** This post is a guest post by Admiral Markets Ethan Featherly **
When it comes to online trading, luck and mastery of skill using mathematical values and analysis are often intertwined. In the recent years, information has become readily available which has led to more instances of making lucky trades. Luck becomes inevitable as people become more skillful in particular areas. The discussion below deliberates on the role of each aspect in making successful online trades.
Making A Lucky Trade
Most traders get enthused by outcome biases where they tend to make judgments based on recent results and overlook other inputs into the process. For instance, a mutual fund manager may invest a significant percentage of his fund into one stock and outperform the index in a year.
The performance may be out of sheer luck or skill as a result of using a methodology that suggested the stock was poised to outperform and predicted a good trade? He may be a reckless manager who made a safe bet, making other traders fawn over him.
An adept fund manager demonstrates a decade of consistent performance. Investors should analyze the frequency of outperformance and its magnitude over a period to confirm the trader’s mastery of the skill. Lucky trades show several good years of business, but the overall trend demonstrates underperformance and lack of obvious advantage in the market.
Critics are bound to argue that some investors make consecutive lucky trades in a year. In such instances, the traders have learned to understand and improve the process. Lucky deals are somewhat random, hence the need to have a historical backing or research that supports your move and the expected results.
Traders also need to recognize the difference between making a good trade and a winning trade. The latter allows traders to make money despite conducting haphazard research and decision making. A good trade involves sticking to the process and employing strategies that are consistent with it regardless of the outcome.
Using Math For Successful Stock Trading
Making insanely good deals out of sheer luck is extremely rare, thus the need to employ more practical models. Mathematical models have been known to give near accurate predictions about the performance of stocks. As such, they have become invaluable tools in most if not all spheres of life; from movies to TV shows to casino games and now to making successful online trades.
The systems may not predict the future with certainty, but sophisticated mathematical algorithms can calculate the probability of events, which helps stock market traders reduce the likelihood of making bad trades. Legendary stock traders like Warren Buffet may have given the impression that good deals mean 100% accuracy.
The truth is that successful stock traders are only right half the time at best and investors have to contend with the disappointment of losing money. For example, an investor who makes $ 2,000 for four of every ten trades and loses $ 1,500 on the other six deals still makes a profit of $ 500. Investors who rely on mathematical analysis of stocks use two proven math laws:
Power Laws vs Gaussian Laws
Let us take a closer look at the mathematical aspects of online trading.
Power laws calculate how a change in the value of one quantity affects another quantity. For instance, how the value of a company affects its stock price in the market.
The results help calculate standard deviations that allow traders to understand risks and make buy or sell trades accordingly. Gaussian laws, on the other hand, estimate the random changes on uncorrelated entities, a noticeable feature in the particularly volatile stock market except that most transactions are related. Gaussian logic is unlikely to predict sudden crashes.
Traders who use this form of math laws are known as quants. Computer aided quantitative analysts study how amounts relate to each other, which is a standard that mathematical model trading houses employ. The calculations allow traders to anticipate potential risks ahead of time and make appropriate buy or sell actions.
How Luck and Mathematical Values Intertwine
Evidently, factors like probabilities, records of historical data of successful trades, and criteria used to make such deals come into play when trading and investing.
The essence of gathering such data is to confirm results about trading strategies employed. While most performance is judged based on calendar systems like months, quarters, and years, probabilities and particular statistics assert themselves over extended periods and vast quantities of data.
More data and time on Renko Indicator charts demonstrate the role of luck and mathematical models in stock trading. Additionally, experts cite that calendars are not as material as the number of decisions made over that period. Thus, investors should resist the urge to shoot from the hip by selling or buying when everyone else is.
Tim Grittani, a trader who turned $1,500 to $ 1 million in just three years, explains how he lucked out from trading in penny stocks. He had studied penny stocks and noted that they were prone to pump and dump scams but continued trading in the speculative companies.
The trade that raked over $ 1 million was a short bet against a company that was a target of a pump and dump plan. The company’s stock had tripled in a month, and Grittani noted it was losing momentum drastically. He made his move and earned $ 8,000 in ten minutes.
The bottom line is both luck and mathematical analysis play out in making online trading decisions. As such, traders should not be blind to short-term outcomes but employ decisions based on accurate information from mathematical models in a timely manner to be reckoned as lucky.
Ethan Featherly is a financial analyst and Admiral Markets content manager. His interests range from financial predictions to mathematical and technology-related topics.