Question 1

Young programmer's journey to trading success underscores importance of discipline and system adherence.

Accepted Answer

The book begins with the author, Curtis Faith, describing his experience visiting the Chicago Board of Trade and interviewing with legendary commodities trader Richard Dennis. Faith was only 19 years old at the time but had a strong background in computer programming and analyzing trading systems.

Dennis and his partner William Eckhardt were running an experiment to see if they could train people to become successful traders. They had placed ads seeking applicants and received over 1000 responses for just 13 spots. The interview focused on assessing the applicants' intelligence, reasoning abilities, and beliefs about trading.

Faith was selected as one of the trainees, later nicknamed the "Turtles" after Dennis mentioned raising traders like they raise turtles in Singapore. The group consisted of individuals with diverse backgrounds, including gaming, linguistics, and trading experience. While Faith initially lacked trading experience, his system testing background gave him an edge.

After a 2-week training session, the Turtles began live trading with small accounts. Based on their performance over the first month, some like Faith received multi-million dollar accounts while others received smaller amounts or were asked to continue with their initial funding. Despite the short training, Faith had full confidence in Dennis' approach and was able to follow the trading rules precisely.

In the end, the Turtles achieved remarkably successful results, averaging over 80% returns per year. Faith himself earned Dennis' trust to manage the largest account. He credits their success to what he calls the "Way of the Turtle" - a psychological foundation that enabled them to apply the trading lessons correctly during live markets. Let's explore this way.

Question 2

Understanding trader psychology is key in the evolving landscape of electronic trading.

Accepted Answer

Traders deal in risk. There are two major groups of traders: liquidity traders and price traders. Liquidity traders, known as scalpers or market makers, profit from the spread between the bid and ask prices. Price traders, known as speculators or position traders, profit by buying low and selling high.

An example illustrates how this works in practice. A company buys futures contracts from a floor trader to hedge its business risk. The floor trader immediately sells those contracts to a speculator betting on a price decrease. If buying activity suddenly increases, indicating more contracts might be purchased, the floor traders get nervous about further price rises. This causes them to stop selling and instead start buying to close out their short positions. The increased buying activity drives prices up as more traders scramble to cover their shorts. The collective perception of buyers and sellers determines price movements.

In the past, futures contracts were traded in chaotic trading pits. Scalpers and speculators battled face to face using hand signals and shouting. Electronic exchanges are now replacing pits in most markets. While some miss the excitement of pit trading, electronic markets offer lower costs, faster execution, and more volume. The players are the same, though the game has changed. Understanding the psychology of different trader types is still key to success.

Question 3

Emotions and cognitive biases significantly influence trading strategies and market outcomes.

Accepted Answer

Human emotion plays a large role in trading and markets. Cognitive biases like loss aversion, sunk cost effect, and recency bias can lead traders to make poor decisions. Successful traders like the Turtles understand these tendencies and take advantage of the opportunities they create. Different trading strategies work better in different market conditions. Trend following makes money from long term trends but suffers during choppy periods. Countertrend trading profits when markets oscillate in a range. Swing trading targets shorter multi-day moves. Day trading focuses on very short term intraday moves. Good traders don't try to predict markets but react to what the current market state is based on price action and volatility. By avoiding emotional biases and trading appropriate strategies for current conditions, traders can profit from irrational market behavior.

Question 4

Successful trading hinges on probability theory, risk management, consistent strategy, and simplicity.

Accepted Answer

Trading successfully requires following four core principles: trade with an edge, manage risk, be consistent, and keep it simple.

Dennis and Eckhardt first taught the foundations of probability theory, money management, risk of ruin, and expectation. These concepts provided the basis for trading rationally rather than relying on gut feelings. The key was having a trading strategy with a positive expectation, meaning it would produce positive returns over time. Managing risk was critical so traders could survive periods of losses inevitable with any strategy. Consistency in executing the plan allowed its edge to play out. Keeping it simple by catching every trend was emphasized - just a few trends could account for all profits in a year.

The specific method taught was a trend following system called the breakout or Donchian channel. It involved buying when the market price broke out above the high of preceding days and selling when the price dropped below the low of preceding days. The system's parameters were less important than the principles behind it. After paper trading for a month, an account size based on performance was assigned. Despite learning the same method, traders had vastly different returns based on their ability to execute consistently without missing trades. Psychological factors mattered more than knowledge. The first big trend was in heating oil. One trader fully captured it by strictly following the method while others missed a large part of the move due to hesitance and fear. This reinforced the importance of unemotional adherence to the principles taught.

Question 5

Success in trading isn't about prediction but adapting psychologically and learning from mistakes.

Accepted Answer

Successful trading is not about being right but about trading right. Focus on the long term and ignore individual trade outcomes. Many traders who witnessed the Turtle traders' success concluded that trading can be taught. However, some Turtles were much less profitable than others. The difference was psychological makeup. Some took more readily to the Turtle way. Good trading requires the right qualities. These include thinking in the present, avoiding biases, and taking responsibility.

Beginners want to predict markets. They feel like heroes when they win and failures when they lose. This is the wrong approach. Turtles care only about making money, not being right. Turtles do not pretend to predict the future. The future is unknowable in specifics but foreseeable in character. There will be trends, but their timing is unpredictable.

It is easier to profit when wrong most of the time. This shows no attempt to predict. With no expectation to be right, individual trades do not indicate intelligence. With a trading system, winners eventually outweigh losers. When making a trade, Turtles did not judge self-worth by the outcome since most trades lose. They thought probabilistically and so could handle risk and uncertainty.

Some Turtles felt a need to predict and so traded inconsistently. For example, one thought hidden secrets explained worse performance. But no secrets existed. Simpler methods like longer-term breakouts actually worked better. Some blame external factors like markets, brokers or advisors for failure rather than taking responsibility. But markets unambiguously reflect your own trading. Success comes from learning from mistakes, not denying them.

Question 6

Successful trading hinges on identifying and exploiting quantifiable market edges over time.

Accepted Answer

Trading successfully requires having an edge, which is a statistical advantage based on exploitable market behaviors. An edge comes from pairing favorable entry points, where a move in a particular direction is likely, with exit strategies to profit from those moves.

To quantify an edge, compare the maximum favorable excursion (MFE), the most price moved in the direction of the trade, to the maximum adverse excursion (MAE), the most it moved against. The edge ratio (E-ratio) measures this by dividing the average MFE by the average MAE over a specified timeframe. An E-ratio above 1 indicates an edge.

Applying this to a Donchian channel breakout system shows no edge in the short term but a positive edge emerges over longer periods. Adding a trend filter to create a portfolio of markets in an uptrend enhances the edge further by removing trades against the trend. Though hard to quantify for exits, the right exits improve overall system performance. Ultimately, developing and exploiting edges is key to trading success.

Question 7

"Support and resistance levels in trading signal market psychology and trading opportunities."

Accepted Answer

The concept of support and resistance levels in trading results from cognitive biases like anchoring, recency bias, and the disposition effect. Support levels are prices where there tends to be more buying interest, while resistance levels are where selling interest increases. These levels form because recent high or low prices become anchors that traders use for comparisons.

The disposition effect also causes traders to want to sell to lock in profits as prices approach previous highs. When support or resistance levels break down, it indicates a change in market psychology and presents trading opportunities. Breakdowns of support signal downtrends where trend followers sell and countertrend traders exit longs.

Breakdowns of resistance indicate uptrends where trend followers buy and countertrend traders close shorts. Trading near support and resistance represents greater price instability and lower risk. Like armies in battle, wise traders wait for the right opportunity when one side has nearly won the psychological war between buyers and sellers.

Question 8

Effective trading balances personal risk tolerance with reward expectations.

Accepted Answer

Mature traders understand and respect risk. The key question when evaluating a trading system is how to assess if it is good. The financial industry often defines risk in ways that miss certain risks. Traders worry about drawdowns, low returns, price shocks and system failure. Drawdowns are the losses that reduce account capital. Even good systems can have large drawdowns that most traders cannot withstand psychologically. Low returns are periods of small gains where one does not make enough to live on. Price shocks are sudden market moves causing large unrecoverable losses. System failure is when a profitable system stops working.

There are ways to measure these risks like maximum drawdown, longest drawdown, standard deviation and R-squared. Reward measures include compound annual growth rate, average trailing returns and average monthly returns. The Sharpe ratio compares returns to variability but was designed for mutual funds, not leveraged trading. The MAR ratio divides annual return by maximum drawdown. Strategies with the best historical risk/reward often attract the most investors, then stop working. Each trader has different pain tolerance and reward expectations. No single measure fits all. The future will differ from the past. Great traders stick to methods others discard. What looks best historically often fails soon after new investment. Prudent traders balance risk and reward for their own preferences.

Question 9

8. Risk and Money Management

Accepted Answer

Risk and money management are crucial aspects of trading. The primary goal should be to stay in the game, as time is on your side. Even modest steady returns compound into large gains over time. However, taking excessive risk can lead to ruin. Common reasons for failure include having no plan, unrealistic expectations, and trading with too much leverage relative to account size. Proper money management keeps risk of ruin low while maximizing profit potential through appropriate position sizing based on volatility.

The "Turtle" traders used an innovative method to determine contract size based on a market's average daily price range. This normalized volatility across diverse markets. Limits on units per market and overall exposure further reduced risk, especially during market shocks that tend to correlate instruments. Simulating past crises helps gauge risk levels. The key is finding a personalized balance between too much risk that can wipe out capital versus too little that leaves money on the table. With persistence, proper risk management allows you to stay in the game long enough to compound modest gains into substantial wealth.

Question 10

Simple trading tools effectively identify market trends, enhancing profitability with practice.

Accepted Answer

Building blocks are tools that help identify when market trends start and end. Breakouts occur when prices exceed recent highs or lows, signaling a trend may be starting. Moving averages track prices over time - crossovers between short and long averages indicate trend changes.

Volatility channels add price ranges above/below moving averages - prices outside the channel indicate a trend. Time exits simply close positions after a set period. Lookbacks compare current price to an earlier price - large differences indicate a possible trend. Many complex indicators exist but simple tools often work well. The key is finding tools that improve the odds of catching trends, not searching for the perfect indicator. Focus on basic blocks like breakouts and moving averages to build systems with an edge. With practice, traders can use simple tools to profit in trending markets.

Question 11

Backtest results challenge the value of complexity and stop-losses in trading systems.

Accepted Answer

Trading systems were tested on historical data to compare performance. The systems included ATR Channel Breakout, Bollinger Breakout, Donchian Trend, Donchian Trend with Time Exit, Dual Moving Average and Triple Moving Average. Common elements like money management, markets and test dates were kept same.

The Donchian Trend system did not perform as well as others, showing breakouts have lost edge over the years. Surprisingly, Dual Moving Average system outperformed the more complex Triple Moving Average system, demonstrating complexity does not necessarily improve performance.

Systems without stops performed better, challenging the belief that stops are essential. This is because trend followers experience drawdowns from trend reversals after major trends, not from entry risk. When tested further over more months, results changed dramatically for some systems.

This highlights the difference between backtest and actual results, and factors influencing the disparity. More understanding is needed of how to build systems likely to meet expectations.

Question 12

Backtesting is deceiving as it's subject to trader effects, randomness, overfitting, and optimization paradox.

Accepted Answer

Backtesting trading systems on historical data can produce misleading results that do not reflect real-world performance. There are four main reasons for this: trader effects, random effects, the optimization paradox, and overfitting.

Trader effects occur when too many traders adopt the same system, altering the market conditions that the system was based on. Random effects mean pure chance can greatly influence backtest results, so high returns may simply be due to luck rather than skill. The optimization paradox is that optimizing parameters improves theoretical performance but reduces predictive accuracy, as the future will not replicate the past exactly. Overfitting adds complexity that capitalizes on quirks in the historical data that are unlikely to recur.

To build robust systems, traders should be aware of these pitfalls. Using proper optimization techniques, analyzing sample sizes, and detecting performance cliffs can help avoid overfitting and create systems that are more likely to succeed in live trading. Though historical data provides valuable insight, backtests do not guarantee future returns. The best systems capture enduring market behaviors and human psychology rather than transient historical patterns.

Question 13

Historical trading testing with robust methods offers valuable, yet approximate, insights into future performance.

Accepted Answer

Testing trading systems using historical data provides only a rough estimate of future performance. To get the best results, it is important to use robust statistical methods and test over long time periods across many markets.

Key concepts include:

- Using robust performance measures like RAR% and R-cubed that are less sensitive to small changes in the data. This avoids overfitting and gives more stable results.

- Testing over long time frames with many markets to get a representative sample. Complex systems and single market optimization give unreliable results due to small sample sizes.

- Techniques like rolling optimization windows and Monte Carlo simulation show the variability of results. Performance will fluctuate in real trading.

- No test can precisely predict future returns. At best, testing provides a rough guide to the range of likely performance. Expect real results to differ from backtests.

The main message is that historical testing has limitations. By using robust methods and understanding these limitations, traders can still gain valuable insights into the potential of a system. But they should view results as rough approximations and be prepared for fluctuations in actual trading.

Question 14

Robust trading programs embrace diversity and simplicity, adapting to unpredictable market conditions.

Accepted Answer

Trading is a long-term endeavor, like boxing. The market will challenge you, but to win you must withstand the blows and remain standing at the final bell.

New traders often seek the perfect system with optimal historical results. However, no system is perfect for all market conditions. A system may excel during certain conditions prevalent in past data, but those conditions may not recur at the same frequency. The future is unknowable.

To build a robust trading program, diversity and simplicity are key. Like nature, diversity provides resilience against failures in any one component. Simplicity enables adaptability during times of change.

Robust systems incorporate rules to adapt to varying conditions. Simple rules are more durable across market regimes. Portfolio filters, like in the Donchian Trend system, improve robustness by avoiding trades during unfavorable conditions.

Diversifying across many markets increases the chance of encountering favorable conditions. Even if some markets underperform, their inclusion can still improve overall robustness. Liquidity constraints may dictate excluding certain markets. Different market classes behave distinctly, warranting potential exclusion of entire classes from certain systems.

Diversifying across uncorrelated systems can also improve robustness. Combining systems that excel in different conditions can smooth performance. System diversification, like market diversification, often requires significant capital.

By acknowledging the unknowable future, robust trading programs built on diversity and simplicity are more likely to perform consistently despite varying conditions. Mature trading accepts unpredictability and adapts accordingly.

Question 15

Mastering psychology, conquering ego and exercising humility lead to successful trading.

Accepted Answer

Trading successfully requires mastering your psychology. The market is impartial, so you must face the truth about it and your limitations. Legendary trader Richard Dennis proved simple, teachable principles can lead to profit if followed consistently. But many struggle to accept this, thinking trading must involve secret, complex knowledge to feel superior. This ego-driven belief in discretionary trading leads many astray.

An example comes from the famous Turtle traders. One Turtle was the clear best at Ping-Pong, easily beating the rest. But in a tournament, his ego drove him to smash shots to finish opponents quickly. A less skilled Turtle played conservatively, returning shots steadily. As the games wore on, the best player grew frustrated and angry, making mistakes. Though he was superior, his ego caused him to lose to an inferior player.

This same Turtle struggled as a trader, unable to accept the simple reasons he lost money. He thought it was because he lacked secret knowledge others had. But the real problem was psychological - not following the rules consistently. His ego prevented him from facing his shortcomings.

To be a great trader, you must conquer ego and develop humility. Humility allows you to accept the future as unknowable and avoid predictions. It prevents taking losses personally and lets you use simple systems without requiring special secrets. Ego drives the need for complexity and discretionary trading. But consistently following rules with humility leads to success. Mastering psychology is essential to trading well.

Question 16

Accepted Answer

Final Summary: "Way of the Turtle" by Curtis M. Faith is a compelling account of his experience in Richard Dennis's Turtle experiment which sought to prove that trading could be taught effectively. The book shines a light on the significant role psychology plays in traders' success and emphasizes the importance of following a systematic approach. Faith asserts that it’s not only about the trading system; it's the trader’s ability to execute the trading system efficiently that matters. He asserts that most traders will experience more losses than gains, but the gains will typically be larger, yielding a positive net outcome. This understanding of reality gives traders the confidence to trust their systems for long-term wins.

10 specific actions that reflect the learnings from the books and help to implement the learnings from the book into one's life are:
1. Develop and follow a consistent trading system.
2. Embrace the high probability of being wrong and focus on the larger gains.
3. Accept responsibility for your own trades, learn from your mistakes rather than blaming others.
4. Apply game theory to your thought process to enhance decision making.
5. Continuously test your trading system and have confidence in it.
6. Keep emotions at bay and avoid cognitive biases while trading.
7. Risk and money management should be a key focus.
8. Be unafraid to be different, take your own path; this can be applied both in trading and life. 
9. Engage in consistent learning and knowledge enhancement about trading techniques and strategies.
10. Apply the lessons learned from trading, like mitigating cognitive biases, into other areas of life.

Way of The Turtle - Book Summary (2024)