Quantitative Finance & Algo Trading Blog by QuantInsti

Author: Chainika Thakar In the fast-paced world of finance, where markets ebb and flow with the speed of information, proprietary trading stands as a dynamic and influential force. Proprietary trading, the practice of trading financial assets using a firm's own capital, has witnessed significant evolution, driven by regulatory changes, market trends, and the pursuit of profit. This evolution has …

In this EPAT project, Shant Tondon builds a statistical arbitrage strategy using cointegrated stock pairs in the Indian equity market. The study uses walk-forward backtesting, z-score mean reversion, transaction cost modelling, and portfolio-level risk analysis.

In the dynamic world of trading, understanding the language of the markets is imperative and that includes the most valuable skills of the ability to read and interpret candlestick patterns. Among these, bearish candlestick patterns stand out as crucial indicators of potential price declines. In this all-encompassing guide, we embark on an enlightening journey through the world of bearish candles…

By QuantInsti Options Trading is much popular today compared to the yesteryears, and this has led to the creation of various types of Options trading strategies. New to options? Start with options trading basics to get comfortable with calls, puts, and spreads before exploring the Broken Wing Butterfly. Some have stayed, some have evolved, while some might have ceased to exist. Butterfly options …

By QuantInsti Newer technologies, better software, improvements in connectivity, etc. happening at a tremendous pace has led to a boom in the way knowledge is shared and accessed. Trading has always maintained the front seat position for primary advantage and the same goes for trading strategies. Every trading strategy can't give you the same outcome, and it is also true that neither can assure c…

Author: Chainika Thakar In the dynamic world of finance, where opportunities and risks intertwine, options have emerged as a versatile tool for traders seeking to navigate the market with precision. For traders new to options, a strong grasp of options trading basics will make it much easier to follow the concepts covered in this straddle strategy guide. Among the myriad strategies available, the…

By QuantInsti Traders dealing in options enjoy the leverage of choosing the size of investment that they make and reducing the risk of losing a lot in the trading process. Options are believed to be cost-efficient and less risky in comparison to a lot of other instruments in the market. What I like the most about Options trading is that there are numerous strategies that one can practice and foll…

Author: Chainika Thakar Navigate the intriguing landscape of options trading with a specific focus on covered calls – a potent tool in the hands of traders. Options trading can be perceived as a complex concept, often deterring newcomers from delving deeper. However, with the right knowledge the concept will be much simpler to understand. In this blog, you will learn the fundamentals of covered c…

By QuantInsti The current market environment is pretty challenging and there is a need to be clever in the way we invest and look for other opportunities. As a trader, one is always on the lookout for assets that can perform well in the markets and at the same time realise good profits. Sideways performing strategies provide a good opportunity for a trader to grab hold of. And if the trade is mod…

By QuantInsti We have previously come across the following strategies: - Iron Condor Trading Strategy is a combination of the Bull Put Spread and Bear Call Spread Options trading strategy - Butterfly Spread Trading Strategy is a combination of Bull Spread and Bear Spread, a Neutral Trading Strategy These Options Trading Strategies are a combination of both a Bull Spread and a Bear Spread. If spre…

Growing markets, regulatory approval, and an increasing number of algorithmic trading API, all have made trading markets using API a trend. Also, brokers have played a key role in making algorithmic trading accessible to retail traders and firms to a great extent. There are different ways in which one can trade markets. One method is using the trading API provided by the brokers. This blog covers…

By Manusha Rao Before you begin, go through Python Programming Fundamentals to build a solid base in core concepts like syntax, functions, and basic problem-solving. Next, set up your environment using Setting Up Your Python System, where you’ll learn how to install Python and get your workspace ready for coding smoothly. After that, move to Python Data Structures to understand how to work with l…

By Ishan Shah Success in the trading journey requires the trader to know the key concepts before starting trading and one of them is mastering the stock market data analysis. For conducting the data analysis, the trader first needs to fetch the data and visualise it for the “identification of historical price trends and patterns”. You must be wondering “What is the benefit of this identification”…

Author: Chainika Thakar (Originally written By Punit Nandi) Before be jump into the blog! Checkout our new video on Intraday Implied Volatility: What Python + Options Data Reveal. This video focuses on building that foundation by working directly with intraday options data using Python. We move beyond charts to show how minute-level Bank Nifty data is structured, cleaned, and prepared for analysi…

Practical introduction to AI in quantitative trading using Python, QuantConnect and AWS. Explore deployable strategies, research workflows, NLP signals and risk-aware models designed for newcomers entering applied quant trading.

Catch up on QuantInsti’s 2026 highlights: the launch of Agentic AI for Trading, the AI AlgoTrader Bootcamp, new EPAT curriculum and placement updates, an alumni meet-up in Singapore, academic sessions with SGX and leading campuses, plus key press coverage.

Explore machine learning for market regime detection using Random Forest and market breadth indicators. Identify bull, bear and volatility regimes and adjust capital allocation with Python.

By Chainika Thakar & Sushant Ratnaparkhi Artificial intelligence (AI) and machine learning (ML) are revolutionising our lives in numerous ways. From the tailored recommendations we receive on shopping sites to automating the trading domain, AI makes our daily routines more efficient and enjoyable. In trading, machine learning includes concepts like regression analysis, which can be used to predic…

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.

By Chainika Thakar and Rekhit Pachanekar Machine learning is the most ideal choice for not only the financial technology domain, which algorithmic trading is a part of, but also for other industries such as healthcare, retail, education, etc. Alan Turing, an English mathematician, computer scientist, logician, and cryptanalyst, surmised about machines that, “It would be like a pupil who had learn…