its gains due to the advent of war to be at $1935.80 per ounce. Silver too closed at $25.24 per ounce on 18th March, 2022, up by 10% from the start of the year as against over 14% at the start of the war. The PGMs too shed their gains, while platinum gains were reduced to 6%; palladium too lost more than 50% of its earlier gains. Oil too fell sharply as it was poised to go below $100 a barrel. The stock markets on the other hand gained some of their lost ground. It would seem that the war premium had vanished just as suddenly as it had appeared at the advent of the war. Once bitten twice shy is a very well known adage. Scalded by their ‘way off the mark’ precious metals predictions in 2021, LBMA analysts were ultra-cautious with their price prediction for all the precious metals. While the predicted average gold price in the LBMA annual price forecast at $1,801.9 per ounce for 2022 was just 0.2% above the average price forecast for 2021, it was in negative territory for the rest of the precious metals. Silver was slated to be down -6.4% at $23.54 per ounce, platinum down by -2.5% at $1063.4 per ounce and palladium set to decline -18% to $1967.8 per ounce. So much so, that even the war premium-shorn prices of the precious metals on 18th March, 2022 were comfortably above the price predicted by analysts in the LBMA Survey in three of the four precious metals, barring platinum. However, the solace is that the highest price predicted by the same analysts for the precious metals was way above the current levels. So, what will be in store for the precious metals, gold in particular, in the remainder of the year? What will be the main drivers of the gold price? Geopolitical tensions would continue to disrupt the global economy. The continuation of Russia-Ukraine conflict that threatens to spread in the region could severely upset global markets and impacted the economies across the world. Even a financially maimed Russia would not bode well for the health of global economy. Rising energy costs could fuel inflation across the globe and impact productivity in energy deficient economies. The US continues to be the bulwark in the global economic scenario. US inflation at 7.5% is at its highest level since 1982. It could severely hurt the economy, impair unfettered hike in interest rates and corrode the value of the US dollar. The Fed, after tapering off QE has embarked on hike in interest rates. The first hike of 0.25% was made just in the week gone by with five more slated for the year. The target set by the fed to reduce balance sheet could be difficult as an aggressive hike in interest rates could hamper the ability to service the mounting US debt. The fear of stagflation and recession looming on the horizon too is for real. Neither Russia nor US-led NATO could afford a long war over Ukraine. Economic consequences could be disastrous for the world at large. With the 4th wave of Covid-19 on the rampage across Asia and Europe, it would seem that the pandemic is far from over. Although, the impact could be lesser than the previous waves, it would be the proverbial Sword of Damocles hanging over the world. All of the above could be positive for the gold price. Demand could be seen from ETFs and central banks buying gold. Jewellery demand from countries like India and China could be hit if the gold price soars again towards its all-time high levels or scale the highs predicted by some analysts. Although markets (both commodity and equity) discount for the worst, gold price prediction could be a tricky affair for the rest of 2022. Some forecasters, chartists, analysts still predict gold above $2,200 per ounce and well above. However, there are those who warn that war premium (of around $150 per ounce) would soon dissipate once ceasefire is announced and peace returns. They predict gold to go even below $1,750 per ounce or lower. Gold is in for uncertain times again. As a result, it could still soar in 2022! Meanwhile, closer home, the gold reforms juggernaut is gathering speed in India. Hallmarking has more or less been accepted by everyone concerned. However, while hallmarking centres want hallmarking to be made mandatory all over the country, retailers want the infrastructure to be in place before it is made compulsory throughout the country. As only 256-odd districts are under the mandatory hallmarking system, the hallmarking centres have their incomes only at few centres while the rest face survival issues due to skewed incomes. The retailers are apprehensive about the burden of responsibility regarding jewellery pieces as per the hallmarking marks resting mainly on them. Then, the recent Comprehensive Economic Partnership Agreement (CEPA) with UAE has cast apprehension in the minds of a few in the gold industry. The zero import duty on gold imports from Dubai could cause a surge in such imports (around 200 tonnes) and disrupt the domestic gold market. They remind one of the disruption caused when gold imports surged from South Korea (just 60 tonnes) after a similar trade deal. Then, the domestic market went into deep discount as compared to the international price. Moreover, domestic gold refiners too are likely to be hit as the CEPA could impact flow of dore as well as make refining of dore unviable. The India International Bullion Exchange (IIBX), a consortium of the three premier exchanges in the country, at GIFT City is likely to become operational soon. Mock trading is said to be going on and the membership drive in full swing. However, if India aspires to become a gold hub as well as an international finance centre, then, it is imperative that import duties and tariffs are in tune with global trends. Moreover, both import duty as well as GST should be such that there are no compliance issues, even agree to suggestions made by the trade. Then, even the trade would not grudge if the erring players face harsh action. As a precursor, import duty and GST would require a downward revision. Recently, an MoU was signed for the Domestic Spot Gold Exchange by IBJA and NSE. Members of IBJA would have a 49% stake while remaining 51% would be owned by institutions (banks, finance institutions as well other exchanges). Then, the government is having a relook at the GMS to find out if the expenses on the scheme are more than the returns. Thus, look at course correction if required. Finally, with many predicting India’s CAD to be around 10-year highs in the coming year, will the authorities continue its pro-gold policies? Or will they revert back to the old ways and pin the blame on gold imports? In the past, particularly after the sub-prime crisis of 2008 pushed the gold prices to the then all-time high of $1926 per ounce in September 2011, the knee-jerk reaction was to hike the import duty from around 1% to 10% in a very short span of time. Will history repeat itself and we see a rise in the import duty on gold? Or will better sense prevail? For, at stake would be the success of the newly formed (and not yet running) India International Bullion Exchange at GIFT City and the dream of making India a Gold Hub! To know more: https://gjepc.org/solitaire/gold-sheds-war-premium-but-uncertainty-may-see-price-soar-again/

    From user gjepcindia

  • henrywan16 / stockdataanalysis

    Real-time-stock-market-prediction, StockAnalysis can grab the real time information about the stocks you subscribe, and make a prediction about the price of the stock tomorrow based on the history data. It can evaluate live data. According to historical trends, there is an 80% chance for this stock price going down in a few minutes. Live data becomes historical trends over time. With the help of historical trends, if historical information is sufficient, we can do data mining among all the information, so that stock prices could be predicted. Our aiming users are those retail investors in second-level circulation market. Most of them could not analyze the information instantly and efficiently, so the stock prediction would not only help them make more profit, but also avoid potential risks.

    From user henrywan16

  • hrshl04 / stock-market-predictor

    Real-time-stock-market-prediction, This project uses machine learning to predict stock market prices and creates a user-friendly web interface using HTML, CSS, and Dash. Users can input stock symbols, view historical data, and receive real- time predictions for informed investment decisions.

    From user hrshl04

  • karthik-02 / nifty-50-mlproject

    Real-time-stock-market-prediction, The NIFTY 50 is a benchmark Indian stock market index that represents the weighted average of 50 of the largest Indian companies listed on the National Stock Exchange. We use real-time dataset to calculate the stock predictions for future years.

    From user karthik-02

  • kianhaghighi / stock-forecast-pro

    Real-time-stock-market-prediction, This repository contains a web app built w/ Django, Streamlit & Pyplot, that allows user to visualize & predict stock market trends using data from Yahoo Finance & Alpha Vantage APIs. Features include user registration, portfolio management, real-time updates, prediction models, stock comparison.

    From user kianhaghighi

  • kumbharedu / eda_stockmarket_dataset

    Real-time-stock-market-prediction, Stock Market Analysis and Prediction is the project related to Exploratory data analysis(EDA), Data visualization and Predictive analysis using data, provided by [The Investors Exchange (IEX)](https://iextrading.com/apps/stocks/). I looked at real-time financial data from the stock market.

    From user kumbharedu

  • mohak1 / rnn-stockpriceprediction

    Real-time-stock-market-prediction, This RNN is trained on real stock price data of Google and tries to predict the price of stock in next time-step. It uses the LSTM model because stock prices depend on time which is a constantly changing quantity. Understanding that stock prices depend on a lot of things like economic conditions, value of currency, market share of the company and many other things but this project takes in consideration only the opening and closing of the price each day and tries to make a prediction.

    From user mohak1

  • muzammilmemonz78 / stock-market-analysis-nye

    Real-time-stock-market-prediction, Stock-Market-Analysis Analysis and prediction of the real-time stock market trend for investment decision making. Accessed real time ticker data from yfinance for user-chosen timeframe. Performed descriptive analysis (Mean, Std, Min, Max, Range, Quartiles) Visualized several plots for trend understanding (Raw plots, Moving Average, Daily Returns, MACD, Buy-Sell Signals, Weighted Moving Average) Use of Arima and Linear Regression for trend prediction. The script can be executed by running the Stockquotes.py file

    From user muzammilmemonz78

  • oisavictor / stock-market-predictor

    Real-time-stock-market-prediction, A web and mobile platform that allows users to share their stock market predictions and discuss stocks with other traders in real-time.

    From user oisavictor

  • onkarxo / financewizard

    Real-time-stock-market-prediction, The ML-Based Stock Price Prediction and Financial News Aggregation Web App is a platform designed to provide users with insights into stock market trends, predict future stock prices, and aggregate relevant financial news. The application leverages Long Short Term Memory to forecast stock prices and integrates real-time financial news

    From user onkarxo

  • ozanm / stock-predictor-python

    Real-time-stock-market-prediction, This is a python program that analyzes real-time current stock market day for any symbol, and produces a graph of what the price will be for the rest of the year. UI is in Swift, data managing is in Python, and algorithmic predictions is in R.

    From user ozanm

  • paddingright / big-data

    Real-time-stock-market-prediction, Real time stock market prediction using sentiment analysis on tweeter (X)

    From user paddingright

  • poonam3030 / gold-price-prediction

    Real-time-stock-market-prediction, There are many real time series dataset present in the market. Mostly, time series dataset used in stock market. By using machine learning algorithm , prediction of future values take place. In this project, prediction of future values(30 days) taken place using LSTM.

    From user poonam3030

  • stockx-python-project / stockx

    Real-time-stock-market-prediction, StockX is a web application that provides real-time stock market data and predictions powered by news.

    From organization stockx-python-project

  • timothypowell / stocktracker

    Real-time-stock-market-prediction, A easy-to-use stock analyzer and predictor that uses information from all stock market data sources to make real-time, accurate predictions.

    From user timothypowell

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