لایب سان

Author(s): Laurent Bernut

Publisher: Packt Publishing, Year: 2021

ISBN: 1801815194,9781801815192

Table of Contents Preface xv Chapter 1: The Stock Market Game 1 Is the stock market art or science? 2 How do you win this complex, infinite, random game? 3 How do you win an infinite game? 4 How do you beat complexity? 4 How do you beat randomness? 5 Playing the short selling game 7 Summary 8 Chapter 2: 10 Classic Myths About Short Selling 9 Myth #1: Short sellers destroy pensions 10 Myth #2: Short sellers destroy companies 13 Myth #3: Short sellers destroy value 14 Myth #4: Short sellers are evil speculators 15 Myth #5: Short selling has unlimited loss potential but limited profit potential 18 Myth #6: Short selling increases risk 19 Myth #7: Short selling increases market volatility 20 Myth #8: Short selling collapses share prices 21 Myth #9: Short selling is unnecessary during bull markets 21 Myth #10: The myth of the "structural short" 22 Summary 23 Chapter 3: Take a Walk on the Wild Short Side 25 The long side world according to GARP 26 Structural shorts: the unicorns of the financial services industry 27 Table of Contents[ viii ] Overcoming learned helplessness 28 Money "is" made between events that "should" happen 29 The unique challenges of the short side 30 Market dynamics: short selling is not a stock-picking contest, but a position-sizing exercise 30 Scarcity mentality 32 Asymmetry of information 32 Stock options and transparency 33 Sell-side analysts are the guardians of the financial galaxy 33 Summary 36 Chapter 4: Long/Short Methodologies: Absolute and Relative 39 Importing libraries 40 Long/Short 1.0: the absolute method 40 Ineffective at decreasing correlation with the benchmark 41 Ineffective at reducing volatility 44 Little, if any, historical downside protection 44 Lesser investment vehicle 44 Laggard indicator 45 Long/Short 2.0: the relative weakness method 45 Consistent supply of fresh ideas on both sides 51 Focus on sector rotation 53 Provides a low-correlation product 53 Provides a low-volatility product 53 Reduces the cost of borrow fees 54 Provides scalability 54 Non-confrontational 54 Currency adjustment becomes an advantage 54 Other market participants cannot guess your levels 55 You will look like an investment genius 55 Summary 57 Chapter 5: Regime Definition 59 Importing libraries 60 Creating a charting function 61 Breakout/breakdown 62 Moving average crossover 67 Higher highs/higher lows 73 The floor/ceiling method 74 Swing detection 77 Historical swings and high/low alternation 77 Establishing trend exhaustion 84 Putting it all together: regime detection 89 Table of Contents[ ix ] Regime definition 93 Methodology comparison 96 Timing the optimal entry point after the bottom or the peak 104 Seeing through the fundamental news flow 104 Recognizing turning points 105 Let the market regime dictate the best strategy 105 Summary 107 Chapter 6: The Trading Edge is a Number, and Here is the Formula 109 Importing libraries 110 The trading edge formula 110 Technological edge 111 Information edge 112 Statistical edge 112 A trading edge is not a story 113 Signal module: entries and exits 119 Entries: stock picking is vastly overrated 119 Exits: the transmutation of paper profits into real money 121 Regardless of the asset class, there are only two strategies 122 Trend following 123 Mean reversion 127 Summary 131 Chapter 7: Improve Your Trading Edge 133 Blending trading styles 134 The psychology of the stop loss 136 Step 1: Accountability 138 Step 2: Rewire your association with losses 139 Step 3: When to set a stop loss 141 Step 4: Pre-mortem: the vaccine against overconfidence 141 Step 5: Executing stop losses: forgiving ourselves for mistakes 142 Step 6: What the Zeigarnik effect can teach us about executing stop losses 143 The science of the stop loss 144 Stop losses are a logical signal-to-noise issue 146 Stop losses are a statistical issue 146 Stop losses are a budgetary issue 147 Techniques to improve your trading edge 147 Technique 1: The game of two halves: how to cut losers, ride winners, and maintain conviction while improving your trading edge 147 Technique 2: Mitigate losses with a trailing stop 149 Table of Contents[ x ] Technique 3: the game of two-thirds: time exit and how to trim freeloaders 152 Technique 4: The profit side: reduce risk and compound returns by taking small profits 153 Technique 5: Elongate the right tail 162 Technique 6: Re-entry: Ride your winners by laddering your positions 163 Final exit: the right tail 165 Re-entry after a final exit 166 How to tilt your trading edge if your dominant style is mean reversion 166 Losses 167 Profits 167 Partial exit 168 Exits 168 Summary 169 Chapter 8: Position Sizing: Money is Made in the Money Management Module 171 Importing libraries 172 The four horsemen of apocalyptic position sizing 172 Horseman 1: Liquidity is the currency of bear markets 173 Horseman 2: Averaging down 174 Horseman 3: High conviction 175 Horseman 4: Equal weight 176 Position sizing is the link between emotional and financial capital 177 A position size your brain can trade 179 Establishing risk bands 180 Equity curve oscillator – avoiding the binary effect of classic equity curve trading 181 Comparing position-sizing algorithms 190 Refining your risk budget 198 Risk amortization 198 False positives 200 Order prioritization and trade rejection 200 Game theory in position sizing 201 Summary 202 Chapter 9: Risk is a Number 203 Importing libraries 204 Interpreting risk 204 Sharpe ratio: the right mathematical answer to the wrong question 205 Building a combined risk metric 210 Table of Contents[ xi ] The Grit Index 210 Common Sense Ratio 213 Van Tharp's SQN 218 Robustness score 221 Summary 223 Chapter 10: Refining the Investment Universe 225 Avoiding short selling pitfalls 225 Liquidity and market impact 226 Crowded shorts 227 The fertile ground of high dividend yield 228 Share buybacks 229 Fundamental analysis 230 What do investors really want? 232 Lessons from the 2007 quants debacle 232 The Green Hornet complex of the long/short industry 234 Lessons from Bernie Madoff 235 Summary 237 Chapter 11: The Long/Short Toolbox 239 Importing libraries 240 Gross exposure 241 Portfolio heat 242 Portfolio heat bands 243 Tactical deployment 244 Step-by-step portfolio heat and exposure management 244 Net exposure 254 Net beta 256 Three reasons why selling futures is the junk food of short-selling 257 Selling futures is a bet on market cap 257 Selling futures is a bet on beta 257 Selling futures is an expensive form of laziness 258 Concentration 258 Human limitation 259 Hedges are not tokens 259 The paradox of low-volatility returns: structural negative net concentration 260 Practical tips about concentration 260 Average number of names 260 Ratio of big to small bets 260 Keep your powder dry 261 Other exposures 261 Sector exposure 262 Table of Contents[ xii ] Exchange exposure 262 Factor exposures 263 Design your own mandate 263 Step 1: Strategy formalization 264 The signal module 264 The money management module 267 Step 2: Investment objectives 268 Step 4: Design your own mandate: product, market, fit 269 Step 5: Record keeping 269 Entry 270 Exits 270 Position sizing 271 Journaling 271 Step 5: Refine your mandate 272 Summary 272 Chapter 12: Signals and Execution 273 Importing libraries 274 Timing is money: the importance of timing orders 274 Order prioritization 275 Relative prices and absolute execution 276 Order types 276 Exits 277 Stop loss 277 Pre-mortem 278 The Zeigarnik effect 278 Profitable exits 279 Entry 280 Rollover: the aikido of bear market rallies 282 Moving averages 283 Retracements 283 Retest 284 Putting it all together 285 Summary 292 Chapter 13: Portfolio Management System 295 Importing libraries 296 Symptoms of poor portfolio management systems 297 Ineffective capital allocation 297 Undermonitored risk detection 298 High volatility 299 High correlation 300 Poor exposure management 300 Table of Contents[ xiii ] Your portfolio management system is your Iron Man suit 301 Clarity: bypass the left brain 302 Relevance: the Iron Man auto radio effect 309 Simplicity: complexity is a form of laziness 311 Flexibility: information does not translate into decision 312 Automating the boring stuff 312 Building a robust portfolio management system 313 Summary 320 Appendix: Stock Screening 323 Import libraries 324 Define functions 324 Control panel 331 Data download and processing 333 Heatmaps 336 Individual process 339 Other Books You May Enjoy 347 Index 351

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