Financial X-Rays: Dissect any Price Series with a simple Payoff Diagram


Not many people understand the financial alchemy of modern financial investment vehicles, like hedge funds, that often use sophisticated trading strategies. But everybody understands the meaning of rising and falling markets. Why not simply translate one into the other?

If you want to get your hands on a simple R script that creates an easy-to-understand plot (a profit & loss profile or payoff diagram) out of any price series, read on!
Continue reading “Financial X-Rays: Dissect any Price Series with a simple Payoff Diagram”

Parrondo’s Paradox in Finance: Combine two Losing Investments into a Winner


Wikipedia defines Parrondo’s paradox in game theory as

A combination of losing strategies becomes a winning strategy.

If you want to learn more about this fascinating topic and see an application in finance, read on!
Continue reading “Parrondo’s Paradox in Finance: Combine two Losing Investments into a Winner”

How to be Successful! The Role of Risk-taking: A Simulation Study


When you ask successful people for their advice on how to become successful you will often hear that you have to take risks, often huge risks.

In this post we will examine whether this is good advice with a simple multi-agent simulation, so read on!
Continue reading “How to be Successful! The Role of Risk-taking: A Simulation Study”

Create Return Triangle Plots with R


How lucrative stocks are in the long run is not only dependent on the length of the investment period but even more on the actual date the investment starts and ends!

Return Triangle Plots are a great way to visualize this phenomenon. If you want to learn more about them and how to create them with R read on!
Continue reading “Create Return Triangle Plots with R”

How to Catch a Thief: Unmasking Madoff’s Ponzi Scheme with Benford’s Law

One of my starting points into quantitative finance was Bernie Madoff’s fund. Back then because Bernie was in desperate need of money to keep his Ponzi scheme running there existed several so-called feeder funds.

One of them happened to approach me to offer me a once-in-a-lifetime investment opportunity. Or so it seemed. Now, there is this old saying that when something seems too good to be true it probably is. If you want to learn what Benford’s law is and how to apply it to uncover fraud, read on!
Continue reading “How to Catch a Thief: Unmasking Madoff’s Ponzi Scheme with Benford’s Law”

Financial Engineering: Static Replication of any Payoff Function


In the area of options strategy trading, it has always been a dream of mine to have a universal tool that is able to replicate any payoff function statically by combining plain vanilla products like calls, puts, and zerobonds.

Many years ago there was such a tool online but it has long gone since and the domain is inactive. So, based on the old project paper from that website I decided to program it in R and make it available for free here!
Continue reading “Financial Engineering: Static Replication of any Payoff Function”

Kalman Filter as a Form of Bayesian Updating


The Kalman filter is a very powerful algorithm to optimally include uncertain information from a dynamically changing system to come up with the best educated guess about the current state of the system. Applications include (car) navigation and stock forecasting. If you want to understand how a Kalman filter works and build a toy example in R, read on!
Continue reading “Kalman Filter as a Form of Bayesian Updating”

Time Series Analysis: Forecasting Sales Data with Autoregressive (AR) Models


Forecasting the future has always been one of man’s biggest desires and many approaches have been tried over the centuries. In this post we will look at a simple statistical method for time series analysis, called AR for Autoregressive Model. We will use this method to predict future sales data and will rebuild it to get a deeper understanding of how this method works, so read on!
Continue reading “Time Series Analysis: Forecasting Sales Data with Autoregressive (AR) Models”

Learning Statistics: Randomness is a Strange Beast


Our intuition concerning randomness is, strangely enough, quite limited. While we expect it to behave in certain ways (which it doesn’t) it shows some regularities that have unexpected consequences. In a series of seemingly random posts, I will highlight some of those regularities as well as consequences. If you want to learn something about randomness’ strange behaviour and gain some intuition read on!
Continue reading “Learning Statistics: Randomness is a Strange Beast”