Built For
Instruments: Multi Assets
Strategy Overview
This trading framework is built around a simple principle: before deciding what indicator, pattern, or setup to trade, understand where the trading edge actually comes from.
Many traders begin by learning tools. They find a moving average crossover, breakout pattern, RSI setup, or another technical signal and then try to apply it to the market.
The problem is that a trading tool is not the same thing as a trading edge.
The same strategy can behave very differently depending on the asset class, timeframe, liquidity, volatility, competition, holding period, and trading costs involved.
Because of this, the framework starts at a more fundamental level.
First, understand the environment you are trading in.
Then understand the type of market behavior you want to capture.
Only after that should you choose the tools that help identify that behavior.
The framework eventually leads to three primary directional approaches for individual traders: short-term momentum, mean reversion, and long-term momentum or trend following.
But before getting to those strategies, it is important to understand why certain approaches may have a stronger edge in some markets than others.
Understanding Trading From First Principles
One of the biggest mistakes traders can make is becoming confident in their tools before becoming competent in understanding the market.
A trader may learn a few concepts and quickly feel as though they understand how trading works. They learn a pattern, an indicator, or a strategy and assume that consistently following it should eventually produce profits.
But learning how to recognize a setup is different from understanding why that setup should make money.
This is where the difference between confidence and competence becomes important.
Real competence develops when a trader begins understanding what drives an opportunity, why an edge exists, where that edge should be traded, and what can cause it to disappear.
This changes the way a strategy is built.
Instead of asking:
“Which indicator should I use?”
The trader begins asking:
“What market behavior am I trying to capture, and why should that behavior provide an edge?”
The indicator then becomes a measurement tool rather than the strategy itself.
Trading Is a Competitive Environment
Trading is a competitive activity because every participant is there for a financial reason.
Individual traders want to make money. Hedge funds and professional trading firms want to make money. Market makers provide liquidity because there is a financial incentive to do so. Brokers also generate revenue through trading activity and fees.
This is particularly important for short-term trading.
Before costs, many short-term approaches operate close to a zero-sum environment. Once commissions, spread, and slippage are included, those costs create another obstacle that must be overcome.
This means the trader’s objective cannot simply be to participate in the market.
The objective is to find and exploit a genuine trading edge.
The Trader’s Main Objective: Maximize Edge
A trading edge is a statistically significant advantage.
In simple terms, if a trader repeatedly takes the same type of opportunity over a large enough sample and that behavior has a positive expected outcome, the trader has an edge.
The objective is to find the strongest edge possible and exploit it.
But because other participants are trying to do exactly the same thing, the trader also needs to consider competition.
If an opportunity is highly profitable, stable, scalable, and easy to trade with large amounts of capital, professional participants have a strong incentive to exploit it.
This leads to an important principle:
To maximize trading edge, also think about where competition can be reduced.
Playground vs. Approach
Before choosing a strategy, separate trading into two decisions:
The playground and the approach.
The playground describes where you are trading.
This includes the asset class and the timeframe.
The approach describes how you are attempting to make money within that environment.
A strategy should not be selected independently of its playground.
An approach that works well in one asset class may perform very differently in another because the underlying liquidity, volatility, efficiency, and competition are different.
The same applies to timeframe.
A strategy operating on a one-minute chart exists in a very different competitive environment from a strategy holding positions for several days.
The first step is therefore not to find a pattern. It is to understand the playground.
Sharpe Ratio and Why Institutions Care About Stability
To understand where competition is strongest, it helps to understand what professional market participants are trying to achieve.
One important measurement is the Sharpe ratio.
In simple terms, the Sharpe ratio compares the returns generated by a strategy with the volatility of those returns.
Suppose two strategies produce approximately the same return.
- The first strategy has large swings in its equity curve.
- The second produces the same return with much smaller fluctuations.
The second strategy has the higher Sharpe ratio because it is generating the same return with greater stability.
- If returns increase while volatility remains similar, the Sharpe ratio also improves.
- If returns decrease while volatility remains high, the Sharpe ratio becomes worse.
This matters because professional trading firms and institutional vehicles generally want to maximize returns while keeping volatility as low as possible.
Stable returns are extremely valuable.
Institutions have significant capital, technology, data, research teams, and the ability to hire highly skilled people to search for these opportunities.
As a result, the environments capable of producing high Sharpe ratios can also become some of the most competitive areas of the market.
Timeframe, Sharpe Ratio, and Competition
There is an important relationship between timeframe and potential Sharpe ratio.
Shorter-term strategies can potentially provide faster capital turnover, shorter drawdowns, and more frequent opportunities.
These characteristics can help create smoother return streams.
That makes shorter-term opportunities attractive to professional trading firms.
As the timeframe becomes longer, the potential Sharpe ratio of an individual strategy can become lower. Trades occur less frequently, drawdowns can last longer, and returns may be less stable.
At first, this may sound like a disadvantage.
But for an individual trader, it can actually create an opportunity.
Professional firms have a strong incentive to compete aggressively for highly scalable, stable return streams. An individual trader does not necessarily need the same characteristics from a single strategy.
This means the retail trader may be better served by operating in areas where the edge is stronger even if the individual strategy produces a less perfectly smooth equity curve.
Stability can later be improved by combining multiple strategies.
Understanding the Different Asset Classes
Timeframe is only one part of the playground. The trader also needs to think about the asset class.
The major markets discussed within this framework include:
Forex, commodities, stocks and ETFs, and crypto.
These markets do not offer the same environment.
Their liquidity, volatility, efficiency, and level of professional participation can be very different.
Understanding those differences helps determine where an individual trader may have the greatest potential edge.
Liquidity and the Retail Trader’s Advantage
Highly liquid markets allow very large amounts of capital to be traded efficiently.
This is attractive to institutions because they need markets capable of absorbing large positions.
A strategy might contain an excellent theoretical edge, but if a professional firm cannot deploy meaningful capital into the opportunity, the strategy may not be worth pursuing for them.
This creates one of the biggest advantages available to an individual trader:
Small size.
An individual trader with an account below the size required by a major institution does not need an opportunity capable of absorbing enormous capital.
A relatively small inefficiency can still be valuable.
This means individual traders can potentially participate in opportunities that are too small or too illiquid to be attractive to the largest professional firms.
Liquidity and Volatility
There is an important relationship between liquidity and volatility.
Generally:
- Higher liquidity tends to come with lower volatility.
- Lower liquidity tends to come with higher volatility.
This relationship is especially important for directional traders.
Many retail strategies rely on price moving significantly in one direction.
- Momentum trading needs movement.
- Breakout trading needs movement.
- Trend following needs movement.
Greater volatility creates more directional movement for these approaches to potentially capture.
This does not mean the trader should simply search for the most volatile market available.
The goal is to find the right balance between volatility, liquidity, competition, and the trading approach being used.
The Immature-to-Mature Asset Cycle
Markets can also change as they mature.
An immature market can begin with relatively low liquidity and very high volatility.
These conditions create inefficiencies and potentially large trading opportunities.
Those opportunities attract capital.
As more traders and professional participants enter, liquidity increases.
Greater liquidity allows larger firms to participate.
As competition grows and inefficiencies are exploited, volatility can gradually decrease.
The market begins moving from:
Low liquidity + high volatility
toward:
Higher liquidity + lower volatility.
Crypto provides an example of this process.
Its volatility and inefficiencies attract capital, but that same capital gradually changes the characteristics of the market.
This is important because traders should not assume that the opportunities available in a market today will remain unchanged forever.
Edge Decay
This leads directly into another important concept:
Trading edges decay.
Suppose a certain market behavior consistently produces profits.
Other traders eventually discover it.
More capital begins trading the same opportunity.
As participation increases, the inefficiency that created the edge becomes smaller.
The strategy may continue working, but the amount it earns per unit of risk can gradually decrease.
Eventually, the edge may become too small to trade profitably.
This means research is not something a trader does once.
Ongoing research is part of trading because strategies and markets continue to change.
Why Lower-Timeframe Edges Decay Faster
Edge decay is also connected to timeframe.
Generally, lower-timeframe edges can decay faster than higher-timeframe edges.
One reason is that shorter-term strategies can offer attractive Sharpe ratios, which draws sophisticated competition.
Another reason is capacity.
There is less liquidity available within a very short period than across several days or weeks.
Because the opportunity has less capacity, less capital may be required to arbitrage the edge out of the market.
A one-minute edge can therefore disappear much faster than an edge operating on daily or weekly data.
For an individual trader who wants an edge to remain useful for longer, this provides another reason to consider higher timeframes or longer holding periods.
Expectancy and Timeframe
Another important relationship is between timeframe and expectancy.
Expectancy is the average return produced by a trade over a large sample.
As the timeframe or holding period becomes larger, the amount of movement available to capture within an individual trade can also become larger.
Consider a simplified breakout example in crypto.
A breakout traded on the daily timeframe might produce approximately 1.5% expectancy per trade.
The same general breakout traded on the one-hour timeframe might produce approximately 0.4% expectancy per trade.
These numbers are examples rather than fixed strategy parameters.
The important point is the relationship.
The lower-timeframe strategy is attempting to capture a much smaller movement.
That becomes particularly important once trading costs are included.
Trading Costs
Trading costs include more than commissions.
They can include: Trading fees, spread, and slippage.
Suppose the one-hour breakout has an expectancy of approximately 0.4%.
If entering and exiting the position costs approximately 0.2% after fees and slippage, half of the theoretical expectancy has disappeared.
Now consider the daily breakout with approximately 1.5% expectancy.
Similar costs consume a much smaller percentage of the expected return.
This is why trading costs become especially important on lower timeframes.
The smaller the expected movement, the larger the percentage of the edge that can be lost simply through execution.
Holding Period Matters
The important factor is not only the chart timeframe.
Holding period also matters.
A trader could use five-minute data to identify an entry and still hold the position for three days.
Another trader could make the decision using daily data and hold the position for the same amount of time.
Both are attempting to capture a larger movement than a trader who enters and exits within several minutes.
The objective is to make sure the expected movement is sufficiently large relative to trading costs and competition.
What This Means for a Retail Trader
Putting the first part of the framework together gives a clearer picture of where an individual trader should look for opportunities.
The more liquid the market, the stronger the argument becomes for considering higher timeframes or longer holding periods.
The combination of very high liquidity and very low timeframe can create one of the most competitive environments available.
Individual traders should instead look for places where their smaller size becomes useful, where expectancy is large enough relative to trading costs, and where the edge has enough capacity to survive.
Once the playground is understood, the trader can move to the next question:
Which trading approach should be used?
The Four Main Trading Approaches
From a first-principles perspective, trading can be separated into four broad approaches:
Arbitrage, market making, momentum, and mean reversion.
Arbitrage attempts to exploit pricing differences between related markets or instruments.
Market making attempts to profit by providing liquidity and capturing structural advantages such as the spread.
In extremely liquid markets, both approaches are dominated by sophisticated professional participants.
Trying to compete in arbitrage or market making on a major Forex pair, for example, means competing directly against firms with enormous technological and capital advantages.
But as liquidity decreases, the potential opportunity for smaller traders can increase.
Markets such as crypto and certain small-cap stocks can contain inefficiencies that are too small or difficult for large professional firms to exploit at meaningful size.
For most individual directional traders, however, the two broad areas of focus are momentum and mean reversion.
Momentum can then be separated into short-term momentum and long-term momentum.
This gives us the three primary directional approaches used throughout the rest of the framework.
1. Short-Term Momentum: Breakout Trading
Strategy Overview
Short-term momentum is based on a simple market behavior:
When price begins moving with significant strength, there is a probability that the movement will continue for a period of time.
The stronger the initial push, the greater the potential for short-term momentum to continue.
This is the foundation behind breakout trading.
The trader’s job is therefore to identify when the market is experiencing a meaningful expansion in momentum compared with its normal behavior.
Measuring Volatility Expansion
Suppose the previous five daily candles have moved approximately 1% on average.
This provides a baseline for normal recent movement.
Now the next candle moves approximately 2%.
The market is suddenly moving at roughly twice its recent normal rate.
This is a volatility expansion.
That expansion tells the trader that new momentum has entered the market.
The strategy attempts to participate in the continuation of that momentum.
Using Momentum Indicators
Price movement itself can be used to measure the expansion, but indicators can also help describe the condition.
RSI, CCI, or another momentum indicator can be used to identify when momentum has become significantly stronger than normal.
The important point is not which indicator is selected.
The trader already knows what they are trying to capture:
A significant expansion in short-term momentum.
The indicator is simply a tool used to measure that behavior.
Entry Rule
Enter when the market demonstrates a meaningful expansion in momentum or volatility relative to its recent normal movement.
The exact measurement and threshold should be researched for the specific market being traded.
Exit Rule
Short-term momentum on a daily timeframe can last approximately two to five days.
One possible approach is therefore a time-based exit.
For example, if research shows that the momentum effect typically lasts several days, the trader can exit after a predetermined number of days.
The second option is to continue measuring momentum.
As long as the momentum remains present, stay in the position.
Once the momentum disappears, exit.
The objective is to capture the continuation while avoiding the deeper correction that may develop once short-term momentum has been exhausted.
2. Mean Reversion
Strategy Overview
Mean reversion represents the opposite side of the market.
Short-term momentum says that when movement becomes sufficiently strong, it may continue.
Mean reversion says that when movement becomes too extreme, price can become more likely to move back toward its normal level.
The trader is therefore measuring how far price has moved away from a defined mean.
Establishing the Mean
A simple moving average can be used as the mean.
For example, use a five-day moving average.
Then measure how far the closing price normally moves away from that average.
Suppose price normally trades approximately 2% away from its five-day moving average.
That provides the baseline.
Now suppose price suddenly moves 6% or 7% away from the same average.
The movement is much larger than normal.
The market has become unusually stretched.
That can create a mean-reversion opportunity.
Entry Rule
First determine the market’s normal distance from the chosen mean.
Then identify when the current movement becomes significantly larger than normal.
When the deviation becomes sufficiently extreme, enter in the direction of the expected reversion.
The strategy is not simply buying because price fell or selling because price rose.
The movement must be abnormally large relative to normal market behavior.
Using Indicators
A moving average is only one possible tool.
A shorter-period RSI can also help identify overbought or oversold conditions.
Price-action measurements can be used as well.
Again, the exact tool is secondary.
The underlying strategy is based on measuring when price has moved unusually far from its normal level.
Exit Rule
Mean-reversion trades on the daily timeframe can typically develop over approximately one to four days.
A simple time-based exit can therefore be researched and used.
Another approach is to exit when price returns to the mean.
If the trade was entered because price became unusually stretched away from its mean, the original reason for the trade disappears once that deviation has normalized.
How Short-Term Momentum Can Become Mean Reversion
There is an important relationship between these first two approaches.
A strong price movement can initially create short-term momentum.
But if that same movement becomes sufficiently extreme, the market can eventually become stretched enough to create a mean-reversion opportunity.
This is why the two concepts should not be treated as contradictions.
The question is how far the movement has progressed relative to normal market behavior.
At one stage, increasing momentum can favor continuation.
At another stage, an extreme deviation can favor reversion.
The trader needs to measure which condition is currently present.
3. Long-Term Momentum: Trend Following
Short-term momentum should also be separated from long-term momentum.
Long-term momentum is what traders normally call a trend.
A significant trend can develop because of macroeconomic changes, fundamental developments, structural changes in a market, or another major shift in conditions.
The trader generally does not want to continually fight against a strong long-term trend.
Instead, a trend-following strategy attempts to identify the movement and remain positioned for as much of it as possible.
How Trends Are Actually Built
A long-term trend is not one continuous straight-line movement.
It is usually made up of multiple periods of short-term momentum followed by mean reversion.
Price expands.
Then it corrects.
Momentum develops again.
Another correction follows.
Together, these individual movements form the larger trend.
This means short-term momentum, mean reversion, and long-term momentum can all exist on the same chart.
They are not competing theories about how markets work.
They describe different stages and different horizons of market movement.
Once this relationship is understood, different trading approaches can also be combined.
Identifying Long-Term Momentum
A simple technical method for identifying a long-term trend is to monitor significant support and resistance levels.
When a strong resistance level is broken, there can be a tendency for price to continue in the direction of the breakout.
The more significant the level, the greater the potential importance of the breakout.
One simple method is to look at the previous 100 days.
Identify the highest high during that period.
When price breaks above that 100-day high, enter the trend-following position.
Longer lookback periods can also be used.
A 100-day or 200-day high can identify an important long-term level.
An all-time-high breakout represents an even larger resistance break and can provide one of the strongest forms of long-term momentum.
Entry Rule
For a bullish trend-following setup:
Identify the highest high over the selected long-term lookback period.
Enter when price breaks above that high.
The same principle can be adapted to downside trends where appropriate.
Exit Rule
Trend following is about remaining in a strong movement for as long as possible.
A small correction should therefore not automatically close the position.
One simple management method is a moving average.
For example, use a 10-day moving average.
After entering the long-term breakout, remain in the trade while price continues closing above the moving average.
When price closes below it, exit the position.
This allows the market to determine when the trend has weakened instead of requiring the trader to predict where the trend will end.
Combining Trend Following and Mean Reversion
Once these concepts are understood individually, they can be combined.
One of the most common examples is entering a long-term trend during a correction.
Suppose price breaks above a 100-day high.
That breakout establishes long-term momentum.
Price then begins correcting.
Instead of treating the correction as a completely separate event, it can be measured as a mean-reversion movement within the larger trend.
The trader can then enter during the correction with the expectation that the long-term momentum will eventually resume.
Why Confirmation Can Create a Worse Entry
Many retail traders wait for confirmation before entering a correction.
They allow price to pull back, wait for the market to turn, and then enter once price begins moving back in the direction of the trend.
But this can work against the logic of a mean-reversion entry.
As the correction moves deeper, the mean-reversion opportunity can become more attractive.
Once price has already reversed and started moving back toward the trend, part of the opportunity has already disappeared.
For this type of entry, the goal is therefore to measure the correction itself and enter when the mean-reversion condition is present, rather than automatically waiting for confirmation afterward.
Choosing the Approach for Each Asset Class
After understanding the different approaches, the next step is returning to the original playground.
The question now becomes:
Which trading behavior makes the most sense for each asset class?
Stocks
For larger stocks and broad stock indexes, the strongest approaches are generally long-term momentum to the upside and long-side mean reversion.
Broad stock markets have a long-term tendency to appreciate.
When significant corrections occur, they can therefore create opportunities for price to revert upward.
Major upside breakouts can also develop into long-term momentum.
This makes bullish trend following and bullish mean reversion particularly suitable approaches for large stocks and broad indexes.
Small-cap stocks are different.
They are generally less liquid and less efficient.
Because the largest professional participants cannot always deploy significant capital there, additional inefficiencies can exist.
This can create opportunities for short-term momentum and even short-side mean-reversion approaches that may be more difficult to exploit consistently in highly liquid large-cap stocks.
Commodities
Commodity markets provide more flexibility.
Depending on the individual commodity and market conditions, traders can potentially use all three directional approaches:
Long-term trend following, short-term momentum, and mean reversion.
Commodities can develop significant long-term trends while also containing enough volatility and inefficiency for shorter-term approaches.
Forex
Forex is extremely liquid and highly competitive.
For individual traders, the framework therefore favors long-term momentum and mean reversion.
Trying to compete for very small short-term inefficiencies places the trader in one of the most competitive environments available.
Moving toward longer holding periods allows the trader to target larger movements where costs represent a smaller percentage of the potential expectancy.
Crypto
Crypto is comparatively less mature, less liquid, and more volatile.
Because of this, a broader range of approaches can potentially work.
Short-term momentum, mean reversion, and long-term momentum can all be considered.
In certain areas, arbitrage and market making can also remain possible because some crypto markets do not yet have enough liquidity to attract the largest professional participants at full scale.
However, these characteristics can change as the market matures.
Increasing liquidity and professional participation can gradually reduce the inefficiencies that originally created these opportunities.
Why Long-Term Momentum Is the Most Robust Approach
One trading approach appears across every major asset class discussed in the framework:
Long-term momentum.
Stocks can trend.
Commodities can trend.
Currencies can trend.
Crypto can trend.
This makes trend following one of the most robust trading approaches available across different markets.
It also operates in an environment where individual traders do not necessarily need to compete directly for the highest Sharpe ratio short-term opportunities.
For a trader who does not know where to begin, a simple long-term momentum approach across multiple assets can therefore provide a strong starting point.
Moving From One Strategy to Multiple Strategies
Once a trader has developed one profitable approach, the next step is not necessarily to keep modifying that strategy until it produces perfectly stable returns.
As the trader becomes more advanced, another option is to add different trading strategies.
For example, one strategy could trade short-term momentum in commodities.
Another could trade mean reversion in Forex.
A third could trade long-term momentum in stocks.
The objective is to build strategies that exploit different behaviors and therefore do not produce identical return patterns.
Why Correlation Matters
The most important part of combining strategies is correlation.
If every strategy makes and loses money at the same time, combining them provides limited diversification.
The goal is to combine strategies that are less correlated, uncorrelated, or in some cases negatively correlated.
When one strategy struggles, another may perform well.
This can reduce the volatility of the combined portfolio.
As volatility decreases while returns are maintained or improved, the portfolio’s Sharpe ratio can increase.
This creates an important alternative to chasing stability through increasingly short-term trading.
Instead of competing for extremely smooth individual strategies in highly competitive markets, the trader can combine several stronger but less-correlated edges and create stability at the portfolio level.
Diversification vs. Portfolio Trading
Simply dividing money between multiple strategies is diversification.
Portfolio trading takes this one step further by adding:
Rebalancing.
A simple example shows why the difference matters.
Suppose a trader begins with a $20,000 account.
The trader allocates:
$10,000 to Strategy 1
and
$10,000 to Strategy 2.
Diversification Without Rebalancing
During the first year, Strategy 1 makes 100%.
Its $10,000 becomes: $20,000.
Strategy 2 loses 50%.
Its $10,000 becomes: $5,000.
The total portfolio is now: $25,000.
During the second year, the results reverse.
Strategy 1 loses 50%.
Its $20,000 returns to: $10,000.
Strategy 2 makes 100%.
Its $5,000 returns to: $10,000.
The portfolio ends the second year back at: $20,000.
The trader was diversified, but there was no rebalancing.
Portfolio Trading With Rebalancing
Now use the same two strategies and the same returns.
After the first year, the portfolio is again worth:
$25,000.
But instead of leaving $20,000 in Strategy 1 and $5,000 in Strategy 2, the trader rebalances back to the original 50/50 allocation.
The $25,000 is divided equally.
Strategy 1 receives: $12,500.
Strategy 2 receives: $12,500.
Now the second year begins.
Strategy 1 loses 50%.
Its allocation falls to: $6,250.
Strategy 2 makes 100%.
Its allocation grows to: $25,000.
The total portfolio is now: $31,250.
The strategies did not change.
Their percentage returns did not change.
The difference came from rebalancing between the two negatively correlated strategies in this simplified example.
How Often Should You Rebalance?
Rebalancing does not have to happen once per year.
It can be performed daily, weekly, monthly, or according to another schedule.
In general, more frequent rebalancing can increase the effect, but an individual trader does not need to make the process unnecessarily complicated.
The main objective is to understand the principle.
Build several strategies with lower correlation.
Allocate capital between them.
Periodically rebalance the portfolio back toward the intended allocation.
The combination of diversification and rebalancing can reduce volatility and improve the stability of the overall trading portfolio.
Complete First-Principles Trading Framework
The entire process begins before choosing a trading setup.
First, understand the playground. Choose the asset class and timeframe.
Understand its liquidity, volatility, efficiency, and level of competition.
Recognize that the most liquid markets and shortest timeframes can attract some of the strongest professional competition. Then consider the potential expectancy.
Make sure the movement being captured is large enough that fees, spread, and slippage do not consume a significant portion of the edge.
Remember that edges decay.
The more attractive an inefficiency becomes to other traders, the more capital will attempt to exploit it. Lower-timeframe opportunities can be particularly vulnerable because they have less capacity and can be arbitraged away more quickly.
Once the playground is understood, choose the approach.
- For short-term momentum, look for a meaningful expansion in volatility or momentum and trade the potential continuation.
- For mean reversion, measure how far price has moved from its normal level and look for opportunities when that deviation becomes unusually large.
- For long-term momentum, identify significant long-term breakouts and stay with the trend while it remains intact.
These approaches can also work together.
Short-term momentum and mean-reversion movements help form larger trends, while mean reversion can provide an entry into an established long-term trend.
Only after deciding what market behavior is being traded should indicators and technical tools be selected.
RSI, CCI, moving averages, support and resistance levels, and other tools should help measure the underlying condition.
They are not the reason the edge exists.
Finally, as the trader develops multiple profitable approaches, those strategies can be combined.
Instead of relying on one strategy to produce perfectly stable returns, the trader can combine less-correlated strategies and periodically rebalance capital between them.
The objective is not to find one perfect indicator, setup, market, or strategy.
The objective is to understand where an edge exists, why it exists, where it has the best chance of surviving, how to trade it efficiently, and how multiple edges can eventually be combined into a more stable trading portfolio.
