Trade in the Now

Trade in the Now

Trade in the Nowwith Market Depth Velocity

Hello, my name is David ODell.This presentation is about the Market Depth Velocity indicator for TradeStation 9.0 and how we can Trade in the Now

Lets take a look at Market Depth Velocity running on SPY. (segue to next slide)

Video on next slide from:C:\Users\David\Documents\!QCL Solutions\_TS 9 Solutions\Developer Challenge\MARKET DEPTH VELOCITY (!QCL.MDVELOCITY)\Webinar\Videos\MDV_SPY_1min_Pntbrs_2011-06-15_1221.swf

Presentation is after hours, so will not show running live on TradeStation:C:\Users\David\Documents\!QCL Solutions\_TS 9 Solutions\Developer Challenge\MARKET DEPTH VELOCITY (!QCL.MDVELOCITY)\Webinar\!QCL.MDvelocity-Webinar.tsw1Market Depth Velocity of SPY2011 June 15 until 12:22 PM ET

Here is the Market Depth Velocity indicator running a week-ago Wednesday.The recording precedes one of the highest volume 1-minute bars that had occurred for SPY, in several weeks.That 12:26 PM ET bar was a capitulation selloff followed by a bounce.It is interesting to watch the incoming quotes relative to transactions, to get a feel for where the market may be going.

2Market Depth Velocity of SPY2011 June 15, 12:29 PM ET

Several minutes later, you see the high volume 1-minute bar at 12:26 PM ET, followed by a bounce, as I had mentioned.Watching the incoming bids move up and incoming asks move away, a bounce, rather than a further breakdown in price, made sense.

So whats the point? (segue)

3It has been saidWith the past, I have nothing to do; nor with the future. I live now. ~Ralph Waldo EmersonSkate where the puck's going, not where it's been. ~Wayne Gretzkys father

It has been said4Presenters backgroundGraduate of Georgia TechProfessional EngineerSystem trader since 1996Fund ManagerEasyLanguage EngineerTradeStation Product ManagerAnd now Institutional Trading Consultant

Before we go further, my background is as follows:

You can find more information on my LinkedIn profile.5A problem trading NowSmart trading is based on projections of reward relative to risk, over time.Price = Established Value + Effects from Old & New InformationOld info can impact price cyclically with diminishing magnitude over time.New info is key, especially as market efficiencies continue to improve. But new information is largely ignored.

In TradeStation 9.0, we have fantastic new tools to address some old problems.But, before we start, lets establish that trading is a business. As a well-reasoned business we are seeking rewards with acceptable risks.Our rewards are derived from asset prices. So it is important to be able to project future prices.In general, we can say that Price = Old information both establishes the current value and can have reverberating effects over time.The cyclical price impact of old information is a basis of classical strategy trading, which essentially seeks to answer the question What if I had?There can be value in this.But for price projections, new information is most critical.And since most traders havent had, and many still dont have, the necessary tools; the effects of new information are largely ignored in trading strategies.It is for this reason that many traders shutdown their systems ahead of key news releases.6A Solution for NowMarket Depth is your best view of where an electronic market is Now.Market Depth is both old and new.Incoming quotes factor new information and can best forecast change.(Caveat: Market Depth is only a portion of a market. Much can be unseen.)

So what is a solution and what new tools can we leverage? Tools to deal with, what Ill refer to as the Now problem.In TradeStation 9.0 we have programmatic access to Market Depth through the MarketDepthProvider class.Take a look at my example indicator, Market Depth Velocity.Market Depth is our best viewKeep in mind that Market Depth Quotes are both old and new.Market Depth is not always the best reflection of the Now we care about, in that it includes old information, which is fading in importanceThe leading edge of Now comes from new information and best indicates how a market, and thus prices, may change.Our profit opportunities are in the change (or lack thereof).Caveat7Improve trading Nowwhere the transactions take place, with new information to know good dealsImprove entry & exit efficiencyAnd reduce slippage (knowing bad deals)

So with programmatic Market Depth access in TradeStation 9.0, how can we improve our trading to address the Now problem?What can we expect to accomplish?

In short for an asset, we can get real-time insight into what is fair value now, including the newest information being assimilated into price.This means we can improve entry and exit efficiency of our system trades by having a way to measure current fairness.We have a real-time framework for setting system limit prices. When market depth is favorable, take advantage of it.When a market is setup to move away from our orders, we can have our systems trade more aggressively.We can determine when market orders are OK, or when our systems would be better to use limit orders. And by doing so, reduce slippage.We may further be able to identify times when it is best for our systems to wait for incoming quotes to have an effect reasonably expected to be favorable.8Now, our trading experiencesHow often have you bought before a quick drop or sold before a spike?What percent of your average trade is lost to slippage?Market orders: Part of Spread + ImpactStrategies: Paying beyond estimated fillsStrategies: Missing estimated fillsHow much could your trading improve?

So again with the Now problem. How have we felt it?How oftenWhat percent

If you could mitigate the effects of such common trading experiences, How much

How about slippage?Slippage in its simplest form is the spread plus additional losses from the impact of a market order.Slippage can also be thought of as any losses from not being able to execute planned orders of a strategy at assumed possible prices.I use the term strategy generically for any trading system, developed with assumptions that may not be possible in real time trading.For instance, if you use TradeStation Strategy Automation, what is the difference between simulated fills and real order fills?And if you use Limit orders, how often are they partially filled or not filled at all?Of those that go unfilled, do they prove to have been the more profitable possibilities? Likely so.So, even though more difficult to quantify, in my definition of slippage, I include the impact of assumed orders that go unfilled.As a personal example, when trading a private fund my average trade resulted in about a 0.5% return- there were of course big winners and losers too, and for those particular cases, slippage was insignificant- but on average slippage proved to be very important, despite what I would have guessed- the execution slippage relative to theoretically possible trades was between 0.05 to 0.2% (i.e. up to 40% of the average profit)- the average missed-entry slippage was about 2x the profit of captured trades- So trade execution slippage and missed-trade slippage are important issues to address in strategy trading

Again, if you could mitigate inefficiencies and slippage, How much

9Improve by knowing good deals when price nears newest quotesOr newest quotes approach priceWatch the VWAP of incoming quotesAnd reduce slippage knowing bad dealsTest: Is the incoming quote spread fair?Can it help distinguish good and bad deals?Is there central tendency?Are trades, relative to incoming quotes, symmetrically distributed? (normally?)Examples from Monday, 2011 May 13th

Improve by knowing good deals when price nears newest quotes or newest quotes approach price.

Watch the VWAP of incoming quotes: With the marketdepthprovider we can monitor new quotes (incoming quotes) as they arrive.Collect these incoming quotes over a period like 15 seconds, 30 seconds or a minute.And volume weight each quote to come up with an average incoming bid price and average incoming ask price.This way we utilize all three data elements available to us for each side of the market with each Market Depth quote: Price Quantity Time (i.e. within our rolling window)

The VWAP of incoming Bids and incoming Asks helps us identify whenCurrent prices may be favorable to sellers or buyers* Logically, knowing this can help us improving system trading efficiency and reduce slippage- Knowing a good deal is to avoid slippage from missing favorable trades- Knowing a good deal also helps one price limit orders, and avoid uncertain slippage from market orders- Knowing a bad deal can help one decide not to cross the market and thus incur slippage

Note: As opposed to Incoming quotes, Inside quotes (i.e. inside bid and inside ask) are not necessarily newInside quotes are often olderInside quotes generally represent the influence of older informationLogically inside quotes tend to move in the direction of incoming quotes

To know a good deal is to know what is fair, so lets Test: Is the incoming quote spread fair? Can it help distinguish good and bad deals? Is there central tendency? Are trades, relative to incoming quotes, symmetrically distributed? Are they normally distributed? Because, if we can assume that, we have a nice simplifying assumption for trading system development.

Lets take one day of 1-minute bars for some very liquid symbols and see how incoming quote spreads look relative the latest associated trade

C:\Users\David\Documents\!QCL Solutions\_TS 9 Solutions\Developer Challenge\MARKET DEPTH VELOCITY (!QCL.MDVELOCITY)\Webinar\Data\MDvelP_SPY_1 Min_1sec.xlsm* Tests for SPY, 2011/06/13, 1-min barsChart1 Distribution of trades relative to 1-min VWAP incoming Bids(-1) and VWAP incoming Asks(1)Has central tendency and a normal-distribution fits reasonably wellChart1 (2) Distribution of trades relative to Bollinger bands for the same period (1-min, 20 bar, +/- 1 StdDev)Bollinger bands show a less normal distribution of trades, with less central concentrationChart1 (3) Overlay incoming quote spread compared to Bollinger bandsQuote spread does not require as much history as Bollinger bands to establish a rangeQuote spread appears better for forecasting tradesNote that for SPY, the quote spread was around 1.3x Standard Deviation of trade prices

10Distribution of trades w.r.t. 1-min VWAP incoming quotes for SPY

Here is a distribution for SPY trading on Monday, 2011 May 13th

This is the distribution of closing prices on 1-minute bars relative to the incoming quote spreadwhere -1 on the x-axis is the VWAP of incoming bidsand +1 on the x-axis is the VWAP of incoming asksfor the 1 minute period preceding the bar close11Distribution of trades w.r.t. Bollinger bands (20 bar, 1 sd)

Here is a similar distribution for the same day, on 1-minute bars using Bollinger Bands of length 20where -1 on the x-axis is the -1 standard deviation bandand +1 on the x-axis is the +1 standard deviation band12Distribution w.r.t. incoming quotes & Bollinger bands

Here are the overlaid plots.Where we see trade distributions relative to incoming quotes, compared to the trade distribution relative to Bollinger bands.The distributions of trades relative to the incoming quote spread looks appealing.

We see similar distributions for other liquid equity symbols like: IWM, QQQ, DIA, BAC, C

MDvelP_IWM_1 Min_1sec.xlsm - Chart1 => IWM distribution.png (see\Webinar\Pictures\Distrib\)MDvelP_QQQ_1 Min_1sec.xlsm - Chart1 => QQQ distribution.pngMDvelP_DIA_1 Min_1sec.xlsm - Chart1 => DIA distribution.pngMDvelP_BAC_1 Min_1sec.xlsm - Chart1 => BAC distribution.pngMDvelP_C_1 Min_1sec.xlsm - Chart1 => C distribution.png

13Distribution of trades w.r.t. 1-min VWAP incoming quotes for IWM

For IWM trading on Monday, 2011 May 13th14Distribution of trades w.r.t. 1-min VWAP incoming quotes for QQQ

For QQQ trading on Monday, 2011 May 13th15Distribution of trades w.r.t. 1-min VWAP incoming quotes for DIA

For DIA trading on Monday, 2011 May 13th

16Distribution of trades w.r.t. 1-min VWAP incoming quotes for BAC

For BAC trading on Monday, 2011 May 13th

17Distribution of trades w.r.t. 1-min VWAP incoming quotes for C

For C trading on Monday, 2011 May 13th

This distribution of Citi Group is a little noisier.There is a high number of trades on the incoming bid side of the spread.This distorts the best-fit normal distributionand shows that incoming bids were chasing the marketand as makes sense, Citi was up about 3.3% by the close of the day (Monday, 2011/06/13)18Apply to trading ranges when you feel a market is range boundBuy relative to VWAP of incoming bids and Sell relative to VWAP of incoming asks.Test: Do forward prices correlate with current prices relative to incoming quotes?Graph y-axis forward prices versus x-axis current prices, relative to incoming quotes.R-Squared for SPY 2011/06/13, 1-min bars:1 min forward = 0.000409 (i.e. uncorrelated)2 min forward = 0.0042933 min forward = 0.002067However, relative to original incoming quotes, there is some correlation of forward prices to current prices. There is room for momentum trading too.

When you know fair value Now, and can distinguish between good and bad deals Now

You can better execute planned trades.You may also find opportunities to trade for scalping profits.

For instance, we can use the incoming quote spread as a basis for estimating ranges, to short-term trade.(Doing this depends on the trader or trading system identifying a market as range bound.)

To test this possibility, lets see if trading prices relative to the quote spread correlate with subsequent prices.

If a trade is very low or very high relative to the current quote spread,then there may be trading opportunities if there is a strong tendency for subsequent prices to revert to mean.This means that there would be little correlation between extreme pricing and subsequent pricing.That is, an extreme price would not tend to lead to more extreme prices.Better yet, for the contrarian range trader, would be if there were a predictable inverse relationship between extreme prices and subsequent opposite price changes.Would be nice, but this is expecting too much. A simple tendency to revert to mean can be good enough for profit.

So lets take a look at prices relative to the quote spread and see how prices tend to occur 1, 2 and 3 minutes later.C:\Users\David\Documents\!QCL Solutions\_TS 9 Solutions\Developer Challenge\MARKET DEPTH VELOCITY (!QCL.MDVELOCITY)\Webinar\Data\MDvelP_SPY_1 Min_1sec.xlsm* Tests for SPY, 2011/06/13, 1-min barsChart2-fwd1 1 minute later => SPY-fwd-1.png (see\Webinar\Pictures\Distrib\)Chart2-fwd2 2 minutes later => SPY-fwd-2.pngChart2-fwd3 3 minutes later => SPY-fwd-3.png

19SPY trades v. trades relative to incoming quotes, 1-min forward

Here we are 1 minute forwardEach point is a trade withX-coordinate = Original price relative to the incoming quote spread (-1 for VWAP of incoming bids and +1 for VWAP of incoming asks)Y-coordinate = Forward price relative to the incoming quote spread

There are only very slight correlations with extreme prices and subsequent extreme pricingThere is largely randomness which works out to average over timeSo this indicates there is at least potential for trading the incoming quote spread for profitBut this is relative to the VWAP of incoming quotes

20SPY trades v. trades w.r.t. original incoming quotes, 1-min forward

And 1 minutes forward relative to the original incoming quote spreadSo for the Y-coordinateIt is the Forward price relative to the incoming quote spread of the Original trade(not based on the incoming quote spread of the 1 minute preceding the forward price)

Note that relative to the original incoming quotes, there is some correlation of forward pricing with current pricing. There is some continuation.But relative to the incoming quotes (that are also forward), the earlier scatter plot and earlier distribution plots show that pricing tends to stay centered between incoming quotes (i.e. tends to revert to mean quickly after an extreme).21SPY trades v. trades relative to incoming quotes, 2-min forward

Here we are 2 minutes forward


And 2 minutes forward relative to the original incoming quote spread

23SPY trades v. trades relative to incoming quotes, 3-min forward

Here we are 3 minutes forward


And 3 minutes forward relative to the original incoming quote spread

Trading systems that scalp profit from market depth information, can be complexAnd as can be seen in the plots of forward pricing, relative to original incoming quotes;there can be some correlation of current price relative to the spread, to future prices relative to the same historical spread.This argues for momentum considerations.For now, my point is simply that it is possible to trade for profit on market depth quotes.Fast and reliable programmatic access to market depth information is essential, in doing this.

Note that being in a trading range can be thought of as a situation where there is reverberating old information being debated for impact.The incoming quote spread can help trading in such situationsIt may also be worth considering the relative total volume of incoming quotes per sideAnd the direction of change of incoming quotes relative to price, and older quotesFurther, in such situations, trading could be augmented by other technical indications

25Other ways to Trade in the NowDeduce hidden market interestsMonitor scheduled impactful eventsMeasure propagation of impactful newsDig for information fundamental to asset pricing, that is not widely knownUse weather projections for commodity markets and similarly affected marketsEtc.

Breeze through this part.Other ways to Trade in the Now:Get more insight into market depth by trying to figure out real trading interests that arent visibleGo a step further and get new information as it happens, which impacts trading interest and will factor into the market over time- specific, typically scheduled, news events of known influence over the market (earnings announcements, etc.)- aggregate news sentiment especially of stories propagating at an increasing rate, concerning topics known to have impact

Skip this unless have lots of time on hand:(Note, some very successful commodity traders have been good at anticipating the effects of weather phenomena on their markets.I for one have heard many stories of commodity traders who anticipated the impact of El Nino weather phenomena.)26SummaryUse market depth, esp. as incomingKnow good prices for efficient tradingTrade range bound markets, etc.In general with newest informationImprove price, volatility and time projectionsAnd thus one can improve portfolio balanceGet in early on sector rotations: before profit opportunities decrease and risks increase

27What to do NowUse Market Depth in TradeStation 9.0 e.g. the Market Depth Velocity indicatorCollaborate with other tradersFind services on the Strategy NetworkJoin us at www.QCLsolutions.comNew products for Market Depth analysisNew tools for key economic & market dataNew collaborations for institutional-level news sentiment analysis with TradeStation

Use Market DepthCollaborateFind Strategy Network productsJoin us at QCLas we will be releasing products for Market Depth analysis for institutional-level tradingand as we will be releasing new products for institutional-level access to economic dataand most importantly as we will be releasing products for real-time global news sentiment analysis with price impact, volatility and time projectionsWe are focused on extending high-end information access, technical analyses, trading tools, and automated systems for mid-sized firms to compete and grow.

Again, visit us at www.QCLsolutions.comWe are excited about our new products and collaborative efforts soon to further benefit the active trading community.28Improve each trade where the transactions take place

In closing29where the puck's going

Thank audience.Open for questions.Close with What to do Now slide30