Powerful Predictors of Success of New Traders contd…

2)  Mentorship – Every single young trader I’ve seen go from zero to hero, where I directly observed the evolution, has benefited from a high degree of mentorship.  I am not talking about taking trading courses, reading trading books, or working with “coaches”.  Rather, I’m referring to working side by side with a talented senior trader; observing their preparation, research, trading, and risk management; and absorbing the lessons of those observations.  There is a reason mentorship is embedded in most professional training programs, from the apprenticeships of master plumbers and electricians to the clinical rotations of medical students and the training of fine artists.  Role modeling channels and accelerates performance development.

Now , role modeling channels & accelerating performance development, this aspect when elaborated to strategising, we can come out with comparision. Comparision when considered amounts to a chain re-action, creating a viscious circle to or towards ones learning curve, thus again bringing us back to the first point of discussion “diligence”.

Powerful Predictors of success of new traders

1)  Diligence – All of the successful young traders were workhorses and not show horses.  They put significant time into studying markets, learning from others, and learning from their mistakes.  All spent much more time in preparation, research, and idea generation than in trading.  They also displayed diligence in managing their capital.  All were very good at being open-minded, recognizing when a trade was not working out, and limiting losses.  This diligence in preserving capital helped them not lose too much money during their learning curves.

Now , to elaborate on learning curves : With repetition of almost any motor task, learning occurs, and a person becomes more efficient or effective at carrying out a task. In the pursuit rotor tasks, time spent on the metal dot increases. In the mirror-tracing task, the tracing becomes more accurate. Progress in skill learning commonly follows an S-shaped curve, with some measure of skill on the Y axis and number of trials on the X-axis. Progress is slow at first, then a subject may experience a burst of learning that produces a rapid rise on the graph.

People often speak of a steep learning curve when they mean the opposite. A steep learning curve is one in which skill improves quickly, meaning something is easy to learn.However, what most people mean by “steep learning curve” is difficult learning experience. No doubt they are thinking of steep hills and steep mountains which make climbing difficult In actuality, the steepest part of the learning curve is the portion where learning is fastest and easiest.

Two of the Biggest Mistakes Traders Make

This is one of the most important aspects to be considered while trading what are the biggest mistakes, on which there is a very insightful article below:

As I look across the good trading and not-so-good trading that I’ve observed over the years–my own, as well as that of others–there are two big mistakes that stand out as key differentiators:

1)  Putting Prediction Ahead of Understanding – In a sense, this boils down to acting before we truly understand the rationale for action.  At first blush this makes no sense at all.  Still, the fear of missing moves and the need to make money sometimes lead us to anticipate market behavior before we’ve fully done the work of understanding why markets should move in such a fashion.  Traders often speak about the importance of having confidence in their views.  Genuine conviction, I find, is a function of deep understanding.  If we perceive that we have a grasp of what is driving markets, we are more likely to stick with the trade ideas emanating from that understanding.  Nothing guarantees, of course, that our explanations of market behavior are correct.  It’s a pretty good guarantee, however, that if we anticipate market movement and put on positions before we achieve a grasp of why that movement should occur, we’ll be easily shaken from our ungrounded convictions.

In the chart above, I track what I call “Demand” for stocks.  It is a running five-day average of upticks vs. downticks among NYSE shares.  There is some predictive value to those data, but particularly important from my vantage point is putting the data into context to understand what is happening in markets.  When markets move quickly from a point of negative Demand–net selling pressure–to a point of high Demand (net buying pressure), that momentum reflects an important shift in market participation that tends to persist over the near term.  Conversely, when markets bounce higher but net Demand remains negative, that suggests a lack of upside participation and, ultimately, a vulnerability to the rise.  Note how that was the case during the market topping in September.  One important component of understanding is simply identifying whether buyers or sellers are in control of the market and which way that balance is moving.  Identical chart patterns can follow from very different configurations of net Demand.

2)  Mismatch of Time Horizons – This is the result of conceptualizing trade ideas on one time horizon and managing the risk on a very different time frame.  A classic example would be a “macro” trader who develops a fundamental thesis about how stocks should move over the next 3-6 months, but then is forced to stop out of positions on retracements that, ultimately, are expectable over such a time period.  In other words, the psychological tolerance for loss is poorly matched with the trader’s conceptual framework.  This occurs at trading firms where risk is managed tightly, but where traders still feel a need to stick with ideas and maintain their convictions.  I recall working with a rookie daytrader whose hit rate on trades was startlingly abysmal.  It seemed as though the results were not random, but represented a significant negative alpha.  What that trader would do is set stops insanely close to the point of entry, pride himself on a “good risk-reward trade” and then get stopped out 80% of the time on a putative 3:1 good bet.

When the press for opportunity greatly exceeds the tolerance for loss, it’s a sure bet that good trades will be managed poorly.  We can have superior market understanding, derive excellent trade ideas from that understanding, and still fail to make money simply because we our psychological misalignment between risk and reward leads to poorly aligned position management.  Far better to stay in good trades with modest size than continually stop oneself out on noise and fail to capitalize on solid understanding.

From the above two mistakes of a trader i would like to elaborate on Putting prediction ahead of understanding. Most of the time , traders don’t have a discipline for their trades, moreover having a trading system is very important. Peer group discussions having an effect on ones prediction for the markets.Putting prediction ahead of understanding can be considered as that taken sort as a result of such discussions. Discussions demand a subject matter understood in the right context, as a result putting prediction ahead of understanding based on ones context of trade.

Breadth Volatility and Stock Market Cycles

Above is a measure that I’ve been working with lately that I call breadth volatility.  The indicator is created by tracking the percentage of stocks trading above various short term moving averages and then calculating the standard deviation of that series.  What we find is that breadth volatility tends to be low ahead of cycle peaks and crests as markets make–and rally from–bottoms. Going back to 2012, when breadth volatility has been in its highest quartile (greatest volatility of breadth), the next five days in SPY have averaged a gain of +.54%, much greater than the +.10% for all other occasions in the sample.

nterestingly, the breadth volatility measure shown above correlates only .41 with VIX going back to 2012.  That’s a significant correlation to be sure, but suggests that VIX only accounts for 16% of the variance in breadth volatility.  Indeed, when I’ve tracked breadth volatility for specific VIX regimes, the predictive results with SPY have been quite good.

As you can see from the chart above, we made a low in breadth volatility ahead of the recent price peak in stocks and now have been trending higher as the market has sold off.  As of yesterday’s close, we were not yet at levels associated with intermediate-term market bottoms.

The previous two posts have looked at variables that I have found useful in tracking short-term movement in the stock market:  buying/selling pressure and volatility.  A third variable I have found useful is the breadth of movement among stocks.

There are many ways of tracking breadth.  Of all of these, I have found advance-decline lines to be among the least useful in predicting forward price movement.  This reflects my more general experience that the most commonly tracked market measures are among the least useful, perhaps precisely because they are so widely tracked.

Above are three breadth measures that I have found to be useful.  The first (top chart) is the number of common stocks across all changes that are making fresh three month highs minus those making new three month lows.  (Data available from the Barchart site).  You can see that breadth has deteriorated in recent days, leading to the most recent market weakness.  You can also see that breadth has deteriorated since the early August decline, as the market rally grows increasingly selective.

The second measure (middle chart) covers all stocks listed on the NYSE and tracks the daily number that close above their upper Bollinger band minus those closing below their lower Bollinger band.  (Data available from the Stock Charts site).  This, too, shows a recent pattern of deterioration, even as stocks moved to new highs.

The third breadth measure (bottom chart) is specific to the universe of S&P 500 stocks.  It is a composite measure of the percentages of SPX stocks trading above their 3, 5, 10, and 20 day averages.  (Data available from the Index Indicators site).  What we see again is a tendency for this measure to peak ahead of price, as has happened most recently.

In general, I find that strong breadth leads to short-term upside momentum, followed by reversal.  Weak breadth leads to short-term downside momentum at important market bottoms (i.e., bottoms of longer-term market cycles) and short-term reversal at market corrections.  In a qualitative sense, these measures give me a picture on whether markets are getting stronger or weaker day over day–very useful information for gauging where we might be at in a market cycle.

Vocational interests are expression

Vocational interests are expressions of what an individual finds rewarding in terms of social interaction, external rewards (i.e. remuneration) and social status, and a sense of personal meaning. For example, many people go into finance or trading because they like the potential for high income; an example would be Charles Schwab. The same type of people, interestingly, would make great intelligence analysts

Over 100 years of world-wide professionally conducted empirical research on human performance, combined with a few more decades of study on human cognition, could be summarized as follows:

Cognitive ability enables one to make sense of data, integrate new information with previously learned information, and retrieve information to create new work products. But before your readers with perfect SAT scores or A-level exams start congratulating themselves, let’s acknowledge that being among “the smartest guys in the room” doesn’t mean you’ll be successful; just look at what high IQ did for Enron. And as you and I know from our work with traders, a lot of successful traders think people with academic smarts are, well, stupid. What distinguishes “smart” from “successful” is good decision-making. So the question is, why and how do people make good decisions?

Sector Correlations in the Stock Market and What They’re Telling U

Some demographic groups will care about brand name and image; others will emphasize value and price.

  The successful marketer constructs multifaceted campaigns to reach segmented groups of consumers.  If the marketer were to become identified with a single strategy and expect all people to respond to that, the results would be mixed at best.   

Presence of aperiodic cycles in the stock market.  These are cycles that occur, not in chronological time, but in event time. Imagine market cycles that can occur over periods from minutes to hours to days to months, depending on the unfolding of critical events.  A successful trader of such cycles would be neither a daytrader, nor an investor. As Bruce Lee’s insight suggests, that successful trader would be all of them–and none of them.  It is not a small challenge when the market’s flexibility exceeds our own!

Railway Budget Comprehensive

NEW DELHI: As many as 58 new trains, including five new ‘Jansadharan’ trains and an equal number of premium group of trains have been proposed in the Rail Budget presented by railway minister Sadananda Gowda on Tuesday.

The new trains include six AC Express trains, 27 Express trains, eight passenger trains, two Mainline Electric Multiple Unit (MEMU) services and 5 Diesel Electric Multiple Unit (DEMU) services besides extension of 11 existing trains.

“It is the wish and dream of every Indian that India runs a bullet train as early as possible. Indian Railways is on its way to fulfil that long cherished dream,” Gowda said.

The Minister said while bullet trains will require completely new infrastructure, higher speed for existing trains will be achieved by upgrading the present network.

“Hence, an effort will be made to increase the speed of trains to 160-200 kmph in select sectors to significantly reduce travel time between major cities,” he said.

EI Nino Impact on the Economy what is EI Nino?

 

 

 

There is a phase of ‘El Niño– Southern Oscillation’ (ENSO), which refers to variations in the temperature of the surface of the tropical eastern Pacific Ocean and in air surface pressure in the tropical western Pacific. The two variations are coupled: the warm oceanic phase, El Niño, accompanies high air surface pressure in the western Pacific, while the cold phase, La Niña, accompanies low air surface pressure in the western Pacific.[2][3] Mechanisms that cause the oscillation remain under study.

El Niño (/ɛlˈnnj//ˈnɪn/Spanish pronunciation: [el ˈniɲo]) is a band of warm ocean water temperatures that periodically develops off the Pacific coast of South America, El Niño is defined by prolonged warming in the Pacific Ocean sea surface temperatures when compared with the average value.

The Southern Oscillation is the atmospheric component of El Niño. This component is an oscillation in surface air pressure between the tropical eastern and the western Pacific Ocean waters. The strength of the Southern Oscillation is measured by the Southern Oscillation Index (SOI). The SOI is computed from fluctuations in the surface air pressure difference betweenTahiti and Darwin, Australia.[8] El Niño episodes are associated with negative values of the SOI, meaning there is below normal pressure over Tahiti and above normal pressure of Darwin.

The studies of historical data show the recent El Niño variation is most likely linked to global warming. For example, one of the most recent results, even after subtracting the positive influence of decadal variation, is shown to be possibly present in the ENSO trend,[51] the amplitude of the ENSO variability in the observed data still increases, by as much as 60% in the last 50 years.[52]

The exact changes happening to ENSO in the future is uncertain:[53] Different models make different predictions.[54][55] It may be that the observed phenomenon of more frequent and stronger El Niño events occurs only in the initial phase of the global warming, and then (e.g., after the lower layers of the ocean get warmer, as well), El Niño will become weaker than it was.[56] It may also be that the stabilizing and destabilizing forces influencing the phenomenon will eventually compensate for each other.[57] More research is needed to provide a better answer to that question. The ENSO is considered to be a potential tipping element in Earth’s climate.[58