How to Create a Function that Fetches Market Sentiment Data.
Market sentiment is an extremely important part of trading. It allows us to understand the positioning of the players who potentially could move the markets. Knowing that the majority of hedge funds are bullish on an asset gives us more confidence to invest in it. Similarly, knowing that almost all of the hedge funds are bullish on an asset could give us a signal that the market may be overly bullish and that it is wiser to wait before investing or even be brave enough to initiate a contrarian position in case the fundamentals start to justify it.
In this…
Presenting a New Idea of Using the Fibonacci Sequence in the RSI.
The Relative Strength Index is a well known contrarian indicator that can be used to find oversold and overbought levels. The Fibonacci sequence also has its place in the world of trading. What if we try combining these two elements together? It is worth investigating. Spoiler alert, the results show more value in discretionary trading than in systematic trading.
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The Relative Strength Index
The RSI is without a doubt the most famous momentum indicator out there, and this is to be…
How to Import OHLC Data from MetaTrader5 to Python for Analysis.
In research, we need the idea generation phase to have enough time to deliver good results and this cannot be done if we have a long process of transforming the ideas into visible results. One thing we can do is automating the import of historical data and this precisely the point of this article. By creating a few simple functions, we will be able to call thousands of OHLC data almost immediately. For this, we need to download a library which is described below.
If you are also interested by technical indicators and using Python to create strategies, then my…
Coding and Trading the Reversion to Equilibrium in Python.
Markets swing between extremes and move in cyclical phases. Sometimes, they are a bit overbought due to a superior optimistic feeling and other times they are oversold due to looming fear. The self-similarity and fractal natures of the financial markets tell us that this goes for all the time frames. In this article, we will see how to profit from fading extreme moves using the Equilibrium method.
If you are interested by market sentiment and how to model the sentiment of institutional traders, feel free to have a look at the below article:
The Concept of Moving Averages
Moving averages help us confirm and ride…
Creating an Indicator that Uses Percentiles to Derive Trading Signals. A Python Back-test.
Statistical concepts are always present in trading whether in risk management or in strategy elaboration. Percentiles form one of the pillars of descriptive statistics, but are they helpful in trading? This article will discuss the use of percentiles to generate trades.
If you are interested by market sentiment and how to model the sentiment of institutional traders, feel free to have a look at the below article:
The Concept of Percentiles
A percentile is simply a threshold where a certain percentage of value lies beneath the current value. Here is a more detailed example:
- If your score in the CFA level II exam is…
Coding & Back-testing the Envelopes as a Trading Strategy.
The concept that something is overbought or oversold is very known in Technical Analysis and yet it does not seem to always deliver something positive even though there are many good and stable strategies that deliver above average returns as we have seen in previous articles. This article will present the Envelopes Indicator and see how to create a trading system that uses it to generate trades.
If you are interested by market sentiment and how to model the sentiment of institutional traders, feel free to have a look at the below article:
The Concept of Moving Averages
Moving averages help us confirm and ride…
Creating and Coding a Trend-Following Trading Strategy From Scratch.
Trend-following strategies are concerned with time in the market rather than market timing and they seek to find stable environements so that a position in the way of the trend becomes profitable as the market continues. In this article, the strategy discussed is a simple indicator created to measure the trend’s intensity. We will code it and then back-test it.
If you are interested by market sentiment and how to model the sentiment of institutional traders, feel free to have a look at the below article:
The Concept of Moving Averages
Moving averages help us confirm and ride the trend. They are the most known…
Coding and Back-testing the Famous %Bollinger Indicator in Python.
Statistical trading is a fairly complex field but has some concepts that we can easily understand. Volatility remains a main concept in finance and using it right can unlock the keys towards a robust trading model. Bollinger Bands can be considered one of the simplest yet most famous statistical method to analyse the market. Even though it belongs to the realm of Technical Analysis, we cannot deny its statistical heritage. In this article, we will present and code the Bollinger Bands and then transform them into a whole new Indicator which we will later back-test.
If you are interested by…
Coding William’s Ultimate Oscillator and Back-testing its Strategy.
Larry Williams developed an indicator that he called the Ultimate Oscillator which relies on a combination of buying pressure, true range, and moving averages. The idea of the indicator is to find oversold and overbought zones from where reactions are possible. In this indicator, we will code and back-test the Ultimate Oscillator and see whether it has some predictive power or not.
If you are interested by market sentiment and how to model the sentiment of institutional traders, feel free to have a look at the below article:
The Concept of Moving Averages
Moving averages help us confirm and ride the trend. They are the…
Creating and Coding a Contrarian Trading Strategy From Scratch.
Contrarian strategies are concerned with market timing and they seek to find extreme environements so that a position in the other way becomes profitable as the market corrects. In this article, the strategy discussed is a simple one based on a differencing method of one famous momentum indicator called the Relative Strength Index of which we have discussed many times in previous articles. We will then back-test the strategy and see how to optimize it.
If you are interested by market sentiment and how to model the sentiment of institutional traders, feel free to have a look at the below…
