The Finance Book Club

Chapter 6 - Cross-Market Trading and the Stress Indicator

1. The stress indi allows identification of buy and sell levels, across different markets, maybe more flexibly than the momentum difference method
2. Stat-arb pairs trading has become more difficult
   1. Widely known method
   2. Many novice traders don’t know how to balance risks correctly
   3. Small profit margins with stocks, but more promising in other pairs
   4. Relative value trading
      1. Using a stoch indicator, calculate the value of each leg
      2. See how often the values move apart far enough to offer a profit opportunity

      
      

3. The stress indi is another way to identify trigger points

The crossover trade

1. Identify a business whose primary product is a commodity
   1. Major oil producers
   2. Mining operations
   3. Agribusiness
   4. Avoid companies that are too diversified because we want dependency on price of the underlying commodity

   
   

2. More discussion of trading hours - this underscores the importance of knowing this material but it’s likely out of date

Stress indicator

1. Stress is like a rubber band
2. The farther we stretch it the harder it pulls to return to its normal shape
3. Calculation
   1. 1. Find the raw stochastic for leg 1 over an n-day period
      1. Raw(leg1)today = Close(leg1)today - low(leg1)n-days / High(leg1)n-days - Low(leg1)n-days
      2. This is effectively the position of today's closing price within the high-low range of the past n – days, measured as a percentage from the bottom of the range. Note that n – days is the entire n – day period.

      
      

   2. 2. Find the raw stoch for leg 2 (same formula)
   3. 3. Find the difference the two stoch values
      1. Diff(today) = Raw(leg1)today - Raw(leg2)today
      2. This is the same procedure as in previous chapter so far but now comes the twist

      
      

   4. 4. Stress(today) = Diff(today) - Low(Diff)n-days / High(Diff)n-days - Low(Diff)n-days
      1. Even though the Diff values do not have highs and lows each day, the stress indicator can provide added value. There is also no smoothing involved in this calculation, so there is no lag, as there is in most trending indicators.

      
      

   5. Easily calculated using a spreadsheet - I got you

   
   

4. The method of application is the same as before, the difference is this indicator can find a peak/trough with relative values
5. PK starts with an oil example but I think his metals example is clearer

Gold, Copper, Platinum

1. Starting with mining stocks (because they are in the news)
2. Mining company stock should go up with the price of gold

Trading Rules

1. A 10 year test starting in 2000
2. “The stress indicator takes the metal price as leg 1 and the stock price as leg 2.
3. The stress indicator will use a 10-day calculation period.
4. We sell the metal and buy the company shares when the stress indicator moves over 95.
5. We buy the metal and sell the shares short when the stress indicator falls below 5.
6. We volatility adjust the position sizes of both legs in order to have the same risk.
7. We exit both longs and shorts when the stress indicator crosses 50.”

Dynamics of Changing Parameters

1. This is a couple of pages of PK saying that if we change parameters different things will happen; for example changing the exit threshold will change unit returns, and the number of trades
2. Attached Image (click to enlarge)

   
   

Costs

1. “charge the commodity leg $25 for each round turn. We assume stocks can be traded for less than 1 cent per share; therefore, no cost is used for the stock side of the trade”

The Test

1. Overall results are remarkably good, with an average information ratio above 1.0 and an annualized return of 12.5% at an annualized volatility of 12%.
2. Running this test from 2010-2020 would be extremely interesting
3. Again, to improve results, PK recommends trading during higher volatility times, by using a vol filter

1. PK repeats the tests with Agribusiness, major energy producers, but I won’t.
2. “All trading methods benefit from diversification, and short-term strategies tend to show differences more often than longer-term approaches because they are more sensitive to smaller changes in price moves, resulting in more frequent entries and exits. The cross-market strategy can produce different signals when crude oil is measured against different petroleum companies, but it is far better to incorporate both oil and metals combinations in the same portfolio.”

Chapter 7 - Revisiting Pairs Using the Stress Indicator

1. PK proposes revisiting the pairs that he looked at in chapter 4, but this time use the stress indicator to generate signals
2. Spoiler alert: “We will find that the results using the stress indicator are very different from the original momentum difference calculations.”

Futures markets and the stress indicator

1. The stress indicator is a simple manipulation of the two momentum values calculated for leg 1 and leg 2 of the pair. By taking the difference in the two values and using those numbers to create a third momentum indicator, we change the dynamics of the trading signals
   1. More uniform signals
   2. More generalized concept
   3. More robust (perhaps)
   4. However the stress indi doesn’t consider volatility; quite the opposite, ‘all sense of volatility is lost in the process’
   5. We might need a vol filter to take only the trades with the best return potential

   
   
   

Equity Index Futures

1. Momentum difference worked well, but ‘a more generalized solution is always best’
2. Attached Image (click to enlarge)

   
   
3. An information ratio of 1.521 and annualized returns of 18% were “very acceptable”
4. However 347 trades on average per pair is maybe too high, this is the opposite problem now
5. A vol filter like the one in chapter 3 might cut down on the number of trades and improve the size of the average profits

Comparative Results

1. It’s important to compare results using all pairs, not just the best ones
2. A strategic improvement should help all pairs

1. What to make of this?
   1. The correlations cluster into two groups
   2. All the pairs that have the CAC or FTSE as one leg post the strongest returns and have the lowest correlations.
   3. "Knowing that, we can reason backward that the French and British economies are very different from the German economy, which dominates Europe and has greater impact on the EuroStoxx. This can be seen because the correlation between the EuroStoxx and DAX is .955, similar to the S&P and DJIA relationship. It is interesting that the top three performers are all European pairs, although in the top two groups, most of the pairs are combinations of U.S. and European markets."

   
   
   

1. We all prefer that a trading system generate trades through all conditions and that those trades are profitable. However, that's unrealistic.
2. Each trading method targets a particular type of trade and market condition. If it can do that consistently, even on a limited basis, it is a success. It is then up to us to find other markets, or other strategies, that work when these methods stand aside.
3. “The DAX-FTSE pair had a ratio of 3.0, about in the middle of the group of 13 best performers. If we created a portfolio from those pairs, it would look excellent, although the reliance on the CAC and FTSE would limit diversification, increase risk, and require that the portfolio is deleveraged to keep risk under control. It's a sacrifice we can all live with.”

PK continues to go through the other sectors and, to his credit, he admits that he finds the stress indi isn’t universally an improvement.

For example, for interest rates

1. The stress returns were lower.
2. The stress ratios were lower.
3. The stress returns per contract were too low for comfort.
4. However volatility threshold can again come to the rescue, but it needs to be smaller than the 3% used before, 1% seems to work

1. “It may be tempting to start the portfolio in mid-2007, when volatility and trading activity increased. That way, the annualized returns would be maximized and look better. But that is ex post selection, making the decision based on observing past data. In real trading, we will have periods when trades are filtered because of low volatility, and we can't erase those periods from our performance." (and yet he did precisely that last chapter!)

Pairs Trading Summary

1. PK covered pairs trading stocks, futures
2. And a combination of both which is ‘cross-market’
3. Overall it worked - it found the right entry/exit points and ‘often’ returned a profit
4. It failed when the volatility of markets was too low to overcome costs
5. That could be avoided by waiting patiently, but traders aren’t known for their patience (Oh, but the good ones are)
6. Futures are more interesting than stocks because of higher volatility and ability to vary leverage
7. It’s not as profitable as it was 10-20 years ago (and has this worsened in the ensuing decade?)
8. The easier trading becomes (in the sense of convenience) the more competition there is
9. The challenge is to become more technical, stay aware
10. The opportunities won’t go away until all stocks/futures markets merge into one company
    
    Attached Image (click to enlarge)

    
    
    Arriving ca. 3000 AD

Next: Traditional Market-Neutral Trading

Chapter 8 - Traditional Market-Neutral Trading

1. Any strategy that balances longs vs shorts can be called market-neutral == direction neutral
2. Not exposed to the risk of outright price direction
3. During uncertain economic times investors shift money to blue chips
4. During boom times they throw money at small-cap stocks
5. If that relationship holds then you should be able to buy the Russell 2000 and sell the Dow or S&P when the economy is ‘robust’.
6. Profit would be = Russell gain minus Dow gain regardless of whether either index goes up or down (Doesn’t this ignore the fact that the Dow and S&P go up no matter what the economy is doing, or it did, until this year? Remember Tina Sogu.)
7. The advantage of such a strategy is immunity to price shocks
   1. If you were long Russell and short the S&P on 9/11 (vol adjusted) the losses in the long Russell position would be offset by the short profits in the S&P
   2. Exposure is small as long as you can adjust for differences in volatility
   3. Even leveraged futures (4x) the exposure would have been smaller than the declines in an outright long position

   
   

8. “In this book, we have focused primarily on pairs trading. The advantages are that you can choose a small set of markets and a modest investment.
9. In addition, the calculations involve only two stocks or futures markets at a time and can be done on a spreadsheet. However, traditional market neutral programs are much broader, serve a somewhat different purpose, and are not correlated to pairs trading”

Home Builders

1. PK uses the same 5 stocks that were used in the pairs trading example (HOV, KBH, LEN, PHM, TOL)
2. The pairs trading test returned better than $0.14 per trade; this is the benchmark for this test

Trend or Mean Reversion?

1. If you’re planning to go long some stocks and short others you have to decide if your position will be trending or mean-reverting
2. Trends tend to persist but you might also believe in the ‘dogs of the Dow’ theory
   1. This advocates that, with some qualifications, the weaker companies in the Dow will cycle to become the stronger ones in the near future
   2. They are after all, solid institutions that just need to get past some short-term issues (Re-read Taleb or just go to the post about survivorship bias. With no time limit, inevitably, the weakest stocks in the Dow will eventually become the leaders over vast aeons, but only the ones that don’t go bankrupt first.)

   
   

3. For pairs trading mean-reversion was chosen
4. One way to decide is to find the profitability of a simple trend-following system on a group of stocks

Basic Market-Neutral Concept

1. Find a metric that allows comparison of the five stocks in the home-building group to decide which are stronger or weaker
2. One way would be to use the same 20 day moving average on all stocks and compare the 1-day changes in the MA differences
3. Look at the change in the MA from the previous day
4. MA(t)-MA(t-1) or over n days MA(t) - MA(t-n)
5. Stocks with the largest positive change are strongest
6. Stocks with the largest negative change are weakest
7. PK opts for a linear regression line

Putting all the markets into the same units

1. Comparing line slopes won’t work unless all the stocks are expressed in the same units - percentages
2. If a stock priced at $10 goes up by $1 each day the slope is $1
3. If another stock priced at $5 goes up $0.50 each day the slope is $0.50
4. Comparing these without conversion, the higher priced stock will have the steeper slope, and appear to be stronger, when they are actually the same
5. The solution is indexing - which is the same as converting to %
6. Starting each series at 100, the next index value X(t) is:
   1. X(t) = X(t-1) * (P(t)/P(t-1)) where P(t) is the current price and P(t-1) is the previous price
   2. This is only for calculating relative strength of sector components. Profits and losses are calculated using the original prices.

   
   

Relative Strength and Weakness

1. Convert each stock series to %age returns using indexing
2. The slope can then be found using the spreadsheet function SLOPE(y, x) where y is the column of dependent variables and x is the column of independent variables, which in the case of a price series is the time (days)
3. Since stocks don’t trade on weekends we don’t use dates, but an integer sequence (1,2,3, … n) for as many days as needed
4. For this strategy we’ll use n = 10 and apply it to the SPX

Example of a 10-day linear regression slope calculation applied to SPX

Ranking and Choosing Which Markets to Trade

The five home builders showing the calculations need on day 1 (Jan 10, 2000) of the first two days.

 

1. Homebuilders suffered during the 2008 crisis so it’s not surprising to see wild volatile price swings
2. Attached Image (click to enlarge)

   
   
3. Looking at row 4 of table 8.2 we see Pulte is weakest, and Lennar is the strongest, with the rest ranked based on their slope

Selecting the Specific Stocks to Trade

1. Decide:
   1. Sell the two highest-ranking stocks; buy the two lowest-ranking stocks
   2. Sell the single highest ranking stocks and buy the single lowest-ranking stock

   
   

2. PK chooses the first option; four stocks offers more diversification than two
3. PK buys Pulte and Hovnanian, sells Lennar and KB Homes

Number of shares to trade

1. The goal is risk neutrality; long positions must be equal to short in terms of risk
2. Two ways to balance risk
   1. Trade equal dollar amounts of each stock
   2. Volatility adjust the position size

   
   

3. The first option is much simpler, and commonly accepted on Wall St.
   1. This is based on the loosely accepted principle that volatility increases as price increases
   2. Generally true, but specific vol for two stocks trading at the same price could vary as much as 50% (!) if one stock is in the news and the other is under the radar
   3. Stocks at low prices have erratic volatility; often much higher than stocks trading at higher prices
   4. For ex. Wells Fargo, jumping from $3 to $3.75 is a large percentage for one day but a small gain after falling from above $50.
   5. Attached Image (click to enlarge)

      
      
   6. Attached Image (click to enlarge)

      
      
   7. “Volatility reaching 250% is unheard of and can be sustained only over short time periods; however, this surge of volatility, in excess of 100%, is now approaching one year. This unusual scenario makes any measurement of volatility subject to problems but is an opportunity to prove that a strategy can survive under stress.”

   
   

4. Initial investment is $10,000
5. Each stock gets an allocation of $2500
6. Divide 2500 by the stock closing price on day 1
7. “transaction costs are very important because the returns per share are typically small for market-neutral strategies in the stock market”
8. PK says the transaction cost per share is $0.005. So selling short 1025 shares of Lennar comes to $5.12 for example.

Next: Day 2

Day 2

1. Day 1 we have 2 longs, 2 shorts each committed to $2500
2. End of day 2
   1. Update the prices
   2. Calculate the net index value
   3. Attached Image (click to enlarge)

      
      
   4. Find the 8 day slope of each index series
   5. Rank the stocks by their slope
   6. Choose the two strongest to sell short and the two weakest to buy
   7. Determine shares number by dividing 2500 by the current price
   8. Enter orders based on the difference between yesterday’s positions and today’s
   9. Calculate profit or loss for each stock as the shares held yesterday times todays’ close minus yesterday’s close
   10. Subtract the cost of trading applied to the difference of today’s position size and the previous day’s size

   
   

3. The stocks on this day kept their relative strength - the rankings don’t change
4. The prices changed so the size of the positions changed
   1. Lennar’s price increased so its shares dropped from 1025 to 1011
   2. Since PK is short Lennar, he buys 14 shares, to reduce the short position

   
   

5. He continues in this way til the last trading day

Certainly not as easy as padding out a trading book!

For this system PK proceeds to discuss changing critical parameters

1. Change the period of the slope calculation
2. Filtering out low volatility
3. Quantizing the position size change threshold to reduce costs
4. Filtering by price (avoiding low-priced stocks whose price changes are comparatively big percentage-wise)
5. Trading only at extremes (something you should do anyway)
6. Volatility-adjusting the position size (the more complex way of choosing position sizes)

Each of these has variable results on the outcomes, just like in the rest of the book.

Next: Chapter 9 and the exciting conclusion!

Chapter 9 - Other Stat-Arb Methods
The rest of the book (chapter 9) is a series of un-tested proposals for producing other types of stat-arb trades.

These include:

1. Arbing the Dow using a large-scale market-neutral program (successful if you use enough stocks, says PK)
2. Same thing but with SP500
3. Regime-switching using the slope of the equally weighted average of stocks
4. Market Neutral trading using Futures.
   1. Success comes with finding a particularly volatile interval in stocks or by using cross-regional futures. Futures have the better payout. Globalisation has caused equity indices, and interest rate futures to be ‘dirty linked’ so that they don’t follow too closely but ultimately drift back together.
   2. This makes mean-reversion the strategy of choice

   
   

5. Creating a custom index to use as one leg of a pairs trade
6. Using the upgrade/downgrade services offered by financial firms to pick pairs
7. Use a Ratings Service to create a stat-arb pairs trade (depends on forecasts being something other than random)
8. Using P/E, analyst recommendations (like Jim Cramer’s - before he become a running gag) or some DIY metric like Return on Equity
9. Ranking arbitrage - trade all stocks making new highs and new lows (Thorpe’s MUD system basically?)
10. Merger arb - not really arbitrage - but traders try to anticipate an acquisition and buy an option in the target company. ⅕ successes is enough to make this profitable
    1. Another way is to wait for the acquisition to happen
       1. Buy the target company and sell the acquiring company
       2. The theory is the purchase will add to debt and uncertainty reducing the value of the acquirer
       3. The movements of the two stocks are ‘not very predictable’ so there is no assurance that one move will offset the other (but can’t we make this criticism of all the strategies presented here?)

       
       

    2. If a deal fails to close it can cause a big loss but these are rarer

    
    

PK goes into the rules, details, and his thoughts about possible system tinkering for each one, however his endurance seems to be flagging as each section gets shorter than the last.

The last words really sum up this book and maybe the experience of all retail traders.

“While others are out there looking at the same opportunities, taking a slightly smaller profit and a slightly bigger risk may give you an edge.”

Whether that’s a positive or a negative edge is left as an exercise for the reader.

Conclusions

Pros:

1. Highly educational
2. Refreshing to get a quantitative perspective on trading for a change
3. Nothing is dumbed-down or oversimplified
4. Full of good ideas and interesting takes on possible strategies.
5. Highly inspirational for someone who likes to design systems.

Cons:

1. Like drinking from a firehose - without a prior background in the maths or the pairs trading arena most readers will quickly be in over their heads.
2. This is not really a book where an expert trader reveals his methods for success. It’s more like a mad scientist’s experimental logbook where he records all his notes, errata, experiments and future plans, whether or not they have been successful or have any chance of being successful in the future. I get the impression that PK wrote this book because he had all this material lying around and didn’t know what to do with it. That’s a temptation I’m familiar with, but I’ve rejected it mainly because it’s unfair to the reader who expects a payoff.
3. A dying gasp from a method that has been squeezed out of the market by an algorithmic arms race? I’m not sure and it would be difficult for me to put much of this to the test, without major overhauling.
4. Trading someone else’s system is unlikely to succeed and everything here is specific to how PK likes to work, from his spreadsheets to his way of seeing the market. Ironically the best part of the book is nearer the end when he stops actually backtesting his system ideas but just speculates about creative ways to put together new types of arbitrage. Unfortunately by that time the reader (at least me) is tired of it all.
5. This (probably) suffers from the classic quant pitfall - treating all market data as part of an unthinking system whose past results will behave like the future, with recent data being more reliable than distant data.
   
   This is just my opinion but the market isn’t like that. It’s not a static or dynamic system - it’s a reactive system, as Soros told us way back in the first book. Anything that gets too noticeable gets attacked. Sometimes the best way to be profitable is to be less profitable, so trying to optimise (very much) is pointless.
   

Footnotes

It looks like there is a 3-way tie for the next book so you can vote in the poll if you like, and I will pick it mid-week or so. Thanks for reading.

1. The Education of a Speculator by Neiderhoffer 4 Votes 10%
2. A Man for All Markets by Edward Thorp 4 Votes 10%
3. Cycle Analytics for Traders by John Ehlers 4 Votes 10%

On average, how long does it take an intermediate forex trader to become very profitable.

There is not enough data on profitable forex traders to answer that question, at least not public data.

I know everyone says 'it depends' but it really depends, on a LOT of factors. Since I don't know what we're starting with, I'm going to say 10 years. That should scare anyone away if they're not serious and if they are serious, maybe they're smarter than everyone else and it will take them less time.

Ok thank you

A Man for All Markets by Edward O. Thorp


This book is mostly an autobiography so much of it is not really applicable to trading. Despite this, it's an engaging read about a very interesting figure, undoubtedly one of the great characters, academic adventurers, and egos of American history. Whether his actual achievements match his reputation/mythology I suppose we can never know for sure, but just having the audacity to attempt to build a wearable computer to beat a casino in the 1960s is amazing by itself and Thorp did so much more.

I highly recommend reading the book, but here is everything that I thought was worth noting, arranged not by chapter but by subject when it is first mentioned in the book.

1. “tendency not to accept anything I was told until I had checked it for myself”
2. lifelong values of fair play, a level playing field for everyone
3. Photographic memory, or so he says, until about the age of 10 “when it faded into a memory that is very good for what I’m interested in and, with exceptions, not especially remarkable for much else”
4. The skill “to make rapid approximate calculations, remains valuable, particularly for assessing the quantitative statements that one continually encounters”
5. “I fell asleep at night mentally reviewing the material (a chemistry textbook), a habit that proved, both then and later, remarkably effective for understanding and permanently remembering what I had learned.”
6. Working from multiple texts, “When a concept wasn’t clear in one of them, it was generally clarified in another”
7. “when I wanted to know some organic chemistry to explore ideas for extending healthy human longevity, I learned it as I needed to” (and Thorp is still alive, according to the internet - aged 90!)
8. “If you do this what do you want to happen? and If you do this, what do you think will happen? These two questions became valuable guides for me in the future.”

The Martingale System

1. “The Martingale system, or doubling-up system, is one of the many betting schemes that gamblers had devised in an attempt to win.”
2. Often used at roulette for bets with even-money payoffs
3. With an even-money payoff, for each thirty-eight spins, you can expect to win a bet on red or a bet on black on average eighteen times and lose twenty for a net loss of two.
4. To get around this disadvantage, start by doubling your bet after each loss
5. Eventually when you win you recover all your losses plus the profit you would have won from the original bet
6. “The catch is that after many doublings, your required bet can be so large that either you have run out of money or the casino won’t allow it.”

On testing betting systems

1. “With an infinite number of possible sequences of outcomes in a gambling game, it was impossible to ever know through trial and error whether any particular betting system worked. To analyze each scheme mathematically, one at a time, was hopeless as well, as there was always a new one to test. One of the triumphs of mathematics had been to prove with a single theorem that all such systems must fail. Under fairly general assumptions, no method for varying the size of your bets could overcome the casino’s advantage.”
2. Henri Poincaré, had “proven” that physical prediction at roulette was impossible. His proof was sound, only assuming a modest and plausible randomness in predicting the final resting place of the ball.
3. Understanding and dealing correctly with the trade-off between risk and return is a fundamental, but poorly understood, challenge faced by all gamblers and investors.

Beating Roulette

1. Thorp asks Feynman if roulette can be beaten and he says it cannot be - which Thorp finds reassuring because it means no one had yet beaten him to the punch
2. Thorp begins experiments using a wooden track and marbles and a ½ scale roulette wheel
3. “the surest way to get rich is to play only those gambling games or make those investments where I have an edge.”
4. After attempting to play Blackjack using a system he realizes most players are ignorant of the mathematics of the game and depend on superstition
5. He goes home determined to beat Blackjack

Beating Blackjack

1. The system Thorp had used (the Baldwin strategy) depended on the fact that every card has an independent chance of being dealt and somehow this reduces the house’s edge to 0.62, almost even.
2. The weakness, he realizes, is that the chance of drawing certain cards changes as the game progresses and fewer cards are left in the deck
3. A player who keeps track of what cards remain in the deck can vary their bets accordingly
4. Bet more when the odds are favorable, less when not; the casino wins more small bets, but you win the big bets
5. 55 pairs of cards can be dealt to the player x 10 possible values of the dealer’s upcard = 550 different situations to react against; do this for a few hands and the calculations grow into millions
6. Baldwin’s group couldn’t do exact calculations with hand calculators in a feasible time
7. Thorp’s task is even bigger because he has to calculate probabilities for partially played decks
8. He simplifies the problem by predicting that the edge for partly used decks depends mainly on the fraction of each card type remaining
   1. 12 tens, with 40 cards remaining has about the same effect as
   2. 9 tens with 30 cards remaining
   3. The fraction remaining is what matters, not the total number
   4. This turns out to be correct

   
   

9. Thorp starts out trying to do the calculations by hand but realizes even with shortcuts it will take too long
10. He teaches himself FORTRAN and uses an IBM 704
11. Results indicated that the casino advantage, when you played as perfectly as possible without keeping track of the cards that have been played, was 0.21 percent
    1. So any form of card counting should give the player an edge

    
    

12. In 1980 Thorp was finally able to prove his rules in ‘Beat the Dealer’ (without card counting) gave the player a 0.13 % edge
13. The IBM computer can do in minutes what would take human thousands of man-hours and Thorp calculates that the edge in the game changes as cards are removed or ‘added’ (not played)
14. He invents a 5-count, 10-count and ‘ultimate’ system
15. To get his blackjack paper published he meets with Claude Shannon and this famously leads to them cooperating on the first wearable computer designed to beat roulette
16. The rest of the story has been covered in other books - he is bankrolled by a couple of gangsters, goes to Vegas to prove his theory, nearly gets killed, inspires the movie ‘21’, etc.
17. “This plan, of betting only at a level at which I was emotionally comfortable and not advancing until I was ready, enabled me to play my system with a calm and disciplined accuracy. This lesson from the blackjack tables would prove invaluable throughout my investment lifetime as the stakes grew ever larger.”
18. “the Ten-Count System had shown moderately heavy losses mixed with “lucky” streaks of the most dazzling brilliance. I learned later that this was a characteristic of a random series of favorable bets. And I would see it again and again in real life in both the gambling and the investment worlds.”
19. My updated version of the book was published in 2017. Thorp still says you can beat the dealer, with a ‘qualified yes’. You have to find tables that haven’t modified the rules too much from the original.

Betting Systems Don’t Work

1. The Labouchère system - doesn’t work
2. Defective roulette wheels - can be exploited
3. Russian roulette isn’t always random - a well-oiled chamber will spin so freely that the weight of a bullet in the chamber will cause it to rest at the bottom once it stops spinning.
4. Heraclitus : “Character is destiny.”

Wall Street: The Greatest Casino on Earth

1. Gambling is investing simplified
2. “Both can be analyzed using mathematics, statistics, and computers. Each requires money management, choosing the proper balance between risk and return.”
3. Thorp analyzes the errors of his first stock purchase
   1. No knowledge of the company - bought based on a news story
   2. Held on when the price declined
   3. Focused on getting out at his purchase price - anchoring bias

   
   

4. Then he buys part of an insurance company
   1. Average price of such companies had risen for the past 24 years
   2. As soon as he buys, the winning streak ends and he loses money
   3. Do not assume that what investors call momentum, a long streak of either rising or falling prices, will continue unless you can make a sound case that it will.

   
   

5. He tries ‘charting’
   1. Finds nothing of value.

   
   

6. Then he becomes a silver bug
   1. Gets wiped out due to excessive leverage

   
   

7. For a few thousand dollars I learned from this to make proper risk management a major theme of my life for more than fifty years thereafter.
8. He learns about warrants and hedging
9. To form a hedge, take two securities whose prices tend to move together, such as a warrant and the common stock it can purchase
   1. Buy the relatively underpriced security and sell short the relatively overpriced security. If the proportions in the position are chosen well, then even though prices fluctuate, the gains and losses on the two sides will approximately offset or hedge each other. If the relative mispricing between the two securities disappears as expected, close the position in both and collect a profit. (pairs trading!)

   
   

10. Thorp begins collaborating with an economist - Sheen Kassouf, and they make 25%/year pairs-trading warrants and common stock.
11. Kassouf ends up parting ways as he believes the neutral hedges don’t allow him to profit from his economic understanding of the companies involved.
12. Thorp starts his own managed fund for friends and family
13. Thorp offers no explanation of how he prices warrants apart from mentioning ‘Occam’s Razor’

Warren Buffett

1. Thorp gets invited to dinner as sort-of secret test of his investment knowledge/skill
2. Famously, they discuss compound interest and non-transitive dice
3. We know Buffett’s philosophy. Here’s how Thorp contrasts his approach to Buffett’s:
   1. I didn’t judge the worth of various businesses. Instead I compared different securities of the same company with the object of finding relative mispricing, from which I could construct a hedged position, long the relatively undervalued, short the relatively overvalued, from which I could extract a positive return despite stock market ups and downs.

   
   

4. Buffett advised Schwarzenegger to reverse proposition 13 because of the lost tax revenue to the state; naturally Arnie wasn’t interested
5. Thorp decides to follow Buffett’s example and form a limited partnership

Jay Regan

1. This part of the story is also well known. Regan persuades Thorp to start a hedge fund (Convertible Hedge Associates) based on the ideas in ‘Beat the Market’ with himself as the business side and Thorp as the researcher. This appeals to both of them but Regan turns out to be crooked.
2. Later it becomes Princeton Newport Partners - one of the first quant firms
3. Thorp’s trades are guided by formulae from Bachelier -> Browning -> Einstein regarding the random movement of particles in water. “Brownian motion”.
4. “Using plausible and intuitive reasoning, I supposed that both the unknown growth rate and the discount factor in the existing warrant valuation formula could be replaced by the so-called riskless interest rate, namely that which was paid by a US Treasury bill maturing at the warrant expiration date.” (Surely this wasn’t an original idea?)
5. The formula is independently developed by Myron, Black and Scholes, claims Thorp, and of course they get the credit. Thorp claims Fischer even wrote to him and thanked him for the idea behind ‘delta hedging’.
6. The fund’s performance is much better during downturns and only slightly worse than the S&P during bull markets
7. Never had a losing year or losing quarter
8. Thorp leaves academia.
   1. “One problem in large bureaucracies is that many of the members decide it is better not to cross people, instead of standing on principle.”

   
   

9. He uses the ‘integral method’ to properly value American put options (no details given) and it has applications to wider distributions of stock prices, unlike Black-Scholes, he claims.
10. Buying warrants and hedging by shorting stock
    1. Pays off throughout the 70s

    
    

11. Convertible bonds
    1. Imagine the case of the hypothetical XYZ 6s of 2020
    2. EAch bond sold for $1000 on 2005-07-01, redeemable for face value on 2020-07-01
    3. Promises to pay 6%/yr in 2 semiannual payments of 3% or $30 on Jan1 and Jul1
    4. Can be converted into 20 shares of XYZ common stock at any time before maturity
    5. This combines features of bonds and options
    6. The market price
       1. Value of a comparable (unconvertible) bond (fluctuates with interest and fortunes of the company) and sets the ‘floor’ price +
       2. Option value of the conversion feature, doesn’t gain value until the stock rises above the face value of the bond
       3. Companies issue these because the conversion feature is like a lotto ticket on the company’s future and it allows the company to reduce the interest rate they need to pay

       
       

12. Thorp rejects VaR (value at risk)
    1. It doesn’t account for the worst long tail risks
    2. Extreme events are where ruin is to be found

    
    

13. He claims credit for ‘stress testing’ portfolios by simulating major calamitous events
    1. Simply replaying the past is inadequate
    2. Their portfolios were unaffected by a 25% drop in the market in a single day (1987)
    3. “When, with our expanding range and size of trades, we moved our account to Goldman Sachs as our prime broker, one of the questions I asked was: “What happens to our account if Goldman Sachs New York is destroyed by a terrorist nuclear bomb smuggled into New York Harbor?” Their reply was: “We have duplicate records stored underground in Iron Mountain, Colorado.” “

    
    

Indicators Project

1. object was to study the financial characteristics of companies, or indicators, to see if they could be used to forecast stock returns
2. Some metrics correlated to past performance
   1. earnings yield (annual earnings divided by price),
   2. dividend yield,
   3. book value divided by price,
   4. momentum,
   5. short interest (the number of shares of a company currently sold short),
   6. earnings surprise (an earnings announcement that is significantly and unexpectedly different from the analysts’ consensus),
   7. purchases and sales by company officers, directors
   8. Ratio of total company sales to the market price of the company

   
   

3. MIDAS (multiple indicator diversified asset system)
   1. The best stocks are bought and the worst are shorted
   2. They close this in 1988 but Thorp doesn’t give any hint as to why. (my guess: doesn’t work)

Thorp describes a gold trade and a trade in AT&T but I can’t really find any generalizable lesson in either one, as they were mostly one-off opportunities caused by unusual market situations that only a big hedge fund would have access to.

However he makes a trade after the crash of 1987 that is fairly interesting.

1. Friday, Oct. 16, 1987 market falls 4 percent
2. Monday, Oct 19, 1987, at lunchtime it had fallen another 7 percent
3. Dow off 18 percent
4. Thorp reasons that either his hedges will work or they won’t. He does nothing that day.
5. EOD the market was down 23 percent, nearly ¼ of the market value was ‘gone’
6. US national wealth decreased 5%
7. Thorp’s models didn’t measure distributions using lognormal probabilities but he doesn’t say what he did use; however he claims because of this he wasn’t nearly as shocked as everyone else
8. He believes the crash was caused by portfolio insurance
   1. Automated program designed to switch from equities to T-bills during market drops
   2. When the market fell 4% the algos started selling stock and buying T-bills
   3. This created a positive feedback loop, driving stock prices down, and triggering more selling; ironically the cure for market declines became the cause

   
   

9. Portfolio insurance firms saved on fees by buying contracts on S&P futures rather than selling and buying back stock
   1. Usually the price of the futures and the S&P price track very closely
   2. That Monday morning the price of futures was 185-190 and the S&P was at 220
   3. This difference of 30-35 was ‘unheard of’, because arbitrageurs usually kept the two prices within a point or two
   4. However now institutions had sold massive amounts of futures, but the index itself didn’t fall as much because the arbs were terrified and wouldn’t exploit the spread
   5. Or they couldn’t - the ‘uptick’ rule specified that short-sale transactions are allowed only at a higher price than the previous different price. The rule was designed to prevent short-sellers from driving down the price of stocks.

   
   

10. Thorp quickly sees that selling stocks short and buying index futures should lead to quick riskless profit
    1. However upticks are scarce
    2. He calls the head trader, a ‘minor general partner’ (?) who is ‘highly compensated’ by his share of ‘our’ fees
    3. He tells him to buy $5M of index futures at the market (190)
    4. And sell short at the market, double the optimal amount of hedging stocks - not $5M but $10M
    5. Thorp assumes that missing upticks will only allow about ½ this amount to be shorted, so it should balance out, producing the proper hedge
    6. The trader, gripped by the panic fear of the crash, refuses to execute the trades (!)
    7. Thorp tells him to do it for PNP (so is this trader not working for PNP?) or else he wanted it for his own account. Thorp also (threatens? cajoles?) him by saying he would tattle on him to the other partners if he made a profit and the other partners missed out (I think?)
    8. Thorp’s reasoning
       1. If only ½ the shorts ‘get off’ then they would be properly hedge and make about $3/4M.
       2. If none get off, they were buying futures at a big discount. The market would have to fall another 13% before they began to lose (but how is that not a possibility if it’s already dropped 25%!?)
       3. If all the shorts got off the market would have to rise 14% to lose money
       4. So to protect against this Thorp instructs the trader to cancel the rest of the shorts after they’re half-filled

       
       

    
    

11. Finally the trader complies
12. Thorp orders a second round of this
13. They end up with $9M futures long vs $10M stock short, locking in $1M in profit.
14. Thorp says if the trader hadn’t stalled he would have done ‘several more rounds’ and made additional millions
15. PNP is ‘flat’ for October but the S&P is down 22 percent
16. Aug-December, index was down 22 percent, but PNP gained 9 percent
17. Thorp subtly accuses Fischer Black of stealing his computerized analytic system

Vonnegut and Heller
“Joseph Heller and Kurt Vonnegut were at a party given by a billionaire when Vonnegut asked Heller how it felt to know that their host might have made more money in one day than Heller’s Catch-22 since it was written. Heller said he had something the rich man could never have. When a puzzled Vonnegut asked what that could be, Heller answered, “The knowledge that I’ve got enough.” “

Bernie Madoff

1. Thorp claims he detected and predicted his fraud in 1991, 17 years after he was convicted in 2008.
2. He saves one of his clients from getting entrapped in Madoff’s scheme
3. The SEC continually failed to act from at least 1992
4. Thorp uses the evidence of thousands of Madoff suckers ranging from housewives to celebrities to billionaires as proof that the markets are not ‘efficient’

Adjustment Period

1. The Wisdom of Crowds vs. The Lunacy of Lemmings
2. On negotiation: “It doesn’t pay to push the other party to their absolute limit. A small extra gain is generally not worth the substantial risk the deal will break up.”
3. Scalping to save money isn’t worth it if you miss opportunities by not entering at market price
4. Satisficers vs. maximizers
5. Secretary or Marriage problem
   1. Optimal strategy is to interview 37% of prospects and then choose the next one you see who is better than the first 37% you passed over
   2. If no one is better you are stuck with the last one on the list

Swindles and Hazards

1. The internet has made swindling people easier
   1. Online hoaxes - fake anonymous tipsters, both long and short
   2. Ponzi schemes - usually no audited statements
   3. Once a scammer always a scammer
   4. ‘First-look’ and HFT - wastes wealth and creates no social good (like crypto then?)
   5. Routine financial reporting / creative accounting
   6. Offering explanations for insignificant price changes

Statistical Arbitrage

1. “By luck, one of our researchers almost immediately found the basic idea behind statistical arbitrage. He ranked stocks by their gain or loss over the previous two weeks. The stocks that had gone up the most did worse as a group than the market in the next few weeks, and the stocks that were the most down did better. Historically, the annualized return was 20 percent from buying the one-tenth of stocks that had fallen most and selling short the tenth that had risen most. We called the system MUD, as it was constructed from the “most-up, most-down” stocks. As UCI mathematician William F. Donoghue would joke, “Thorp, my advice is to buy low and sell high.” The portfolio of long stocks tracked the market and the short portfolio did the opposite, so the two sides together mostly canceled the movement of the market. This gave us what we liked, a market-neutral portfolio.”
2. Gerry Bamberger refines this by trading industry groups separately
3. Thorp refines this further using ‘factor analysis’
   1. The most important ‘factor’ is market factor which reflects a stock’s tendency to move up or down with the market
   2. Movement additional to the market factor is the ‘residual’

   
   

4. The new model is confirmed to be factor-neutral while Bamberger’s model fails in simulations
5. Morgan Stanley expanded their investment in the Bamberger model and end up losing 6-12 percent. When they shut down their stat-arb group some of the defectors join Thorp & co. One of these is D.E. Shaw
6. Shaw ends up starting his own firm and hires a young Jeff Bezos. This story has been told before.
7. “I had no immediate plans to use our new statistical arbitrage technique and I expected that continuing innovations by investors using related systems would, as is the way of things, gradually erode its value.”
8. Every stock market system with an edge is necessarily limited in the amount of money it can use and still produce extra returns. One reason is that buying undervalued securities tends to raise the price, reducing or eliminating the mispricing, and selling short overpriced securities tends to lower the price, once again shrinking the mispricing.
9. Opportunities for beating the market are limited in size by how trading them affects market prices.
10. After many record-breaking years Thorp shuts down ‘Ridgeline partners’ in 2002 due to declining returns and the expansion of stat-arb programs.

Mutual Savings and Loans

1. It takes Thorp nearly a whole chapter just to explain this crazy scheme which involved travelling around to hundreds of small towns and opening up savings accounts at many different branches.
2. I still don’t really understand how it worked
3. He claims this generated a million dollars in one year
4. “The game has slowly wound down over the last two decades. Mutual S&Ls have converted, leaving fewer opportunities.”
5. I guess the lesson is there are a dozen ways to skin a cat if you have the brains and the willingness to risk. The single biggest advantage of being wealthy is it doesn’t take as much fortitude to pull the trigger and you have more rounds to shoot.

Berkshire Hathaway

1. Thorp began to realize its potential in 1983 and started investing
2. The sad story of Carolyn, the divorced house cleaner
   1. She gets $6k from car-accident settlement
   2. Begs Thorp to help her invest it
   3. He finally relents and warns her not to sell before checking with him
   4. She buys 2 shares of BRK.A
   5. It rose to $5k a share before the 1987 crash
   6. His broker tells him that she sold near the post-crash bottom at $2600 a share
   7. 16 years later that stock was worth $60-74k (and today just under a cool million; but sometimes you just need cash now; investing is not for the working poor)

Historical Returns

Rule of 72
The rule of 72 gives quick approximate answers to compound interest and compound growth problems. The rule tells us how many periods it takes for wealth to double with a specified rate of return, and is exact for a rate of 7.85 percent. For smaller rates, doubling is a little quicker than what the rule calculates; for greater rates, it takes a little longer.




Footnotes

The Education of A Speculator
by Victor Niederhoffer

Preface

1. His daily bread depends on reversing big moves. His function is to balance supply and demand. Sell when prices are high. Buy when they are low.
2. Prefers to draw attention to and accentuate his weaknesses and losses - to keep him humble
3. Refutes efficient markets
4. Doesn’t own a tv, follow the news or talk to anyone during the trading day
5. Dislikes reading books < 100 years old
6. Losses of 7-8 figures, > 25% of liquid worth and client net assets in a single day
7. 2 million contracts traded with average profit of $70 / contract after slippage
   1. 700 standard deviations away from randomness

8. Will not share secrets or systems; it’s ‘inconceivable’ that anyone would share a truly effective get-rich scheme for the price of a book
9. Better to go against the gurus
10. Chess teacher is Art Bisguier - “You have to know the lesson is there in order to use it”

The main part of this book is written like a novel. Neiderhoffer clearly harbours some literary ambitions and decides to mix business with pleasure. He writes with a skill that is rare for a business book writer. In fact the prose is florid, and in some places even poignant. When was the last time a trading book made you cry?

The trouble is you can’t be sure if he’s being serious (he has a wickedly subtle wit) and if the things that are happening actually happened, or are part of a literary device. I can see why this book never really took its place in the classics of trading literature, as the reader looking for some solid trading advice has to wade through pages of the golden age of ancient Greece, romantic trysts under the boardwalk at Brighton beach, and conversations with ghosts.

The reader who wants a surreal journey through the life of a Wall Street trader (with George Soros and his departed father and grandfather as companions, no less) well, who is that reader? I guess it’s me. Probably just me in the entire world, so I doubt this book sold too many copies.

It has good reviews on Amazon, but I sympathize with this annoyed fellow.

But Cory Mitchell is wrong, because it’s choc-a-bloc with trading insights, you just have to work very hard to find them. I will save you the trouble, dear reader; the pleasure is mine.

Chapter 1 - Brighton Beach Training
This first chapter is written in the style of Hemingway, as a stream of consciousness, mixing actual trading thoughts with random daydreams. Here’s a sample:
“I love you yen. You are so orderly, so loyal, like your country. I don’t hold it against you that you would not take my dollars when I tried to buy food in Tokyo for my family of eleven. Now take my dollars. You feel the gaijin are dirty. They will not take their shoes off in your crowded restaurants. But I do take my shoes off. I’ll build a rock garden and sit and pray to Shinto gods if you’ll just take my dollars at 93.50 and then go down to 91.”

At the same time I find myself relating to a lot of his daily fears. Aging. Thoughts of former coworkers. Loneliness. Lack of sleep. This is very real, despite being written as fiction.

 

1. The wholesale failure of brokerage firms during a panic is often associated with market bottoms
   1. Nikkei bottom in 1995 coincides with failure of Barings & co.
   2. Jim Rogers bought Pakistan stocks because their stock market was shut down

2. The inverse is also true - when brokerage houses are flush with profits, time to sell
3. However Neiderhoffer warns that sage advice is easy to give and knowing what to listen to requires experience and principles

Lessons from Livermore

1. The only thing a man should do when he is wrong is cease to be wrong
2. You can beat the market in grains but not the grain market
3. There is the plain fool, who does all the wrong things everywhere, but then there is the Wall St. fool who thinks he must trade all the time
4. Their (broker) accounts didn’t always agree with mine, and the differences uniformly happened to be against me. Curious coincidence - not!
5. If a man didn’t make mistakes he’d own the whole world in a month. But if he didn’t profit by his mistakes he wouldn’t own a blessed thing.
6. The mistake family is so large that there is always one of them around when you want to see what you can do in the fool-play line.
7. The weaknesses that all men are prone to are fatal to success in speculation. It is inseparable from human nature to hope and to fear. It is absolutely wrong to gamble in stocks the way the average man does.

1. The best way to taste (test?) plausible theories is to quantify, test, and analyze them rigorously.
2. Niederhoffer (VN from now on) tests the brokerage house theory
   1. Collected monthly prices for Merrill Lynch 1972-1995
   2. Computed monthly and yearly returns and compared to S&P500
   3. Excess returns of ML vs S&P should be an inverse predictor of future S&P moves

1. Unfortunately there is no support for the inverse theory for monthly returns but there may be one for yearly returns (cycles)
2. VN has not had one satisfactory day of trading
   1. When he makes money he kicks himself for not being more aggressive
   2. When he loses he kicks himself for not staying away

3. Whitlow Wyatt’s rules for staying ahead
   1. Never let down for a moment. Pitch to every batter as though you were facing him the first time. That keeps you careful.
   2. Pitch to every hitter as though you were trying to keep him from getting a long hit
   3. No matter how low a batter’s average may be you can’t afford to show him too much of even your Sunday pitch or he’ll hit it.

4. No phone calls, lunch breaks, or visitors on trading days, no signing checks or filling out forms
5. “The more he talks about his honesty, the faster I count my silver.”
6. “I have never seen a success in any field who didn’t have some internal mechanism for economizing on energy at work at all times.”
7. The Judas steer - the story of the steer who leads his fellows to the slaughter but always manages to escape somehow himself; the markets also do this - move a few wild ticks in one direction just to induce investors to take a wrong position in stocks.
   1. Tax breaks are usually a sucker’s play

Chapter 2 - Panics and Hoodoos

 

1. Old Wall St. hands know to take out their canes and hobble to the Street after the panics; then they always buy good stocks to the extent of their bank balances

 

1. Buying after panics in bonds is not such a profitable activity
2. Panics have ‘all but stopped’ in the 1990s says VN
3. VN’s panic definition is 10 percent and one month

1. “Ghosts” or dead ducks - former members of the exchange who lost all their money
   1. “They have studied every influence, every feature that had any bearing on the market, and worked them out in detail; and yet with all their determination to succeed they are now numbered among the hapless ghosts of the Street. They have passed the sixty year limit, and must eventually end their days in an East Side lodging house.” - Riggs

2. The public is trained to buy before it sells. Most people don’t even understand the mechanism of shorting.
3. VN tells this part of the story through the eyes of his grandfather, Martin and his wife, Birdie. Like many married couples, the wife is the better speculator but Martin does all the trading, and usually doesn’t listen to reason.
4. Martin liked to sell short the day after a bloodbath. This is a mistake even VN doesn’t make he says
   1. He doesn’t like to sell stocks short
   2. Brokers have contrived reasons for refusing to pay interest on the credit balances (a bit like Forex charging negative interest rates on swaps both long and short)
   3. So VN loses an interest rate, a dividend, and a risk premium when shorting
   4. Soros told him that he lost more money selling short than any other speculative activity
   5. Individual shorting of stocks is a ticket to the poorhouse

5. Everything changes - the great companies of yesterday become the dogs of today
6. VN’s first stock, a bar mitzvah gift, was the cheapest stock on the NYSE -Benguet mining
   1. While the Dow rose the stock stayed riveted to 50 cents for four years.
   2. Then a miracle - it rose to $1. On his grandfather’s advice he sells it for the $50 profit
   3. Then it promptly advances to $30 in three years.

7. Repeatedly VN has made the mistake of grabbing small profits and selling at a targeted round number
8. A number of nonrandom phenomena occur around target prices
   1. After a break up and subsequent pullback the markets ‘tend to be quite bullish’

9. “He should have known he was at the mercy of unscrupulous operators. They always sniff out the players who have gotten in over their heads and crush them like ants underfoot. Make sure they don’t do that to you.”
   1. ‘They’ are the collective Jungian unconscious of the market

10. A ‘hoodoo’ - much like a ‘ghost’ but they offer tips and try to borrow money; they are bad luck
11. There are also anti-hoodoos of which VN considers himself one. They make their partners and assistants into millionaires, directly or indirectly.
    1. Everyone copies an anti-hoodoo

12. His grandfather martin gives him the following advice, implied to be bad
    1. Stay with the old standards (blue chips)
    2. Don’t be deceptive
    3. You never go broke taking a profit
    4. Stay away from Fridays.
    5. Never buy a stock or a bond on Fri. the 13th
       1. VN tests this out and discovers actually there is a statistically significant advantage to buying bonds and stocks on Fri. 13th

13. VN recommends fading published technical analysis of academic systems
    1. He dismisses pairs trading as a fad
    2. Even a professor is shrewd enough to keep the good stuff, if any, private

Chapter 3 - Delphic Oracles and Science

1. Oracles, forecasts and prophecies are a business
   1. You should regard them with the same scepticism reserved for used car sales, or rug auctions

2. VN compares the Delphic temple to the Federal Reserve
3. VN classifies modern forecasters into several ‘species’
   1. The mystic: uses Fib levels
   2. The unappreciated, bitter, angry, lonely: permabears pointing out that some local event is very bearish while the Dow continues to make new highs
   3. The Other World Person: doesn’t read TV or newspapers; looks at parking lot occupancy
   4. The Mathematician: calculus, chaos theory, evolutionary programming; looks at obscure equations to find periodic cycles (LOL)
   5. The Traditionalist: Gann, Livermore or other historical figures; “I spoke with Colonel Roberts, the greatest living expert on Gann-Elliott and he agrees.” LOL!!
   6. The Washingtonian: worked for the government or attended a conference in Wash. once; his source says the president will resign before the end of his term (60% chance) (These days it’s a 60% chance the president won’t peaceably give up his term.)
   7. The Correlation Expert: Soybeans traditionally go into the gutter before a big bond rally
   8. Stand-Alone Artist: a maverick who can’t be bought
   9. The Insider: attributes all moves to people like Soros
   10. Among these VN identifies with the Other World Person

4. Browne’s lampoon of self-evaluations by forecasters
   1. They are always around 87% correct (can you imagine how much money you could make if you had access to 87% accuracy)
   2. January’s review doesn’t actually reproduce last year’s forecasts (space limitations)
   3. Instead there is a scorecard
   4. Some right, some wrong, some inconclusive
   5. He cites a couple of forecasts that were especially shrewd (expected)
   6. However he also cites some near-misses as ‘wrong’ and now we are won over by their honesty (LOL!) - said gold high would be 450, but it was only 406.
   7. His talent and standards tower over yours, obviously
   8. “Any man who’s wrong only 13% of the time and who’s that close when he’s wrong, must be a genius.”
   9. The truth is he’s barely 40% right, he never repeats last year’s forecasts accurately and the gold high of 406 was already in when he said the high would be 450-500. So he missed the high by 10-19% and failed to foresee that gold would spend the rest of the year heading downward.

5. Feynman one month before he died in 1988
   1. “It’s a game, and it’s not serious.”

6. A good gamester, good musician, good scientist, and good speculator often turn out to be one and the same
7. VN launches into a detailed examination of the scientific method and decides he will make his living by applying the scientific method
8. “I was fortunate to find one area for application of this method - an area that had not advanced beyond the scientific techniques of the dark ages, an area where preconceived ideas and logic rather than counting and questioning formed the basis for accumulating knowledge. I found the field of technical analysis of markets.”
9. VN notes that the techniques of bogus scientists and supernaturalists are virtually identical to those deployed by market gurus
   1. Appeal to authority
   2. Absence of counting
   3. Framing of predictions in a form that is untestable
   4. Tautological prediction guaranteed to be true under almost all circumstances
   5. No allowance for chance variations; no allowance for sampling variation
   6. Paranoia
   7. Disregard of alternative explanations
   8. Self-evaluated accuracy
   9. Retrofitted systems

10. Differences observed for many market phenomena are merely due to sampling variations resulting from the large number of samples taken and high variability within the population
    1. Superbowl indicator (chance of correlating any 5 major sports contest outcomes to a 250 point rise in the Dow is ~50%)
    2. “Enough practitioners of losing methodologies exist to ensure profits to those aware of their tactics.”
    3. Some people think the markets are not random - too many anomalies
    4. However, enter the multiple observances problem. The more inferences are made, the more likely erroneous inferences become. When you wait for clusters of something to happen you are making potentially millions of implicit comparisons. So you are very likely to find unusual coincidences. VN mentions the Bonferroni correction but doesn’t explain how it works.
    5. Attached Image (click to enlarge)

       
       
    6. People tend to underestimate how much clustering occurs in random shuffling; The bunching effect
    7. Speculators should never engage in casual gambling
    8. Odds of there being the same birthday in a room with more than 23 people = 50/50; the birthday paradox
    9. Soros and his backaches before a major move against his positions

Chapter 4 - Losses, Comebacks, Trends and the Weather

1. Perhaps the best way to achieve victory is to master all the rules for disaster and then concentrate on avoiding them
2. “Always make friends with the ref; it can’t do you any harm, and it may help in that he may not go out of his way to hurt you.”
3. VN follows this in his dealings with the commodities exchanges

How to Lose

1. Know that you are the greatest, winning is a foregone conclusion; let your opponent know that; tell your broker how much you like a particular trade and how well you’ve been trading lately
2. Insult the referee’s motives; write letters to the IRS objecting to the level of regulation imposed
3. Cut your gains when you’re ahead; never think about what could go wrong; grab small profits, refuse to take losses
4. When behind, put everything into catching up; after catching up, coast for a while and give yourself some well-deserved praise; dwell on past victories; never look at defeats trying to figure out what you did wrong; don’t learn from traders who have poor results; losses are just bad luck
5. Let the market know your intentions; leave limits and stops with the broker at round numbers
6. Don’t worry about Fed announcements or activities
7. When the market goes your way, get out immediately and think about what to do next
8. When trading, invite your significant other to come by and see you in action; if you’ve got it, flaunt it!
9. Take a break with a paramour in the middle of the trading day
10. Apply systems without paper trading
11. Attend to other business while trading; trade around positions during breaks
12. Make enough money trading each day to cover one special purchase
13. Stick to your guns if the market moves against you, gains are bound to come back when the market is wrong
14. Celebrate victory the evening before; tally your profits in a trade; don’t get less than your due; don’t even show up for trading just leave an order with your broker to exit at the close
15. Don’t worry about your fills, what’s a tick or two going to matter?
16. There are 1M others, in poker, sports, gambling or speculation, losing is easy

Lessons from VN’s losses

1. Don’t get in over your head
2. Political events are unpredictable, especially when the market is on a tear
3. Information that seems to be completely fresh is often as smelly as a dead fish (what you think is news may be widely know by insiders by the time you hear about it)
4. Never use stop losses. Invariably price moves to the level of the stop. They are tools to reduce your broker’s risk, not yours.
5. Never be flippant, especially when forces are with you
6. After a loss, victory becomes more likely (but isn’t this the gambler’s fallacy?)
   1. VN is saying that after a loss your will to win can become sharper
   2. He cites quotes from René Lacoste (tennis) and J.R. Capablanca (chess) about how losing is a learning experience, and sharpens willpower
   3. All great champions are humble; the same is true for speculators

7. The danger of hyping your performance is you might come to believe it after the fact
8. VN never heard Soros talk about a winning trade despite working for him for 10 years
9. After a loss markets generally become more bullish
   1. The average change for the worst performing commodity market in the next year is 20.2%, a good return over the usual 5%

10. The most dangerous time is when you’re ahead
11. Why fight the trend; why make it hard on yourself; Markets are reflexive, positive feedback; You’re only as good as your last trade - all from Soros

Price Action

1. Taussig found ‘penumbras’ of price oscillation - what later became known as ‘support and resistance’
2. Cootner tried to merge the penumbra with the random walk
   1. Price behaves as a random walk with "reflecting barriers"

3. VN has extensively studied the phenomena of price reversals and breakouts
   1. Studied principles of music, nature, deception, gambling, games
   2. Speculation is an art-science
   3. Price sometimes moves like a wild beast, a gentle lamb, or a playful trout

4. Buy grains after a volcanic eruption
5. Attached Image (click to enlarge)

   
   

Undergraduate thesis

1. VN’s idea which he describes as ‘naive’ is that two consecutive price rises accompanied by two consecutive volume increases = positive breakthrough; the opposite is a negative breakthrough. Price is more likely to rise on the latter.
2. He tests stock prices from 1928-1961 and believes he has disproved the random walk theory, or at least put the burden of proof on showing there is randomness
3. However the theory doesn’t hold up when testing the data from 1946-1991
4. Price moves can be predicted using the trading room as a laboratory, he says

Congestion of Prices

1. Certain members of exchanges have the exclusive license to make markets in stocks - they are called specialists (recall Sperandeo)
2. Specialists have traditionally been the most profitable denizens of Wall St.
3. Limit orders are given to specialists and this creates congestions of orders at prices that are multiples of 5 or 2 ½ and multiples of ¼ in the lower cap stocks (less than $10/share).
4. Buy market orders are executed at the price where sell limit orders are concentrated.
5. Sell market orders are executed at the price where buy limit orders are clustered.
   1. If there are buy limits at 99 ½ and sell limits at 100, the price will fluctuate between 99 ½ and 100. This creates opportunities for fast-moving professionals.
   2. Limit orders act as barriers to short-term price movement

6. Shrewd pro traders, limit order-users, market makers are all reversal creators
7. Strong underlying demand or supply cause predominance of continuations (trend)

Chapter 5 - Winning and Self-Reliance

1. VN waxes philosophical on the value of self-confidence; all you need to know is that’s good to have
2. Being around books is a good way to gain knowledge (worked for me, maybe, but my kids, I’m not so sure. If YouTube shorts are a way to gain knowledge they will be geniuses)
3. What’s good for everyone else isn’t necessarily good for us
4. Attached Image (click to enlarge)

   
   
5. This is almost word-for-word what I’d say to my kids, but sub ‘laptop’ for ‘TV’. The response is also the same.
6. VN likes to go for a walk in the woods, unfortunately that’s usually when the markets like to make a move
7. On math tests: the answer is likely to be 1, pi or e. If that doesn’t work try the perpendicular to the base.
8. It’s amazing how often simple guesses tend to be accurate (Blink - Gladwell’s ‘thin-slicing’ but 7 years earlier!)
   1. Where will a stock be at the end of the year? - most likely unchanged
   2. If a commodity has a big move at the start of the week, the best guess for the second half - the opposite
   3. NYSE daily unchanged issues - 2%, much higher than chance
   4. Close at the same price - excessively common
      1. Take advantage of this by selling at the money option straddles
      2. Sell a call and a put at the current price
      3. Make money on both sides when it expires at the same price you sold it

9. The market shares VN’s love of unchanged issues
   1. In a day 3100 issues are traded on the NYSE
   2. 725 or ¼ show no change for the day
   3. 10 days a year 15% of issues go unchanged
   4. 10 days a year when percentage of unchanged stocks is 30% or more the market is bullish over the next 12 months, going up 10 percentage points a year above norm
   5. Never sell a quiet market
   6. FX - the NY range is often == the range in Tokyo and Europe
   7. MFM Osborne vs. Oskar Morgenstern; VN says Osborne wins

It was studies like this that drew me to Niederhoffer in the first place. Something so simple to understand and easy to prove should be important - and infallible right? Alas, maybe not.

1. After a small positive change (less than 1.00) the average move the next day is close to zero
2. Same for negative changes
3. There are more large positive than negative changes which refutes the notion that declines are more violent than rises

Harvard

1. A fun chapter with little to do with markets or economics but
2. “Grade inflation, egalitarian marking, numerous pass/fail courses all have made most grade-point averages as meaningful as the lines on a stock chart.” Tells us that VN has little truck with charts or academics.
3. VN games the system as he realizes the minimum grade for an undergraduate class is a B+. So he takes only graduate classes and doesn’t study.
4. This technique allows him to come in 2nd out of 150 econ majors and it becomes known as “Neiderhoffering”
5. Years later one of his former professors says, “Here you are Neiderhoffering the commodity markets by picking up the detritus of Soros’s trades, just as you did in my classes.”
6. Similar tales like this makes it seem like Harvard was a cakewalk back in the 60s, which it probably was.
7. Rules for the market derived from rules for test-taking
   1. Go with the market at the beginning of a period
   2. Go against it near the close
   3. When in doubt stay out
   4. Spend time trading liquid markets about which you have superior insight
   5. Forget about the markets that are followed by 200 analysts

8. The urge to get even is one of the most costly habits of speculators
   1. It happens most often after a ‘disastrous move’
   2. This is why when prices manage to come back after a huge move they’re ready to go much further
   3. A speculator could ‘make a fortune quantifying this tendency’.

9. Market rises tend to take the shape of a ‘U’.
10. Declines generally have the shape of an inverted ‘V’; occurring spontaneously and quickly and offering little time to get on board.
11. However VN admits he can’t back this up with any evidence.
12. The best opportunities emerge out of the blue and are gone in an instant.
13. If you need lengthy prep just to get your orders in you can’t compete with faster competitors (or robots!)

Use your [butt]

1. Jack, the squash coach, tells VN to use his bum to mislead opponents. By moving it more than usual it makes it seem like he’s teeing up for a big swing but he ends up going the other way.
2. In the same way, the market sets up players to pick the wrong side
   1. Six days in a row, the market opens down, and closes down on the day
   2. The seventh day, it twists its bum, and goes up; players jump in to buy, thinking it will keep rising
   3. Instead it ends the day down
   4. The next time it twists its bum and opens up again, but this time it has a ‘wide’ day’ and closes limit up

Chapter 6 - The Nature of Games

1. The Sharpe Ratio - measures reward per unit of risk
2. VN says he ‘frequently’ racks up 12 consecutive winning months before ‘reaping the whirlwind of a disastrous decline’

Disaster lies in the middle

1. The bulk of risky transactions in conducted through middlemen - in trading its asset allocators and trading managers
   1. They charge 2-4 % of assets per year and relieve the customer of making the ultimate decision
   2. They choose the advisors who also charge fees
   3. After all these fees, what’s left over?

2. Humans like the comfort of a herd in choosing risky investments
3. Diversification of a fund’s holding, certification of the fund’s size, rating and past performance remove the perceived risk of investment
4. A desire to stay in the middle afflicts most speculators
   1. VN admits he’s too scared to buy something at market when it goes straight down
   2. Too frightened to sell it when it goes straight up
   3. After it has retraced part of the move, ‘he’s all too ready’
   4. He ‘compromises’ by leaving a limit order in below the market when it’s crashing but this is the worst strategy of all
      1. ‘Half the time I get filled I can count on an immediate drubbing as trend followers, and other dynamic hedgers jump in’

5. VN has a high regard for Francis Galton - the mathematician who coined ‘wisdom of crowds’
   1. He studied herding behaviour in oxen
   2. “Incapability of relying on oneself and faith in others are precisely the conditions that compel brutes to live in herds”
   3. “The vast majority of persons have a natural tendency to shrink from the responsibility of standing and acting alone. They exalt the vox populi even when they know it to be the utterance of a mob of nobodies”

6. Trading from the middle is the surest ticket to disaster
7. Faint heart never won fortune or the fair lady
8. When the central banks are out to get him, he tries to wait until someone with inside info takes profits then he ‘strikes out’ to escape his ‘pursuers’. In the evenings these are usually the BoJ, the BoE and the Bundesbank
9. “You can’t outgun them but you can make them fear you”
10. VN compares his situation to the Titanic. He relives the noble deaths of Guggenheim, et al.

Seize the Moment

1. One of his biggest ‘coups’ happens when he learns the cost of office rental space per square foot in Bombay (Mumbai) was 10x the cost of New York. Yet its stock market was valued at ½ the level, relatively speaking. He buys the Indian stock market with abandon.
2. He saves his skin while short silver during the Hunt bros. cornering of the market by buying the spot month up $1 on the day and then ‘switching’ out of his shorts by selling the spot and buying the forward.
   1. Of course, immediately after doing so, a rumour that the Hunts were selling causes a reversal; despite this he figures covering at $11/oz was the right move

Chains

1. A good speculator builds his position from a single base linked to a long, flexible chain of trades
2. If you’re short dollar; buy marks, German stocks will benefit so buy those; pressure will be put on pound and lira, sell those; and their stock; and bond markets; the suppor system might entangle (??) so sell the peso and sell Indian global depository receipts, calls on Telemex and CBOE.
   1. But if the Bundesbank thinks the dollar is overvalued? Your chain will break at its base with lethal consequences

3. The market is always mixing up the patterns; “ only the utmost attention to the principle of ever-changing cycles enables you to stay on the mixer.”
4. VN points out that ‘rogue traders’ are really just bad traders who lost their firms lots of money

1. Endowment effect - no loss is as horrible as giving back what you’ve won
   1. No victory is as satisfying as coming back from the grave
   2. When you own something you need more than the purchase price to induce you to give it back; but before you bought it you were on the fence

2. Clients were angry when VN made 150% in 15 months but lost 20% in one day
   1. But he was golden after losing 30% in one day and ending the month down only 5%

Animal Instinct

1. As in the animal kingdom, we learn from play
2. Karl Sigmund - life is like a game consisting of gambling payoffs and tradeoffs
3. Games help us come to grips with the world
4. Gamer’s goal is to reach a standard of excellence; as required by life
5. Updike - Golf is life and life is lessons.
6. In 1995 VN figured big moves in currencies were becoming more common

Chapter 7 - Essential Board Games

1. VN claims that George Soros beat Art Bisguier (a GM) in chess at least twice. (Very suspicious. Maybe with piece odds?)
2. VN claims that learning checkers before chess prevented him from mastering chess. (Um..yeah…me too!)
3. Buying and holding is great for stocks; not great for futures
4. Soros: “Victor, if I can stay close to even when the door is closed, and come in for checkmate when the door is open, I’m delighted.”
5. Marry a woman who understands your profession

Tom Wiswell’s proverbs

1. A former checkers champion who starts teaching VN private lessons at his office
2. He writes, if we can believe it, 10,000-15,000 little ‘tips’ or proverbs on playing checkers, but not specifically checkers - any game and even life.
3. You can read a bunch of them at VN’s website https://dailyspeculations.com/Letter/wiswell.htm Those are not in the order that they are presented in the book nor are they identical; in fact it seems these are entirely different!
4. Moves that disturb your position the least, disturb your opponent the most
5. The importance of little and lowly things - waiting moves, quiet moves, the correct decision between two choices
6. To be certain of your position you must begin by doubting it
   1. When you are too comfortable in a position - exit it
   2. Anything can happen

7. A string of good trades can lead to inattention to detail
8. A draw is a win for both players since they each avoided defeat
9. The clock is your enemy but can become your friend with discipline, mental agility, visualization and nerves of steel
10. You can’t have two moves but you can have second thoughts
11. Play is in a constant state of flux; moves that were thought to draw are now known to lose and moves that were thought to win are now known to draw
12. Save deep calculation for the endgame when it’s easier to see far ahead
13. The losing genie can’t easily be put back in the bottle
14. Not every day is a winning day but we may not like it.
15. Most of the masters and experts have their own grapevine and spies to keep track of the latest play and promising contenders
16. Few players reach the top alone
17. This goes on for pages, I’ve already curated this a bunch but I think you’ll have to read the book to get the whole benefit

Chapter 8 - Gambling the Vig

1. Speculation, Investing and gambling are all close cousins, says VN
   1. The main difference is that the risk in gambling is created by the casino for entertainment
   2. The risk in speculation is inherent, allowing for transference of risk, as well as price discovery, balancing what’s desired against what’s available in quantity, quality and time

2. VN’s father, Artie, warns him that gamblers die degenerate and broke. He warns him off playing money games of handball
3. His wife always asks him - why not sell half? when he’s holding a big losing position
   1. He never does because he’s afraid there will be a big rise after he sells (of course there will be - doesn’t he know about order flow?)

4. This follows a few stomach-churning cautionary tales about problem gamblers who ruined their lives
5. The house take
   1. Often no one at the table walks away a winner
   2. The house take of 2-5% a pot adds up when 40 hands are played in an hour
   3. The take is small and the house is adept at diverting the chips so that most players don’t notice
   4. Brokers in low-priced stocks, ibid.
   5. The spread in stocks can amount to 2x commissions
   6. Derivative markets will have no problem quoting spreads with an implicit house take of 25%; in contrast 0.3-0.4% is standard.
   7. There is no single price for the public in stocks
      1. The bid/ask spread of ¼ on a $10 stock on NASDAQ comes to 2.5%
      2. A turnover of 4x a year erases the 10 percent secular annual trend that favours stock markets
      3. A typical bid/ask spread in futures like silver or soybeans is ½ cent on a $5 item which is 0.1 %
      4. For bonds the spread is 0.03 percent
      5. This makes it seem like small hurdles to overcome compared to stocks but combined with commissions and bad execution it ‘quickly adds up to a staggering load’

6. Consider a coin-fliping game (every trading book needs at least one!)
   1. Heads you win $1
   2. Tails you lose $1
   3. But on every toss the broker takes out 20 cents
   4. What are the chances of ending up a winner after 200 tosses?
   5. 1 out of 10,000!
   6. 20cents per 1$ is probably an underestimate of the house vig in all but recent years
   7. Commissions were $100 to $50 not long ago
   8. Even with declining commissions the the outcome hasn’t significantly changed
   9. The high vig relative to average variation will gradually grind down the public
   10. As bad as this all is, it gets worse because leverage sometimes finishes the job that the vig starts

A typical example

1. Joe Public has $2000 to lose
2. He puts up $1000 to control a future with a face value of $50,000 fluctuating $400 per day
3. The fluctuation is 400/2000 or 20% of the bankroll
4. A very small move against Joe of 3 average daily closes in a row, or one daily move 3x that size is enough to cause a 100 percent loss of margin and 50% of the bankroll
5. Gambler’s Ruin makes it almost impossible for the average public speculator to stay in the game, even if he can overcome a 20% house take
6. The public loses to vig and leverage
   1. VN estimates leverage does the job 20% of the time, and the vig, 80% of the time

7. Attached Image (click to enlarge)

   
   
8. If the public avoided unfair bets it would be the end of gambling houses, insurance businesses and the markets
9. The fundamental problem of speculation - when to go for it based on edge and variability, considering the size of the initial stake, the odds, and when to stop

The Monte Carlo vacationer

1. A man used to go to Monte Carlo was successful each year in recovering the cost of his vacations
2. He believed he had a magic power over chance
3. Assuming he had 10x the amount of money that he wins each year
4. This gives him chances of succeeding of about 0.9 each year. (how this is calculated would be good to know)
5. The chance of an unbroken string of 10 successes is 0.37 (actually 0.3487) which is not improbable
6. One failure would simply be blamed on an oversight or momentary indisposition (how many traders think they were uncharacteristically careless when they really just had a built-in 0.1 chance of ruin in their system? Just one more reason to appreciate algo trading because it removes any doubt about what is to blame for failure.)

The Classic Gambler’s Ruin Problem

1. Applies to all speculative situations
2. Initial capital is C
3. Casino game pays $1.00 each play with probability P
4. Loses $1.00 with probability Q.
5. Q = 1-P
6. The gambler plans to stay in the game until his capital appreciates to A or depreciates to ruin at zero.
7. The speculator’s risk of ruin is:

1. Plug numbers into this formula
   1. 60 percent chance of winning
   2. 1-0.6 = 0.4 or 40% chance losing
   3. Starts with $1.00
   4. Aims for $10
   5. 66.1% chance of ruin for the session
   6. That’s also a 33.9% chance of finishing with $10
   7. 0.339 x 10 = $3.39 final bankroll but don’t forget to deduct the dollar you started with (but why? Isn’t this a $10 gain irrespective of starting capital?)
   8. 3.39 - $1.00 = $2.39 expected payoff

2. Now try changing the size of the initial bankroll

1. Math is powerful - notice that the max expected payoff tapers off with any bankroll larger than $4.00. That’s because the decreased risk of ruin is offset by the diminished benefit of winning the $10 max gain.
2. With $9 your ruination is rare, but the upside is only a $1 gain (to be fair though I would have expected the gain to be $19, not $1; but I suppose we need a different formula then - something more like Kelly’s formula?)
3. The point is clear though - the speculator wants to bet lightly enough relative to his capital to fend off gambler’s ruin, but heavily enough to make his desired rate of return
4. Unfortunately the real-life speculator doesn’t know his true odds of winning on each trade; so he can’t look up the optimum betting levels in a table/formula
5. A player with an edge should bet small, grinding out a profit
6. A player with a <50% chance of success (no edge) should bet the maximum because that’s the only way he can win and avoid ruin (but also, even better, don’t bet at all!)
   1. That’s why casinos have house limits
   2. And exchanges have position limits on what the public can hold (but they’ll say it’s for your own protection!)

7. Gambler’s ruin, house take, and leverage combine to make the chances of winning negligible
8. Price tends to move inexorably to a ‘ruin point’ within the trading day, only to bounce right back once the traders get tapped out
9. VN has trouble getting his friend to realize that it didn’t matter whether he bought or sold silver, he was sure to be a loser regardless.
10. Balancing initial capital, the size of the spec position, in relation to the size of the edge, the variability of price, is the central problematic equation of speculation
11. In poker, it’s adjusting the size of your bets to your stakes, skill and opponents
12. A small edge against on each trade leads to certain loss in the long-term (50+ trades)
13. Keeping transactions low, and reducing the house take to a minimum increases chances of survival
14. The house edge in a typical options trade ranges from 12 to 50%; even worse than the zero % chance of winning in American roulette
15. Life can be seen as a series of speculations, finding a date, job, deciding when to retire
16. The same six variables are at play
    1. Initial capital
    2. Commitment size
    3. House edge
    4. Variability of play
    5. Quitting point
    6. Duration

The road to riches is paved with bodies

1. Gamblers may have a deep-rooted psychological need to lose
2. Sometimes VN will relax his personal rule about no visitors allowed during trading hours, if a friend is leaving town early; invariably that person will ask to participate in 1% of his action for the day
3. Flashing lights/prices bring out the gambler in people
4. Some speculators are on an inexorable journey to ruin and everyone can see it (hoodoos on arrival?)
   1. VN’s story about his friend’s brother
   2. After 1987’s crash he convinced himself it was a repeat of 1929 and there would be a deluge after the rally
   3. Sells S&P futures and loses heavily on 12 consecutive trades, decimating his equity
   4. VN suggests index puts instead of shorting futures; then the only risk is premiums risk instead of infinite risk of futures
   5. He tries this and loses six more times
   6. VN suggests he take a break from trading; “the market will be there when you get back and your thinking will be clearer when you’re not involved”
   7. He rejects this advice because something big might happen while he’s away

5. The sugar trader who committed suicide
   1. He bought sugar below 5 cents and sold above 8 cents. Then one move sent sugar up to 40 cents, a 30x loss on margin.

6. Wm Worthington Fowler
   1. the losers on Wall St. regret what they might have made and didn’t, more than what they actually lost.
   2. Speculators can become obsessive - the optimum (opium?) eaters of finance
   3. Speculating is like strong brandy compared to the weak claret of an ordinary business
   4. They lose health, character, heart and life, not just money
   5. They arrive with money, credit, reputation, hope, strength, confidence, and leave without money,credit,reputation; with shattered nerves, blunted senses, seared consciences, faith in mankind destroyed, hopes crushed by despair
   6. The field has never been so dangerous (19??) with stocks watered by as much as 5x the amount represented eight years earlier (what is it now? 800x?)

7. VN points out now many stocks don’t even have earnings to water down; only debt
8. Shorting stocks is a gamble with a house take of 3% or more, and 10% a year going against, with 50% variability. No way he can end up a winner, says VN.
9. Ratings services of hedge funds that specialize in shorting periodically show their returns at something like -20% a year but this doesn’t factor in the ones that went belly up (survival bias)
10. The body’s response has great survival value
11. VN compares his championship squash game to Omar Sharif
    1. Sharif made more errors in a game than VN would make in a whole match
    2. But while VN was conservative and careful, Sharif was willing to take chances
    3. VN admits he can never be a Soros; to go for broke takes the instinct of a professional gambler;
    4. “It takes courage to be a pig” - Stanley Druckenmiller

12. All pro gamblers eventually go bankrupt because of their willingness to throw down every last chip
    1. ‘Proposition’ bets are usually pre-arranged by the proposer so beware!
    2. Johnny Moss (famous for his 5-month long game vs Nick the Greek) lost all his money at the poker table on his wedding night and staked his wife’s wedding ring in order to win the pot.

13. VN claims he lost $2000 in a game at Harvard and his dad had to drive up to bail him out, forking over the family’s life savings directly to the kids who won it
14. Poker theory has more practical value for the speculator than the study of statistical distributions with infinite variances
15. After losing $5k in a game where he has to borrow money from his wife he quits gambling (poker at least)

Lessons from Poker

1. Trade with a reserve equal to at least five times your margin
2. Don’t trade around funerals or after a fight with a spouse
3. Think about gambler’s ruin. Any one trade or series of trades can go badly astray. Make sure your stake and backers are big enough to withstand it. Before increasing volatility of returns, be sure you have the capital to handle swings.
4. The market will always be there. Wait for a good opportunity.
5. Don’t trade just for the sake of trading.
6. Trouble comes in bundles. Especially if your counterparts smell blood.
7. Go for the jugular when you have a winning position.
8. Let your broker make a decent profit for small trades. Accept quotes for small amounts even when you don’t have an edge. This will improve ‘liquidity and opaqueness for when you will need them.’ (?)
9. Downplay wins. Emphasize losses.
10. Who’s paying for the yachts? The suckers.
11. Consider reversing big up openings and buying small up openings.
12. When the market goes up in the few minutes before an announcement, be careful about selling.
13. When the market has its largest open of the last six months (for ex. Yen 150) it’s probably not a bluff and should not be reversed
14. Don’t share trading strategies with friends. Your broker doesn’t have to know how smart you are.
15. Close out positions at a loss quickly.
16. Don’t call your broker for quotes. It gives away your hand.
17. Trade aggressively when you have an edge, even if it’s small.
18. If you are in a position that you would like to be out of or that is moving against you, it is often to your advantage to double up. This trade might encourage others to come in with you and allow you to get a better price (surely not applicable to retail)
19. Don’t stay with a position unless you’re willing to stay with it longer than expected in the event of an adverse move in the near term
20. Don’t try to muscle the market before an announcement. People are already playing it ‘close to the vest’
21. Attached Image (click to enlarge)

    
    
22. When your position is going your way, don’t get out thinking you will get in later at a better level. Your cleverness will often prevent you from taking the profit.
23. When you get an unexpected bonanza, take profits at the close.
24. Don’t waste energy spending time on other pursuits during the trading day (but it’s so damn boring!)
25. During periods of extreme volatility, or prior to economic announcements, trade only if you have very strong reasons and can hold through an adverse initial move.
26. Some trades work better in liquid markets. Others when there’s only one open.
    1. When bonds are open and stocks are closed you don’t have to worry about a crash scenario

27. During calm periods, trade aggressively if you have a solid edge.
28. When the explicit news announcements are negative for your position yet it goes in your favour anyway, trade aggressively.
29. If you have an edge any individual trade doesn’t matter; trade with your edge
30. Minimum depth of thinking in markets:
    1. What is the effect of an announcement?
    2. What is the expected number?
    3. What is the anticipated reaction to above or below?
    4. Was it discounted or leaked?

31. Give yourself multiple ways to win a trade
    1. For ex. Get out if it’s up either the next 2 days or the next week

32. Let your counterparties think you’re a fish who always loses, but with incredibly deep sources of capital; that way they’ll be encouraged to reach to take your trades directly rather than marking them up and brokering them to another player (This could only work if you had for example, known connections with George Soros, surely.)
33. VN recommends a book by someone named Bacon. A racetrack bettor. Even better, his website has some extracts. https://dailyspeculations.com/Letter/cycles.html
34. “how long can one man be ahead of the pack? Be a man for all seasons?” (my research says, not very long)

Chapter 9 - Horse Racing and Market Cycles
That book by Bacon is such a favorite of VN’s that he devotes a chapter to it.

1. No one doubts that the public must lose at the racetrack in order to fund the prize money, stable care, employees and land upkeep. The 20% house take pays for expenses.
2. The same models apply to markets and racing. Who pays for the CBOT and NYSE? Not the brokers, dealers, floor traders, jockeys or the insiders and large hedge funds. The public.
3. Bookie’s (a track bookie) rules for being a successful bookie
   1. Integrity. The customer has to believe in my fairness or they won’t come back.
   2. Guts. You have to have courage to take on a big bet every now and then.
   3. Initiative. You have to give the customer something exciting all the time or else he’ll get bored.
   4. Live a good balanced life without too many personal risks.

   
   

4. Bookie becomes VN’s mentor
5. Laying off a bet - wagering on one side to win at odds, then betting on the other side at better odds, so he would be sure to make a profit regardless of which side won.
6. A Dutch book - why take risk when you don’t have to?

Elements of Handicapping

1. A horse walking listlessly to the gate is like a market after a big move. Volume’s dried up and trading is light. Buyers and sellers are saying they aren’t happy with the recent price, the same way the horse is saying “I don’t want to race.”
2. A favorite tactic was to bet on a horse ridden by a top-notch jockey that had performed miserably in a high visibility race. His thinking was that professional pride would lead to a particularly effective race next time out. (that and standard deviation)
3. Also horses that were odds-on favorites to win a previous race but got beaten; bettors would avoid the horse because of bad memories, and this would improve the odds he would receive
4. Since then, ‘betting the beaten horse’ has become such a well-known tactic with the public that it’s now one of the worst bets at the track
5. Steve Kagann - buys companies with a 50% decline and are the subject of unfavorable newspaper publicity
6. Or stocks that declined but have insider buying
7. O’Higgins -Beating the Dow
   1. Buy highest dividend yield, worst predicted earnings change or lowest current P/E ratio
   2. All such systems have above average results says VN

   
   

8. You can’t have just one system for all occasions since the form is always changing
9. VN considers Bacon’s ‘Secrets’ one of the best books he’s ever read (and he’s read a lot) and he urges us to read it. Should I?

The Take

1. A racetrack handicapper has to overcome a 20% house take just to break even; this is a good annual return for an investment fund
2. Add to that admission cost, racing programs, newspapers
3. Breakage - rounding down of the payoff to the nearest $0.10 or $0.20 (!!)
4. The odds are then stacked against them so average racegoers are big losers
5. “Copper (bet against) the public’s ideas…at all times.”
6. If the majority of the public are losers the winners must be doing something different
7. You will lose less if you bet less

The Consensus

1. Most people get their info from a public and unreliable source

Discipline

1. Most people don’t have the ‘iron ass’ to bet only on the most likekly 2-3 races
2. Bookmakers earn a premium to quote two-sided markets
3. The only advantage a price-taker has is in being selective
4. To make them earn their money the speculator must watch many prices before placing the optimal trade
5. You can beat a race, but you can’t beat the races; when an advantage arises, press it; otherwise wait patiently

Emotion and Self-Doubt

1. You won’t notice the long-term winners because they remain inconspicuous; they don’t show obvious emotion at winning or losing
2. Removing all emotion is easier said than done
3. The pro has no emotional attachment to his money
4. Bankroll is just a means of keeping score
5. VN enforces a ban on all jocularity and temper tantrums (!) in his operation
6. Irving Redel, whenever anyone including family asked him how he was doing, he said “fair”.

Beware of Switches

1. Racetracks and financial markets are uncanny at shaking out the weaker hands
2. “The average racegoer has no right to lose so much; it’s almost as though they did it on purpose.”
3. The culprit? The Switch
4. Pros bet on the winner, not the horse to place or show (2nd and 3rd); this helps them avoid the amateur’s position switches
5. The amateur bets to win but the horse comes third, then he bets for second and it comes third, etc
6. Then the amateur switches the size of their bets; they demand consistency from the horses but are utterly inconsistent themselves
7. Switch-itis is lethal; stick to a constant number of contracts
8. Stay with a systematic approach; a bad system is better than no system (and boy are there a lot of bad systems)
9. Pros avoid switches by not playing too many races. They don’t play the bad races at both ends of the daily programs. They don’t play bad races. Period.
10. It’s not the losses that do you in, it’s the switches (but also the losses)

The Principle of Ever-Changing Cycles

1. The single most important principle about speculation says VN!
2. It has been applied to fishing, baseball, fencing, elections
3. A vital, cardinal principle! (oh boy oh boy)
4. This is too important to risk transcribing or interpreting so here it is directly

1. In other words, it’s a pattern-erasing machine?
2. New information files off the edge that is held by a select few; when that information is widely disseminated it loses effectiveness
3. The example given is ‘Beyer speed figures’ for each horse which used to give a bettor a big advantage but now does barely better than a 38% loss. It has been overbet by the public so that now it has no meaning.
4. The ever-changing cycle will continue to turn though, and bettors will become disgusted with their inability to realize a profit; they’ll switch to a new popular indicator
5. This could make some old tricks new again
6. The ever-changing-cycles work over short and long-term
7. VN again uses a racetrack example;
   1. some tracks (new ones?) had a clueless betting public;
   2. The favourites were not bet down to unfavourable prices
   3. So the horsemen just grabbed ready purses
   4. The horses can keep winning as long as the public doesn’t get wise
   5. But eventually they do. However they’re behind the cycle
   6. The early winners are now tired and they’ve picked up weight penalties
   7. Cash goes to horses that were running out of the money
   8. The public goes looking for long shots and trick plays
   9. The early form horses are now rested and lost some penalty weight so they have medium odds
   10. If the favourites are bet down by smart money, second, third choices win

   
   

8. Powerful, says VN. Keep this in mind when on a winning streak says Bacon
9. Speculators in commodities notice that the trend-followers have had a great run and are sitting on cash.
   1. When too much easy money is made, speculators look to make a fast buck by imitation
   2. Dealers who study points know that a trend change will occur if certain key points are triggered
   3. They start moving prices up to those points
   4. The chances of a successful trend follow is reduced; their fills will be less favourable
   5. The public is never in sync with these cycles; just when they’re ready to follow a system it’s the wrong time
   6. The gurus who called the 1987 crash gained big followings but then couldn’t match the success of future recommendations because their following was tagging along; they can only play in liquid issues that tend to be fairly valued
   7. VN looks for the worst performing manager or fund to handle his money

   
   

Old Haunts

1. After starting a family VN rarely goes to the track but decides to revisit it to see how things have changed in the ‘cyberspace’ era
2. He compares it to Rip Van Winkle waking up in the space age.
   1. Computerized access to info
   2. Big screens/monitors
   3. Live simulcasts, etc.

   
   

3. What hasn’t changed is the contrast between the pro and the public
4. The pro records and follows anything that affects the outcome