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.