Portfolioupdate H1 2026
Portfolio Review - Transitioning to Systematic Quant Trading
At the beginning of the year, I transitioned from an equity factor investing approach to a broader quantitative trading framework. This represents a significant shift in both portfolio construction and execution, as the new approach relies on a diverse set of systematic strategies rather than a single investment style.
Because the individual strategies were developed and deployed at different points throughout the year, their live track records vary considerably. Many of them have only been running for a relatively short period, so it is important to keep this in mind when evaluating both the overall portfolio performance and the results of the individual strategies. The current performance reflects an ongoing implementation process rather than a mature, fully deployed portfolio.
The largest challenge and the biggest detractor from performance has been operational execution, or what Kris Longmore refers to as the “fourth hat”. Building profitable strategies is only one part of the job; implementing, monitoring and maintaining them reliably is an equally important skill. Whenever I make major changes to something like my trading infrastructure, I fuck up operational stuff, so this was an expected risk. For that reason, I deliberately chose not to deploy all available capital immediately. Instead, capital is being allocated gradually as confidence in the stability of the overall system increases.
The transition introduced too many moving parts at once, while leaving too little time to resolve every issue as it appeared. I wanted too much, too fast. As a result, operational inefficiencies created a significant drag on performance during the last few months. Fortunately, most of these problems have now been identified and addressed. While no trading operation is ever completely free of operational fuck ups, I estimate that roughly 80% of the major implementation issues have now been resolved, providing a much stronger foundation going forward.
Portfolio Performance
Unless stated otherwise, all performance figures are reported after costs but before German taxes and are denominated in euros. Since the portfolio includes assets traded in multiple currencies and I currently do not hedge FX exposure, currency movements can meaningfully influence the reported returns.
Over the past six months, the portfolio (excluding crypto) generated a return of 2.34% with a realized volatility of 6.52%. On an absolute basis, the return is clearly below my long-term expectations. However, it should be viewed in the context of an ongoing transition rather than as a representative result of the investment process.
The portfolio is still in its deployment phase, with strategies being introduced gradually and several key portfolio management components not yet fully implemented. Most notably, volatility targeting has not yet been activated. As a result, the portfolio has been operating well below its intended risk budget, limiting overall return.
Considering these circumstances, I view the performance as satisfactory. The portfolio has remained profitable while the majority of the operational issues have been resolved and the underlying infrastructure has become considerably more robust.
Strategies in my Portfolio
Presented below are my current trading strategies, listed in no particular order. The reported performance metrics reflect the results achieved using leveraged positions. Consequently, all reported returns, profits, and losses are expressed relative to my invested capital (equity) rather than the total notional market exposure.
#1 DYNVRP 1
This is the dynamic volatility risk premia harvesting strategy that I presented here.
Why Fear Is Mispriced — and How to Profit From It
For the vast majority of investors, market volatility represents one of the most psychologically challenging aspects of managing a portfolio. It is the force behind sudden, unsettling swings in asset prices. The kind that trigger anxious portfolio check-ins, impulsive decision-making and, for many, genuinely restless nights.
Return: 60.53%
Volatility: 45.51%
The strategy generated a cumulative return of 60.53%, demonstrating strong performance over the evaluation period. However, this return was accompanied by a relatively high level of risk, as reflected by an volatility of 45.51%.
#2 Undisclosed
I will reveal this strategy in a couple of weeks.
Return: 4.24%
Volatility: 21.15%
The strategy produced a cumulative return of 4.24% over the evaluation period while exhibiting volatility of 21.15%. The return generated was modest relative to the amount of risk assumed. It is the strategy that got hit most by my messed up operational stuff. What you see here is more of a beta-test with the goal of having a fully functional strategy in a couple of weeks.
#3 EOM
This is the End-of-Month strategy that I presented among other things here.
The Hidden Calendar Pattern in Bonds
In my first post on the End-of-Month (EOM) Effect, I explored the phenomenon using a simple equity–bond reversal strategy built with SPY and TLT. The idea behind that analysis was to illustrate how market flows around the turn of the month, e.g. driven by institutional portfolio rebalancing, can create (short-term) recurring patterns in asset prices. By…
Return: -4.68%
Volatility: 4.66%
The strategy recorded a cumulative return of −4.68% over the evaluation period while maintaining a relatively low volatility of 4.66%.
#4 LAB
The LAB is a convolute of strategies in an alpha testing phase. They are far away from fully functional strategies. The LAB is designed for testing stuff. It is not intended that every tested strategy will be developed further to a fully functional strategy.
Return: 13.24%
Volatility: 8.20%
The strategy generated a return of 13.24% while exhibiting a volatility of 8.20%. It is important to note, however, that the LAB is not designed with the primary objective to make a significant positive contribution to the overall portfolio performance. Instead, its role is to alpha-test ideas under real world conditions. A positive return is therefore an additional benefit rather than an expected outcome.
#5 RP3
This is the all weather core strategy that I presented here.
Create an All-Weather Core strategy
Over the long run, investors are compensated not for being clever, but for bearing risk that others are unwilling or unable to take. This simple idea sits at the heart of risk premia harvesting. Risk premia harvesting is a systematic approach to earning returns by gaining exposure to well-documented sources of compensated risk, accepting periods of disc…
Return: -3.52%
Volatility: 6.73%
The strategy recorded a return of −3.52% while maintaining a relatively low volatility of 6.73%. This is the second strategy in the portfolio to generate a negative return during the evaluation period.
#6 HERORATS
This is the dynamic equity trading strategy that I presented here.
Strategy Review of the HeroRATs-Strategy by Chrilly Donninger
After the very positive feedback on my review of the Value & Opportunity BOSS-Score, I’m back with another strategy deep dive. This post is a bit longer, so please make sure it’s displayed correctly in your email client to get the full picture.
Return: 19.44%
Volatility: 11.55%
The strategy generated a return of 19.44% while exhibiting volatility of 11.55%.
Despite this solid performance, the strategy is likely to be discontinued in the coming months. This decision is not driven by results or deficiencies in the strategy itself, but rather by portfolio management considerations. Specifically, the intention is to reallocate both capital and operational capacity to a new strategy that is currently under development, provided it becomes fully operational.
#7 AuraBit Momentum
This is the Gold and Bitcoin Dual-Momentum strategy that I presented here.
Golden Dual-Momentum Rotation
Gold has been humanity’s go-to store of value for thousands of years. Bitcoin, with its built-in scarcity and fixed supply schedule, has been dubbed “digital gold” by its proponents. But should you own one, the other or both and in what proportion?
It has been fully in Cash since the start, so nothing to report yet.
Conclusion
Taken as a whole, the first half of 2026 was less about performance and more about process. The transition from a equity factor approach to a diversified quant portfolio was always going to introduce operational friction and that friction turned out to be the defining challenge of the period.
The 2.34% return, achieved with 6.52% realized volatility, understates what is actually happening beneath the surface: a portfolio still in the process of being built out, with capital deliberately held back, volatility targeting not yet switched on and several strategies still accumulating the needed track record.
Individually, the strategies tell a more nuanced story than the headline number suggests. DYNVRP1 and HERORATS both delivered strong returns, the LAB performed better than its testing-oriented mandate ever required. On the other side, EOM and RP3 posted modest losses.
With roughly 80% of the major implementation issues now resolved, the second half of the year should look meaningfully different: more capital deployed, volatility targeting active and a clearer picture of how the individual strategies perform once they’re no longer competing with operational hick-ups. None of this changes the fact that the first half fell short of long-term return expectations in absolute terms, but given the scale of the transition undertaken, a profitable, increasingly stable portfolio is a reasonable outcome, and one that sets up a stronger foundation for H2 2026 and beyond.
Disclaimer
The above article constitutes my or the authors’ personal views and is for entertainment purposes only. It is not to be construed as financial advice in any shape or form. Please do your own research and seek your own advice from a qualified financial advisor. I / The authors may from time to time hold positions in the aforementioned securities consistent with the views and opinions expressed in this article. The information provided in this article is not making promises, or guarantees regarding the accuracy of information supplied, nor that you guarantee for the completeness of the information here. The information in this article is opinion-based and that these opinions do not reflect the ideas, ideologies, or points of view of any organization the authors may be potentially affiliated with. The authors reserve the right to change the content of this blog or the above article. The performance represented is historical and that past performance is not a reliable indicator of future results and investors may not recover the full amount invested.