The update for this week shows little difference in performance between my investment strategy, ParaTopia, and the OMX 30 benchmark.  The communication stocks ERIC-B.ST, TELE2-B.ST, and TELIA.ST seem to burden the performance. Meanwhile SINCH.ST remains an evident winner.  

A lot of developments have been made since I first started to open the black box  and shared my investment strategy with you in as in  A few simple rows . Also, as promised, I will today show you the details of my most recent strategy. Namely, the Dolvol + Mom (Dynamic) strategy from Let’s turn the GAS on .  A lot of the things that I show here today are already included in old posts. And for any frequent readers, that may seem a bit repeating. However, since I want everything that I do here to be as open and accessible as possible, I have decided to compile all my most up-to-date work here in one place.  Starting with the method, my investment strategy uses a combination of the parametric portfolio policy  and a generalized autoregressive score  (GAS) model to decide which stocks within the OMX Stockholm 30 Index  to invest in each month.  In essence, I model the asset weights of each stock each month as where 1/N stands for equally weighted benc...

It’s time to present a new alteration of my investment strategy. In doing so, I take use of a model that I have been aiming to include ever since the very start of this project. Namely, the generalized autoregressive sore model, or GAS.  The idea is to use GAS in combination with the parametric portfolio policy  and thereby obtain more dynamic or time-varying values of theta to determine the asset weights. I will soon show you how to do so in practice, and I will also show that this yields good potential for higher returns. But first and foremost, here follows some more theoretical details concerning GAS. I. Generalized Autoregressive Score (GAS) In short, I use GAS for modelling dynamic variables (i.e., dynamic values of theta) via functions of lagged and predetermined variables. This is probably best expressed in the equation below. Omega (ω) stands for the long run or unconditional mean. Hence, this is the value that theta is supposed to converge towards in the long run. B...

As displayed by the cumulative return of ParaTopia, vs. OMX Stockholm 30 index , my investment strategy continues with its competitive voyage also this week.  However, what is notable when looking at the returns of the second graph, is that the distance between ParaTopia and the benchmark is alarming close (only 0.3 ppt.).  Meaning, that the beef is far from settled until next week’s update. 

 My latest update since This is what I buy in November shows two positive trends. First, both my strategy, ParaTopia, and my nemesis benchmark, OMX Stockholm 30 , have continued to gain green figures. Meaning, that I’m no longer losing money.   Second, for the very first time since I started this project, I have managed to obtain a higher return (ParaTopia = 11.4%) than the market (^OMX = 9.7%). Yes, that is true, I have finally beaten the market (at least for a week or so), and I’m eager to see how this is to develop further. 

This month’s buy continues to come with a lot of SINCH.ST but surprisingly less of ABB.ST. Below, you will see the allocation of stocks which are planned to enter the market on Monday, 7 Nov 2022.  I am still waiting for the day when I can welcome AZN.ST and EVO.ST to my portfolio, but it seems like my model would like me to keep waiting a bit longer.   Recently, I have been wondering if it’s a weakness to only include the asset factor dolvol  for determining my portfolio weights. Might it be that the past trading volume is a bit too homogeneous over the different stocks? Hence, resulting in my strategy always choosing “kind of” the same assets?  I plan to explore this potential issue more soon. Or, at least, I’m working with an alteration to my investment strategy that could potentially behave a bit more dynamically over month-by-month.