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Mar 15, 2023
The five most important Lessons Learned After 10,000 hours of Trading

The five most important Lessons Learned After 10,000 hours of Trading

Ten thousand hours of active trading, broken down into forty-hour weeks, amounts to almost five years. Having surpassed that milestone myself, I now understand why it's significant for any trader's journey. The early years taught me valuable lessons that have shaped my approach to trading.

It's a misconception that great traders are born with innate talent. The truth is that it takes years of actual trading to achieve consistent success. You may experience beginner's luck by following good advice initially, but individuality and emotions can lead to mistakes. It's a common pitfall for every trader.

In this article, I'll outline the five most crucial lessons I learned during my 10,000 hours of trading. While some were imparted to me when I first started, it was only through experience that their significance became clear. If you're new to trading, pay close attention to these lessons.

Lesson #1: Risk Management is Multi-Dimensional

At the beginning of my trading journey, I viewed risk as a simple and static principle. I determined how much I could invest and stuck to that budget. I made purchases based on this budget and relied on gut instincts to decide when to sell.

However, I failed to consider the amount of loss I was willing to accept before selling. I rarely sold during a downtrend, thinking that the market would eventually bounce back and I would recover my initial investment. In hindsight, this was not a sound risk management strategy, but rather a combination of gambling and gut instincts, which have led to the downfall of many traders.

Effective risk management is a multi-dimensional concept. Establishing a trading budget is a good start, but discipline around setting stop losses is also crucial. I made the mistake of letting my ego take over after hitting big on a few options early on.

To ensure proper risk management, it's best to use automation tools like Tickeron. Since implementing Tickeron, I've been able to more accurately predict the appropriate exit points for both gains and losses. It's important to remember that risk works both ways, as greed can also lead to holding onto a position for too long.

Lesson #2: Ignore the Stock Promoters

Stock promoters like Jim Cramer may use flashy theatrics to hype up their audience and create a buying frenzy. However, basing trading decisions on their opinions is a recipe for disaster. In reality, it's all hype and not science.

Over time, I have learned to completely shut out the noise of stock promoters. I no longer watch CNBC, and instead rely on technical analysis to determine when a position is likely to gain or lose money. Any opinion I hear on television is just that - an opinion.

While Cramer and other stock promoters may have a decent win percentage, relying on them as an "informed source" is not reliable for developing a trading pattern. Promoters are more suitable for long-term investors rather than traders.

In my experience, the talking heads on financial news networks are not relevant to trading decisions either. A press release about a merger or acquisition may provide useful information, but hours of debate about the motives behind the deal are not worth my time.

Personally, I prefer to stick to chart patterns for trade decisions. I have a list of preferred stocks that offer the volatility I am looking for, diversified across several sectors. I don't rely on anyone else's opinion when it comes to buying and selling these stocks.

Edit: Lesson #3: Chart Patterns are More than Just Line Graphs

Imagine every stock is nameless and all you have to guide you is a performance chart. Professional traders analyze the chart patterns to make their trade decisions. In my early days, I relied too much on supporting documentation and slowed down my trading. But not anymore.

Financial reports and media stories are useful for long-term investors, but for traders, the chart pattern is the main indicator. Reading patterns correctly and understanding their indications has made me a better trader.

Eliminating background noise and meaningless chatter is perhaps the most important lesson I’ve learned. The media is good for identifying sector trends, not individual stocks. Chart patterns, on the other hand, reveal what a stock is likely to do.

However, identifying the right pattern is not always easy. What looks like a cup and handle could easily turn out to be a bearish head and shoulders or the second leg of a triple bottom. I made many mistakes early on, but experience has taught me to identify patterns accurately.

Another advantage of relying on chart patterns is the ability to make more trades during the day. Since I view stocks as nameless entities, I can buy and sell without emotion or attachment.

Edit: Lesson #4: Trading Strategies Must Evolve

The stock market is unpredictable, and no one could have foreseen the global pandemic of 2020, which shook up the market. The pandemic affected the stock market, and it's hard to tell if tech stocks would have increased in value if the pandemic didn't happen. The pandemic also accelerated or decelerated existing trends.

During uncertain times, such as the one we're experiencing today, I tend to become more of a scalp trader. Quick trades with fast exits are a great way to test the waters of an uncertain market. It also helps me watch new chart patterns as they develop.

I've learned that trading strategies need to evolve constantly. Even when the market isn't experiencing major upheavals, it still changes. Markets shift, and new technology is developed. It's all part of doing business.

One lesson I learned in my first five years is that changing strategies doesn't mean going "all in" on specific stocks because I've recognized a new pattern. My risk tolerance should be pre-set, and I don't change it when I sense a favorable situation.

For instance, let's consider the pharmaceutical sector. I'm not a big fan of drug stocks, but the race for a Covid-19 vaccine has created some opportunities this year. Moderna and Pfizer are two favorites of mine that have generated some short-term profits.

I incorporated these companies into my trading portfolio by reallocating my resources from other sectors. I didn't add additional funds or change dollar amounts on individual trades. These companies are simply nameless entities with chart patterns, just like all the other positions in my portfolio.      

Lesson #5: Diversification can Take Many Forms

In the previous scenario, diversification was achieved by reallocating funds to previously avoided sectors. Before this year, I typically stayed away from healthcare and consumer discretionary stocks and focused heavily on energy and tech stocks. However, as a trader, my concept of diversification may differ from that of a financial advisor.

The market is divided into sectors (11), industry groups (24), industries (69), and sub-industries (158). While financial advisors create portfolios diversified across all sectors, traders have more flexibility. The key is finding what works for you.

My advice is to not diversify just because someone said you should. Diversification looks different for everyone. As a trader, you're not necessarily looking for long-term trends that will affect multiple sectors. Money can be made and lost in a single day.

Personally, I prefer to work with fewer variables in the equation. Sectors and industries display diverse chart patterns. Pharmaceuticals, for example, can rise and fall quickly and unexpectedly. Blue-chip tech stocks are more predictable. A balance can be achieved by trading both.

Some traders focus on a single sector and diversify across industries within that sector. This approach is too narrow for me, but many traders make good money doing it. Diversification can take many forms, but the concept remains the same: don't put all your eggs in one basket.

Life Lesson: Discipline and Emotional Detachment

Perhaps the most valuable lesson I have learned as a trader is the importance of discipline and emotional detachment from any particular stock. My personal feelings about the companies I buy and sell never come into play. Only gains and losses matter during the trading day.

This is a major difference between investors and traders. Investors often put together portfolios based on personal beliefs, such as investing heavily in "green" stocks or avoiding petroleum stocks. As a trader, I use chart patterns and rarely even know what a company does.

Discipline is crucial when implementing a trading plan. As we've discussed before, it's possible to experience big losses in the morning and recover late in the day. But that won't happen if you alter the plan at noon. It's important to discipline yourself to stick with the plan, even when emotions are running high.

Tickeron’s Approach to Fintech: Artificial Intelligence for Retail Investors

Hedge funds and large institutional investors have been using Artificial Intelligence to analyze large data sets for investment opportunities, and they have also unleashed A.I. on charts to discover patterns and trends. Not only can the A.I. scan thousands of individual securities and cryptocurrencies for patterns and trends, and it generates trade ideas based on what it finds. Hedge funds have had a leg-up on the retail investor for some time now.

Not anymore. Tickeron has launched a new investment platform, and it is designed to give retail investors access to sophisticated AI for a multitude of functions:

Finding stock patterns in the market
Finding trends in the stock market
Testing portfolios to see if they are well-diversified
Back-testing statistics to see how different stock patterns generated trading results
Making Predictions for price movements in the future, with “A.I. Rank” and level of confidence in the trade.
And much more. No longer is AI just confined to the biggest hedge funds in the world. It can now be accessed by everyday investors. Learn how on Tickeron.com.


Contributor

Sergey Savastiouk, Ph.D. has a degree in Applied Mathematics from Moscow University and has extensive experience as an entrepreneur, investor, manager, and mathematician. His professional expertise is in applied mathematics, mathematical modeling, system and pattern analysis, and software and hardware system integration. He has served as the CEO of several hi-tech start-up companies and nonprofit organizations, which has given him proven capabilities in business strategy for high-tech start-up companies, market assessment, company formation, team building, product development, marketing, and sales. He has published numerous articles in journals and magazines on related fields. As a retail investor, he spent 15 years developing his proprietary trading and quantitative algorithms (now Tickeron’s A.I.), which brought him significant returns in trading the stock market. His current work and goal in founding Tickeron is to bring professional, sophisticated stock market analysis capabilities to retail investors via an easy-to-use interface.


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