2008 Jun 15 - Sun
Mean Reversion Thoughts
While still putting together the code for a trading solution, I've been thinking about
what algorithms to implement for a trading strategy. I have access to live intra-day tick
and quote data, so mean-reversion aka contrarian strategies seem like interesting
candidates.
In the course of manual trading, I've learned that one needs to keep track of a number of
items: current portfolio costs, current holding costs, existing profit/losses, expected
market direction, current market location, external influences. This is a lot to do
manually. Hence the desire to implment tools to automate, or even semi-automate the
process.
A paper by Subramanian Ramamoorthy called
A strategy for stock trading based on multiple models and trading rules
discusses a state space mechanism for determining how to manage the portfolio composition.
Another item he brings to the foreground is a description of the Sharpe Ratio, a ratio which
helps one to keep profit consistent rather than widely dynamic.
Using different terminology, the makers of NeoTicker have a blog with an article called
Counter-Trend Trading with Simple Range Exhaustion System. The key point, which could
be hard to do, is "most counter-trend traders will try to time their entries as close to the
extreme reversal points as possible to maximize the profits and minimize the risk
exposures". Using multiple time frame charts, and
reading the tape, along with some possibly helpful technical analysis tools, it might be
possible to home in on the zones of reversal.
Working my way into a little scalping in the futures, an older article at Interactive
Brokers explains the birth of the
Dow Mini Futures. Some interesting points:
- "try to identify the leader in a group and how its price movement can help us predict
movement in others in the group"
- "we start to trade it by hand so we can get a better understanding of the nuances in
that particular trade"
- "We have a trader and a programmer trade together for a while and then we start the
process of automation. We define our risk parameters and write the rules that we feel give
us an opportunity to be profitable."
- "In our back testing we saw that if we were patient it would be profitable for us. The
hard part was learning to be patient because our other successful trades were very high
frequency. In the mini-sized Dow we may be in and out of 5 to 10 trades in a less than
minute."
- hedge the mini dow with the underlying basket of stocks
- "We don't have scalping targets. We generate a theoretical value and make markets
based purely on that value If we our pricing is accurate and we should naturally be able to
scalp."
- "In the Dow because the bid-ask spread is so tight most of our profits are generated
from trading."
- "he dow has a much tighter spread compared to the mini-spu. Also it is much easier to
watch the stocks in the underlying basket to ascertain their effect on the future."
- "The Russell tends to be trendier than other indices."
[/Trading/AutomatedTrading]
permanent link
Adaptive Arrival Price
A keynote lecture at the April 7th Algorithmic Trading Conference in London was by Mr.
Julian Lorenz of ETH Zurich. The abstract for his lecture reads as follows:
Electronic trading of equities and other securities makes heavy use of "arrival price"
algorithms, that balance the market impact cost of rapid execution against the volatility
risk of slow execution. In the standard formulation, mean-variance optimal trading
strategies are static: they donot modify the execution speed in response to price motions
observed during trading. We show that with a more realistic formulation of the mean-variance
tradeoff, with no momentum or mean reversion in the price process, substantial improvements
are possible by using dynamic trading strategies. We develop a technique for computing
optimal dynamic strategies to any desired degree of precision. The asset price process is
observed on a discrete tree with a arbitrary number of levels. We introduce a novel dynamic
programming technique in which the control variables are not only the shares traded at each
time step, but also the maximum expected cost for the remainder of the program; the value
function is the variance ofthe remaining program. The resulting adaptive strategies
are"aggressive-in-the-money": they accelerate the execution when the price moves in the
trader's favor, spending parts of the trading gains to reduce risk. The improvement is
larger for large initial positions.
I think I'll add 'arrival price algorithms' to my key word searches. The above extract
was from a search on 'mean reversion trading system algorithms'.
[/Trading/AutomatedTrading]
permanent link
2008 Jun 08 - Sun
Stocks & Commodities, 2008/06
In a recent issue of Technical Analysis of Stocks and Commodities, there was an interview
with Tom Busby. A number of his comments struck home with some things I've learned. He
also introduced a few more things about which I should think.
He noted that trading can be a twenty four hour operation. There is always some market
open to trade. The world starts off with the Nikkei and the Hang Seng in the far east. In
Europe, primary markets are CAS, FTSE, DAX and the Swiss. I'd say in today's market the
IPE, with the Brent Crude Futures, is also important. Here in the west, we have the morning
New York market and the afternoon California market.
Busby made mention that 'market open' is an important event. As such, it is important to
know the time each of the markets open. I've been working on an algorithm that selects a
series of instruments, selects a direction and lets the instruments run. I've been
wondering what to set for an exit though. Busby, in the interview,
suggests exiting once a third of ATR
(Average True Range) has been reached. I'm not sure why he would use ATR (which accounts
for any opening gap) rather than just the daily average range. Assuming one gets in
sometime in the open, and exits by the end of the day (in order to eliminate what gaps in
the wrong direction can do to one's portfolio), then using ATR doesn't seem quite right.
Anyway, To set the tone for a trading day, he suggests some benchmark indexes to be
watched. Seven, which he calls the Seven Sisters are:
- S&P
- NASDAQ
- Dow Jones Indexes
- DAX
- Crude Oil
- Long Bonds
- Gold
As for micro-signals, he uses three kinds, with each needing to be in the same direction:
- Volume
- Tick (gainers vs loser)
- Trend
To finish things off, he suggests splitting an entry into three parts:
- Tick Part: the trickiest part of the entry based upon the three variables above
- Trade Part: with confidence building, try to make twice the reward vs risk
- Trend Part: capture the full movement of the day
[/Trading/ReadingMaterial]
permanent link
2008 Jun 06 - Fri
SmartQuant QuantDeveloper & DataCenter Release
SmartQuant has released a revision
to DataCenter and
QuantDeveloper. DataCenter and QuantDeveloper are at the following revision levels:
DataCenter
Version 3.0.2 (06-Jun-2008)
QuantDeveloper Enterprise Edition
Version 3.0.2 (06-Jun-2008)
QuantDeveloper Source Code
Version 3.0.1 (21-Apr-2008)
* Recent Versions available through
version control
[/Trading/SmartQuant/Releases]
permanent link
2008 May 31 - Sat
Decision Trees, Automated Trading, Simulations, and Strategies
A paper called
Stock Picking via Nonsymmetrically Pruned Binary Decision Trees by
Anton V. Andriyashin discusses a method for picking stocks for inclusion in a portfolio. By
integrating technical analysis with binary decision trees, the author indicates that
"BNS clearly outperforms the traditional approach according to the backtesting results and
the
Diebold-Mariano test for statistical significance", where BNS is Best Node Strategy. David
Aronson of Evidence Based Technical Analysis fame may call the use of some the technical
indicators as 'so much snake oil', the paper, at its heart, does describe a methodology for
selecting a potentially profitable portfolio if one can use alternate forms of trading
signals.
Alternate forms of decision tree based automated trading can be found in two papers by
German Creamer and Yoav Freund called
Automated Trading with Boosting and Expert Weighting and
A Boosting Approach for Automated Trading. These represent algorithms used in the
Penn-Lehman Automated Trading Project. Anyway, the two papers get down
and dirty with some of the indiators they use in their trading simulation. Their
bibliography references a number of good sources of information.
In the PLAT paper, here are a few strategies worthy of further investigation:
- Case-based reasoning applied to the parameters of
the SOBI strategy (see text for SOBI description).
- Predictive strategy using money ow (price movement
times volume traded) as a trend indicator.
- Market-maker that positions orders in front of the
nth orders on both books.
- Mixture of a Dynamically Adjusted Market-Maker
which calibrates by recent volatility, and a trendbased
predictive strategy.
- Sells on rising prices, buys on falling prices.
- Trades based on relative spreads in the buy and sell
books, interpreting small standard deviation as a
sign of codence.
- Simple predictive strategy using total volumes in
buy and sell books.
Peter Stone's group has done well with the PLAT simulations. His papers, with this one
as a example,
Two Stock-Trading Agents: Market Making and Technical Analysis have many good
implentable ideas for an automated trading strategy. Outside of the world of finance,
general algorithmic bidding and optimization strategies are described in
The First International Trading Agent Competition: Autonomous Bidding Agents. Another
interesting Peter Stone paper called
Designing Safe, Profitable Automated Stock Trading
Agents Using Evolutionary Algorithms They discuss the concept that common trading
rules have weaknesses under various trading conditions. By identifying the conditions,
and adaptively switching among rules, trading results can be improved. One more Peter Stone
supported effort is the poster:
Safe Strategies for Autonomous Financial Trading Agents:
A Qualitative Multiple-Model Approach.
Through the use of evolutionary reinforcement on data to which us mere mortals have no
access, M.A.H. Dempster has a number of related papers. The bibilographies may be good
sources of further inspiration:
In a sort-of-related paper, Robert Almgren and Julian Lorenz provide an insight into
Adaptive Arrival Price. A couple of extracts from their abstract:
- Electronic trading of equities and other securities makes heavy use
of .arrival price. algorithms, that determine optimal trade schedules
by balancing the market impact cost of rapid execution against
the volatility risk of slow execution.
- We show that with a more realistic formulation of the
mean-variance tradeoff, and even with no momentum or mean reversion
in the price process, substantial improvements are possible
for adaptive strategies that spend trading gains to reduce risk, by
accelerating execution when the price moves in the trader.s favor.
Now for a really un-related paper:
A market-induced mechanism for
stock pinning. The authors suggest that some stock prices can be pinned at strike
prices on option expiration dates. As various market participants cover their positions
with options and the related underlying securities, some interesting market dynamics unfold.
[/Trading/ReadingMaterial]
permanent link
2008 May 30 - Fri
The Joy of Volatility
I initially had this embedded in my follow on article, but I think the information in
this paper bears further scrutiny and testing, in regards to what could be classified as
what I think is called pairs trading. I guess the secret is in the selection of the pairs.
The paper is by
Dempster/Evstigneev/Schenk-Hoppé, and called
The Joy of
Volatility. They take a coin flipping strategy to picking a couple of assets. They
show that the volatility is a positive benefit to portfolio profitability in a dynamic
rebalancing strategy versus a buy and hold mentality. A couple of key quotes though:
Poverty is the inevitable fate of the passive investor.
Consider making an investment according to a simple active management style:
buying or selling assets so as to always maintain an equal investment in both. On average,
wealth will double in 80 periods and grow without limits. This investment style rebalances
wealth according to a constant proportions strategy. It succeeds, where buy-and-hold fails,
because of the volatility of asset returns.
However, as with any investment advice, a word of caution is in order:
Constant proportions strategies do well in the long term but, over short time horizons,
their superior performance cannot be guaranteed!
[/Trading/ReadingMaterial]
permanent link
2008 May 28 - Wed
Put Me To Sleep Reading Material
Someone in some data provider's forum was making mention of doing order flow analysis in
Excel through Interactive Brokers, and the person felt that they weren't getting enough
data. Which is true, Interactive Brokers sends data based upon what is necessary for
someone viewing a screen, not based upon some automated data hungry automaton looking to
crunch full data feeds.
That got me to thinking and to reading more about order flow analysis. This gets in to
market orders, limit orders, bid/ask spreads, order books, market makers, rational traders,
uninformed traders, instantaneous impact of variable sized market orders, as well as whole
raft of other micro-economic activity that comes with high frequency trading.
Marco Avellaneda and Sasha Stoikov and recently released a paper entitled
High-frequency trading in a limit order book, with another version of the
same thing here. They develop some interesting equations on determining a bid/ask
spread in the midst of a moving market, based upon a market maker's inventory and risk
capability. I'm wondering if that is what BATS does for their trading capability.
Karl Ludwig Keiber has a paper called
Price Discovery in the Presence of Boundedly Rational Agents. In the paper, he
discusses some market maker concepts and what they deal with. Momentum as well as mean
reversion are discussed in the context of bid/ask spread and price discovery. There is a
minor discussion regarding adverse selection during a transition from momentum to reversal
trading on page 25 which may be of some value. The cross over between reversal and momentum
is a weakness in my trading.
Bruce Mizrach has a paper called
The next tick on Nasdaq. Although a recently published paper, he uses data from 2002.
The paper goes into some history of market making, limit books, and how Nasdaq grew up.
Some of his interesting observations:
- This paper asks a
surprisingly simple but neglected question: does the entire
order book help predict the next inside quote revision?
- Lillo and Farmer (2004) find
that orders on the
London Stock Exchange follow a long memory process.
- Bouchaud et al. (2002), while
analysing the Paris Bourse,
found a power law for the placement of new limit orders
and a hump shape for the depth in the order book.
- Weber and Rosenow (2005)
find a log linear relationship between signed market order
flows and returns on Island.
- I find,
for example, that the number of bids or offers is more
important than the quoted depth.
- In general, I find that the bids
(offers) away from the inside increase the probability of a
down (up) tick.
- The last result I obtain is that this volatility decreases with
larger market capitalization and the presence of more
market makers.
- Traders call the market makers or ECNs that frequently
appear on the inside market the .ax., and they claim that
taking note of the ax's activity is informativey.
- for example, the advice from the
Daytrading University at http://www.daytrading-university.com/ samplesson4ways.htm.
..Even with the ECN routing that mm.s [market makers] use to hide their order flow, there.s
still plenty of profitable trading to be
had by correctly: (1) Avoiding buying when a major mm/ax is selling (e.g. if you see MSCO
and MLCO both sitting on the inside
ask you probably shouldn.t buy if their bid is three levels outside the market) and (2)
.Shadowing. the ax.s buying/selling behavior, if
you see that all else looks okay, e.g. no suspiciously strong ECN buying/selling on
INCA/ISLD...
- The presence of a particular participant does
not by itself indicate that they are significant contributors
to subsequent quote revisions though.
- Looking more closely at individual participants,
there
are some interesting results. When ARCA takes the inside
bid, the next tick is more likely to be a downtick than an
uptick in 65 of 71 cases.
- When
ARCA takes the inside ask, there is an uptick in 63 of
73 instances
- The effect of specific participants in the small cap
market differs from the large caps. ARCA has a negative
impact from the bid in all 41 cases in which it
is statistically significant.
- A vector autogression can be inverted into its moving
average representation, and one can then compute
impulse responses functions. In our model of trades and
quotes, these have the interpretation of market impact
functions, or the effect on stock returns of an unexpected
buy order arriving into the market.
- It can also be explained in an order driven market
by what
Biais et al. (1995) call the .diagonal effect. in which they
observe that a limit order that improves the inside bid (ask)
is more likely to be followed by another limit order which
increases (decreases) the inside bid (ask). A similar
diagonal effect for trades is present as well. The negative
serial correlation in the small caps suggest that the quote
revision process for that group can be explained without
assuming informed traders,
- As in
many auction designs, additional buy (sell) side interest
makes the next price change more likely to be an uptick
(downtick). Biais et al. (1999) observe this behaviour even
in an environment in which quotes are only indicative.
Similarly, in the period in which quotes are firm, the
authors find that additional depth on one side of the book
helps predict the appearance of additional liquidity on the
same side of the book.
- The number of buyers and sellers, I find,
is almost always more important than quoted depth.
- Aggregate depth, either at the
inside market, or as
a weighted average of the demand curve, is also helpful,
and this information is surprisingly persistent. In general,
the results are more successful for large cap stocks than
small caps.
- Quotes away from the inside
are generally not informative. Large numbers of buyers
(sellers) at tiers away from the best bid (offer) are more
likely to result in a downtick (uptick).
- The model of trades and quotes presented also
produces
dynamic estimates of market impact. The impact of a buy
order can be determined beyond its impact on the current
spread. The estimates appear to vary sensibly with
standard measures of liquidity.
I wonder if the above snippets could be coded as in an expert system.
In
Relation between Bid-Ask Spread,
Impact and Volatility in Order-Driven
Markets by Wyart/Bouchaud/Kockelkoren/Potters/Vettorazzo, the BATS philosophy of
infinitesimal market-making can be expressed in terms of spread and the instantaneous impact
of market orders. They indicate that there is an empirical correlation between the spread
and the volatility per trade. As mentioned in one of the other papers, they confirm that
the main determinant of the bid-ask spread is adverse selection. They also confirm that
volatility comes from trade impact. The paper has an extensive bibliography worth looking
into. There is an interesting corrolary in the conclusion, namely that "when the
volatility
per trade is large, the risk of placing limit orders is large and therefore the
spread widens until limit orders become favorable."
[/Trading/ReadingMaterial]
permanent link
2008 May 23 - Fri
A Half Hearted Day
Last night I got some chart software programming accomplished. I can now see bars,
trades and quotes. Over the weekend my task to get some indicators on to them,
particularily pivots, Bollinger Bands of two or three different time frames, volume
historgrams, and a zig
zag indicator. A little further down the road, the zig zag indicator will be used for
'snapping' trend/support/resistance lines in to place to help solidify some chart patterns.
I looked in on COIL again this morning. I got sidetracked watching it and didn't realize
the rest of the market had opened. When I did notice what was happening, a lot of things
went south. It was all well and good that I didn't do anything. There will always be
another trading day, and hopefully for Tuesday I can have my basket trading in place.
That is, I'm hoping to finish off the order entry bit that talks to Interactive
Brokers. In doing so, I can then finish the integration my order basket tracking. Each
evening, I run three different stock selection filters and come up with a total of about 40
different
symbols with associated entry parameters. If all goes well, I can do some semi-automated
trading: ie let the computer get my entries in first thing in the morning, then I can
monitor the profit curve and start setting stop-loss points to generate automated exits.
[/Trading/Diary/D200805]
permanent link
2008 May 22 - Thu
Trading Notes: 2008/05/22
I've been trading most days during the month of May. I've been using Interactive Brokers
as a broker, and have been using their BookTrader to execute my trades. Regarding things
I've learned while using the BookTrader, I'll leave that for another post.
My trading account (real money) is up by 9.4% since April 28, when I first started manual
trading, and
so far, knock on wood, I've had all positive days, some more positive than others, some a
lot more work than others.
I think it is time to keep track of what I do and what I see so I can ensure I don't do
the same mistakes more than once.
Limit orders is what I started with. Using a mostly contrarian strategy, I've been able
to find some profit areas. I have been caught a couple of times when the market kept going
in the wrong direction, and I was getting in deeper and deeper. Those were the rough days
where I had to do tricky trading, and through mostly luck, the symbol recovered enough that
I could end positive.
With that said, it is now time to figure out the price levels at which to do reversal
orders. I'm setting up some charting to help me with that, and hope to have it done for
trading next week.
The news over the last 12 hours has been heavy with the news of the large leap in oil
(COIL), traded on IPE. I've been watching the 2008/July contract. That I traded with paper
trading. The contrarian trading would have worked interestingly enough between 11:30 and
12:30 GMT, where it went from 134.25 down to 133.25. I lost my
nerve and closed out half an hour into the decline, right at what
turned out to be the bottom. It recovered and then some in the following half hour, to be
back around 134.50 for a few minutes. I was thinking afterwards that I could have put Stops
at various levels and caught it when it went back up, but thinking it was going to go back
up was not really on my mind.
All in all, it was interesting to carry out a risky trade on paper just to see how things
would have gone. It is easier to dispasionately analyze the results (monetarily and
emotionally) than if that had been real money.
Update 10:05 AST. I saw COIL taking another dip, even lower this time. It went down to
132.50. This one, with real funds, I managed to work 18 trades in and out for a real profit
of $643, after commissions, over five minutes.
Regular day trading accounts have a 4:1 margin ratio during the day, and an overnight
carry margin of 2:1. On COIL, Interactive Brokers has a different margin structure.
When you right click on the symbol and look for symbol details, it shows a multiplier of
1000. Which means each contract is worth 1000 times the BookTrader value. So if the ticker
is at $133.23, you'll be buying a $133,230 contract. Margin for this is an initial margin
of $9375 and an overnight maintenance margin of $7500. This gives over a 10:1 margin
capability. The commission ended up being $2.02 per contract.
While writing this, it took another dip and fast recovery. Traders with deep pockets
must be making good money on this.
Update EOD: Well, that was an exciting day. Instead of just closing out at the end of
those trades, I stayed in for more, but found I didn't reverse when I should have. I lost
what I made and now have to try it again. Smarter this time. Watch for the reverses and
run with them instead of against them.
The instances where I've gone against them in the past worked out, they came back. Not
this time. They kept on going.
Breakouts are good thing, if you've got them going in the right diretion. I really need
to get my charting fixed tonight to show some of the patterns I've seen. The programming is
happening tonight. I hope to have it ready for a try in the morning.
[/Trading/Diary/D200805]
permanent link
2008 Apr 21 - Mon
SmartQuant QuantDeveloper & DataCenter Release
SmartQuant has released a revision
to DataCenter and
QuantDeveloper. DataCenter and QuantDeveloper are at the following revision levels:
DataCenter
Version 3.0.1 (21-Apr-2008)
QuantDeveloper Enterprise Edition
Version 3.0.1 (21-Apr-2008)
QuantDeveloper Source Code
Version 3.0.1 (21-Apr-2008)
* Recent Versions available through
version control
[/Trading/SmartQuant/Releases]
permanent link
|
