Sigma1 Financial Software: Development Begins
I started Sigma1 with $35,000 in seed capital, a Linux workstation and a domain name I acquired in auction for $760. The original plan was to create a revolutionary hedge fund with accredited investors as clients. I started studying for the Series 65 exam and all went well until I started reading about securities laws and various legal case studies. I gradually realized two things:
- U.S. Securities Law is very restrictive, even for “lightly regulated” hedge funds
- The legal start-up costs for a hedge fund were much higher than I anticipated
The first realization was the most devastating to my plans. The innovative fee structure I wished to use was likely to face serious legal challenges to implement. Without a revolutionary fee structure, more favorable to clients, the Sigma1 Fund would be hard to differentiate from the hundreds of other funds already available.
The second objective of Sigma1 has been to develop proprietary financial software. Until now the Sigma1 Proprietary Trading Fund has been constructed based on research, pencil-and-paper securities analysis and some rudimentary Excel simulations. Some quantitative analysis has been applied, but without the mathematical rigor I prefer. That is about to change.
I recently devised a way to apply techniques developed while studying Electrical Engineering and Finance in grad school. In a nutshell, I will apply evolutionary algorithms to optimize portfolio construction. The same fundamental techniques my electrical engineering colleagues and I used to explore and optimize around the random perturbations inherent in fabricated silicon circuits can be used to optimize portfolios by efficiently exploiting conventional (linear) and unconventional (non-linear) correlations between diverse assets.
I have sequestered myself in a beautiful, tranquil location while on a well-earned sabbatical from work. While genetic algorithms (also called evolutionary algorithms) will be a significant part of the software suite I will develop, I also intend to incorporate heuristics and machine-learning techniques as well. Similarly I intend to use techniques from CAPM such as efficient-frontiers, but only as a first-order guide. Many of the limitations of CAPM (and Fama-French enhancements thereof) consist on their intrinsic reliance on Gaussian or “normal-distribution” statistical models. Such models do not properly model long-tail events, nor asymmetrical distributions, nor even log-normal distributions. Classic CAPM models even struggle with geometric-mean of expected or passed returns and generally use arithmetic means to preserve the use of linear systems analysis. Genetic algorithms and other AI techniques need not use such assumptions as a mathematical crutch. The software I intend to develop should be able to find near-optimal solutions to financial problems that classic statistical methods “solve” only by making grossly inaccurate assumptions about probability distributions.

5 Financial Resolutions for the New Year
Improve your financial health with these financial resolutions:
- Diversify with non-traditional and non-Wall Street investments. For example real real estate.
- Lower your ETF (and mutual fund) expense ratios. The ETF revolution is constantly competing for your money with an expense-ratio war. For instance, consider VEA vs EFA.
- Consider employing a buy-write strategy, either on your own, or via an ETF such as PBP as a modest part of your investing strategy.
- Improve your investment tax savvy. Know your ETF and mutual fund distribution dates, and consider selling before them (if you are going to sell any way). Use option-strategies to lock in short-term gains until they become long-term capital gains. Use tax-deferred accounts for high-tax investments (like junk bonds).
- Re-balance and re-align with your long-term investment allocation strategy.
Forget SDRs — The New International Currency is Digital
If you’ve no heard of BitCoin (BTC, $BCOIN) you’re missing out on a long-shot currency bet opportunity. The risk: value could plummet to zero. The reward: If all goes perfectly you could buy a sizable piece of the next reserve currency. Likely something in-between will happen. Read more about BitCoin.
Sigma1 Fund Asset Allocation and NAV
Currently all-long, mostly-equity positions:
- 50 shares EFA
- 100 shares SCHB
- 100 shares VEA
- 100 shares JNK
- 200 shares PBP
- 100 shares VTI
- 100 shares SPY
NAV: 36,604.55 USD.
Sigma1 Fund Trades
Yesterday I made several trades. I bought BWX and WIP to close my short positions, while maintaining long positions in EFA and VEA, effectively going shorter against the USD.
Even though I have been emulate the CBOE S&P 500 BuyWrite Index (BXM) for somewhat less than PBP’s 0.75% expense ratio, I decided eat some crow and just buy some PBP. This saves me the hassle of trading options every month.
The fund is now has no short positions, other than cash, which currently costs over 1.6% to borrow. Current closing NAV of the Sigma1 Proprietary Trading Fund is $36,571.
Wall Street Interview
Years ago, a successful friend of mine was telling me stories about his early Wall Street interviews with a big-name investing house. One stood out to me. The question:
If you had to invest $1,000,000 for a client, and your had only two choices, which would you choose? (A) “Invest” the whole $1,000,000 on red or black at the roulette wheel. (B) “Invest” on red or black $1000 at a time, one thousand times.
My friend said he knew the right answer, to that question and most of the others. I believe he was offered this particular job, but declined it in lieu of better offers elsewhere. Anyhow, he asked what my answer would be.
I said (B). If single zero roulette, the client can expect to lose on 1/37 (about 2.7%); if double zero, 2/38 or about 5.3%. My friend said, sorry, wrong answer. If you lose money for a high-net-worth client, even 2.7%, they are likely to be disappointed and take their business elsewhere. If you double their money, a roughly 50/50 proposition, you will have an ecstatic client who will stick their $2,000,000 with you for years. If you lose their whole $1,000,000 they will be disappointed and walk away, but “them’s the breaks.”
This story resonates with me to this day. This is an absurd question from a financial standpoint, but it is a powerful question on ethics. The business rationale behind answer (A) is valid. However, I chose to work for a company where the correct answer is (B).
Rocky Investing Week For the Fund
Since May 10th the Sigma1 Fund is down over 1000 dollars, closing today at $37,856.48. I’ve been thinking about reducing the leverage of the fund from its current 1.57X to closer to 1.2X. I have been weighing the cost of realizing some short-term capital gains versus a desire to deleverage.
On a separate note I’ve been bogging up a storm at my other other investing blog at Balhiser Investing. There, I try to keep the topics less technical and more accessible to a wider investing audience.
* Sigma1 is a proprietary trading group fund, and is not currently available to outside investment. It is currently structured as a long-short macro-centric hedge fund with long positions in equities (domestic and foreign) and junk bonds, and short positions in international bond ETFs.
US Economy
I believe the US economy is finally, gradually, haltingly emerging from its drug-induced slumber.
So, what is my opinion on US equities? Neutral to mildly bullish.
The fact of the matter is that US equities are leading economic indicators. Unless you believe in momentum investing, which I don’t (see disclaimer), past market moments do not predict similar future market movements. To the contrary, from a value investing standpoint, sharp upward market fluctuations simply presage undesirable valuations. Or in plain English, when the stock market skyrockets, be cautious. That is why I’m not a fan of “plain English”; it is too untextured, abstract, and strangely foreign to my financial ear.
My opinion has very little to do with my asset allocation. In painfully plain speak, “I pretty much stay the course with my investment choices, no matter how I feel at the time.” In other words, I stick to a purposely pseudo-static asset allocation strategy with the empirically grounded assumption that impromptu reallocations increase standard deviations without increasing alpha.
I apologize for the last two sentences.
My opinion, for what it worth, is that I’m less certain about my bullish equity positions. Simultaneously, I’m quite bearish on US debt securities… like US Treasuries (or as the WSJ writes it, Treasurys.)
All said, I am have not significantly changed the holdings of Sigma1. Not yet.
Disclaimer: Momentum investing is, in my opinion, only viable on a scale of seconds or microseconds in terms of algorithmic or “high frequency” trading. In general it is a guise for other investment bets, some of which pay off and some of which do not.
Sigma1 Fund Reallocations
This morning I realized that the Sigma1 Proprietary Trading Fund was allocated slightly dollar-centric rather than dollar-neutral. To bring it back to USD-neutral I bought some BWX shares to cover a portion of my short positions. Today the NAV of Sigma1 closed at $39,035.
Sigma1 Fund Performance Update
As of this evening, the total NAV of the Sigma1 Proprietary Trading Fund is: $38,672.43, up over 10 percent from the original investment of $35,000. Currently the Fund has no options positions and only long and short equity and EFT positions plus cash.
Note: Returns for outside investors would be lower after fees. Currently the Sigma1 Fund is not available for outside investment.



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