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Tuesday, June 18, 2013

Thinkscript: The Trend_Fuzz Indicator for Think or Swim

Here is the thinksript code for one of my favorite custom made indicators.  I've used it quite a bit over the last three or four years..now maybe you can get some use out of it as well. Here's a chart of the SPY daily chart with the indicator:


 Here's the code:

###delete this line when pasting into thing or swim###

input ThermoLookBackBars = 50;
input PlotType = {default AdaptiveMovingAverages, Standard};

def HighLowScore = 1000 * ((high - high[1]) / (high[1]) +
(low - low[1]) / low[1]);

#######ATR TrailingStop Code
input trailType = {default modified, unmodified};
input ATRPeriod = 5;
input ATRFactor = 3.5;
input firstTrade = {default long, short};

def HiLo = Min(high - low, 1.5 * Average(high - low, ATRPeriod));
def HRef = if low <= high[1]
    then high - close[1]
    else (high - close[1]) - 0.5 * (low - high[1]);
def LRef = if high >= low[1]
    then close[1] - low
    else (close[1] - low) - 0.5 * (low[1] - high);
def ATRMod = ExpAverage(Max(HiLo, Max(HRef, LRef)), 2 * ATRPeriod - 1);

def loss;
switch (trailType) {
case modified:
    loss = ATRFactor * ATRMod;
case unmodified:
    loss = ATRFactor * AvgTrueRange(high, close, low, ATRPeriod);
}

rec state = {default init, long, short};
rec trail;
switch (state[1]) {
case init:
    if (!IsNaN(loss)) {
        switch (firstTrade) {
        case long:
            state = state.long;
            trail =  close - loss;
        case short:
            state = state.short;
            trail = close + loss;
    }
    } else {
        state = state.init;
        trail = Double.NaN;
    }
case long:
    if (close > trail[1]) {
        state = state.long;
        trail = Max(trail[1], close - loss);
    }
    else {
        state = state.short;
        trail = close + loss;
    }
case short:
    if (close < trail[1]) {
        state = state.short;
        trail = Min(trail[1], close + loss);
    }
    else {
        state = state.long;
        trail =  close - loss;
    }
}

def BuySignal = Crosses(state == state.long, 0, CrossingDirection.ABOVE);
def SellSignal = Crosses(state == state.short, 0, CrossingDirection.ABOVE);

plot TrailingStop = trail;
TrailingStop.Hide();
####End ATR Trailing Stop Code

def A = Highest(high[1], ThermoLookBackBars);
def B = Lowest(low[1], ThermoLookBackBars);

def FiftyTwoWeekHigh = A;

def FiftyTwoWeekLow = B;

def FiftyTwoWeekScore = 10 * (((high
- FiftyTwoWeekHigh) / FiftyTwoWeekHigh) + 
((low - FiftyTwoWeekLow) / FiftyTwoWeekLow));

def ThermoScore = ExpAverage(HighLowScore + FiftyTwoWeekScore, ThermoLookBackBars);

input FastLengthShort = 5;
input SlowLengthShort = 15;
input EffRatioShort = 10;
input FastLengthLong = 10;
input SlowLengthLong = 25;
input EffRatioLong = 5;

def AMA = MovAvgAdaptive(ThermoScore, FastLengthShort, SlowLengthShort, EffRatioShort);
def AMA2 = MovAvgAdaptive(ThermoScore, FastLengthLong, SlowLengthLong, EffRatioLong);

plot Line1;
Line1.Hide();
plot Line2;
Line2.Hide();

switch (PlotType) {
case AdaptiveMovingAverages:
    Line1 = AMA;
    Line2 = AMA2;
case Standard:
    Line1 = ThermoScore;
    Line2 = ThermoScore;
}

def InvisibleLine = close * 0;
plot Line3 = InvisibleLine;
Line3.Hide();

def Buy = Line1 > 0 and Line2 < 0 and state == state.long;
def StrongBuy = Line1 > 0 and Line2 >= 0 and state == state.long;
def Sell = Line1 < 0 and Line2 > 0 and state == state.short;
def StrongSell = Line1 < 0 and Line2 <= 0 and state == state.short;


AssignPriceColor(if Buy then Color.DARK_GREEN else if StrongBuy then Color.GREEN else if Sell then Color.DARK_RED else if StrongSell then Color.RED else Color.BLUE);

AddLabel(yes, Concat("Current Reading is ", (if Buy then "Up Trend" else if StrongBuy then "Strong Up Trend" else if Sell then "Down Trend" else if StrongSell then "Strong Down Trend" else "Neutral")),  if Buy then Color.DARK_GREEN else if StrongBuy then Color.GREEN else if Sell then Color.DARK_RED else if StrongSell then Color.RED else Color.GRAY);

#######Stochastic Code

declare upper;

input over_bought = 80;
input over_sold = 20;
input KPeriod = 10;
input DPeriod = 10;
input priceH = high;
input priceL = low;
input priceC = close;
input slowing_period = 3;
input smoothingType = {default SMA, EMA};

def lowest_k = Lowest(priceL, KPeriod);
def c1 = priceC - lowest_k;
def c2 = Highest(priceH, KPeriod) - lowest_k;
def FastK = if c2 != 0 then c1 / c2 * 100 else 0;

def FullK;
def FullD;

switch (smoothingType) {
case SMA:
    FullK = Average(FastK, slowing_period);
    FullD = Average(FullK, DPeriod);
case EMA:
    FullK = ExpAverage(FastK, slowing_period);
    FullD = ExpAverage(FullK, DPeriod);
}

def pricefilterup = if close > close[50] then 1 else 0;
def pricefilterdown = if close < close [50] then 1 else 0;

def OverBoughtAdd = if FullK < over_bought and FullK[1] >= over_bought then 1 else 0;
def OverSoldAdd = if FullK > over_sold and FullK[1] <= over_sold then 1 else 0;

def na = Double.NaN;

#Plot arrows
plot up = if StrongBuy and OverSoldAdd  and pricefilterup then low - (3 * TickSize()) else na;
plot down = if StrongSell and OverBoughtAdd and pricefilterdown then high + (3 * TickSize()) else na;
up.SetPaintingStrategy(PaintingStrategy.ARROW_UP);
down.SetPaintingStrategy(PaintingStrategy.ARROW_DOWN);

###delete this line when pasting into think or swim###

Take care,

TLT

Monday, June 3, 2013

Equity Curve Analysis: Can Prediction Beef Up an Edge?

I've been doing lots of research lately on trading systems and analysis of trading system results.  Equity curve analysis is not necessarily a new idea, however, it is something that I've not spent much time on until now.  So how does it work and what can it tell you?  Well, I'll share what I've done.  Surely there are some great methods that have been discovered and refined by others, however, I just started from scratch and started tinkering with some math that made sense to me.  Sometimes you can get some good results with doing that..other times you spin your wheels but you generally end up learning something.  The following breakdown is my version of equity curve analysis and I share this not to necessarily say it works and that you should copy it, but to possibly share some ideas that others can build on.

First, I started off with a mechanical day trading system that I created.  The system itself doesn't really matter, I'll just say that it's a fairly decent performing momentum strategy that makes about one trade a day on average.  I took a few years worth of daily returns and plugged them into a spread sheet.  This creates a time series out of the daily returns and the great thing about having this is that you can line it up in a column next to other pieces of data or indicators and look for patterns in what is useful.

Second, I took several other pieces of data like:  1, 3, and 5 period daily ATR (average true range) readings, volume, prior day return, 2 Period RSI and a few other pieces of data, and I lined up the indicator data with the returns.  Then I shifted the return row (moved it down/forward one day) so that the end of day data that I had could be used to try to predict the return of the system for the next day.  This exercise alone was very interesting.  To determine what factors (indicators/data) were useful, I ran regression analysis on the various factors and looked for significant R Squared and P-Value readings to tell me what factors were actually predictive and what factors/indicators were more random and not useful.

Third, after determining a handful of factors that regression analysis said was useful, I normalized the data by taking all of the factors and then divided them by that day's close.  This way, an ATR would be useful whether the instrument being traded was currently traded at $10 a share or $100 a share.  I also took a five period moving average of the data and then divided each factor's data point by it's trailing 5 day average.  This is particularly useful for volume because an instrument might trade an average of 50k shares a day for a while and then bump up to 300K shares a year later.  I wanted to isolate above average and below average conditions relative to the instrument's recent trading history and then compare those reading to values from several years before.

Fourth, I took a neural net program and several years worth of data and trained the neural net with the data..this is straight data mining at this point.  The most important part of it was knowing that I'd likely used relevant factors (b/c of the regression analysis) and I'd used normalized data so the neural net would learn on apples-apples data.  After I had a fairly decent neural net that was trained with a significant amount of good data..it was time to start predicting.

Fifth, I had the neural net predict the system's returns for a couple of years of out of sample data.  One problem with neural net predictions, at least the one that I've been using, is that it's often decent at catching turning points but it's not great at predicting magnitude i.e. how large the move is.  So I took the daily change of the neural net prediction (for example if yesterday's prediction was +1% and today's is +.5%, the reading would actually be a -.5%) and this helps actually gauge whether the system will likely make more or less money tomorrow.  

Sixth, I made the output binary and had the data transformed into 0s and 1s.  A zero merely meant the system would likely lose money and a 1 merely means it will likely make money for the day.  Now it's time to throw in some money management or position size rules based on whether the prediction for the system would likely make money or lose money.  The initial results for the plus day/minus day readings are about 60%..meaning that sixty percent of the time the prediction was correct.  This is not a huge edge but it seems to be a little better than random.

Seventh, I tested a basic money management rule based on the predicted profitability of the following trading day.  If the prediction said that the system would make money the following day, a double sized position was taken on the trades for that day.  And if the prediction was that the system would lose money, a half position was taken for the trades of that day.

And the results please...

It appears that there's some merit to this.  Below is a chart of the returns of the predicted money management system along side the normal system without the money management rules.  Also, there is a line of random money management rules too just to see what a random result would look like.  The random line was developed by having a random 0 or 1 drawn from a random number generator and then applying the money management rule based on the random drawing..kind of a control group.  The fourth line of the graph is the difference between the prediction money management system and the straight returns of the system.  Here's the chart:


As you can see, the prediction money management system outperformed the non money management system by about 80% (the horizontal axis is the cumulative returns, just in a non percentage format..so 1.0 is 100% and 2.6 is actually 260% etc.) over 489 trading days.  Furthermore, the random money management system was actually in the middle of the predicted and straight returns.  Another interesting aspect is that the difference from the predicted money management and the regular returns levels off and stays flat..this could be indicative that the further the neural net gets from the training data, the less accurate it's predictions become.

The results indicate that the predictions on the profitable trading days tend to maximize gains and minimize losses over time.  It's obviously not perfect, but what is in finance and trading.  The prediction seems to add to the edge that this system has and it helps provide a fairly linear equity curve.  The analogy that I've used to explain this concept is that it's like counting cards in black jack.  Keeping up the count doesn't give you a huge edge, but it gives you enough of an edge to tell you when to bet more or less which allows a good black jack player to slowly grind out a profit.  Also, the count doesn't necessarily tell you to play the cards different from basic strategy (ok, it does some but for examples sake we can say it doesn't).  The predicted money management rules tell me nothing about the buy and sell signals from the system, it just says to dial up or dial down the position size..much like the count in black jack.

So where to go from here?  A little more testing wouldn't hurt.  Also, there's some work that can be done with the actual money management rules as well..i.e. something a little more complex than bet half or double for any given day.  I could easily run a solver program to optimize the position strategy, but that type of curve fitting is getting a little ahead of yourself if you're just testing to see if there is an edge to begin with.  Also, I could test the actual buying a selling rules based on the predictions..such as, let trades run longer on profitable days and cut losses quicker on predicted negative days.  I might dabble with some of these extensions, however, the more rules you add to it, the more curve fitting and the less robust the actual system will be.

For now, I have a fairly decent result showing me there's an edge with running and applying this type of analysis.  Hopefully this all made sense and maybe it will spark some ideas for some that are out there testing the same types of concepts.

One last thing to note..the use of a neural net was not particularly important with the example.  For those unfamiliar with them, they are really just another type of forecasting tool.  One could easily come up with something similar using linear regression, polynomial regression, arima, garch..etc.  Any type of forecasting can be used and combinations of these different methods can be used as well.  Just didn't want anyone to think that if you're not knowledgeable about A.I. and neural nets that it's not worth bothering...that is not the case at all.

Take care and good luck with your trading endeavors.

TLT

Saturday, January 19, 2013

A New Year and A New Direction

It's been quite a while.  No the blog is not dead, I've just been thinking about it and I decided to wait for some new and fresh things before I posted.  My life has taken some good, yet intense, turns over the last few months..hence, the lack of posts.

Coming up..I've got some posts ready that will be appearing soon.  The new direction of this blog has been inspired by a new (updated) direction in my trading, thinking and living.  For starters, my wife and I had our first child towards the end of 2012..that sets everything in a new direction!  Although a blessing, the introduction of child puts lots of things into perspective and trading is no exception.  My trading and philosophy in regards to trading has shifted (not necessarily changed, matured might be a better way to look at it) and this blog will be reflecting those changes.  Posts will be more infrequent..likely 1 or 2 a month but they will be more in depth and higher quality..at least I hope so.

Over the last year, I've been in the process of preparing for a child, building a new business, planning the start of a new business, and intensely defining, testing and systematizing my trading.  I'm glad to say that after years of programming, testing, trial and error and much hard work, my systematized trading is finally coming on line.  It was kind of the perfect storm of events to get me here.

I've been working on quantitative trading strategies for 4-5 years now and over the last year, a few pieces fell into place and some lights clicked on...a transformation if you will.  As I was coming to grips with the transformation, as it's hard to let go of old beliefs and accept new ideas, I read Nassim Nicholas Taleb's new book, Antifragile.  This was kind of the nail in the coffin, as I realized that what I was working towards and trying to explain to business partners, clients, potential clients, family members and anyone who would listen was very much in line with what Mr. Taleb is preaching in his new book.  Fortunately, a man of such genius took the time to layout some very interesting and though provoking ideas in a well organized and thoughtful manner...now people like me get to piggy back on his ideas and explanations to our benefit.  Thank you Mr. Taleb!  Also, note that the Antifragile book is now at the top of my "Highly Recommended Reading" list..even above Market Wizards!

I'll be publishing a post within the next week that breaks down my new trading philosophy in more detail..some come back soon.  The long and the short of it for those that can't wait or won't return is that periods of stability achieved through control will continue to dominate and with that stability will come jumps in volatility and chaos .my trading now takes advantage of that chaos by thriving on volatility.  With politicians and central bankers getting more and more enmeshed in our financial system, this cycle will likely continue and even grow for some time.

In the past, I've always leaned towards trend following and momentum..concepts that do well with falling volatility and that follow the consensus.  It's fun to buy when things are smoothly going up and everyone is happy..however, the returns are highly volatile and inconsistent over the long run.  Before reading Antifragile, I started realizing that the most promising systems that I had were excelling during the worst years..they would under perform in 1998, 1999 and then knock it out of the park in 2000, 2001 and 2002.  Interesting! Same happen in 2005, 2006 then 2007 and especially 2008, they began way outperforming.  It has really shaken up many of my investing/trading beliefs.  Okay, enough of my brief summary, more to come soon.

Hope everyone is having a great new year so far!

TLT

Tuesday, October 16, 2012

Interesting Action in the Eur/Usd

I hope everyone is watching the Eur/Usd right now.  We're seeing a strong move higher and it looks like it's going to test the highs of September--roughly 1.3170.  I've got a long position and have been trading in and out of some short term rallies..break outs like these are when you've got to trade heavily in the currencies.



From here, I'll be looking for intra-day rallies to open additional longs (like the opening range break set up) and then I'll look for the Eur/Usd to take out the 1.3170 high from September.

TLT 

Wednesday, October 10, 2012

AEGR: The Highest Implied Volatility of any Optionable Stock

Straight from Options Alert today, they announced that AEGR has the highest IV of any trading optionable stock.  The stock is at 14.17 as of the close of today.  Right now, you can sell a Oct 15 call for $2.55.  That is some serious implied volatility.  So why the IV?  Because the FDA is meeting on October 17th and October 18th to debate the risks and benefits of two experimental drugs..one of which is from AEGR.  Here's a chart:

So how does one play this?  I bought the stock and sold a call...a covered call position as it is known in the options world.  My main risk is that the FDA announces something negative and the stock gaps down.  The FDA is meeting on the 17th and 18th and the option expires on the 18th, so I'm betting that either good news is released early or no news is released prior to expiration.  The ideal situation will be for the stock to trade up to the $15 area by next Wednesday and be able to cover the call after some loss of time value and hopefully some loss of IV.  We'll see.  This is one of those longer shot trades that you don't want to allocate too much to, but it's just attractive enough to nibble on.  I'll post an update on it next week.

TLT

Friday, October 5, 2012

Romney Coming Back on Intrade

At this point, everyone seems to be in agreement that Romney won the debate...I'm pretty sure that was the consensus going into the debate as well.  The interesting thing that I noticed is that after selling of heavily for the last month, the Romney To Be Elected President contract on Intrade is rising again.   In fact, check out the price action on the day of the debate..a big rise on much larger volume.  
It will be interesting to see how predictive Intrade was once this is all over.

Have a great Friday!

TLT

Thursday, September 27, 2012

The Fat Finger F#%$ Up!

Well, it wasn't truly a "fat finger" trade but I did manage to accidentally put on a trade that was 10 times the size intended..so it's pretty much the same thing.  Tuesday, I scanned for potential weekly options trades, meaning I would put the options trade on Tuesday morning and the options would expire, hopefully worthless, on Thursday.  I put on 3 trades, all of them Bull Put Spreads.  A bull put spread is where you sell an out of the money put and then buy a put that's got a lower strike than the put you sold...the idea is that the stock trades up and you keep the spread between the contracts as your profit.  Worst case, the stock tanks and you're out the spread..generally $500 or $1,000 per contract on a 5 or 10 point spread.

Well, I put on trades in AAPL, BIDU and GOOG..all good candidates at that time.  The only problem, I accidentally put an extra zero behind my AAPL contracts and that meant the position was ten times larger than it should have been.  Even worse, I didn't realize the error until Wednesday morning when I checked my account and noticed a large loss.  As it would happen, the only stock to trade down to its strike was AAPL and after fretting about it for a couple of hours, I decided to take the position off and eat the loss.  For these types of trades, I risk between 1-3% of my account value.  The AAPL f-up instantly took my account down 10%..however, the account could have gone down to 25% if I'd of left the position on and it kept going against me.

As much as this sucks, it could have been worse.  I can make up a 10% hit, it will just take time.  The take away for me is to double check my orders when entering the order and then check it again after the trade is put on.  I have had a busy week and was likely multi-tasking when this trade order was entered...that should never be the case.  Furthermore, I hesitated on getting out of the trade when I realized the mistake..not a good idea.  The loss would have been a little less had I just bailed immediately.  I haven't made a good tuition deposit to the school of hard knocks trading university in a while, but that was a good one.

Mistakes happen and we have to deal with them.  We also have to deal with the psychological effects of the mistakes.  One can easily begin to over trade in order to make up a loss and that generally turns things from bad to worse.  For me, the game plan is still the same.  Next week, I'll be scanning for weekly options trades that fit my trade criteria and slowly but surely, I'll dig out of this little draw down.  Just thought I'd share this with everyone...you might relate to it or will some day.

TLT

Wednesday, September 19, 2012

DT 2000 Gave a Buy Signal a Month Ago: Here's the Thinkscript Code for the Indicator

The DT 2000 is a trend following indicator that I came  up with about a year ago.  It uses linear regression and it's purpose is to determine the trend of the overall market.  It uses linear regression slope readings on 4 different symbols and its defaults are qqq, xlv, xlf, tlt.  The indicator tends to work well on the weekly time frame..which makes sense because the longer time frames smooth out the choppy price action of equities.

Here's a chart, the DT 2000 is at the bottom and it's coloring the bars on the chart as well:

This indicator is just one more tool in my collection that I look at to help gauge risk and market bias.  I don't necessarily trade this like a system in and of itself--such as buying the SPY or SSO on buy signals.  What this buy signal does for me is it gives me the confidence to put on more long positions, whether the positions are stocks or covered calls or options spreads.  As you can see from the chart, we've had 3 other buy signals in the last 4 years and the buy signals tend to last several months before petering out.  We'll see if this signal has any legs to it.

Here's the thinkscript code for you thinkorswimmers out there:

####DELETE THIS LINE WHEN PASTING INTO TOS####


declare lower;

input symbol1 = "qqq";
input symbol2 = "xlv";
input symbol3 = "xlf";
input symbol4Inverse = "tlt";
input lrlength = 20;

def data1 = close(symbol1);
def data2 = close(symbol2);
def data3 = close(symbol3);
def data4 = close(symbol4Inverse);

def trend1 = linearRegressionSlope(data1, lrlength);
def trend2 = linearRegressionSlope(data2, lrlength);
def trend3 = linearRegressionSlope(data3, lrlength);
def trend4 = linearRegressionSlope(data4, lrlength);

def score1 = if trend1 > 0 then 1 else -1;
def score2 = if trend2 > 0 then 1 else -1;
def score3 = if trend3 > 0 then 1 else -1;
def score4 = if trend4 < 0 then 1 else -1;

plot DT = score1 + score2 + score3 + score4;    

def buysignal = crosses(DT, 0, crossingDirection.ABOVE);
def sellsignal = crosses(DT, 0, crossingDirection.BELOW);  

assignPriceColor(if dt > 0 then color.green else if dt < 0 then color.red else color.blue);


####DELETE THIS LINE WHEN PASTING INTO TOS####


I hope everyone is having a great week so far.

TLT

Sunday, September 16, 2012

2016..I you haven't yet, go see it.



This is a well done and very interesting moving.  I encourage everyone to go see it, regardless of which party you affiliate yourself with.

TLT

Friday, September 7, 2012

Do More of What Works...

I've been reading Jack Schwager's Hedge Fund Market Wizards, which is a phenomenal book and is just as good as his first two and I highly recommend it to anyone who trades or is interested in trading.  One of the hedge fund managers in the book gives the advice of "find out what works and do more of that" or something to that effect.  Although simplistic, there is a lot to this.  One thing that I've been doing more of lately is active currency trading.  Why?  Simply because my account records show that it works for me.

That is why I want to talk about how smooth the currency market and in particular the Eur/Usd currency pair has been lately for short-term trend and swing trading.  When trading currencies, you must have a routine and specific set ups that you look for and then trade them.  And when those set ups are working well you have to trade them more.  Right now, the opening range breakout trade has been excellent.  The past two days have provided great opportunities to make significant returns with only trading this set up.

I have addressed the opening range break out trade in several posts, but I'll quickly explain what it is for those that are unfamiliar with it.  Basically, you take the first 15 minutes of trading (or it can be 5 minutes or 30..different people use different times) and you note the high and low of the period.  That creates the range. Then you patiently wait for the price action to trade out of the range and trade in that direction.  Generally, I'll day trade with the 5 minute and 1 minute charts.  I'll first look to the hourly and daily charts to determine the bias or the primary trend and then look to for break outs in that direction to trade.  So for the past few days, the bias has been to the higher side...that tells me the path of least resistance is higher and I should look for long trades.

Then I wait for the break out and put the trade on immediately after a 5 minute bar closes outside of the range.  After that I trail a stop with the 1 minute chart and look to book partial profits into momentum and use the trailing stop on the remainder of the position.  If the currency trades back into the range or to the bottom of the range you get out..or have a stop sitting there.  With currencies, it is a little difficult to determine the open.  I will generally trade the 8:30 stock market open with the Eur/Usd since it is pretty correlated with the US stock market.  After I've exited a profitable trade, I look for pullbacks and the support to initiate a follow up trade back to the highs.  After this, I'll look for the highs to be taken out and then trade that break out.  Then I'll look for another pullback from the new high and once it finds support I'll put on another trade.  That's it..plain and simple.  If I'm seeing follow through and the trade is working, I'll keep doing it over and over and over.

Here's a 5 minute chart with today's Eur/Usd with an opening range plot on the chart and some of the trades that I made today.
The opening range is the yellow shaded region.  The bars are all green on this chart because my trendfuzz indicator was in Strong Up Trend mode all day long...not a common event.  Notice that I did not take the OR break below the opening range, as this was a low probability trade given that the trendfuzz was green and the overall bias was up...that's not to say that it always turns out this way, just that today was a perfect day not to take the short trade.  Other days I might take the short trade even with a prevailing bias to the upside, I would just trade a smaller position and book profits very quickly.  Today was a little different because yesterday was incredibly strong and my personal sentiment is very bullish.

This type of trading can be very profitable and very rewarding, you just have to maintain discipline to wait for the proper entries and cut losses quickly.  It is by no means easy and often is very frustrating which is why some people are not suited for day trading.  Over the years, I've gone through periods where I thought I was good at it and was very suited for it and other times where I questioned whether it was for me.  The thing that I've noticed is that day trading equities is a little more hit or miss with me but currencies have been profitable for several years..I just have to stick with it and trade through those incredibly difficult draw downs that have a tendency to leave traders gun shy right at the moment that the next winning trade needs to be put on.  Ok, that's enough rambling for one day.  Hope everyone had a great week and has a great weekend.

TLT

Saturday, August 25, 2012

Bullish Percent: Another Useful and Free Indicator

A friend of mine showed me the Bullish Percent charts on Stockcharts.com about a month ago.  I guess I've never paid attention to these but I'm glad he showed them to me because they seem very useful.  The chart that I like the most is the Bullish Percent of the Nasdaq with a couple of exponential moving averages.  Here's a chart:


As you can see, the crossover's have some fairly decent signals...at the very least they can indicate when to aggressively trade to the long or short side for you shorter time frame trades and for the longer time frame investor/traders, it could indicate a time to lighten up or put on a hedge.

Here's the link to this actual chart.  I keep this chart, along with several others, bookmarked on my computer and I just glance at each chart once a day.  It's just one tool in an arsenal that I use to help navigate the markets.  Remember, this chart is using moving averages so it will be a little lagging in nature, but it can help confirm moves as they are occurring.

Hope everyone's summer was good.  We're about to enter the fall, which is generally a great time for trading.

TLT

Saturday, August 4, 2012

Popular Post Replay: The New Erkel

Originally posted on March 10, 2009...it seems more fitting today.