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STOCK VISUALISATION AND
FORECASTING
CREATED BY-
PANKAJ MALVIYA (0863CS201112)
PRITESH PRAJAPAT (0863CS201124)
MANISH PATIDAR (0863CS201082)
KRISHNAPAL ARYA (0863CS201079)
GUIDE-
DR.DEVESH KUMAR LAL
INTRODUCTION
• A stock market is a platform for trading of a company's stocks and
derivatives at an agreed price. Supply and demand of shares drive
the stock market.
• Ability to predict direction of stock/index price accurately is crucial
for market dealers or investors to maximize their profits.
• Should I take a long position? Should I take a short position?
What is going to be the price tomorrow, next week or next year?
RELATED WORK
• Many people these days are looking forward to investing in the share market. For those with
little expertise in this sector, keeping a careful eye on the share market could be a challenging
endeavour.
• As we there are many software which are now aquires a Machine Learning Concept to
Predict the future price of the stock. Such as GROW ,ANGLEONE ,MONEYCONTROL , but
they needs a Subscription or paid by a user to predict a stock price .
• On basis of that cons we Make a Dash App to Forecast a stock Price without any
Subscription or Paid Membership.
OBJECTIVES
• To predict the stock prices in order to make more informed and
accurate investment decisions.
• A stock price prediction system that integrates mathematical
functions, machine learning, and other external factors for the
purpose of achieving better stock prediction accuracy and issuing
profitable trades
METHODOLOGY
• We saw that the new user was afraid to invest in the share market because he did
not have the knowledge and did not have any tool with the help of which he could
do this work.
• So then we created a tool with the help of machine learning , deep learning,
which can tell in a very precise way where the market will move by analyzing
things
IMPLEMENTATION
(TECHNOLOGIES USED)
• Dash
• dash-core-components
• dash-html-components
• dash-table
• Flask
• Pandas
• Plotly
• Yfinance
• scikit-learn
• numpy
SCREENSHOTS
INPUTINGSTART DATEAND STOCKCODE
(TCS)
GETTINGSTOCKPRICEBY CLICKINGON STOCKPRICEBUTTON(TCS)
GETTINGAVERAGEPRICEOF STOCKBY CLICKINGON INDICATORS(TCS)
FORECASTINGOF STOCK PRICEBY INPUTINGNO. OF DAYS
ANDCLICKON FORECASTBUTTON(TCS)
GETTINGFORECASTDATA
(TCS)
CONCLUSION
• The stock market plays a remarkable role in our daily lives. It is a significant factor in a
country's GDP growth.
• It is possible to predict stock market with more accuracy and efficiency using machine
learning techniques.
REFERENCES
• Deploying Dash Apps
• Yfinance Dataset
STOCK_PPT.pptx

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STOCK_PPT.pptx

  • 1. STOCK VISUALISATION AND FORECASTING CREATED BY- PANKAJ MALVIYA (0863CS201112) PRITESH PRAJAPAT (0863CS201124) MANISH PATIDAR (0863CS201082) KRISHNAPAL ARYA (0863CS201079) GUIDE- DR.DEVESH KUMAR LAL
  • 2. INTRODUCTION • A stock market is a platform for trading of a company's stocks and derivatives at an agreed price. Supply and demand of shares drive the stock market. • Ability to predict direction of stock/index price accurately is crucial for market dealers or investors to maximize their profits. • Should I take a long position? Should I take a short position? What is going to be the price tomorrow, next week or next year?
  • 3. RELATED WORK • Many people these days are looking forward to investing in the share market. For those with little expertise in this sector, keeping a careful eye on the share market could be a challenging endeavour. • As we there are many software which are now aquires a Machine Learning Concept to Predict the future price of the stock. Such as GROW ,ANGLEONE ,MONEYCONTROL , but they needs a Subscription or paid by a user to predict a stock price . • On basis of that cons we Make a Dash App to Forecast a stock Price without any Subscription or Paid Membership.
  • 4. OBJECTIVES • To predict the stock prices in order to make more informed and accurate investment decisions. • A stock price prediction system that integrates mathematical functions, machine learning, and other external factors for the purpose of achieving better stock prediction accuracy and issuing profitable trades
  • 5. METHODOLOGY • We saw that the new user was afraid to invest in the share market because he did not have the knowledge and did not have any tool with the help of which he could do this work. • So then we created a tool with the help of machine learning , deep learning, which can tell in a very precise way where the market will move by analyzing things
  • 6. IMPLEMENTATION (TECHNOLOGIES USED) • Dash • dash-core-components • dash-html-components • dash-table • Flask • Pandas • Plotly • Yfinance • scikit-learn • numpy
  • 11. FORECASTINGOF STOCK PRICEBY INPUTINGNO. OF DAYS ANDCLICKON FORECASTBUTTON(TCS)
  • 13. CONCLUSION • The stock market plays a remarkable role in our daily lives. It is a significant factor in a country's GDP growth. • It is possible to predict stock market with more accuracy and efficiency using machine learning techniques.
  • 14. REFERENCES • Deploying Dash Apps • Yfinance Dataset