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The market does not run on chance or luck.
Like the battlefield, it runs on probabilities and odds.
- Market mechanics
- Consistent profitability
- Automated trading
- Equities (stocks) - invest directly in companies
- Fixed income (bonds) - loans
- Real estate investment trusts
- Commodities (metals, agriculture products)
- Exchange traded funds (ETFs) - exchange listed security that tracks a collection of other securities (indexes)
- Foreign exchange (Forex)
- Financial derivatives - options and futures
- Futures - financial contracts to buy or sell an asset at a predetermined future date and price.
- Options - financial contracts giving their owner the right, but not the obligation, to buy or sell an underlying asset at a stated price (strike price) prior to or on a specified date.
- Position traders
- Trend traders
- Swing traders (interested in capturing a move and isn't interested in holding assets that go sideways)
- Day traders
- trade time
- win amount
- time required
Investors - giving money without sole intention of making money in nearest future. Supporting business, values it brings.
Think about options as a way of renting assets for a set period without significant cost associated with a purchase.
With options, potential loses and profits are not symmetrical. Loses are limited and profits are unlimited.
What truly moves the price is AGGRESSION.
If the price goes up, then the buyers are more aggressive (they use market orders).
Traders become aggressive because of fear of either missing out or losing.
Even if a trade entry had a resoning logic, after the entry, trader often sucumb to the emotions of fear and regret and end up selling winners and hanging onto losers.
More risky assets are sold and the money is moved into safer assets (market rotation).
It is not because the safer assets have room to advance, but because they are likely to hold their value better in an economic downturn.
Randomness and efficiency
There is a theory that claims that market moves are a random walk and the future price can not be predicted.
Although we can not predict price precisely, there are patterns in the market that occurs with probability high enough to use them in trading.
Markets are efficient, unless we know if the market is trending or ranging.
If the market is trending - we can benefit from it by following the trend; if ranging - buy lower and sell higher.
What traders are looking at
Traders are looking at price
Once price increases - they experince fear of missing out and buying in (jumping into the train).
Once price of asset drops - they experience fear of losing.
Once price is close to a significant price level (1$ for example), there is more excitement than if price gets to 0.95$. Also support/resistance, ath, atl, moving average works similar.
If price is not volotile enough and do not produces opportunities in the chosen timeframe - traders move money to more promising instruments.
Traders are looking at PnL
Once a trade PnL moves to negative - traders try to exit the trade at break-even or a small loss.
If they didn't exit at a small loss/profit and moved to a large loss - they try to keep assets (don't sell at loss).
Once price rallies again and get's close to break-even - they exit.
Traders are looking at volumes (loocking at top assets = top volume assets)
The more volume - the more traders are looking at the asset, and so more are ready to jump in/out.
The more visible setup (more clear, more time since formed), the more participants to expect.
Study candlestick patterns, price action.
Retail traders are scared of large volume clusters in order book, by projecting their own trading volume they miscalculate the amount of effort required to break through a limit order wall (and often the wall is a fake one).
Put stop loss orders right after support where they are easily hunted by larger players (stops are not given enough space to breath).
Emotional, averaging down, taking losses personally and fighting back an asset, jumping in on a signal/news without proper analysis and plan.
Large volume traders
There are institutions, whales, coordinated groups of traders, insiders.
A large amount of an asset under management causes trouble for them because they can not buy or sell at a specific price and fast.
Large limit order in order book will show their intent and they don't want this.
A large market order would move price significantly and the final price will be much worse than initial.
They need time and other traders willing to sell at lower prices.
Sideways market is a great place for them for buying in.
Low volatility and relatively small volumes make many retail traders move money to other assets, selling to the large traders who are accumulating.
The large traders are monitoring supply in the range, once there is no more retail traders are willing to sell - the price can be pushed lower looking for more selling (testing).
Large drops in market price scare off participants invested in the trading instrument, causing them to sell their holdings and exacerbate the drop.
Large traders may block large price advances by adding large fake sell limit orders. So they can make sure the price will not start a rally until they will have enough asset accumulated.
Once the asset has low liquidity and the large player accumulated enough of it, he can easily create a small pump, that can be picked up by the retail traders. There can be a positive news to give a reason for the price increase.
Large market rallies generate investor confidence, causing more participants to buy more, recursively causing larger rallies.
Then the large trader sells the accumulated asset to the retail traders.
Large traders like liquidity:
- They are happy to consume large limit orders in order book because it does not move price
- They know where stop loss orders are and hunt them
Institutional activities signs:
- Sideways price action area
- Aggressive initiation activity
- Strong rejection
Selling scalable products (10% annually is considered a very good result) to wealthy clients. Charging fee for looking after their money.
Algorithmic trading now accounts for over 80% of the equity trading volume (2019).
- Algorithmic expert advisors (EA) (human makes decisions, bot manages orders, risks, provides signals)
- Fully automated (bot makes decisions)
Bots are like startups: obviously some succeed; also obviously, most don't.
Some bots are designed to get profit from market inefficiency (not enough liquidity to process orders efficiently, not enough time for incoming liquidity to keep up).
Algorithmic market making is an example - a strategy that smooths out large orders on a single exchange (provides liquidity at a worse price).
Another market making strategy implemented by many bots is grid trading.
Arbitrage (one exchange or cross-exchange) also just reduces inefficiencies (balances prices between markets).
They are basically not impacting price much, they are waiting for others to move price, jump in and make a profit.
The flashcrash bot is one of our best bots.
A flashcrash is when prices on an exchange change very rapidly, and the bot exploits this by buying up cheap coins and selling when the price returns to normal levels.
This bot can do between 5 and 15 percent a day, on average. Exchanges love this bot, too: It makes their order books more liquid.
Stephan de Haas
Other bots could trade based on TA indicators, news, etc. They are just adding to the retail traders crowd.
Regime shift is caused by market structure or macroeconomic changes.
Regimes are periods of mean-revertion and trending behaviors, high and low volatility. Each regime requires different strategies or or strategy parameters.
Another regime is no clear regime, when price is random walking.
Regimes can be different for different time horizons.
Markets spend more time in mean-reversion regime than in trending.
|Trend up||Trend down||Range bound||No boundaries|
|Slow||Fast||Very slow||Very fast|
|Buy the deep||Sell the rallies||Buy support||Lock in profits|
|Long positions||Short positions||Cycle positions||Quick trades|
|Easiest||Difficult||Simple||Lower time frame|
|Trend traders like||Short sellers like||Swing traders like||Day traders like|
A technician is someone who cuts right to the chase and studies actual prices and behavior
instead of puzzling over the causes of prices and behavior like everyone else.
Phases (Charles Dow):
- Public participation
Smart money taking profits and selling to an increasingly eager public.
When only price (candles) is taken into consideration.
The charts don't lie.
Charts really are the "footprint of money". What some talking head on a financial news network might say becomes immaterial when you can look at a chart and see what the "money" is saying.
Charting and Technical Analysis by Fred McAllen
Charts allow to see:
- Past performance
- Moving averages
- Trading volume
- and more
Support/resistance: price has memory. This is because humans (who make up the market) are susceptible to "anchoring bias".
Support/resistance can be:
- horizontal line
- trend lines
- SMA(50, 200), EMA
- fib lines
- round numbers
The more times price touches support/resistance, the weaker it becomes.
There is no such thing as a quadruple bottom/top.
Volume reveals whether the price action is valid or false.
- The law of supply and demand (when demand is greater than supply, then prices will rise to meet this demand, and conversely when supply is greater than demand then prices will fall, with the oversupply being absorbed as a result)
- The law of cause and effect (a small amount of volume activity will only result in a small amount of price action)
- The law of effort vs result (the price action on the chart should reflect volume action)
Market weakness early signs:
- Lower volume on advances
- Higher volume on declines
- Inability to make higher highs
- Primary trend line broken
- DMA broken
Trend change signs:
- Lower highs, lower lows
- Higher volume on declines
- Low volume on advances
Volume Price Analysis concepts:
- Selling Climax
- Buying Climax
Buying climax - when the market has moved sharply lower in a price waterfall and bearish trend,
supported by masses of volume. Wholesalers are buying and retail traders are panic selling.
Selling climax - at the top of a bull trend, where we see sustained high volumes.
Wholesalers are selling to retail traders and investors.
Why markets move sideways:
- Pending release of a fundamental news
- Selling and buying climax (warehouses are either being filled or emptied by the insiders)
- Run into old areas of price, where traders have been locked into weak positions in previous moves
Divergence between volume and price: the volume of trading stops expanding and starts to shrink as the averages move to their final highs. Normally at the beginning of a move, the volume of trading continually grows. But then, at a certain point, the market makes new highs but the volume contracts.
- D - market is balanced. A sign of institutions accumulating volumes
- P - aggressive buyers. Usually seen when market is in uptrend, at the possible end of downtrend
- b - aggressive sellers. Downtrend of end of uptrend
- thin - strong uptrend or downtrend
Order book, large volume at price:
- Often can be found on significant levels (round prices, support/resistance)
- Large numbers of stop orders can be found behind large volumes (that can cause a price spike after the price is broken)
- Makes sense to put orders before large volumes, so there will be more chances for them to be executed
- Makes sense to put stops behind large volumes, so there will be fewer chances for them to be executed
- Price can be moved towards large volumes by large players, and then they can consume large liquidity at a good price and don't cause large price change
- Large volumes can be removed or moved a bit (if the intention was just price manipulation without the order to be executed)
- Large volumes can be executed with market order shortly after being removed from the order book
Fibonacci retracement is a tool used to predict the pull-back of price after a period of growth based on a set of predetermined percentages: 23.6, 38.2, 50, 61.8, 78.6.
Fibonacci extension is a tool used to find targets for growth after a pull-back. Commonly used 161.8, 200.
Combine fibonacci with trendlines and moving averages.
- Blue waves (VuManChu Cipher B)
- Central Pivot Range
VWAP - Large institutional buyers and mutual funds use the VWAP ratio to help move into or out of stocks with as small of a market impact as possible. Therefore, when possible, institutions will try to buy below the VWAP, or sell above it. This way their actions push the price back toward the average, instead of away from it.
- Edge in the market (statistical advantage)
- Risk management
- Consistency (for manual trading)
- Psychology (for manual trading)
- Journaling (for manual trading) or logging and monitoring/statistics
Edge in the market
Trading is about probabilities, never certainties.
An entry should not be based on an opinion, prediction, or emotions; it should be based on a statistical edge.
Strategies can be found:
- academic papers
- trading view
What truly make a strategy proprietary and its secrets worth protecting are the tricks and variations that you have come up with, not the plain-vanilla version.
Quantitative Trading by Ernest P. Chan
The goal is to have a strategy with high Sharpe ratio (low drowdown), so we can use higher leverage in order to achieve maximum long term growth.
- Sharpe ration - consistency
- Drawdown - (global maximum - current equety) / global maximum
- Maximum drawdown - (global maximum (high watermark) - global minimum (global minimum should accur after global maximum)) / global maximum
- High watermark - global equety maximum
- Maximum drawdown duration - maximum time to recover loses
The most important rule of trading is to play great defense, not great offense.
Paul Tudor Jones
Attention to profit - a sign of immature, attention to losses - sign or experience.
Parts of risk management:
- Backtest and papertrade new strategies first
- Cut loses short and maximize gains
- Position sizing
Backtest and papertrade new strategies first
Backtest. Test new ideas with paper trading first.
Historical success is a necessary but not a sufficient condition for concluding that a method has predictive power and, therefore, is likely to be profitable in the future.
Evidence-Based Technical Analysis by David Aronson
Transaction costs should be take into account.
- Liquidity cost
- Opportunity cost
- Market impact
Cut loses short and maximize gains
Money is not made on entries; profits are only generated on the exit or a trade.
- Fixed holding period
- Target proce or profit
- Exit signal
- Stop price
Should try to maximize profits when right and minimize losses when wrong.
The primary tool to cut loses short is stop loss, and the primary tool for maximizing gains is a trailing stop.
After a trade is entered, the risk/reward ratio is always shifting, and a trader must act based on how the trade plays out.
Booking partial gains as the asset is becoming profitable and raising stops to ensure profits do not become losses.
Taking action to prevent a small loss from becoming a big loss should be considered a victory.
Stop price can be calculated based on volatility (Average True Range can be used as a volatility indicator).
Give some breath for stop price.
Stop should be applied if price is in momentum, otherwise - it could reverse fast.
Stop is beneficial in momentum regime and harmful in mean-revertion.
Lower RR and higher win rate is more favorable than higher RR and lower win rate (if risk and reward are many times larger than commission) because easier to handle emotionally.
Keep 1-5% of account exposed to risk (use stop orders) per trade.
Can be increased to 10% for small accounts.
Improperly sized positions affect the ability to be disciplined:
- Sizing too large = more excited, frustrated, emotional, exhausted
- Sizing too small = disinterest, boredom, sloppiness, lack of returns
Leverage can be used to maximize strategy output. Should be chosen to withstand strategy maximum drawdown.
After a losing trade - take a break to reduce emotional decision-making.
Bots should have fuses to stop when:
- unusually high trading activity (runaway trades)
- unexpected high daily volume
- overlimits for a single trade volume
Bots should be handling errors (closing positions, sending alerts, etc.).
- Model risk
- Software risk
- Natural disaster
Following a consistent set of actions leads to consistent results.
Behavioral finance studies irrational financial decision-making.
If smart people would be able to be consistently profitable in trading, we would have many rich people.
Loss aversion is the observation that human beings experience losses asymmetrically more severely than equivalent gains.
Each next win gives less sattisfaction. Each loss adds to pain of previous loses.
Negative emotions have a stronger impact than positive ones.
According to one study, the pain of losing $100 still outweighs the happiness of gaining $240.
Causes some traders to exit their profitable position too soon because pain from possibly losing some of the current profits outweights the pleasure from gaining higher profits.
There is a rational part in loss aversion, losses can lead to capital wiped out, even if size of wins is higher than of losses and chances for each outcome is 50/50 because any capital is limited.
Endowment effect causes traders to hold on to a losing position for too long. Demand much more to give up the asset than they would pay to aquire it.
Status quo bias causes traders to hold on to a losing position for too long. A preference for the current state of affairs.
Representativeness bias - put too much weight on ecent experience and underweight long-term average.
It is difficult to accept own mistakes and change.
Trading becomes easy once a trader learns to ignore her own personal opinions, stops trying to be right, stops focusing on making money, and instead focuses on the process of trading.
The Tao of Trading by Simon Ree
Trading requires large time investments in experiments.
Repetition can be boring or tedious - which is why so few people ever master anything.
Boredom associated with slow progress.
Focus on enjoying (and getting good at) the process, without having any specific objectives in mind, the outcomes will be all-the-more rewarding.
Do not set expectations on a trade, it will ruin the trade (robs ability to appreaciate current reality).
You can lose your opinion, or you can lose your money.
To grow: objectivity, impartiality, discipline, focus.
This is not a trader's job:
- be right
- predict the future
- pick tops and bottoms
- try to make money
- listen to media
A lot of us are in the business of quantitative trading because it is exiting, intellectually stimulating, financially rewarding, or perhaps it is the only thing we are good at doing.
Quantitative Trading by Ernest P. Chan
MBAs once scoffed at the thought of relying on a scientific and systematic approach to investing, confident they could hire coders if they were ever needed. Today, coders say the same about MBAs, if they think about them at all.
The Man Who Solved the Market by Gregory Zuckerman
Client algorithmic trading infrastructure:
- Communication with exchange (pulling market data and order entry)
- Pulling historical market data
- Risk management layer (handle errors, runaway trading)
- Strategy implementation (quantitive part)
- Visualization, analytics
- Signal research framework
Statistically significant signals (Medallion):
- Identify anomalous patterns in historic pricing data
- Make sure the anomalies were statistically significant, consistent over time, nonrandom
- Identified pricing behavior could be explained in a reasonable way
Machine learning struggles to predict future price moves.
It can be used for adjusting strategies based on market conditions (predicting our strategy performance).
Recent data can be not enough for testing, older data can be absolete.
Gambling - when odds are unknown and wishing for luck.
Profitable trading does not have a secret recipe for success. There are as many different ways to be profitable as there are traders who know how to utilise the good trading systems out there.
The Quiet Trader by Atanas Matov
- Statistical arbitrage
- Arbitrage (one exchange or cross-exchange) (triangular arbitrage)
- Market making
- Index fund balancing
- Trend following (momentum) strategies
- Mean reversion strategies (time-series mean reversion)
- Pairs trading (cross-sectiona mean reversion)
- Seasonal trading (based on dates of year)
- Keep orders in ob at a worse price for others and wait for large market order (or multiple stops) to cause an impulse, close at a better price
- In order to minimize quote assets required for multiple markets - submit order either after the fact of price drop/liquidations or when price is close to make an impulse (breaking through a large volume cluster or a level)
- When the price drops where low and stays there for some time - buy (chances to drop lower are lower then go much higher)
- After a major decline, the risk of further decline diminishes while the opportunity for maximum profit increases
- Grid trading (when market is in sideways)
- Cross-exchanges arbitrage
- Triangular arbitrage
- Ride pumps
- Spot price, volume, and orders momentum increase
- Look for loss of momentum (failed to make lower low or higher high, double top/double bottom)
- Bollinger Band (deviation from moving averages)
- Build levels based on Volume-price charts
- Trend trading
- If an asset fails to make a higher high - sign of weakness
- Use ichimoku cloud
- Automatically identify supports/resistance/trend lines
- Trade break outs
- Trade pull backs (rejections)
- Spot accumulation and distribution
- Break out from pennant
- Candles getting shorter and shorter (not enough traders willing to sell/buy at the price)
- Channel break out
- If the price is approaching slow - move it, if fast - executed, sell higher on rebounce (break out)
- Round numbers are significant
- Wait for narrowing and put entries at both sides
- For areas without support/resistance - use fib
- Disbalance in candles grow with volume grow
- Large volumes in ob attract price (because large amounts can be bought/sold without impacting price)
- Find sentiment by looking at orderbook - more buy orders/volumes = bull (count only long time standing orders)
- Identify iceberg / real orders in order books by how they behave when price hit them
- Dynamic stops and take profit points based on ob
- When price goes up and many sale orders coming - there is resistance
- Two assets correlated, and then not - create short + long positions
- Buy and hold
- Buy new tokens not yet listed on major exchanges
- Use rich lists to understand accumulation/distribution by large accounts
- Look for institutional activities
- Buy in small amounts once price is in the range
- Buy something that had large volumes before and now - low price and volume
- Buy tokens have real usage (exchange tokens, game tokens, defi, coins host other tokens on their chains, etc.)
- Correlation between 2 assets, move from one to another if more potential
Buy when there's blood in the streets,
even if the blood is your own.
- Watchers on rich list
- Buy before the pay day (people accumulating from salaries)
- Identify supply testing
- Pullbacks on low volume - pull back if not supported
- Trade on news
- If price moves too quickly - stop entering the market
- If the broader market falls quickly - stop buying
- Know orders priority - FIFO or by size?
- Exit on stop and buy deeper
- Wait for candlestick to close
- Analyze executed orders
- Use trailing or ladder stops
- Consider time and dow
- Create zones, when enter - buy, exit - sell, enter next one - buy ... (better exit and enter lower than keep losing position open)
- Look for setups where small movement will invalidate the setup (so profit/loss ratio is higher)
- Estimate stops by cluster info
- When btc drop - other drop even more? Arbitrage?
- lower capital when start losing
Difference between trading and other small businesses: no marketing if you manage only your own money, otherwise your perfomance is the best marketing.
High Sharpe ration is much easier to achieve with smaller account.
Sharpe Ratio - consistency of returns. Helps investors to understand the return of an investment compared to its risk.
When < 1 - not suitable for a stand-alone strategy. Profitable almost every month - > 2, profitable almost every day - > 3.
Black swan (fat tail) events - unexpected events (black swan was discovered in Australia in XVII century).
Alpha decay - decreasing of strategy performance. Happens when many are trading the same strategy. Alpha shows how much the strategy outperforms the market on a risk-adjusted basis.
Data snooping bias - when strategy has many parameters and oveoptimized to perform on historical dataset and may perform purely on new data.
Look ahead bias - using data that should not be available at the moment in backtest.
Strategy capacity - how much a strategy can absorb without negative impacting its returns.
High frequency trading - automated trading where trades are closed in the same day.
- InteractiveBrokers - multiple asset classes
- Coinigy - great number of cryptocurrency exchanges
- BitcoinWisdom - clear and user-friendly
- GoCharting - order flow charting
- BookMap - dom visualization
- Cosaic (ChartIQ)
- All in one crypto
- Crypto terminal
- Trality - trading bots
- Gunbot - desktop trading bot
- DDP Platform - trading bot with visual strategy builder
- QuantConnect - algorithmic trading platform
- Node Binance Trader
- Deep trader - uses ml
- Bitcoin trader - nice idea about small buys
- Crypto Signal
- Indicators wiout TA-lib
- BitScreener - further chart analysis, recent related news
- AtomSignal - excanges monitiring, tracking buy and sell walls
- WenMoon - useful for research
- BitcoinTalk - new altcoin announcements, fundamental analysis
- ICO Drops
- TradingView Crypto screener
- Crypto Bubbles
- Trade ideas scanner
- Crypto Quant
- Dune analytics
- Crypto Currency Alerting
- CScalp Trader signals
- Mining Humster
- Signals Blue (230 pounds/month)
- Crypto Alarm (270$/month)
- Crypto Base Scanner
- BlockChair Sparrows signals
Articles and videos
- Intro to Basic Market Mechanics
- Auction Theory, Volume Profile, and Microstructure
- Practical Applications - Order Flow and Structure
- Crypto Cred
- Trade Pro - testing strategies
- Cryptocurrency Trading Bible Three: Winning in Sideways and Bear Markets
- 5 Stop Loss Mistakes To Avoid
- The bots that make money (or lose it) for you while you sleep
- Trading vocabulary
- Crypto Cred
- Evidence-Based Technical Analysis by David Aronson
- Charting and Technical Analysis by Fred McAllen
- Trading the Trends by Fred McAllen
- An Altcoin Trader's Handbook by Nik Patel
- A Complete Guide to Volume Price Analysis by Anna Coulling
- Volume Profile by Trader Dale
- Price Action Trading Secrets by Rayner Teo
- Hands-On Financial Trading with Python by Jiri Pik, Sourav Ghosh
- The Tao of Trading by Simon Ree
- The Ultimate Guide to Swing Trading by Steve and Holly Burns
- The Man Who Solved the Market by Gregory Zuckerman
- The Quiet Trader by Atanas Matov
- Quantitative Trading by Ernest P. Chan