How to calculate volatility based on the expected return of a straddle strategy has been shown in part 1 of fair bet volatility KVOL. Using and Displaying K-Volatility: KVOL uses the given amount of historic returns to calculate an expected value of an at the money put and call option. The sum of these prices are… Continue reading KVOL Volatility part 2
Year: 2018
Statistics of VIX
This article is about the statistics of VIX. What determines if it is better to sell or to buy volatility. Some simple statistics can provide the answer and also show the dangers of this kind of volatility trade.
Kahler’s fair bet volatility
Volatility is a measure of risk. It describes how far a commodity will most probably move within a given period of time. The most common measure for volatility is historical volatility. But I do not like the complicated formula for standard deviation. There has to be a better way to explain and calculate volatility…. Implied… Continue reading Kahler’s fair bet volatility
A graphical approach to indicator testing
Scatter charts are a great tool to test the prognosis quality of your indicators. A visual approach on indicator quality can help you to get rid of curve fitting when using classical or machine learning trading strategies.
Machine learning: kNN algorithm explained
Can inspiration be replaced by brute force? This article shows how to program and possibly use a simple kNN algorithm to trade Brent. A two dimensional data set will be used. RSI will determine if tomorrows market will move up or down.
Using Autocorrelation for phase detection
Autocorrelation is the correlation of the market with a delayed copy of itself. Usually calculated for a one day time-shift, it is a valuable indicator of the trendiness of the market. If today is up and tomorrow is also up this would constitute a positive autocorrelation. If tomorrows market move is always in the opposite… Continue reading Using Autocorrelation for phase detection
Measuring your EDGE in algorithmic trading
There are a lot of statistics which can be used to describe algorithmic trading strategies returns. Risk reward ratio, profit factor, Sharpe ratio, standard deviation of returns… These are great statistics, but they miss an important factor: Are your returns statistically significant or just a collection of lucky noise. The EDGE statistic might me the… Continue reading Measuring your EDGE in algorithmic trading
Ranking: percent performance and volatility
When ranking a market analysts usually pick the percent performance since a given date as their key figure. If a stock has been at 100 last year and trades at 150 today, percent performance would show you a 50% gain (A). If another stock would only give a 30% gain (B), most people now would… Continue reading Ranking: percent performance and volatility