By: Andreas Procopos In life there is a natural process of things. There is the famous circle of life, a system of predators and prey competing in the animal kingdom. We humans however prefer a different circle of life, a process that is competitive in more complicated ways. A general example of this process would […]
By Jacques Joubert “Since I was a child, I have always loved a good story. I believed the stories helped us to ennoble ourselves – to fix what was broken in us and to help us to become the people we dreamed of being, lies that told a deeper truth.” (Westworld, 2016) One such story […]
Risk is not a simple entity, it comes in many flavours, and requires respect and consideration even when you least expect. If one was to try ‘totally avoid’ risk in their market endeavours they would most likely just be holding cash – where are the returns in that?
The truth is that in almost all circumstances one must take at least some form of risk to have the chance of potentially generating returns. Let’s face it, you’ve got to crack some eggs to make an omelette!
Those, including myself, who have experienced first hand what it is like to feel the full effects of taking on too much risk, will most likely find it a life changing experience. You will either withdraw your remaining investments and consider other ventures, or you will revisit your mistakes with single goal; of never ending up in a similar situation again. Read more
By: Marco Simioni
In the first section, this article describes a Dual Momentum study over an iShares country etfs basket with a new attempt to improve this well-known investing style. I chose iShares because it is the world largest family of Exchange Traded Funds (ETFs) from BlackRock. Although different stock markets correlations have become weaker and weaker in these last 10 years, this article easily shows that countries diversification is still feasible.
In the second part, I briefly recall another Dual Momentum Portfolio, the Famous 5 Portfolio, and apply to momentum concept to the two portfolios. This results in a new comprehensive strategy that rotate monthly from Countries Portfolio to the Famous 5 Portfolio or viceversa.
My backtest, highlight that momentum persists not only through single different assets (etfs) but through portfolios as well.
In this article I show that very basic quantitative trading strategies that generate returns from different market behaviours, when combined, can provide a more desirable and stable returns stream, as reflected in a Sharpe ratio higher than any individual strategy. We show how absolute returns can be some-what ‘sacrificed’ for an improved risk adjusted return stream, which then can be later leveraged as per the investors risk appetite. Read more
For the last 6 months I have been focused on the process of building the full technology stack of an automated trading system. I have come across many challenges and learnt a great deal about the two different methods of backtesting (Vectorised and Event driven). In my journey to building an event driven backtester, it came to my surprise that what you would end up with is close to the full technology stack needed to build a strategy, backtest it, and run live execution.
My biggest problem when tackling the problem was a lack of knowledge. I looked in many places for an introduction to building the technology or a blog that would guide me. I did find a few resources that I am going to share with you today. Read more
In a situation where you wish to determine the returns on an investment, one may have all the expertise to do this but without certain information (missing pieces) it would not be possible to derive to a conclusive figure. In practical terms “assume you have the value of all returns of all assets in your portfolio; without the rate at which each asset produces the returns we will not have a true reflection of the portfolio returns at a specific point in time as such we may not provide accurate returns estimate.” A process termed the Hidden Markov model may be used to shed some light in this problem.
The process is split into two components: an observable component and an unobservable or ‘hidden’ component (van Handel, 2008). Nevertheless, from the observable process we can extract information about the “hidden” processes. As such our task is to determine the unobserved process from the observed one. Read more
Large institutions deal with immense amounts of currencies which enter and leave their accounts on a daily bases. Furthermore they have their own funds that it has to efficiently allocate so as to maximize their return on investment but also wish to hedge against adverse events. With a certain confidence the entities (particularly commercial institutions) should be conscious of their profits and also know how much they stand to lose. With requirements stipulating certain amounts to be kept for times of need, introduction of capital buffers which should build up in prosperous times (SARB, 2015) as well as other regulatory matters institutions have increased the need to know how much they posses and the risks they are exposed to.
In recent years the trading accounts at large commercial banks have grown substantially and become progressively more diverse and complex (Jorion, 2001). To manage market risks, major trading institutions have developed large scale risk measurement models. While approaches may differ, all such models measure and aggregate market risks in current positions at a highly detailed level. Read more
Within the Monte Carlo realm a vast number of applications exist. In this final part I bring together all the previous work as well as put into practice the theory we have gathered so far.
Applying the Metropolis-Hastings Algorithm
From the previous section we deduced a way in which we can generate a sample using arbitrary factors which combined produce a fairly accurate representation of reality
For absolute simplicity we will consider only one variable in which we wish to model, but this process is applicable to combinations of assets or derivatives of those assets with minimal adjustments. Here we make use of Dynamic asset pricing to estimate equilibrium as well as exploit arbitrage opportunities with the theory of mean reversion being the basis of our strategy. I will neglect the actual computation to give an intuitive understanding of the usage of the theory developed here: Read more
Markov Chains, Central Limit Theorem and the Metropolis-Hastings
In the previous article I gave a generic overview of Monte Carlo as well as introduced importance sampling. We now dive deeper by giving strict definitions of some of the widely used and yet misunderstood or rather commonly neglected concepts due to its perceived importance. There after we explore the Metropolis-Hastings algorithm which form a foundation of numerous Markov Chain Monte Carlo methods. Read more