Quant Mashup - Philipp Kahler

A Neural Network based trading strategy [Philipp Kahler]

I always dreamed about the machine which tells me to enter long right before the market starts to go up. Might a neural network be this machine? Using Tradesignal and the free Python Neural Net library Pyrenn it is easy to find out… Part one: Classification of data The first step in the process is

*- 4 weeks ago, 18 Aug 2020, 08:40pm -*

A Simple Neural Network for Indicator Prognosis [Philipp Kahler]

Technical indicators are the base of algorithmic trading. So wouldn’t it be nice to know tomorrows indicator value in advance? This article is about how to use a simple neural network to do so. Python and Tradesignal will be used to do the programming. A single linear neuron A single neuron /

*- 1 month ago, 21 Jul 2020, 11:16pm -*

Overnight Risk Premium in Equity and Commodity Markets [Philipp Kahler]

Over the last 20 years equity markets and ETFs did a significant part of their total performance over night. This article will examine the relationship of in-session moves vs. the out-of-session moves of ETFs and commodities. The overnight risk premium As an investor you can expect to get paid for

*- 4 months ago, 28 Apr 2020, 10:46am -*

Python Regression Analysis: Drivers of German Power Prices [Philipp Kahler]

German Power prices can be explained by supply and demand, but also by causal correlations to underlying energy future prices. A properly weighted basket of gas, coal and emissions should therefore be able to resemble the moves of the power price. This article will introduce multivariate regression

*- 7 months ago, 10 Feb 2020, 09:54am -*

RSI Hellfire Heatmap Indicator [Philipp Kahler]

Chart analysis is all about visualizing data. The RSI hellfire indicator uses a heat-map to visualizes how overbought or oversold the market is on a broad scale. This helps to get a broad picture of the current market setup. Multiple Time-frame Relative Strength Index Wells Wilder’s RSI is an old

*- 9 months ago, 1 Dec 2019, 06:07pm -*

How to avoid unwanted curve fitting during backtest [Philipp Kahler]

Whenever you develop an algorithmic trading strategy, curve fitting is one of the most dangerous hazards. It will lead to severe losses in real time trading. This article will show you some ways to detect if the performance of your algorithmic trading strategy is based on curve fitting. Curve

*- 10 months ago, 14 Nov 2019, 08:07pm -*

The Edge of an Entry Signal [Philipp Kahler]

When developing a new trading strategy you are usually confronted with multiple tasks: Design the entry, design the exit and design position sizing and overall risk control. This article is about how you can test the edge of your entry signal before thinking about your exit strategy. The results of

*- 10 months ago, 28 Oct 2019, 09:13am -*

A simple algorithm to detect complex chart patterns [Philipp Kahler]

Finding complex chart patterns has never been an easy task. This article will give you a simple indicator for complex chart pattern recognition. You will have the freedom to detect any pattern with any pattern length. Not just 2-bar candlestick formations, but complex stuff like V-Tops spread over

*- 11 months ago, 19 Sep 2019, 09:25am -*

The Probability of Normality [Philipp Kahler]

As an option seller you want the market to stay within the range prognosticated by implied volatility. But what is the historic probability that markets behave as expected? And what other analysis could be done to enhance your chances and find the periods when it is wise to sell an at the money

*- 1 year ago, 9 Aug 2019, 10:30am -*

Bitcoin Swing Trading [Philipp Kahler]

I published a bitcoin swing trading strategy in 2015 over here (German only). Time to review the methodology of swing trading and have a look on the performance. Can a rational strategy get an edge in an irrational market? Have a look and be surprised! Swing Point Trading Technique Swing trading is

*- 1 year ago, 1 Jul 2019, 07:40am -*

The Edge of Technical Indicators [Philipp Kahler]

Classical technical indicators like RSI and Stochastic are commonly used to build algorithmic trading strategies. But do these indicators really give you an edge in your market? Are they able to define the times when you want to be invested? This article will show you a way to quantify and compare

*- 1 year ago, 12 May 2019, 10:58am -*

Daily Extremes - Significance of time [Philipp Kahler]

Analysing at which time daily market extremes are established shows the significance of the first and last hours of market action. See how different markets show different behaviour and see what can be learned from this analysis. Probability of Extremes A day of trading usually starts with a lot of

*- 1 year ago, 18 Apr 2019, 10:48am -*

S&P500 - when to be invested [Philipp Kahler]

S&P500 – when to be invested The stock market shows some astonishingly stable date based patterns. Using a performance heat map of the S&P500 index, these patterns are easily found. Date based performance The chart below shows the profit factor of a long only strategy investing in the

*- 1 year ago, 9 Apr 2019, 02:18pm -*

Noisy Data strategy testing [Philipp Kahler]

Algorithmic trading adds noise to the markets we have known. So why not add some noise to your historic market data? This way you can check if your algorithmic trading strategies are fit for the future. Learn how to generate noisy data and how to test your strategies for stability in a noisy market.

*- 1 year ago, 30 Mar 2019, 08:53am -*

Monte Carlo Simulation of strategy returns [Philipp Kahler]

Monte Carlo Simulation uses the historic returns of your trading strategy to generate scenarios for future strategy returns. It provides a visual approach to volatility and can overcome limitations of other statistical methods. Monte Carlo Simulation Monte Carlo is the synonymous for a random

*- 1 year ago, 19 Mar 2019, 09:40am -*