Pooja Jaiswal
Technical indicators are mathematically derived representations of price, and volume, to detect price movement of a security. Learn trading strategies using technical indicators and backtest your ideas on historical data.
This blog, explains the VWAP and also how to calculate it. Along the way, we will also compare it with another simple indicator, i.e. the moving average and understand its advantages and disadvantages, We will see if we can create an intraday trading strategy using VWAP.
Price action is a trading methodology *that has been around for ages and is very popular among the ever-growing trading community. *Retail & Institutional traders often use price action trading strategies to predict & analyze price movements of financial assets in short term
Explore trading with the help of TRIN and its applications. This article will give you thorough information about this oscillator.
Future price movements are indicated by TRIN since it generates overbought and oversold levels to find out when the price index may change direction. Based on the value of TRIN, a trader can find out if there is an upward or downward trend in the market and can make decisions to trade accordingly.
Python Seaborn package is used to create heatmaps to visualize price changes, inspect correlation among stocks, and select features. This robust guide is your perfect companion.
Key Details
In this blog, we will learn what bots are and how they can skew the sentiment analysis used in your trading strategy, along with a strategy to identify bots.
We will cover the following topics:
This blog is a step-by-step guide about how one can use NLP or Natural Language Processing in Trading.
A robust read about the Fama-French 5 factor model and its applications, as well as the drawbacks and improvements of the Fama-French five-factor model.
Stock market data - Explained with this powerful tutorial with Python codes. Learn where to get stock market data and download stock market data as a csv file, how to fetch stock fundamental data, and how to plot, visualise and how to use python for stock analysis.
Learn step-by-step on how to calculate VaR in Excel and Python using Historical Method and Variance-Covariance approach. Downloadable files for Value at Risk (VaR) calculation are available.
Through this blog, learn how to calculate the covariance matrix and analyse the portfolio variance.
We will focus on trading and how to use decision trees to find trading rules that allow us to gain an edge in the market.
Broken Wing Butterfly is the same as a Butterfly Spread wherein the sold spread is typically wider spread than the purchased spread. Read all about it here.
Learn all about Deep Learning, Models, Applications in finance and Future. Get a general overview of Deep Learning and its use in finance.
A guide about Gold price using prediction using machine learning in Python. Learn about defining the variables to create a linear regression model, and eventually predicting the Gold ETF prices.
Import the libraries and read the Gold ETF data
Define explanatory variables
Define dependent variable
Split the data into train and test dataset
Create a linear regression model
Predict the Gold ETF prices
Plotting cumulative returns
How to use this model to predict daily moves?
Zipline Python library is used for trading applications. This blog talks about how to install zipline python, its benefits, and using it to code the moving crossover strategy for financial trade.
In this article, we discuss Random Forest Algorithm in Python, how do they work, and how they help in overcoming the limitations of decision trees using Python.
Grasp the knowledge of using Python for trading through this article. Learn more about its benefits and strategies used in the stock market.
In this blog post, learn how to implement the Johansen Cointegration Test in Python.
Moving average is one of the most widely used technical indicators for creating the trading strategy. Explore the popular moving averages and the moving average trading strategies with this blog!
Algorithmic trading in India has amalgamated finance with cutting-edge technologies and is benefiting from developing regulations and a growing economy. This blog chronicles the past, present and future of algo trading in India and a lot more.
In this blogpost, you will understand the essence of the Johansen Cointegration Test and learn how to implement it in Python.
Autocorrelation and Autocovariance are essential in the time series analysis topic! This tutorial will guide you on their definitions, their computations and plotting using Python and R. Read now!
Autocorrelation and Autocovariance are essential in the time series analysis topic! This tutorial will guide you on their definitions, their computations and plotting using Python and R. Read now!
Not dealing with overnight risk is one of the most important benefits of day trading. Day trader avoids the overnight risk by closing the positions at the en...
Although day trading is a highly profitable way of trading the capital market, one can't generalise the returns expected. The results expected not only depends on the type of trading strategy (momentum, mean reversion, scalping etc.,) it also depends on factors such as position sizing, and risk management.
A day trading strategy with appropriate risk management along with pre-planned position sizing would have higher chances of beating the market and generating consistent returns.
