Stock Exchange Data Analysis

"Domain Knowledge: Fundamental+Technical+Research Analyst | Algorithmic Trading & Value Investing Expertise"

"Technical Knowledge: Data (Analyst+Architect+Engineer+Scientist) | BI Developer | Dev-Ops"

  • BackTesting
  • Calender Spread
  • DCF Module
  • Max Pain
  • ML Models
  • Momentum Strategies
  • Option Strategy
  • Probablity Distribution
  • Pair Trading
  • Welcome to SEDA Web page!!!

    👨‍💻 This is Basic version of webpage,more improvement with more modules will be coming overtime !!!, Currently WIP👨‍💻

    Coding Language- Python

    Library- Plotly | KATS | stats model | Pandas | Yahoo Fin.

    Topics Covered-Data Science | Statistics | Machine Learning

    Database- mySQL | OpenSearch

    Vizualization and Alerting Tool- OpenSearch Dashboards | Grafana

    Orchestration Tool-Docker Container(Docker Compose)

    Data Pipelines-ETL Python Scripts

    Current OS-Windows 10 Pro. (Fut Scope- VM(Linux))

    CICD- Not on cards till dev env working in local machine(Win. OS)

    BackTesting:

    Calender Spreads:

    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.

    DCF & Reverse DCF:

    Discounted cash flow (DCF) valuation is a type of financial model that determines whether an investment is worthwhile based on future cash flows

    Delta Neutral Option Strategies:

    - 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.

    Directional/Momentum Strategies:

    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.

    Probability Distribution:

    - 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)

    Pair Trading:

    A pairs trade is a trading strategy that involves matching a long position with a short position in two stocks with a high correlation.

    Max Pain Theory:

    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.

    ML Models :

    Last updated on 8-Jan-2023:

    - 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.

    Project Timeline:

    - 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.

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