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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
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<title> Stock Exchange Data Analysis</title>
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About
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<a class="hover-white no-underline white-90" target="blank" href="https://github.com/divyankm/Stock-Exchange-Data-Analysis" title="Project page">
Project
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<h1 class="f2 f-subheadline-l fw2 white-40 mb0 lh-title">
Stock Exchange Data Analysis
<p style="text-indent:36px;font-size:20px"><b>"Domain Knowledge: Fundamental+Technical+Research Analyst | Algorithmic Trading & Value Investing Expertise"</b></p>
<p style="text-indent:36px;font-size:20px"><b>"Technical Knowledge: Data (Analyst+Architect+Engineer+Scientist) | BI Developer | Dev-Ops"</b></p>
<!-- <li class="list f5 f4-ns fw4 dib pr3">
<a class="hover-white no-underline white-90" target="blank" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/momentum_strategies.html" title="Momentum Strategies">
BackTesting
</a>
</li> -->
<li class="list f5 f4-ns fw4 dib pr3">
<a class="hover-white no-underline white-90" target="blank" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/backtesting.html" title="BackTesting">
BackTesting
</a>
</li>
<li class="list f5 f4-ns fw4 dib pr3">
<a class="hover-white no-underline white-90" target="blank" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/cal_spread.html" title="Calender Spread">
Calender Spread
</a>
</li>
<li class="list f5 f4-ns fw4 dib pr3">
<a class="hover-white no-underline white-90" target="blank" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/dcf_reverse_dcf.html" title="DCF Module">
DCF Module
</a>
</li>
<li class="list f5 f4-ns fw4 dib pr3">
<a class="hover-white no-underline white-90" target="blank" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/max_pain.html" title="Max Pain">
Max Pain
</a>
</li>
<li class="list f5 f4-ns fw4 dib pr3">
<a class="hover-white no-underline white-90" target="blank" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/ml_models.html" title="ML Models">
ML Models
</a>
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<a class="hover-white no-underline white-90" target="blank" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/momentum_strategies.html" title="Momentum Strategies">
Momentum Strategies
</a>
</li>
<li class="list f5 f4-ns fw4 dib pr3">
<a class="hover-white no-underline white-90" target="blank" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/option_strategy.html" title="Option Strategy">
Option Strategy
</a>
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<li class="list f5 f4-ns fw4 dib pr3">
<a class="hover-white no-underline white-90" target="blank" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/probab_distribution.html" title="Probability Distribution">
Probablity Distribution
</a>
</li>
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<a class="hover-white no-underline white-90" target="blank" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/pair_trading.html" title="Pair Trading">
Pair Trading
</a>
</li>
</h1>
</div>
</div>
</header>
<article class="cf ph3 ph5-l pv3 pv4-l f4 tc-l center measure-wide lh-copy mid-gray">
<p>Welcome to SEDA Web page!!!</p>
<p>👨💻 This is Basic version of webpage,more improvement with more modules will be coming overtime !!!, Currently WIP👨💻</p>
<p>Coding Language- Python</p>
<p>Library- Plotly | KATS | stats model | Pandas | Yahoo Fin.</p>
<p>Topics Covered-Data Science | Statistics | Machine Learning</p>
<p>Database- mySQL | OpenSearch</p>
<p>Vizualization and Alerting Tool- OpenSearch Dashboards | Grafana</p>
<p>Orchestration Tool-Docker Container(Docker Compose)</p>
<p>Data Pipelines-ETL Python Scripts</p>
<p>Current OS-Windows 10 Pro. (Fut Scope- VM(Linux))</p>
<p>CICD- Not on cards till dev env working in local machine(Win. OS)</p>
</article>
<!-- <include src="https://divyankm.github.io/Stock-Exchange-Data-Analysis/NF%20Mean%20Reversion%20Returns%20on%20Expiry%20Day(Thursday).html"></include> -->
<body>
<!-- <h1>Nifty 50 Index Data Analysis and Forecasting Algorithm Test-</h1>
<p>In the below viz's,Data Analysis is done on Nifty 50 Index.</p> -->
<h2>BackTesting: <button><a target="blank" style="background-color:green; border:none; font-size: 15px; padding: 12px 12px;margin: -8px -8px; color:white;display: inline-block" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/backtesting.html" title="">BackTesting</a></button></h2>
<p style="text-indent:30px">
<ul> <li>Backtesting assesses the viability of a trading strategy or pricing model by discovering how it would have played out retrospectively using historical data.
<li>The underlying theory is that any strategy that worked well in the past is likely to work well in the future, and conversely, any strategy that performed poorly in the past is likely to perform poorly in the future.
<li>When testing an idea on historical data, it is beneficial to reserve a time period of historical data for testing purposes. If it is successful, testing it on alternate time periods or out-of-sample data can help confirm its potential viability.
</ul>
</p>
<h2>Calender Spreads: <button><a target="blank" style="background-color:green; border:none; font-size: 15px; padding: 12px 12px;margin: -8px -8px; color:white;display: inline-block" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/cal_spread.html" title="">Calender Spread</a></button></h2>
<p style="text-indent:30px">
Calendar Spread is an options or futures strategy established by simultaneously entering a long and short position on the same underlying asset but with different delivery/expiry dates.<br>
</p>
<h2>DCF & Reverse DCF: <button><a target="blank" style="background-color:green; border:none; font-size: 15px; padding: 12px 12px;margin: -8px -8px; color:white;display: inline-block" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/dcf_reverse_dcf.html" title="">DCF Module</a></button></h2>
<p style="text-indent:30px">Discounted cash flow (DCF) valuation is a type of financial model that determines whether an investment is worthwhile based on future cash flows
<h2>Delta Neutral Option Strategies:<button><a target="blank" style="background-color:green; border:none; font-size: 15px; padding: 12px 12px;margin: -8px -8px; color:white;display: inline-block" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/option_strategy.html" title="">Option Strategies</a></button></h2>
<xmp>
- Mean Reversion Method is quiet significant in Financial Terms.Mean reversion is a financial term for the assumption that an asset's price will tend
to converge to the average price over time.
- Using mean reversion as a timing strategy involves both the identification of the trading range for a security and the computation of the average
price using quantitative methods.
- Calculating the Mean Reversion Returns from Consecutive Thrusday (Weekly Expiry)-
Every Thursday Initiating Delta Neutral Strategy, so Mean Reversion Returns gives insight regarding the volatality in Markets.
Thumb Rule- Lower the Mean Reversion Returns, Higher the changes of NIFTY 50 being in Predicted Probable Range,resulting in low volatality and High
Probablity of making Profit.
</xmp>
<h2>Directional/Momentum Strategies: <button><a target="blank" style="background-color:green; border:none; font-size: 15px; padding: 12px 12px;margin: -8px -8px; color:white;display: inline-block" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/momentum_strategies.html" title="">Momentum Strategies</a></button></h2>
<xmp>
Momentum trading is a strategy that involves taking advantage of price volatility and strong moves in prices by buying in an uptrend and selling when
that trend loses momentum.
</xmp>
<h2>Probability Distribution:<button><a target="blank" style="background-color:green; border:none; font-size: 15px; padding: 12px 12px;margin: -8px -8px; color:white;display: inline-block" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/probab_distribution.html" title="">Probability Distribution</a></button></h2>
<xmp>
- Probability distributions are often used in risk management as well to evaluate the probability and amount of losses that an investment portfolio
would incur based on a distribution of historical returns. One popular risk management metric used in investing is value-at-risk (VaR)
</xmp>
<h2>Pair Trading: <button><a target="blank" style="background-color:green; border:none; font-size: 15px; padding: 12px 12px;margin: -8px -8px; color:white;display: inline-block" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/pair_trading.html" title="">Pair Trading</a></button></h2>
<p style="text-indent:30px"> A pairs trade is a trading strategy that involves matching a long position with a short position in two stocks with a high correlation.</p>
<h2>Max Pain Theory: <button><a target="blank" style="background-color:green; border:none; font-size: 15px; padding: 12px 12px;margin: -8px -8px; color:white;display: inline-block" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/max_pain.html" title="">Max Pain</a></button></h2>
<p style="text-indent:30px">Max pain, or the max pain price, is the strike price with the most open options contracts (i.e., puts and calls), and it is the price at which the stock would cause financial losses for the largest number of option holders at expiration.
The term max pain stems from the maximum pain theory, which states that most traders who buy and hold options contracts until expiration will lose money.
</p>
<h2>ML Models : <button><a target="blank" style="background-color:green; border:none; font-size: 15px; padding: 12px 12px;margin: -8px -8px; color:white;display: inline-block" href="https://divyankm.github.io/Stock-Exchange-Data-Analysis/frontend_html_files/ml_models.html" title="">ML Models</a></button></h2>
<p style="text-indent:30px">
<ul> <li>Machine learning is a branch of artificial intelligence that uses statistical models to make predictions.</li>
<li>In finance, machine learning algorithms are used to detect fraud, automate trading activities, and provide financial advisory services to investors.</li>
<li>Machine learning can analyze millions of data sets within a short time to improve the outcomes without being explicitly programmed.</li>
</ul>
</p>
<p>Last updated on <b>8-Jan-2023:</b></p>
<xmp>
- Calender Spread Strategy went live with Alerting and Vizualizations.Currently 20 F&O Scripts are being tested in real markets based on liquidity.
- Delta Neutral Option Strategies is being executed on Weekly basis based on Market conditions and results are presented in DN option strategy module.
- Dashboards preparation WIP in Grafana for all use cases,Alerting module will be configured later.
- Momentum Strategies module is in WIP,will add more strategies in this module.Backtesting module is in WIP.
i) ATR-TS ETF ii)USD/INR FUT is implemented in live markets,results will be shared soon !!!
- Analysis of Option Chain and in WIP along with dedicated ETL pipelines for data storage and Dashboard building.ML Model can be built on Top of it.
- Calculation of Statistical parameters based on Historical Volatality,Analysis,Storage,Vizualizations completed.Parameters are ready,Design of Data
Wareshousing in WIP.
- Discount Cash Flow(DCF) & Reverse DCF sample code implemented,ETL(Wiring,Storage,Analysis,Vizualization) in WIP.
- ML Algo work on HOLD.Pair Trading automation is in WIP
- BackTesting Module newly added and currently in WIP.
</xmp>
<p><b>Project Timeline:</b></p>
<xmp>
- As this project is under WIP and timeline of completion cannot be provided (it's depending on Backtesting results on Real Time
Data,along with validation of Results in real market), Feel free to connect with me regarding any queries,contributions,corrections
are always welcome!!! 😃
- If any queries do raise PR on this repo in github for any correction/clarification,will be happy to correct/help/solve queries.
Timeline to go Live with Viz/Dashboard/Alerting to be accessible to everyone cannot be given right now.It's still in premature stage.
- Working on Frontend Development for first time,not my core skills,trying to improve UI of webpage during every update.If anyone want's
to improve GUI for webpages, html pages are present in git repo.
</xmp>
</body>
</html>
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