Strategy : Sell at retracement
Friday, February 25, 2011
STI
Strategy : Sell at retracement
Thursday, February 24, 2011
Portfolio update
ABTERRA
Uptrend still intact but weakening. Currently, still in consolidation period.
Strategy - Buy at lower Bollinger/trendline (1.27) and sell at upper Bollinger/trenldine (1.39).
AIMS
Downtrend.
Strategy : Sell at resistance (0.215/0.210)
ANNICA
Downtrend
STRATEGY : Wait for reversal
CHINA SPORT
Weekly chart showing sideways but RSI going downwards.
Strategy : Wait for daily ADX downtrend reversion and buy in.
Note : Because my hand gatal, so today went in at 0.095. May go lower than this in next few days.
COURAGE MARINE
Monthly, Weekly, Daily Chart all shows sideways.
Regretted getting into this stock by impulse.
Strategy : Buy at bottom and sell all at top of Bollinger.Not worth keeping this stock.
EUNETWORK
Wait for 0.01 and 0.005
RAFFLES EDU
Weekly chart shows still downtrend. Daily chart shows some trend starting soon.Dunno whether downtrend or uptrend.
STRATEGY : Wait and see
Strategy - Buy at lower Bollinger/trendline (1.27) and sell at upper Bollinger/trenldine (1.39).
AIMS
Strategy : Sell at resistance (0.215/0.210)
ANNICA
Downtrend
STRATEGY : Wait for reversal
CHINA SPORT
Strategy : Wait for daily ADX downtrend reversion and buy in.
Note : Because my hand gatal, so today went in at 0.095. May go lower than this in next few days.
COURAGE MARINE
Regretted getting into this stock by impulse.
Strategy : Buy at bottom and sell all at top of Bollinger.Not worth keeping this stock.
EUNETWORK
Wait for 0.01 and 0.005
RAFFLES EDU
Weekly chart shows still downtrend. Daily chart shows some trend starting soon.Dunno whether downtrend or uptrend.
STRATEGY : Wait and see
Monday, February 21, 2011
Sentiment Indicators - ING Investor Dashboard Sentiment Data - Student's Post
Quote of the Day: “Far from the madding crowd’s ignoble strife, Their sober wishes never learned to stray; Along the cool, sequestered vale of life They kept the noiseless tenor of their way”
It’s too much to expect that Investor Sentiment surveys have any kind of normal predictive value – usually, the only way they are used in the US is in contrarian manner, taking the surveyed investors as “dumb money” that buys at the tops and sells at the bottoms. Here we investigate the Singapore and HK corollary of these surveys.
A few points to note:
Takeaways for investors
It’s too much to expect that Investor Sentiment surveys have any kind of normal predictive value – usually, the only way they are used in the US is in contrarian manner, taking the surveyed investors as “dumb money” that buys at the tops and sells at the bottoms. Here we investigate the Singapore and HK corollary of these surveys.
A few points to note:
- This survey only began in Oct 2007, and is done quarterly, so we don’t have a lot to go on. Q3 2010 is also not posted on the website – you can only find it here after some hard searching.
- To their credit, investors actually turned neutral in early 2008 BEFORE the massive drop in the indexes in late 2008 – but only turned truly pessimistic after the drop. Hong Kong investors embarrased themselves going optimistic again during the drop.
- Slow on the uptake. SG and HK investors remained pessimistic until the recovery was well and truly underway, with most of the profits from that already gone.
Takeaways for investors
- The ING Sentiment Index appears to have no conventional predictive value in crisis times.
- It is also of limited contrarian value in non-crisis times – sentiment has stayed well above Optimistic levels for the entirety of 2010 when markets did indeed go up.
- However SG and HK sentiment have been optimistic for a very long time, and have already dipped once. I do not think it would take a lot for this sentiment to reverse.
Sentiment Indicators - Ignore the Singapore Purchasing Manufacturers’ Index - Student's Post
For a mere sentiment measure, the PMI is widely watched by economists and stock people for some strange unknown reason. Here is the SIPMM’s self-description of the PMI, with absolutely no sense of irony:
(Please switch the t-1 and t+1 on the above graph as that makes more intuitive sense.)
If you squint you can see that the explanatory power of the PMI on the STI is no more than 10 basis points as a coincident indicator, and 15 bps as a leading indicator. On the other hand, the PMI does fabulously as a lagging indicator, explaining 112 bps. By means of comparison, the explanatory power of last month’s STI return on this month is 44 bps.*
Full data is uploaded at the usual place.**
The fact that all these media outlets report this essentially useless data exemplifies the difference between “news” and “news you can use”. We are looking for tomorrow’s weather forecast, but many of the radio stations we tune in to simply talk about yesterday’s weather. ‘Nuff said.
*While the 112 vs the 44 seems strange, this finding is consistent with the human experience that it is much easier to explain the past looking backward (PMI) than it is to explain the future looking backward (STI return t-1).
**By comparison, HK’s PMI does not even keep a historical record and is released only infrequently according to Bloomberg. A sorry state of affairs for sentiment indicators in general.
The Singapore PMI has become a key barometer of the Singapore manufacturing economy and has been highly sought after by local and international news agencies, banks, investment and stock-broking firms. The Singapore PMI is published monthly in the major language press media, such as The Straits Times, The Business Times, The New Paper, Chinese Daily News LianHe ZaoBao and the Malay Daily News Berita Harian. The index is also reported regularly in the international media, as well as economic and research agencies worldwide. In addition, the Channel News Asia and News Radio 93.8 also broadcast the monthly news release of the index.Any index that is pleased to be reported by The New Paper must have some serious psychological issues going on. Here is my take on the PMI:
(Please switch the t-1 and t+1 on the above graph as that makes more intuitive sense.)
If you squint you can see that the explanatory power of the PMI on the STI is no more than 10 basis points as a coincident indicator, and 15 bps as a leading indicator. On the other hand, the PMI does fabulously as a lagging indicator, explaining 112 bps. By means of comparison, the explanatory power of last month’s STI return on this month is 44 bps.*
Full data is uploaded at the usual place.**
The fact that all these media outlets report this essentially useless data exemplifies the difference between “news” and “news you can use”. We are looking for tomorrow’s weather forecast, but many of the radio stations we tune in to simply talk about yesterday’s weather. ‘Nuff said.
*While the 112 vs the 44 seems strange, this finding is consistent with the human experience that it is much easier to explain the past looking backward (PMI) than it is to explain the future looking backward (STI return t-1).
**By comparison, HK’s PMI does not even keep a historical record and is released only infrequently according to Bloomberg. A sorry state of affairs for sentiment indicators in general.
Sentiment Indicators - The Singapore PMI and ST Sector Indices - Student's Post
Armed with sector information from the FTSE, I have followed up on the prior post looking at the PMI and the STI. The PMI is a sentiment index of purchasers in the manufacturing industry, so I have identified the relevant sector indices to be the FSTBM, FSTIN, and FSTCG, corresponding to the Basic Materials, Industrials, and Consumer Goods indices. I then ran a simple regression on their returns, much like the prior post:
We can see that the PMI doesn’t do that great as a coincident indicator on any of the relevant sectors; the best we get is 34 basis points, and as mentioned in the prior post you can get 44 bps just wagering that this month’s returns are the same as last month’s. In other words, even if you somehow managed to get insider info on the PMI or forecasted the PMI accurately (also suspect; I have recorded PMI survey data on my data subsite for your perusal), you would not be likely at all to make much alpha.
Nothing to write home (or here) about.
However, great news is about “man bites dog”, and a little messing around with the lags show this:
This shows the same regression run on the PMI lagged by 1 month. The R-squared on all three sectors leaps by 7x, 4x, and 9x respectively – in particular, the previous month’s PMI seems to explain almost 3% of the FSTCG Index’s movements over this past decade (N=135). This is a magic number – some quants say that “People have gotten rich off of a 2% r-squared” – however an adult user of statistics would not get overly excited about this if only because the sample size is still not that impressive.
I know some of this talk about R-squared puts some people off, so here’s a simple trading rule conclusion you can make from this study:
When the PMI minus 50 was lower than -0.4 (purchasing managers were bearish), the FSTCG moved up 2.59% in the next month on average. When the PMI minus 50 was above 2.1 (bullish), Consumer Goods stocks dropped on average. The current PMI is at 50.7.
We can see that the PMI doesn’t do that great as a coincident indicator on any of the relevant sectors; the best we get is 34 basis points, and as mentioned in the prior post you can get 44 bps just wagering that this month’s returns are the same as last month’s. In other words, even if you somehow managed to get insider info on the PMI or forecasted the PMI accurately (also suspect; I have recorded PMI survey data on my data subsite for your perusal), you would not be likely at all to make much alpha.
Nothing to write home (or here) about.
However, great news is about “man bites dog”, and a little messing around with the lags show this:
This shows the same regression run on the PMI lagged by 1 month. The R-squared on all three sectors leaps by 7x, 4x, and 9x respectively – in particular, the previous month’s PMI seems to explain almost 3% of the FSTCG Index’s movements over this past decade (N=135). This is a magic number – some quants say that “People have gotten rich off of a 2% r-squared” – however an adult user of statistics would not get overly excited about this if only because the sample size is still not that impressive.I know some of this talk about R-squared puts some people off, so here’s a simple trading rule conclusion you can make from this study:
When the PMI minus 50 was lower than -0.4 (purchasing managers were bearish), the FSTCG moved up 2.59% in the next month on average. When the PMI minus 50 was above 2.1 (bullish), Consumer Goods stocks dropped on average. The current PMI is at 50.7.
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