Hearts and Minds IPO Oversubscribed?

I just got an email with my allocation of shares in this IPO. It's 82% of what I requested and the settlement dates and first trading date have been brought forward. So looks like the IPO is oversubscribed and closing early.

Overfitted

When I started trying to backtest the model with my new program the performance was bad, worse than I expected and worse than backtests I'd done previously. Recent changes to the model seem to have overfit it to the recent data. Therefore, we can't rely on the model going forward. This will need thorough investigation and in the mean time I'll stop trading.

Hearts and Minds IPO

Another Australian IPO of a listed investment company (closed end fund). This one has a twist – there are no management fees and the directors have waived their fees too. Instead of receiving a fee, the managers will donate 1.5% of NAV each year to charity. The board of directors include local investing luminaries like Geoff Wilson and a long list of wealthy Australian families (such as the Lowy family) have agreed to make investments in the fund.

The fund is a long only fund investing in Australian and international stocks. Each year several Australian investment managers present at the Sohn Hearts and Minds conference their best investment picks for the coming year. 40% of the fund will be allocated to these picks. 60% will be allocated to "high conviction ideas" from a number of other "core" investment managers. In total the fund will invest in about 25 securities.

The picks from the last two conferences have done very well:

One of the core investment managers is Regal, whose hedge funds have done extremely well.

In summary, I think this looks like being another good investment opportunity.

Results for the S&P 500

These are the results of the year to date for the S&P 500 model, again without stops. As volatility is lower than the NASDAQ index, returns are lower but are still very good:

Alpha       0.47948 Beta      -0.22355 ror       0.46115 Sharpe       2.62376

Again these are annualized values. Annualized rate of return is 46% for this year.

P.S.
I've now written all the code including stops for NQ and ES. Stops only detract a little from performance for ES but quite a bit for NQ. This suggests that we should use wider initial stops, just to avoid catastrophe, rather than to get out of ordinary bad trades.

More Progress on Programming the Trading Model

Now this is a nice equity curve! This was produced by the computer making daily decisions for each day this year so far, using the full version of my model but without stops. The idea is it tracks what happens to $1000 compounded (without commissions or any slippage etc. - former is not important latter might be). The blue line is the NASDAQ 100 index also rebased to 1000 as the beginning of January. The computer is also printing out a list of instructions one for each day like this:

5082    7637.43018       1.00000       0.00000  D buy. Stay long
5083    7490.00000       0.00000       0.00000  K sell. Go short
5084    7399.00977       0.00000       0.00000  K sell. Stay short
5085    7352.81982       0.00000       0.00000  K sell. Stay short
5086    7371.62012       0.00000       0.00000  K sell. Stay short
5087    7044.50000       0.00000       0.00000  D sell. Stay short
5088    6964.02978       0.00000       1.00000 R buy not confirmed by pdD D sell. Stay short
5089    7157.20996       1.00000       1.00000 R Buy outside BB confirmed by pdD
5090    7068.67041       1.00000       1.00000 R Buy outside BB confirmed by pdD
5091      NA       1.00000       1.00000 R Buy outside BB confirmed by pdD

These are the most recent decisions, including today's decision to stay long. The "NA" indicates that we don't yet know the index value for today...

It also produces some performance statistics:

Alpha       1.76456 Beta      -0.21425  ror       1.68344 Sharpe       5.47108

That means 176% p.a. of alpha... This is based on compounding the daily alpha over the year. Beta to the market is slightly negative and so compound rate of return for the year is a little less than alpha. I don't expect that high rates of return in other years. Conditions are ideal this year and probably the model is a bit overfitted. One of the reasons for doing this programming is to make it easier to test the model on larger samples.

Next I will add some refinements like using futures prices instead of index prices for performance results. Oh yes, and adding stops!

P.S.
When I ran the algorithm on the S&P 500, I found at least one bug which also needs ironing out.

Firetrail Cancels IPO

I looked at the prospectus but decided not to invest. Apparently they got more than the minimum funds raised but claim that there aren't enough different shareholders...

Firetrail Absolute Return Limited withdraws listed investment company IPO offer

Tuesday 16 October 2018

Dear Moom,

After careful consideration Firetrail Absolute Return Limited (Company) (in consultation with Firetrail Investments Pty Limited (Firetrail)) has made the decision, in the best interest of investors, to withdraw the initial public offering for ordinary shares in the Company (Offer) which was scheduled to close this Friday, 19 October 2018.

The Company made the decision to withdraw the Offer (in consultation with Firetrail) as it was in the best interests of investors to do so given liquidity concerns, in particular the concentration of the shareholder base. Listed Investment Companies (LICs) that do not have a well-diversified shareholder base are generally at a higher risk of the share price trading at a discount to the company’s net tangible assets. As such, we believe it was in the best interests of shareholders to withdraw the Offer, despite raising in excess of the minimum investment amount.

Investors that would like to gain access to the strategy are still able to do so through the Firetrail Absolute Return Fund which is still open to investors and has delivered strongly during the recent market volatility over the past week. Since Monday 8 October 2018, the share market has fallen over -4%1. The Firetrail Absolute Return Fund has delivered a positive return of approximately +1.3% over the same period, highlighting the benefit of the strategy which aims to deliver positive absolute returns above the RBA Cash Rate, independent of movements in the underlying share market.

Please contact us if you would like more information on investing in the Fund.

Kind regards,

Firetrail Investments

NQ Equity Curve

This is the equity curve trading NQ futures since the beginning of the trading experiment. It starts at about USD 4k because that was the cumulative profit for 2006-8. This isn't our total trading performance because I've also traded other things like ES futures and earned a little interest.

The little tick down at the end is the "bad trade", which wasn't so bad in the end, but that was mostly luck.

I've done a bit more programming and now the program produces a coherent list of trades, one for each day. But I've only written up part of the system yet, so you wouldn't want to actually trade them :) In fact, here is the fractional gain (i.e. 0.15 is 15% gain, not compounded) if you traded "the strategy" for this year:

In other words, it breaks even in the end, which is what you'd probably expect for a random set of trades. This kind of thing is now easy to produce, which is one of the main things this is all about.

To explain this curve, the model starts at long on 4th January and some of the code is written for what to do if you are long - it might tell you to switch to short, but not much code is written yet for what you should do if you are short. So there is little code to flip you back to long again. As a result the model is stuck on short for much of the time...

Started to Code the Decision Tree

After a couple of hours of coding and debugging I got the first little bit of the model decision tree to work and spit out buy and sell decisions. The output looks like this:

4895    6584.58008 1       0.00000 Stay long
4896    6653.29004 0       1.00000 R Sell Confirmed by pdD
4897    6676.62988 0       1.00000 Go long
4898    6677.93994 0       0.00000 Stay short
4899    6662.66016 0       0.00000 Stay short
4900    6708.49023 0       0.00000 Stay short

As the decision tree is far from complete, only the first two orders – long and then short – make any sense. The first number is a code for the date, the second is the closing value of the NASDAQ 100 index on the previous day (so that it's easier for me to work out where I am than the obscure date codes). Then there are codes for buy and sell and then a verbal description of the decision and why it was taken.

Luckily, writing computer code is a core practical skill for professional economists (or you should have these skills if you don't!) we took programming courses as part of our first year undergrad study.

Should Have Done the Long Trade

Market went up strongly. Model is still long for Monday. But I'm still not in. I needed to take a break from trading. This is why I need an automated system.

Rescued the Bad Trade

I stayed up and closed at 7119.75 the bad trade where I went long at NQ = 7145. So in the end I only lost USD 500 on that trade and am still up more than USD 6k for the month. If I exactly followed the model, though, I would be up USD 13k! The model is now switching to long for Friday, but this trade is based on the adjustment I made for the 1987 crash (picture below from 1987) and doesn't have a lot of statistical support. So, this is a high risk trade and I think I will wait it out. Yeah, I'm not doing what the model says to do but at least I am not trading against it!

In other news, the Tribeca fund (TGF) starts trading on the ASX today . They only sold 63 million shares in the IPO out of a maximum of 120 million, which is a bit disappointing. Maybe, my thesis that it would trade above NAV will take a while to work out. My entry point into Pershing Square was really bad - lost around 4% already on it. I also did a trade yesterday to switch back AUD 20k from CFS Conservative Fund to CFS Geared Share Fund. ASX SPI futures are off 47 points but CME NQ futures bounced after the New York close and the model is switching to long, so hopefully my timing wasn't too bad.

Great at Analysis No Good at Trading

I'm great at analysis and no good at trading. Just like this guy. This is why I need a computer to trade for me. That will now be the top priority.

Australian Corporation Tax

The Australian government has lowered the rate of corporation tax on small businesses and planned to lower the rate on larger businesses too. The latter was blocked by the Senate. The main reason put forward for reducing the tax seems to be increasing international competitiveness, though this is less important for small businesses that mainly don't have international investment in them. Today, the news is that the government wants to bring forward by several years the reduction to 25% for small businesses as a pre-election vote winner. Labor, by contrast, opposes this cut (they withdrew their policy to repeal the previous cut) and wants to raise all sorts of taxes on investment.

As an Australian investor in public companies I didn't used to care too much how high the corporation tax was. This is because when a company pays tax and then pays a dividend, Australian investors get a "franking" credit for the tax paid by the company, so there is no double taxation. Foreign investors usually can't use these credits, hence the argument to partly level the playing field  by bringing down the rate of the tax. If a company doesn't distribute profits and the share price increases and I sell my shares and pay capital gains tax, then there is double taxation. But the long-term capital gains tax is only half the normal income tax rate and so this isn't too bad (Labor want to reduce this discount too). Additionally, the price paid for listed shares takes into account that profits are taxed, which helps mitigate the impact of the tax on the rate of return that investors receive. Australian investors, though, are willing to pay more for Australian shares than international investors are, given their differential tax treatment.

Actually, I like getting franking credits, because after I deduct investment costs like margin interest they reduce the tax on my salary.

But as I think about setting up a private company, I increasingly like the idea of lowering the corporation tax. Profits that are re-invested in the business, rather than paid out as dividends, are greater if the tax rate is lower. Of course, this applies to listed companies too, and cutting the tax rate should raise the price of shares in a one time move. The more that we have existing investments rather than are buying new investments the more we should like increases in share prices... On the other hand, ot all the extra profits from lowering the tax rate will actually be realized. Market equilibrium should mean that after the rate of return increases, firms invest more, lowering the pre-tax rate of return. This mechanism is much like how stock market investors will buy shares raising the price and reducing the expected rate of return again. But lower taxes on investment are economically more efficient.

I Will Do What the Model Says to Do

Maybe today will finally knock my tendency to not follow the model out of me, but I kind of doubt it. I am getting better though. Today, I closed my short position early. That's not such a bad move. But then near the close I went long, because I thought the model was saying to go long tomorrow. But I had forgotten the correct way to read that rule and read it wrongly – I used today's value of the indicator instead of the forecast of it for tomorrow. The model in fact says to stay short into Thursday. The market continued to plummet and took away most of my gains for the day. Still, I am up for the month, for now.

I must fast-track model automation. First step is to convert the decision rules, which I now execute manually and record in an Excel spreadsheet into computer code (in my econometrics package) that can make decisions without errors. Then I need to get better at just doing the decisions at the right time while learning Python etc in order to build an automated system or getting someone else on board to do that. In the meantime, I will stick to trading a single contract to minimize risk.

New Investment: Pershing Square Holdings

I made a small (1% of net assets) investment in Pershing Square Holdings (PSH.L). This is a closed end fund trading on the London Stock Exchange that is managed by Pershing Square Capital Management, the fund founded and managed by William Ackman. Pershing Square funds did very well from 2004 to 2014, which is when they launched the closed end fund. They did very poorly in the next three years:

PSH lost 20.5%, 13.5%, and 4% in each of 2015, 2016, 2017. However, NAV has gained 15% or so year to date. The stock trades at a 27% discount to NAV. Given the past good performance, the return of good performance this year, and the substantial discount which the company is trying to reduce, I thought this was worth trying. Ackman and the firm are in the news for a $900 million investment in Starbucks, discussed here.

If you are wondering why a US hedge fund is listed in London, it's because it's not legal to offer hedge funds to retail investors in the US.

Generation Global Share Fund Closed to New Investors

It turns out that the Generation Global Share Fund is closed to new investors and so I couldn't do the fund switch I tried to do yesterday. CFS's systems allowed me and the guy I phoned to select this option but then rejected the complete portfolio. So I recomputed the numbers and did the switch online now. New allocation is:

CFS Geared Share Fund: 7%
CFS Geared Growth Plus: 40%
CFS Conservative: 11%
Platinum International: 23%
CFS Developing Companies: 19%

Gearing in the Geared Growth Fund is lower than in the Geared Share Fund. Still it is quite aggressive and I will likely delever further at some stage.

Moominmama Allocation

Following up from yesterday's post on delevering in my retail superannuation (retirement) account, here is the desired allocation compared to actual allocation in Moominmama's (formerly Snork Maiden - I mention this because I used to refer to my mother as Moominmama on the blog) Colonial First State managed funds account (in American: taxable mutual fund account). Desired allocation:

CFS Geared Share Fund: 19%
CFS Global Geared Share Fund: 9%
Platinum International: 27%
Generation Global Share: 13%
BT Property Investment: 13%
CFS Developing Companies: 19%

Actual:

CFS Geared Share Fund: 28.3%
CFS Global Geared Share Fund: 16.0%
Platinum International: 11.0%
Generation Global Share: 16.4%
BT Property Investment: 12.6%
CFS Developing Companies: 15.7%

The funds are in: geared (leveraged) Australian shares, geared  global shares, global equity hedge fund, global shares, REITS, small cap Australian shares.

We are moving towards the desired allocation slowly by only adding each month to the underweight funds and by not reinvesting distributions. If things looked worse, maybe I would then actually switch funds, but then there will be a capital gains tax bill. Unlike the US, even at low income levels you have to pay capital gains tax (unless you earned less than AUD 18k a year and paid no income tax), though the long-term rate is half the normal income tax rate (for the moment).

This is how our asset allocation has evolved since the financial crisis:

 This doesn't include our house. The main trend is a reduction in allocation to Australian large cap srtocks since the recovery bounce from the crisis and an increase in other asset classes.

Delevering

I just made a big switch in my Colonial First State superannuation account to reduce risk. Stock markets still look bullish but the Fed shows no sign of stopping raising interest rates, risking an inversion of the yield curve. They have been saying that this time is different and that an inverted yield curve doesn't mean that there will be a recession. But though the sample size is very small, it has been a good predictor in the past. We are not yet at yield curve inversion but it still could make sense to reduce risk. My CFS superannuation account has been invested very aggressively. At the end of September this was the allocation:

CFS Geared Share Fund: 48.9%
CFS Geared Growth Plus: 20.2%
CFS Conservative: 10.2%
Platinum International: 10.2%
CFS Developing Companies: 10.5%

So about 70% was in geared (leveraged) funds. Geared Share Fund is large cap Australian shares. Geared Growth is diversified. The new allocation, which is much closer to our new long-term allocation is:

CFS Geared Share Fund: 15%
CFS Geared Growth Plus: 18%
CFS Conservative: 4%
Platinum International: 23%
CFS Developing Companies: 20%
Generation Global Share: 20%

Both Platinum, which is a hedge fund (long and short global equities) and Generation performed well in the Great Recession. Doing this transaction in a superannuation account is tax free - capital gains tax of 10% is paid on unrealised gains on a continuous basis. There is just the cost of the entry/exit spreads.

I changed the allocation for new investments in Moominmama's CFS account, which is not a superannuation account to only buy the non-geared funds going forward. If things look more bearish, we may yet do a switch there too.

September 2018 Report

The Australian Dollar rose from USD  0.7201 to USD 0.7228. The MSCI World Index rose 0.48% and the S&P 500 rose 0.57%. The ASX 200 fell 1.04%. All these are total returns including dividends. We lost 0.63% in Australian Dollar terms and 0.26% in US Dollar terms. So, we  outperformed the Australian market and underperformed international markets.


The best performing investment in dollar terms was NASDAQ futures gaining AUD 2.6k –  and the worst the CFS Geared Share Fund losing AUD 10.7k. The best performing asset class was private equity, gaining 1.28% followed by commodities (this includes trading), gaining 1.22%. The worst performing asset class was Australian large cap, losing 1.57%.


The following is table of investment performance statistics computed over the last 60 months (extended from 36 months previously) of data:

The first two rows gives the annual rate of return and Sharpe ratio for our investment performance in US dollars and Australian dollars. The other statistics are in comparison to the two indices. Based on beta, compared to the MSCI World Index we seem to be slightly geared, while compared to the Australian index we are less sensitive to market movements. We have a positive alpha compared to the Australian and a negative alpha compared to world markets. We capture more of the up movements and less of the down movements in the Australian market and the reverse in the international markets. The fall in the Australian Dollar over this period explains the poor performance compared to international benchmarks.


This month I made USD 2.5k trading futures. This is the second best result to date and ocurred as the NDX declined for the month. The table * compares my performance to the market and the model:



This month was the sixth month of the futures trading experiment. The first month was the model development phase, and since then I have been trying to get disciplined at trading and further incrementally improving the model. I didn't trade in the first half of the month as I was traveling to Europe and Singapore and the model was short and based on relatively low volatility I thought the profit potential was low. This was a mistake as the model did very well. Then when I got back into trading we were in a corrective phase with the market trading sideways. I traded long NQ short ES for the last few days of the month. The model outperformed the market this month, though its return was not that high. The model is bearish and under-performs when the market is strong and outperforms when the market is weak. It got stopped out a couple of times, which is unusual. As a result the model made 4 trades in 4 days. The second time the model was stopped out, the market ended up on the day and so the stop was too tight. The first time, the stop reduced losses.

What I want to do next on the trading front is write the model's decision algorithm in computer code. At the moment I estimate the indicators I use with an econometric model but I then make decisions manually and record the details in an Excel spreadsheet. It is quite quick to do to make daily decisions in a single market but it is quite hard to do backtesting of different ideas. This will be much easier once we have the decision algorithm coded in the same program as the estimation model. Also, in the long run I plan to automate trading or at least automate data acquisition and decision making for multiple markets. Coding the model in the language of my econometrics program is a first step towards that. Once the model is written in one computer language, converting it to another shouldn't be hard.

I did our tax returns this month. I should get a big refund and Moominmama had to pay a little under AUD 1,000 in extra tax. Otherwise, I am waiting for the probate process to play out before undergoing a big round of financial restructuring.


We made a little bit of progress towards the new long-run asset allocation:

Total leverage includes borrowing inside leveraged (geared) mutual (managed) funds. The allocation is according to total assets including the true exposure in leveraged funds.

We invest AUD 2k monthly in a set of managed funds, and there are also retirement contributions. Then there are distributions from funds and dividends. Major moves tbis month:

• I redeemed the Janus-Henderson Global Resources Fund, which reduced exposure to ROW stocks.
• I reduced cash and the margin loan in preparation for investing in the Tribeca IPO. As a result our allocation to hedge funds will increase substantially next month. 
• I added to the Yellow Brick Road position which is now about 1% of net worth.

* The statistics at the bottom of the table are based on only 5 months of data and so are not at all reliable yet.
    

Internal Rate of Return and Private Equity

Private equity funds like to report the returns on their investment using the internal rate of return metric. The IRR is the discount rate which results in the net present value of the stream of cashflows from the investment being zero. This article points out that it is only the true compound rate of return if you can reinvest the payouts that you receive over time at the same rate of return (r.o.r.). This is correct. But it then goes on to say that IRR is meaningless if you can't reinvest the distributions at the same r.o.r. I don't think that is right. If the IRR is higher than the r.o.r. that you can invest the distributions at, then your r.o.r. from investing in the private equity investment and reinvesting your distributions is greater than the r.o.r. you'll receive by just investing in your alternative investment (and vice versa). Your actual r.o.r. won't be as high as the IRR but the IRR is still useful for making decisions. The main issue is that you need to deduct the funds fees to get the true IRR. Often they will report that they made a $1 million investment and sold for $2 million and give the IRR without deducting fees. Probably as a back of the envelope calculation you could deduct 1/4 of the stated IRR in these cases and then compare to your alternative r.o.r.

So, for example, in Aura's latest report to investors they reported IRR's to date on two investments of 59.5% and 29.2%. So, yes, these are very good. Of course, those are the investments whose carrying values they are marking up. They report a 21.3% IRR on an investment they are exiting. But then there are others that are just breaking even.

Firetrail IPO

Another hedge fund IPO in the coming month. This one is also managed by Commonwealth Securities and so I could participate via the broker firm offer. It is a market neutral hedge fund that can lever up to 200% of NAV in both the long and short sides. The investment team used to work at Macquarie where they got decent returns (22.1% p.a. from July 2015 to October 2017). I'm not so impressed by their performance this year since starting up on their own:

This is not the sign of a high Sharpe ratio investment – it seems there is a lot of risk in this investment relative to the returns. I think this is a fund that is worth tracking over time and seeing if it settles down and performs better. Based on the above, I don't think the shares will trade above the offer price immediately after the IPO, though that is just a guess.

2017-18 Taxes

Here are my taxes for another year:

A lot of items are down on last year. Foreign source income and unfranked distributions are up because the Winton Global Alpha Fund did well in this tax year. This also means that a chunk of the margin interest is directed to foreign source income and appears under "other deductions". Another new item this year is the Early Stage Venture Capital Limited Partnership offset due to my invest in the Aura Venture Capital Fund. Work-related travel expenses are up because the grants and other funding I had are winding down and so I need to spend more of my own money on travelling to conferences etc.

Franking credits (from Australian dividends), foreign tax paid, and the ESVCLP offset are all deducted from gross tax to arrive at the tax assessment. I expect to get a large refund.

Gross cash income deducts franking credits as these aren't paid out as cash and adds in net capital gains, which were around $60k to income before deductions. Net after tax cash income then deducts tax and deductions from gross cash income.

Looking forward to next year, net capital gains will likely become positive as I won't have any more past losses to deduct. Foreign source income will likely grow further as futures trading comes in.

Moominmama's (formerly Snork Maiden) taxes follow:

Salary was up as Moominmama came off maternity leave. Work related travel expenses were also up as she also went to one of the conferences in Europe. Still, we expect to pay extra tax. Next year there should be more in the way of investment deductions following our mortgage restructuring. There will also probably be a lot more foreign source income.

Longer Term Planning

I was rejected for the two jobs I recent applied for. One in Australia after interview and one in the UK pre-interview. So, it looks like we stay in Australia in this city for the moment. It also looks like I will continue in my job next year, but I am seriously thinking about "retiring" at the end of 2019 when I will be 55.

Hopefully, the probate situation is finalized before the end of this year and we can start to restructure our finances. This is what I am thinking to do:

1. We will need to set up a trust account or something less formal for little Moomin for the relatively small amount of money he will inherit. Need to wait to hear what we need to do. According to the will, he won't get the money till he's 23 years old...

2. Almost pay off our mortgage and then redraw it and use it to pay off margin debt and add to a trading account. We can then deduct the mortgage interest from our taxes and it is a lower interest rate than the current margin loan.

3. Set up a self-managed superannuation fund (SMSF) and roll my existing Colonial First State superannuation fund into it as well as contributing AUD 300k for each of me and Moominmama. This would then have about AUD 900k to start with. The reason to go down the road of self-managed super is to be able to invest in managed futures, which are a tax ineffective investment outside super. We would put all our high tax investments into the fund as well as some Australian shares with franking credits to reduce the tax.

4. Scale trading up to full size. At the moment, I am thinking we will need to set up a company for trading. Corporation tax on small businesses is 27.5% vs. top personal marginal rates of 47% +.* My understanding is that you don't need to pay out all profits as dividends and so retained earnings are more lightly taxed. But I will need advice on this. It would also protect the rest of our assets against something catastrophic happening. The company could also be the trustee for the superannuation fund, which would allow us to maintain the SMSF if we left Australia.** These are just my current understandings – obviously I am going to need to get professional advice on all of this.

5. Estate planning. Currently we don't even have wills. This is an area I know little about but will need to deal with. What I want to avoid is the situation we faced with my mother where the government dictated investment policy to us after she wasn't capable of making decisions - despite giving us power of attorney.

* The downside of companies is that they don't get a capital gains tax discount. Individual investors in Australia only pay half the marginal rate on capital gains on investments held for more than a year. But the advantage of only paying 27.5 or 30% tax on trading income rather than 47% tax before investing it in other investments outweighs the discount. If Labor reduce the discount, this will be even more the case.

** You can't be the trustee of an SMSF if you aren't resident in Australia. Using a corporate trustee gets around that. There is a problem in leaving Australia and receiving income through an Australian company as it means we would suffer from double taxation. In Australia, dividends from the company would have attached franking credits so that we would only need to pay the difference between 27.5% and 47% on dividends. But if you live outside Australia in a location where you need to pay tax on foreign income (obviously one reason to move might be to reduce tax...) then we would need to pay the foreign tax on top of the Australian company tax. Investments already inside the company are invested in Australian stocks that pay franked dividends, then the franking credits on the dividends received would mean that the company wouldn't pay net tax on its investment income, so that won't be double taxed if we moved overseas. But trading income would be taxed at 27.5% and then again if paid out as dividends. So, we would need to do a restructure in the most tax-effective way at that point. In an earlier version of this post, I did think about having the company being the beneficiary of a discretionary trust that actually did the trading and then just changing the flow of income. But the trustee of the fund has to pay tax for offshore beneficiaries. So, that doesn't help.

Mean Reversion vs. Momentum Strategies

This is an interesting interview. About half way through he makes a deep point that if you use an oscillator type indicator and sell it when it is overbought and buy when it is oversold that is a mean reversion strategy. If you do the opposite - buying when overbought and selling when oversold then it is a momentum strategy. And those are really the only two options for directional trading using such indicators. Well, he also says that 95% of assets follow a random walk and can't be predicted. My system basically tells me when to switch between momentum and mean reversion. For me there isn't really something that is not predictable though when volatility is low predictability goes down.

How Many Households in Australia are Rich?

Every couple of years the Australian Bureau of Statistics surveys the distribution of household wealth in Australia. The most recent data is from the 2015-16 survey. It doesn't provide a lot of detail though. The downloadable data provides the averages for quintiles and the level at the top of each decile. They report that net worth at the 90th percentile is $1.979 million.

We can get more information by using the reported mean and the Gini coefficients and assuming that the data follow a log-normal distribution. You can get details of the necessary calculation here - use Wolfram Alpha to get the inverse of the erf function.

The distribution fits well for the 30th (ABS: $232k, lognormal: $240k) to 90th percentiles (ABS: $1.979 mil, lognormal: $2.1 mil). Below the 30th percentile the lognormal predicts too much wealth, while right at the top it would predict at most one billionaire in Australia. But I think we could use it up to the 99th percentile without too much error. The top 5% starts at $3.26 million, 4% at $3.7 mil, 3% at $4.3 mil, 2% at $5.3 mil, and 1% at $7.4 mil. All these numbers will be a bit higher now, of course. The most recent figure for mean household net worth is over $1 million rather than $929k here.

The ATO regards anyone controlling more than $5 million as wealthy, so that is the top 2 to 2.5% (with current mean net worth). To be a wholesale investor you need individually $2.5 million of net assets. So assuming a couple have $5 million, that also is the top 2.5%. So, the top 2.5% in Australia are considered "rich". That is roughly 250,000 households.

P.S.
In 2015-16 we were at the 16th percentile.

If You Follow This Advice You Won't Be Able to Buy a House

If you follow this advice from Ramit Sethi, you won't have any money to buy a house or start a business, unless you have a lot left over after doing all these things. The image that accompanies the article is very apt:

If you follow this advice you will be locking all your time away in the piggy bank until you are 59 1/2 (or 60 in Australia). I think I should start writing my own financial advice:

The first step is the same - if your employer requires you to match to their retirement contributions in order to receive it, do it. In Australia that isn't normal, but in some jobs in the public sector there can be additional tax advantaged employee contributions on top of the employer contributions. I would suggest skipping those until you do my step two unless it really reduces the retirement benefits you will get.

Step two is also paying down debt, but only on high interest loans like credit cards. If you have debt where the after tax interest rate is lower than the after tax expected return on investment, pay those off as slowly as you can. So yes, get rid of credit card debt ASAP, but student loans and home mortgages are usually debt you don't want to get rid of in a hurry. Taking on a moderate about of extra debt if the rate is good (as in leveraged managed funds or even margin loans) can be good, but don't overdo it.

Step three is the "emergency fund" or equivalent. Get some cash together to cover emergencies and opportunities. Having the ability to borrow more is good too of course, but don't just rely on that. I had about $20k in cash before I started to invest. As that is 20 years ago, you probably should double that number now.

Step four is probably investing outside of retirement accounts. This means your money isn't locked up till you retire. The supposedly lower tax of retirement accounts comes at a heavy price. With low long-term capital gains tax and reduced rates on dividends (especially in Australia) the tax on non-retirement accounts may be not much higher than on retirement accounts in Aus (and you can make bigger contributions later in Aus as I am now contemplating when you have plenty of money). US 401ks are taxed heavily on withdrawal in retirement though they have no tax during accumulation. The US Roth IRA though is an attractive investment as it leaves options more open.

Step five - if house prices are reasonable relative to rents in your area and you aren't planning on moving a lot, once you have more than enough for a downpayment, buying a house is probably a good move. But do a proper cost benefit analysis of this.

Step six - once you have done these and if you aren't thinking of getting into business, now you can look at maxing out retirement accounts.

I didn't mention trading - unless you have a proven model and want to pursue this as a real business you can do this as a hobby alongside Step 6. Most traders lose money though, so it is definitely an expensive hobby for them.

Mercantile's Bidder Statement Provides No Rationale for 9 Cent Offer Price

Mercantile (MVT.AX) released a bidder statement for Yellow Brick Road (YBR.AX) which provides no justification whatsoever for the 9 cent per share offer price. I think that is quite remarkable. Normally, such statements provide a detailed justification from "independent experts" for the price. Mercantile's bidder's statement for IPE did. YBR shares are currently trading at 10.5 to 11 cents.

August 2018 Report

The Australian Dollar fell from USD 0.7432 to USD 0.7201. The MSCI World Index rose 0.83% and the S&P 500 rose 3.26%. The ASX 200 rose 1.76%. All these are total returns including dividends. We gained 2.04% in Australian Dollar terms and -1.13% in US Dollar terms. So, we  outperformed the Australian market and underperformed international markets.

The best performing investment in dollar terms was CFS Geared Share Fund gaining AUD 9.2k  followed by Unisuper (CDM.AX) gaining AUD 6.9k and Bluesky Alternatives (BAF.AX), gaining AUD 4.5k. The best performing asset class was "real estate", gaining 2.45% followed by US stocks, gaining 2.28%. The worst performing asset class was hedge funds, gaining 0.26%.

The following is table of investment performance statistics computed over the last 60 months (extended from 36 months previously) of data:

The first two rows gives the annual rate of return and Sharpe ratio for our investment performance in US dollars and Australian dollars. The other statistics are in comparison to the two indices. Based on beta, compared to the MSCI World Index we seem to be slightly geared, while compared to the Australian index we are less sensitive to market movements. We have a slightly positive alpha compared to the Australian and a negative beta compared to world markets. Finally, we now capture more of the up movements and less of the down movements in the Australian market and the reverse in the international markets. The fall in the Australian Dollar over this period explains the poor performance compared to international benchmarks.

This month I only made a relatively small amount of money trading futures – USD 1.8k – though this is the second best performance so far in dollar terms. The table * compares my performance to the market and the model:

This month was the fifth month of the futures trading experiment. The first month was the model development phase, and since then I have been trying to get disciplined at trading and further incrementally improve the model. August was rather erratic. At one point I was up AUD 11k over the amount originally put into this trading account and then blew almost all of it in a mixture of bad model trades and bad trading in and out of positions. One of the bad model trades would now not happen, due to improvement of the model, so I have learned something from this experience. In the early part of the month I was trading two NQ contracts. After the bad trading I cut it back down to one contract again. So we are back in Stage 2 of the trading experiment, which is learning to consistently trade one contract. I am only doing long trades for the moment, due to the reduced volatility at the moment. Still, I unnecessarily sacrificed about USD 1,500 by closing a long position early. The model slightly underperformed the market this month. The same thing happened in May when the market had a very strong result. The model is bearish and under-performs when the market is strong and outperforms when the market is weak.

We reversed progress towards the new long-run asset allocation:

Total leverage includes borrowing inside leveraged (geared) mutual (managed) funds. The allocation is according to total assets including the true exposure in leveraged funds.

The deterioration in allocation, came mostly due to investment activity. We invest AUD 2k monthly in a set of managed funds, and there are also retirement contributions. Then there are distributions from funds and dividends. During the month, I also:

• I added another AUD 10k to the Winton Global Alpha fund, but withdrew AUD 50k from the trading account, for a net reduction in the allocation to commodities.
• I received the payment for the takeover of IPE but bought some more shares in OCP.AX, overall reducing the allocation to private equity.
• Added to positions in PMC.AX and CDM.AX, increasing the allocation to hedge funds. 
• I added a small position in Yellow Brick Road (YBR.AX), increasing the allocation to Australian small cap stocks.

* The statistics at the bottom of the table are based on only 5 months of data and so are not at all reliable yet.

Yellowbrickroad and Tribeca Natural Resources

Yellow Brick Road (YBR.AX) is an Australian mortgage broker and financial planning company. Mercantile Investment Company (MVT.AX), who took over IPE has made an offer to take over the company at 9 cents per share. However, the company has rejected the offer and the market is trading higher than 9 cents under the assumption that Mercantile will have to increase the offer. The company has net tangible assets of 13.4 cents per share, though much of that is future expected trail commissions. Regulators are clamping down on trail commissions and these might go away in the future, but I doubt that existing deals would be cancelled. The company just announced it made a small loss this year after a small profit last year. So, net tangible assets would seem to be the minimum reasonable price for the business.

I have started to make a small investment in the company. As it is risky to buy above the announced takeover price, this won't be a big position. The CEO and his brother own 19% of the company as does Nine Network. So, these big shareholders would have to get a price they are willing to accept for the takeover to actually proceed. MVT owns about 20% too, so smaller shareholders have 40% of the company.

Commsec announced the IPO of a listed investment company (closed end fund) managed by Tribeca. This will be a listed hedge fund. The managers have an extremely strong track record, though returns have fallen from the very high returns they made in 2015. I suspect that as money under management increased, returns fell. Still, they show the potential to perform very well going forward and I think this LIC should trade above net asset value. So, I plan to participate in the IPO. I also plan to redeem my units in the Colonial First State Janus Henderson Global Resources Fund, which has not performed that well in recent years.

Just Follow the Model

Yesterday, based on looking at the candlestick patterns and Oscar Carboni's caution about a possible "holiday reversal", I decided to close my long position. I missed a big rally today as a result. At least I didn't lose money. But I shouldn't doubt the model. Now the model is signalling short. However, due to low volatility, I won't take this short signal. There was a similar signal on 9 January that made small gains for a couple of days and then lost big. Another similar signal on 11 May also lost money. So, seems a good point now to just step out of the way, especially as on Tuesday I am traveling to Europe.

The model gained 3.19% on this long trade.

That Worked Pretty Well

The model passed the test. We are now back to a positive return from trading for the month.

Started Trading Again on the Long Side

Following up on this post, I took the next long signal from the model, which was yesterday. I got in at NQ=7418.75, which was almost the low for the day. The market ran up sharply at the beginning of the cash session and then corrected sharply, ending down, but still above my entry point. Today's forecast is long again using the latest version of the model, which smooths one of the signals but using the old version with an unsmoothed signal, it might be short, or maybe I'd invoke the "close to zero rule", which said to ignore a change in direction of the indicator if the indicator was close to zero. Now, we have a clear objective rule. Let's see what happens.

But until volatility shows some sign of increasing, I won't take the next short signal.

NetWorthShare

NetWorthIQ seems to have died. So, following up on EnoughWealth's blogpost, I have opened an account with NetWorthShare. It's surprising that NetWorthIQ didn't make more of their website. I would have thought they could have got a lot of advertising from the financial industry.

Does it Ever Pay to Go Short?

I did some tinkering with the model to avoid the kind of false buy signal that resulted in the stop out last week. I applied Hodrick-Prescott filtering to one of my indicators. This eliminates these kind of false turning points but also eliminates a fairly subjective rule in my decision tree. So, overall that improves the model. This is one step further to a fully objective system that can be automated.

You need to be careful with HP filtering as it uses all the data in computing the smoothed estimate. So in back testing you have to run the filter repeatedly using just the data that was known up to that point.

The model is currently short. But I don't have a trade on. I am thinking to put a trade on when it switches back to long.

In a recent post, I showed that a hedged portfolio levered 1.5 times would track the market when the market does well and track the model when the model does well. Instead of thinking of this as trading plus investment we can examine it as a pure trading strategy. That suggests that it doesn't pay to go short. Just stay out of the market when the model is short and only take the long trades and lever up the returns. In 2018 so far, going short would add to returns though. But in 2017 going short detracted from returns. The model only won 45% of trades in 2017. The average win (1.57%) was almost double the average loss (-0.9%) though so, the expected value of a trade was still 0.2%. When we split trades into long (22) and short trades (24) instead the average long trade made 0.83% and the average short trade lost 0.39%. So, avoiding short trades would have doubled returns, returning 20% instead of 10% for the year. Of course, just going long for the whole year would have returned 32%. But we don't know that will happen ex ante. Levering the 19% by 1.5 times or so reproduces the long-only result.

The question now is whether you can win by going long only in a year like 2008. My intuition is that trading would result in a positive return for the year but that this would be insufficient to hedge the losses in an investment portfolio. It would moderate the downside though.

Testing that hypothesis will have to wait a little while.

But for the moment, volatility is low and so going long only might pay off.

Stopped Out...

My long position was stopped out on Wednesday. Now back to more or less zero profit on this account - still have a positive overall result from the trading experiment. Also, I realised that I still can't really psychologically handle trading overnight futures positions at the moment even at the smallest trade size. I am losing sleep because of it. So, I am going to stop trading for the moment. I need to get a lot of academic work done in the next two weeks before going on another overseas trip. At some point after I am back I will do some further research on trading models. My thinking is I could design a model that would only make trades when the odds were most in favor of winning. The current model trades all the time regardless. The ultimate long-run goal is automation of trading or taking it out of my hands in some other way. To achieve these goals I don't need to be trading continuously at the moment if I'm not making good money at it and  it's having negative effects instead.

I am also at the moment on a trip for a job interview. As I am learning more about the position it seems more challenging and to need leadership skills beyond what I have. I would be shocked at this point, though, if they offered me the position.

Losing Model Trade and Trading Badly

The downside didn't last long... Model switches back to long this morning. The short trade lost the model 0.4%. Due to bad timing - closing my long at pretty much the low point of the down move and going short, I gave back almost all the profits I'd made for the month so far. As a result, I have gone back to trading just one contract until I can get my act together properly.  So, back to Stage 2 of the process, after attempting Stage 3...

The NQ equity curve so far this year (starts at net profits from previous years):

The problem with tactical trades is that I then need to follow the market to see whether to open or close a tactical trade. But they're not necessary for getting a good long term return from the model. It probably would be better to diversify to trade more than one market first instead, as that will result in fewer losing days if the correlation between the markets is low. So, I did recently start to build a model for oil again, though I was a bit stuck in coming up with good decision rules so far.

Turkey Turns the Outlook Bearish

The down day on Friday in response the Turkish crisis switched the model to short going forward. Based on the 3 hour stochastics, there could be a bounce on Sunday evening (US time) continuing the bounce into the close on Friday. This could be a good opportunity to go short.

Looking Bullish

The model state is almost identical with that on 10 January this year. That's presumably pretty bullish for the next week or so... Of course, anything could happen.

Backtesting and Hedged Portfolios

So, I backtested for all of 2017 using the latest model rules. The model makes money for the year, but there are several losing months, and the model underperforms the market. I could quite easily predict which months would be more profitable and which were more likely to be money losing by looking at their volatility. So, that idea works out of sample.

 

The graph shows the NASDAQ 100 index (close) for 2017 and the model return. The interesting thing is that a hedged portfolio of the market and the model, tracks the market quite closely. The hedging strategy would invest 75% of net worth in the QQQ ETF and use 25% of net worth to trade NQ futures with 3 times leverage according to the model. So it is 1.5 times leveraged with 50% of the total exposure long and 50% traded. Of course, you wouldn't really want all your portfolio into the the QQQ ETF. At least I wouldn't. But this is a step towards seeing what a realistic strategy with investment and trading would look like. Now if we look at 2018:

The hedged portfolio tracks the model, which vastly outperformed the market, closely instead now. It seems that you can get the best of both worlds with this strategy.

Soybeans

To try something different I tried a soybean daytrade. Made $107 in 17 minutes, so not bad :) But I only got the beginning of a much bigger move, so I need to be more patient in future trades i this commodity.

Volatility and Return

The graph shows the average true range (ATR) divided by the closing NQ futures price for all 14 day periods in 2018 so far and the average daily NDX model return over the same period. The correlation is very strong. The model tends to make lots of money when the market is volatile and potentially lose money when the markets are not volatile. This is why the model would have lost money in early 2017 for example and probably why the NASDAQ index produces better results than the S&P 500. Clearly, noise dominates signal when volatility is low. However, the correlation between recent volatility and future returns is quite weak. So, this isn't yet a useful tool for deciding when to trade and when not to trade on a daily or weekly basis. But if you were losing money for a while and volatility was low it would make sense to get out of that market and trade something else until volatility appeared to return.

I'm still holding the strategic long contract. It's up around $4k at the moment. I did a couple of tactical trades netting $215 and $980.

Trading on 2nd August

The market came with 4 points of stopping out the long position but then took off to the upside as soon as the New York market opened. Gain for the day was almost USD 3k. Today, I have added a second contract (@ 7391). Stop remains the same.

July 2018 Report

This month was the fourth month of the futures trading experiment. The first month was the model development phase, while May and June were about ironing out the glitches and training myself to trade the model properly (and not give in to gut instinct etc). In the first half of July I only traded one day and lost but model returns were good in the beginning of the month. Then in the second half of the month I got back into regular trading. Initially the model wasn't doing well but then things improved again as a short trade worked out.

The Australian Dollar fell from USD 0.7571 to USD 0.7432. The MSCI World Index rose 3.05% and the S&P 500 rose 3.72%. The ASX 200 rose 1.39%. All these are total returns including dividends. We gained 1.56% in Australian Dollar terms and 2.12% in US Dollar terms. So, we  outperformed the Australian market and underperformed international markets.

The best performing investment in dollar terms was Unisuper gaining AUD 4k closely followed by Cadence Capital (CDM.AX) gaining AUD 3.9k. The next best in dollar terms was Bluesky Alternatives (BAF.AX), gaining AUD 2.8k. The best performing asset class was "private equity", gaining 2.66%. The second best performer was US stocks, gaining 2.58%. The worst performing asset class was Australian large cap, gaining 0.41%.

The following is table of investment performance statistics computed over the last 36 months of data:

The first two rows gives the annual rate of return and Sharpe ratio for our investment performance in US dollars and Australian dollars. The other statistics are in comparison to the two indices. Based on beta, compared to the MSCI World Index we seem to be slightly geared, while compared to the Australian index we are less sensitive to market movements. We have a slightly positive alpha compared to the Australian and world markets. Finally, we now capture more of the up movements in the international and less in the Australian market and suffer less of the down movements in both the Australian and international markets.

This month I only made a small amount of money trading futures: USD 1.0k. The table compares my performance to the market and the model:

The US markets went up and then down. The model did outperform the market.* In the first week of July I didn't trade as I was in Japan and my phone wouldn't receive the text messages needed to log into the trading account. I actually received all these texts after returning to Australia! Then I traded long on a day when the futures price would suggest to be short and the index values suggest to be long and got stopped out. This made me do some more model research and revise the stops policy, though I found that index values provide better trading signals. After that I got back into regular trading trying to trade double the size but the model was losing at first. Then I started doing strategic and tactical trades, which helped psychologically.

We made more progress towards the new long-run asset allocation:

Total leverage includes borrowing inside leveraged (geared) mutual (managed) funds. The allocation is according to total assets including the true exposure in leveraged funds.

The improvement in allocation, came partly due to market movements and partly due to investment activity. We invest AUD 2k monthly in a set of managed funds, and there are also retirement contributions. Then there are distributions from funds and dividends. During the month, I also:

• I added another AUD 10k to the Winton Global Alpha fund, increasing the allocation to commodities.
• I added AUD 50k to the trading account and in the end was moderately successful at trading, increasing the allocation to commodities .
• I closed a small account with Colonial First State, which was invested in the CFS Geared Share Fund, reducing the allocation to large cap Australian stocks. 
• I rebalanced my CFS superannuation account, reducing the allocation to large cap Australian stocks and increasing the allocation to other asset classes.
  
• I bought 75,000 shares of BAF.AX increasing the allocation to private equity and real estate.
• I sold my position in PIXX.AX and bought a smaller amount of Platinum Capital (PMC.AX) and bought more as PMC fell further in price. This reduced the allocation to hedge funds.

* The statistics at the bottom of the table are based on only 4 months of data and so are not at all reliable yet.

Back to the Long Side

Closed short and opened long @ 7261.5. Stop is @ 7211.

The model switched to long today but the signal is close to remaining short and the intraday indicators are signalled short for the first part of the day. So, I kept the short position until now almost 7 hours into the trading day from 6pm New York time (8am Eastern Australian time). I put on a ten point trailing stop for two contracts, so it closed the short and opened a long simultaneously. Gained about 25 points on the short side compared to the market open.

Profit from the closed short was USD 3,000.90. The model gained 1.73% for the trade starting on 25 July and ending 1 August.

Monthly report coming soon.

Friday 27th July Trading

Finally we had some good downside on Friday with the NQ futures falling 126 points to 7299.75 – each point is $20 per contract. I had a strategic short from 7411.75 and a tactical short put on in the morning at 7429.5. My only regret is that I closed the tactical short at 7380 for only a $986 profit rather than setting a wider stop and letting it ride down for another $1600 in profit :) The strategic short is of course still in place as the model remains short. I am now up $885 for the month. Hopefully, I will stay up for the last couple of days of the month. I expect the market will go down further, both the model signals and looking at previous declines this year suggest that there is a lot further to go down before bottoming. All the previous declines went below the 34 day moving average and two went to the lower 34 day Bollinger Band:

If the latter happens, we would be at 6950 or so, $7,000 a contract from where we are now. Of course, given the strong trend it is more likely to be like the declines in April and June, which didn't reach the lower Bollinger Band.

Indications at the moment are that we don't want to do a tactical short during the US overnight on Sunday-Monday. A short near the US market open looks more likely to pay off.

Trading in 2018 is Objectively Better

I computed my average gain per NQ contract traded in 2006-2008 compared to in 2018. In 2006-08, on average I gained 0.46 points per contract traded or $9.31. Commissions on a roundtrip were $4.80 then. In 2018 so far, I made 3.69 points per contract or $73.74. Commissions are now $4.10 on a roundtrip. So, my trading now is almost an order of magnitude better. The average is brought down by lots of small daytrades I've done. As I plan to do fewer of those, the average should improve, I hope. On the other hand, the level of the index is now nearly 4 times higher than it was in 2006-8 and so a given percentage price move translates to more points.

This graph shows the equity curve on NQ trades - the actual number of trades is half this as there is one data point for each opening or closing of a position. Initially in 2006-7 I had a reasonably good increase in profits, peaking around $10k cumulative profit. Then there was a long slow decline into 2008 of a series of small wins, punctuated with larger losses. The big jump is the start of trading in 2018,  when I had a series of big wins. Since then, things have gone sideways, with losses equal to gains.