We begin 2018 with so much to look forward to. With definitely the best yet to come, let’s take a look at what was fabulous in the year 2017. Here’s a collation of our ten most popularly read blogs from last year. Offering a summary of the trending topics from last year which is followed by a category-wise collection of the best reads from last year.
Best 10 Blogs
1. Machine Learning For Trading — How To Predict Stock Prices Using Regression?
This blog summarises why has Machine Learning become such a buzz word lately. The author gives you different scenarios where a computer programme comes across as a more befitting resource than a human mind. Machine Learning is being employed for long. In 1763, Thomas Bayes published a work ‘An Essay towards solving a Problem in the Doctrine of Chances’ which lead to ‘Bayes Rule’, one of the important algorithms used in Machine Learning. Today applications of Machine Learning are everywhere, this blog elaborates on the implementation of strategies like Linear Regression.
2. Machine Learning Classification Strategy In Python
This blog is a step by step guide on how to implement machine learning classification algorithm on S&P500 using Support Vector Classifier (SVC). SVCs are supervised learning classification models. The article will take you through the linear process of implementing the machine learning classification strategy in Python, which begins from importing the libraries, to fetching data and determining the target variable. The next step is the creation of variables to test and train dataset split and create the machine learning classification model using the train dataset.
3. Top Algo Trading Platforms in India
The advent of algorithmic trading has rewritten the rules of traditional broking. With significant volumes on the exchanges now being traded with the help of sophisticated algorithms, it is imperative that traders should be fully aware of the trading platforms that would enable them to implement their strategies and remain competitive. This write-up makes note of the top trading platforms and tools: Omnesys NEST, Presto ATS, ODIN, FLEXTRADE, AlgoNomics, MetaTrader, AmiBroker, NinjaTrader.
4. Top 9 Cryptocurrency Trading Platforms
The article covers 9 Best Cryptocurrency Exchanges: eToro, Kraken, Poloniex, BitFinex, HitBTC, Bittrex, BitMEX, Coinbase and Localbitcoins. Cryptocurrency trading has gained substantial popularity owing to many logical aspects. The concept of Cryptocurrency is based on knowledge-sharing on a distributed platform. The entire transaction is for everyone to see. The data entered cannot be altered, nor can it be removed, enabling a system of complete transparency and trust. The entire money flow for the working model is beyond the traditional practices and hence the rising interest in the subject. Read on to know how to be a part of the bandwagon.
5. Algorithmic Trading Strategies, Paradigms and Modelling Ideas
After having learnt the basics of Algo Trading, acquiring the knowledge of trading strategies is the secondary level of education. An algorithm is just a set of instructions or rules. These set of rules are then used on a stock exchange to automate the execution of orders without human intervention. This concept is called Algorithmic Trading. The article further elaborates on some of the trading strategies.
6. Top Courses after MBA Finance
Even after the dramatic shift in the technological sphere, finance jobs are as much in-demand as roles in technology sector or other domains. MBA graduates in Finance are proving that they can make a difference as leaders in many different industries. This article lists top courses after MBA finance that students can take up to enhance their finance career.
7. Build Technical Indicators in Python
Technical Indicator is essentially a mathematical representation based on data sets such as price (high, low, open, close, etc.) or volume of a security to forecast price trends. There are several kinds of technical indicators that are used to analyze and detect the direction of movement of the price. This blog shall take you through a thorough description of the various indicators like EVM, Moving Average (MA), Rate of Change (ROC), Bollinger Bands, Force Index. Traders use them to study the short-term price movement since they do not prove very useful for long-term investors, read the full article to learn how to utilize the same for your own trades.
8. Learn Algorithmic Trading: A Step by Step Guide
With the boom in technological advancements in trading and financial market applications, algorithmic trading and high-frequency trading is being welcomed and accepted by exchanges all over the world. Within a decade, it is sure to be the most common way of trading in the developed markets. This article shall help you learn how to utilize algorithmics to trade markets profitably.
9. Forecasting Markets using eXtreme Gradient Boosting (XGBoost)
Numerous machine learning models like Linear/Logistic regression, Support Vector Machines, Neural Networks, Tree-based models etc. are being tried and applied in an attempt to analyze and forecast the markets. Researchers have found that some models have more success rate compared to other machine learning models. eXtreme Gradient Boosting also called XGBoost is one such machine learning model that has received rave from the machine learning practitioners. In this post, we covered the basics of XGBoost, a winning model for many kaggle competitions and attempted to develop an XGBoost stock forecasting model using the “xgboost” package in R programming.
10. Essential Books on Algorithmic Trading
A good starting point for an aspiring trader would be to pick up a good book, immerse oneself, and absorb all that the book has to offer. This post pens down core focus areas for aspiring quants and covers some of the good reads in each of those categories. The post also shares a comprehensive list of books considered must-reads for aspiring algo-traders.