Compared to the FX market which i’ve been trading it for the past 6 years now, this HSI market is such a volatility heaven. Its 1min chart has a nice form that’s very suitable for technical trading, thus providing lots of opportunity for doing intraday scalp trades. But need to keep tight SLs because the volatility can also bring hell up to the surface. lol.
(*)
I am going to base the following view with a certain definition of trend following: entering trades when the market start to go in a certain way, maintaining the open trades as long as the market still move in the same direction, and finally exit the trades when the expected trend discontinued. Purely following. The purest form of this strategy can be seen in Curtis’ white paper that was able to be downloaded freely in his website several years ago. Another form of a pure trend following system can be found in Michael Covel’s first book.
So..
In my experience, trading intraday in the FX market by purely following the trend like that, wouldn’t work as good as when we do a pure trend following system in the daily timeframe. The volatility behavior of the intraday price movement would kill the system by producing too many whipsaws. Even if we used some advanced entry technique to exploit a running trend by using multiple entry like what the turtles do, the wild volatility in intraday FX market is a beast can not be tamed with that prescription.
Using a pure trend following system to trade the intraday FX market would be like asking Mr. Bean cleaning your office desk. It would be such a terrible mess. lol.
Intraday market has its own characteristic, thus need to be handled with different approach.
Would elaborate more into that in another posts next time.
(*)
.
Several short term trading systems we have been developing for the FX market relays heavily on the distinctively unique and consistent nature of volatility behavior between market’s sessions.
We even haven’t found any ways to substitute our time-constraint filters with something purely derived from price-only data. It’s like we actually have a different kind of market for each session that is divided by a rigid time mark, not by some hints those can be found in price action.
This has been bringing some serious thought for us, because we thought that we have to stick to our philosophy to relay our systems purely on price action. But then we realize that the market has the dimension of time along with the dimension of price.
And to our surprise, I found this interesting observation by Mr. Steenbarger, Ph.D. In one of his post today in his blog, he stated a similar conclusion as ours:
What we can see is that these seem to be different markets. Indeed, the daily correlations among the three range from .12 to .18, suggesting that what the market does during one time period is only very weakly related to what it will do in the next one.
Although his research is about the stock market, particularly the S&P, this has put us into believing that time dimension is very truly exists, as we also been observing the same phenomenon in the FX market.
This confirmation from Mr. Steenbarger’s research has put a new item to our research agenda, that we will need to check market’s average range for each session. This would probably be useful for developing a better opening range breakout model, by having a better measurement of the opening range width. And for our range trading model, we might get a better basis for the entry and exit strategy. The keyword would be determining the historical and average range of sessions.
(*)
.
———- Forwarded message ———-
From: Darma
Date: May 10, 2007 10:05 PM
Subject: Penurunan volatilitas short term: penyebab dan aplikasi praktisnya
To: indotraders@yahoogroups.com
Dear traders,
Kalau kita pasang indicator ATR (Average True Range), di timeframe 15 menit, dengan periode 15 bar, lalu dipasang moving average nya dengan periode 100 bar, maka kita mendapatkan suatu gambaran seberapa banyak gerakan rata2 per satu bar di 15 menit.
Nah, ternyata ada fenomena menarik.
Kalau di tahun-tahun dulu, misalnya di tahun 2005, rata-rata gerakan per 15 menit di EUR/USD adalah 13 pips (lihat gambar chart di bawah). Sedangkan di tahun-tahun sekarang ini, semenjak tahun 2006 november, gerakan market menjadi lebih tipis. Rata2 hanya 6 pips per 15 menit.
Hal yg sama terjadi di GBP/USD, USD/JPY, USD/CHF dan lainnya.
Penyebabnya adalah: meningkatnya likuiditas market. Yang tadinya rata2 volume transaksi harian di forex adalah $ 1-2 trilliun per hari, semenjak pertengahan 2006, menjadi $ 3 trilliun per hari. Ini menurut report dari BIS (Bank for International Settlement).
Aplikasi praktis dari hal ini adalah:
Untuk trading di short term, intraday, tidak lagi realistis untuk mengharapkan takeprofit seperti di tahun-tahun sebelum 2006. Yang tadinya di GBP/USD mengharapkan bisa take profit 15-20 point dalam waktu 30-60 menit, kini hal itu agak sulit. Mesti di jam2 tertentu saja yang memang volatilitas meningkat seperti saat ada news. Kalau di jam-jam normal, dalam waktu 30-60 menit lebih mudah untuk bias ambil 10-12 pips saja. Itu contoh angka untuk di GBP/USD. Sedangkan untuk di EUR/USD, mesti dilihat masing2. Pasang saja indicator ATR dan moving average seprti gambar di bawah ini.
Ini tentu sejalan dengan menurunnya spread di retail spot di hampir semua broker di dunia. Yang misalnya saja tadinya spread 5 pips di FXCM dan marketmaker lainnya, sekarang rata2 udah pada turun. Spread 2-3 pips sudah lumrah sekali. Bahkan belakangan ini kita lihat spread aneh 1 pips no commission di marketmaker nekat seperti crown dan fxclearing. Kalau di bntuk2 ecn sih biasa, memang 1-2 pips dari sejak mereka hadir untuk retail sejak tahun lalu.
Segitu dulu. Selamat mengeksplorasi lebih jauh lagi. Kalo ada pendapat atau ide lain, silahkan disampaikan.
Rgrds,
Darma
Continuing my recent research on market volatility, i found this report from Bank for International Settlement (www.bis.org). The report can be downloaded from this link (pdf).
My observation on this change in market bahavior is confirmed in the report:
The evidence presented in this Report shows that over the period from mid-2004 to March 2006 the volatility of short-term and long-term interest rates, stocks, exchange rates and corporate spreads has been generally low relative to the previous five to 10 years in both industrial countries and emerging market economies (EMEs). However, if the sample period is extended back to the last two to three decades, for which daily data are available, other periods in which volatility reached similar low levels can be observed. The exception is represented by the volatility of short-term interest rates, which has reached its lowest level for 20 years in all the main currency areas.
Regarding the possible causes of this are:
The sharp decline of financial volatility witnessed over the last few years may have benefited from increased liquidity of financial markets. Since this concept is not easy to operationalise, it is useful to look at several indicators.
Throughout the sample the turnover of stock markets has increased considerably, and now stands almost everywhere around the highest levels since 1990. In the foreign exchange markets volumes were virtually flat over the period 2000-02, but since 2003 an upward trend has emerged.
In recent years financial innovation and the rise of new classes of financial institutions, combined with a change in the trading behaviour of traditional institutional investors, have contributed to increasing market liquidity.
And something more interesting is this part:
A key issue is whether the current low level of volatility is a permanent new feature of financial markets or only a temporary phenomenon. The results suggest that important drivers of the volatility reduction seem to be structural, and may therefore have a permanent effect on volatility.
So ? Less volatility. Smoother charts ? My quick guess is this: trend following strategy may perform better on lower timeframe.
Another good material was posted in my friend’s blog here, tittled “Market Effects of Hedge Funds”.
I’m so happy when last night I found this bug (line 255):
cond_exit = COND_EXIT_BUY;
close_order(OP_BUY, MAGIC_NUMBER_SELL);
Using this MAGIC_NUMBER_SELL on the last line, has made the system unable to close the appropriate BUY trades.
Now it has been fixed to be like this:
cond_exit = COND_EXIT_BUY;
close_order(OP_BUY, MAGIC_NUMBER_BUY);
and for documentation purpose, i’ve put these additional lines:
// vy5 – fixing prm_use_calc_tp wasnt working well in vy4
// – possibility to turn off all logging
// – fixing hedge filter for sell
// vy5b- fixing prm_exit_when_opposit on buy trades was wrong, now fixed
// – putting optimized values on external parameters
These things happen often because of the the copy n paste practice on the initial development stage. It is now named as vy_5b.
I’m replacing the previous vy5 version to the trading server now.
The change will take effect from tonight.
Good luck to us.
This article in Covel’s website once again shows how profitable traders/fund managers do their trading.
Despite
I met with an old pro trader yesterday in his NYC office. He runs one of the largest clearing firms on the NYMEX. He has his unique way of doing things and clearly is not a trend follower. That said, his concern about knowing how to take losses properly echoed the wisdom of Wall Street’s great trend traders. His most interesting comment was about the word “despite”. He loved to see the word. For example, if you see the talking heads saying, “Despite bad news Apple stock went higher”, he would view that as an opportunity to go long even more. Conversely, if he saw “despite good news, Apple went lower”, he would go short. He wasn’t trying to preach fundamentals or “news” reading, but just wanted to pass along his insights from the last 20 years. Sure, it was short and simple wisdom, but then again most good Wall Street wisdom is that way, the hard part as he reminded me is the execution.
A quick note: DESPITE of whatever the news and fundamentals say, they trade the price. But this doesn’t mean they use technical analysis mumbo jumbo. Not analysis. Not prediction.
It has been since January, a basic-to-advance training session, delivered for the TGF’s people.
I hope they will be more than ready for the next step, running some of our mechanical trading systems.
———- Forwarded message ———-
From: Darma
Date: Feb 18, 2007 5:28 PM
Subject: short term trading
To: indotraders@yahoogroups.com
Dear friends,
sharing dikit ya…
kalo ada pihak2 yg kurang berkenan, mohon maaf sebelumnya ya.. maklum deh saya ini masih belajar..
pertama2 saya mohon maaf karena selama ini jadi jarang posting di milis kita ini.
Itu karena selama ini sibuk sendiri, riset, fokus (ngikutin saran/sindiran dari jack, jussi dan eugene,hehehe).. No time for gossip milis…
Sekaligus saya mau sampaikan maaf juga dari teman2 lainnya yg dulunya adalah frequent poster di sini. Mereka juga asik trading, riset, etc.
Dari beberapa yg saya temui beberapa bulan ini, mereka sempat bilang: “aduh gak enak ama temen2 di milis, kita jarang sharing2, abis lagi seru sih, lagian kalo sharing2 ntar malah dibilang sok pamer” he he he.. Maklum deh, belakangan ini sering ada black campaign dalam rangka memajukan milis tertentu, padahal apa sih untungnya punya milis yg rame ya, kecuali utk orang2 pengangguran yg gak punya kerjaan lain, he he he…
Oke, enough for the basa basi.. Now let me start..
di lembaran2 yg lalu, saya selalu sebut: profitable trading dengan long term trend following itu jelas2 nyata.
Saya selalu sebut contoh turtle system yg dari curtis faith, yg kemudian kami bikin EA nya exactly as the said rules, hasilnya bener2 profit. Kami modifikasi, hasilnya bahkan lebih cantik lagi. Begitu juga dengan sistem “Aberration” yg pakai deviasi, alias Bollinger band, yg juga mengadopsi filosofi long term trend following, jelas2 profitable.
Gak ada prediction, gak ada hal2 canggih, hanya averages, deviasi, true range, etc..
Profitabilitas sistem2 di horizon long term itu sangat ditentukan oleh lengkapnya suatu sistem. Gak cuman entry – exit. Karena kalau mengandalkan entry-exit polos, sistem yg entry di 55 day b/o, exit di 20 day b/o, pasti bakalan losing. Apalagi yg entry di b/o bands, exit di b/o bands lainnya. Ugly banget deh..
Tapi ternyata, karena adanya komponen risk management (position sizing, pre-determined SL), trailing exit, dan multiple entry utk memanfaatkan trending session semaksimal mungkin, akhirnya suatu sistem yg sangat simple malah menjadi profitable.
Itu cerita saya di lembaran2 yg lalu. Namanya juga org lagi belajar selalu kena sindrom kaget, baru tau kayak gitu saya pikir: “that was the ONLY answer”..
Tapi ternyata perjalanan belum selesai. Sistem long term kayak gitu nggak feasible utk dijalankan kalau hanya mentradingkan capital $5k, apalagi cuman $400. Kecuali kalau trading itu hanya hobby. Baru layak dijalankan secara komersial kalo ada capital 100k ke atas, itu pun dengan efisiensi di komponen2 fixed cost. “Gak nendang” banget deh…
So, akhirnya, berangkat dari hasil belajar sebelumnya, lanjut bertapa lagi, riset lagi.
Kerangkanya masih sama: systematic trading, yg ujung2nya bisa di-mekanisasi.
Hasilnya: Short term trading si doable. Mission very possible.
Kuncinya:
– FX market punya pola volatilitas intraday yg sangat siklik. Hal ini termanifestasi pada batasan penggunaan suatu sistem tertentu pada jam2 tertentu saja. Akhirnya bakalan ada saat2 di mana kita menggunakan prinsip mean-reversion, dan ada saat2 di mana kita bisa menggunakan prinsip momentum.
– Profil Risk-to-Reward ratio per single trade nya ternyata inverted.
– Penentuan SL dan TP mengacu pada gerakan rata2 historical per satuan waktu tertentu, dilakukan dgn menarik value dari ATR (average true range), sehingga didapat suatu sistem yg sangat robust: menggunakan parameter yg sama utk semua currency pairs, dan profit di semua pairs. Robust.
Jadi, teman2 seperjuangan ku di sini, let me tell you here: jangan menyerah. Jangan berkecil hati.
Kalau gak percaya my story, berikut saya sertakan kutipan tulisan dari blog nya covel, komentar ed seykota dan covel tentang short term trading:
http://www.michaelcovel.com/archives/000314.html
Rgrds,
Darma
===========================================
http://www.michaelcovel.com/archives/000314.html
Ed Seykota was recently asked in his forum:
“I am new to trend following and wish to ask you what your favorite chart is for determining a given market’s trend? Daily, Weekly, Yearly, Hourly?”
Ed responded:
“Hmmm…your list seems to lack scaling options for minute, second, and millisecond. If you want to go for the really high frequency stuff, you might try trading visible light, in the range of one cycle per 10-15 seconds. Trading gamma rays, at around one cycle per 10-20 seconds, requires a lot of expensive instrumentation, whereas you can trade visible light “by eye.” I don’t know of even one short-term trader, however, who claims to show a profit at these frequencies. In general, higher frequency trading succumbs to declining profit potential against non-declining transaction costs. You might consider trading a chart with a long enough time scale that transaction costs are a minor factor – something like a daily price chart, going back a year or two.”
I agree with Ed’s pithy wisdom, but he is not saying short term is impossible.
There do exist shorter term systematic traders who have done quite well (Toby Crabel, Jim Simons). They would agree with Ed that their style is hard. The shorter you go the more you need great execution, fantastic data and multiple systems. To be a great shorter term mechanical trader is a different animal than trend following, but it is a style that a select few have mastered.
============================================
..
Dear friends..
I’ve came to a conclusion from several short term and long term systems that I know up to now.
Short term systems usually produce these outcomes:
Meanwhile, long term trendfollowing systems have the opposite profile:
Short term systems includes the bolltrade, the multilot systems, the short term breakout systems, etc.
Long term systems includes the turtles, the aberration, and several others.
They all pretty consistent with those profile I mentioned.
Any other system developers here observe the same situation ?
Rgrds,
Darma
(*)
Finding a robust short term trading system is not impossible ? Well, maybe. But sure it is a hard task. Given these 3 reasons below, research on a robust ST TS is very appealing:
1. Math
Higher frequency of trades enables increasing positions size faster in a given period of time (compounding) during run-ups, but also enables decreasing positions size faster during drawdowns.
2. Source of profits
Long term trend-following / Turtle System captures profits from existence of trends (trends often connected with macro-economic cycles). As we all know, markets tend to move in trends but also experience long “choppy” periods, without any substantial move in one direction. Hence diversification is used to reduce negative impacts of non-trending periods in a single markets. Unfortunately, most liquid markets are highly correlated. As a result, these strategies performance depend on the magnitude of trends.
Short term trading captures profits from market inefficiencies, more precisely – from market’s over-reactions. If we’ll sum up all inefficiencies in the short-term level, they’ll add up to a greater amount than in the long-term level. Of course in order to play on short-term basis we must have low commissions and high liquidity – two things which have dramatically improved since ’90s or ’80s.
3. Predictability
Volatility in the coming short-term periods is more predictable than in the long-term periods. Try to estimate the average daily range for the next 5 days. Now try to predict the average yearly range for the next 5 years – error will be much bigger.
To add more on the research, here is some other resources to be read later:
Traderclub Forum
One member of the tradingblox forum, Mr. Cyphrograph (from Poland), brought this topic to the forum
Short term VS Long term trading.
Hello everyone. I guess I’m 3rd member from Poland on this forum, together with TK and steady_jake. We had some hot discussion on a polish futures message board, and now I want to continue it at “Trader’s Roundtable” as I believe it is more suitable for that kind of discussion. Here’s the hypothesis: Short term trading can reach the level of robustness (or performance), which can not be achieved by long term methods or long term trend-following systems or – let’s be straight – Original Turtle System. The question I want to ask you is: can we verify the above hypothesis using historical results (hypothetical from backtesing or actual trading figures)? IMHO, Yes we can do it. Since our abilities to predict future are weak, what else do we have beside history? Well-known method used for predicting possible outcomes, namely Monte Carlo Simulation is based on historical figures also.
I want to present a little research I’ve done on this subject. Let’s compare actual trading performance. Turtles vs Active Traders battle. We take 3 famous Turtles on one side (B. Dunn, J.W. Henry, W. Eckhardt) and 3 quants who employ short-term trading methods on the other (T. Crabel, Denali, C-View Limited). Let’s take 2 ratios for measuring robustness / risk-adjusted return / performance quality (name it like you want):
1. Compounded Annual Return / Worst Drawdown (CAR/WDD, monthly basis) – before management and incentive fees,
2. Annualized Sharpe.
Turtles camp:
DUNN Capital Management-DUNN WMA (Nov 84 – Sep 03)
CAR/WDD 0.52, Sharpe 0.64
John W Henry & Company-Financial and Metals (Oct 84 – Aug 03)
CAR/WDD 0.91, Sharpe 0.83
Eckhardt Trading Standard (Jan 87 – Sep 03)
CAR/WDD 1.38, Sharpe 0.75
Active Traders camp:
Crabel Cap. Mgmt-Diversified 1XL (Jan 92 – Sep 03)
CAR/WDD 3.77, Sharpe 1.38
Denali Asset Management-Ascent (May 99 – Sep 03)
CAR/WDD 10.26, Sharpe 2.75
C-View Limited 3XL (Oct 96 – Aug 03)
CAR/WDD 5.62, Sharpe 1.66
Source: www.iasg.com
Disclaimer: I’m not connected with any managers mentioned above.
Well, numbers speak for themselves 
As you may suspect, figures for short term systems backtested and optimized against the past data are much, much better – especially, when you set worst drawdown figure to around 40% by position size management rules.
Turtles camp has one advantage over active traders: they have longer track records. However, I don’t want to wait 15 years in order to have comparable periods. That is the zillion dollar question: will these excellent CAR/WDD & Sharpe figures sustain in the future?
Where are the grounds for differences between short and long term trading performance? IMO, they’re located in 3 main areas:
1. Math
Higher frequency of trades enables increasing positions size faster in a given period of time (compounding) during run-ups, but also enables decreasing positions size faster during drawdowns.
2. Source of profits
Long term trend-following / Turtle System captures profits from existence of trends (trends often connected with macro-economic cycles). As we all know, markets tend to move in trends but also experience long “choppy” periods, without any substantial move in one direction. Hence diversification is used to reduce negative impacts of non-trending periods in a single markets. Unfortunately, most liquid markets are highly correlated. As a result, these strategies performance depend on the magnitude of trends.
Short term trading captures profits from market inefficiencies, more precisely – from market’s over-reactions. If we’ll sum up all inefficiencies in the short-term level, they’ll add up to a greater amount than in the long-term level. Of course in order to play on short-term basis we must have low commissions and high liquidity – two things which have dramatically improved since ’90s or ’80s.
3. Predictability
Volatility in the coming short-term periods is more predictable than in the long-term periods. Try to estimate the average daily range for the next 5 days. Now try to predict the average yearly range for the next 5 years – error will be much bigger.
We are now working on several systems. They are counter trend typed system and swing trading system.
As those previous systems, the development are conducted on MT4 platform, partnering with Balidev’s engineers.
FOREX QUANT 
