Inside the Black Box: The Simple Truth About Quantitative Trading

After some relaxing reading, time to get serious again. As such, I choose one of the topics that remain as a myth to most traders. Well, hopefully this book can provide more insightful stuff to me...

Well, despite the facts that this book was published many years ago; it still serves as a bible or at least a starting point for those who seek to understand quantitative trading more. Having said that, this book is not the know-how or technical stuff about algorithm. This book is conceptual rather than technical. However, for those with basic quantitative trading knowledge, this book is good enough in thought-provoking and I benefited a lot via this book.

The quotes below good enough to support my point:

If a quant is good at forecasting volatility or dispersion, there are far more interesting and productive ways to utilize these forecasts (for example, in the option markets) than there are in a risk model that governs leverage. A more theoretically approach seeks to increase leverage when the strategy had better odds of winning and to decrease risk when the strategy has worse odds. The trick, of course is to know when the odds are on one's side.

Statistical risk models are subject to being "fooled" by the data into finding risk factor that will not persist for any useful amount of time into the future. It is also possible for a statistical risk model to find spurious exposures, which are just coincidences and not indicative of any real risk in the marketplace. This is a delicate problem for the researcher. 

Risk management is frequently misunderstood to be an exercise designed to reduce risk. It is really about the selection and sizing of exposures to maximize returns for a given level of risk. After all, reducing risk almost always comes at the cost of reducing return. So, risk management activities must focus on eliminating or reducing exposures to unnecessary risks but also on taking risks that are expected to offer attractive payoffs.  

Too much emphasis on the opportunity can lead to ruin by ignoring risk. Too much emphasis on risk can lead to under-performance by ignoring the opportunity. Too much emphasis on transactions costs can leas to paralysis because this will tend to cause the trader to hold positions indefinitely instead of taking the cost of refreshing the portfolio. 

The instability of correlations among financial instruments is more or less a fact of the world. It is not the fault of optimizers, nor of correlation as a statistic, that this happens to be the case in the financial industry. 

Near-neighboring sets of parameters should result in fairly similar results, and if they don't researcher should be a bit suspicious about them, because such results may indicate overfitting. 

Models that are parsimonious utilize as few assumptions and as much simplicity as possible in attempting to explain the future. As such, models with large numbers of parameters or trading signals are generally to be viewed with skepticism, especially given the risks of overfitting.

We find that the statement that quants underestimates risk is likely to be true, but we also find this to be due more to human nature and the circumstances are rare events than to something specific in quant trading.

Longer horizon quant strategies tend to go though longer and streakier performance cycles. They can outperform or under-perform for several quarters on end, and it can take several years to evaluate whether there is really a problem with the manager. Some longer term strategies also demonstrated conclusively that they are subject to crowding risk. Short-term strategies, by contrast, tend to be very consistent performers, but they cannot handle much capital. They are therefore very desirable but also not always practical. Furthermore, when one find a good short-term trader, it is not clear that the trader will remain small. Many traders are tempted to grow their assets.   

For a rating of 10, I am going to rate this book at 9. Despite the excellent part, this book is a bit out dated with current algorithm environment. Algorithm evolved a lot these days and the evolve part would not stop in the future. As such, I am very much looking forward for the new version of this book. (Better still if the author decided to write a new book about quantitative trading) Overall, this is an excellent book and I highly recommend traders to explore it. 

Risk-Return Analysis: The Theory and Practice of Rational Investing

This may be a topic that I hate most as I read too much this sort of books in the past. However, as a refreshment purpose, I decided to give it a try.

Ended up, it is still not my cup of tea. First of all, this is definitely not a book for math-phobic like me. The tons of mathematical stuff really drives me crazy at times, LOL. Furthermore, although the author did his best in writing this book, I think many of the items discussed are just some repetition in other books that I read. Overall, after squeezing my brain hard, I found I gained not much at the end.

This is actually the first of four volumes on the subject of risk return analysis. As such, after finish this whole book... although it is not thick, I do not think I will explore further on the other three volumes. As mentioned above, the mathematical stuff really scared me off in the first place. So, I do not think I have the determination to dig further into such a "college textbook", LOL.

Rating wise, I am going to rate this book at 1/10 based on my personal preferences. In fact, I may not be the right person to judge this book due to my poor mathematical skill. This book may turn out to be a real jewel for some readers. But, I am the exception... 

Trading Systems and Methods, + Website

In the first place... surprisingly that I missed this book even though I had read more than 1000 trading books for the past 20 years.

This book really caught my mind when I flip over the few pages. The author did so well to provide readers (traders) with some precise, illustrative and great ideas. Furthermore, all thoughts are fully backed up by research and references. In short, I would say this is a real encyclopaedia reference for trading systems.

In fact, this book brought back a lot of my memories in exploring mechanical trading systems for the past 20 years. I was brought up with mechanical thinking even though I studied sciences throughout my learning time. But, my background and my humbleness lead me to believe that I am not smart enough to be the trading master. As such, I humbly believe that mechanical system with rigid rules suits my character. Hence, the more I read this book, the more it goes back to my memories of back testing. Those days, we are not so fortunate to fully equipped with great computer stuff like what algorithm players do these days. But, this book itself tells the whole story. There is simply no hundred percent robust systems. It is about money management and the volatility calculation to equalize risk that enable thousands of traders to survive in long run.

One small flaw though... In my humble opinion, this book is too complicated to beginners. This is more a book for those who understand certain levels of trading systems. In fact, it is a good refresher for someone like me. I admit that most systems discussed were fully tested by me in the past. However, to revise it... certainly sparks more new ideas for me and it helps to further improve my current systems.

With the small flaw, I am going to rate this book at 9/10. The author did a fantastic book and this book is a must have for all traders. 

Trading Systems: A New Approach to System Development and Portfolio Optimisation

Another investment stuff... well, World cup month... in order to force myself to be more productive, I purposely choose only topic that I am really keen. As such, I ended up reading only investment stuff during this "hectic" month, LOL.

Wow, this is a simple yet full of details book on system development. Before I continue, allow me to rate this book at 10/10. I think all traders need to have this book. Despite its simplicity, all necessary ingredients are presented. As such, it is a must read for beginners and it will be a good reference and refreshment for others too.

This is not a book showing exciting buy and sells signals. The whole concepts discussed are not direct. However, it provides proper guidelines and details explanation in a systematic manner. Having said that, please do not expect direct formulas and systems to make you rich in a quick manner. After all, system development is more than just buying and selling rules. This book at least helps traders to build up basic concept for further assessment into better stuff in long run. In short, grab a copy of this book and it certainly deserved a place in our book shelf.

Last but not least, listed below are some of the quotes that really "refreshed" me after more than 15 years in this industry. Great job by the authors!!!

If you make a bad trade, you have money management, you have a whole bunch of things that will come to your aid, and you're really not in so much trouble if you make a bad trade. But, if you miss a good trade there's really nowhere to turn. If you miss good trades with any regularity you're finished, you're doomed in this game. ~~~ Bill Eckhardt

The wider the sample size and the lower the number of variables, the better the estimation ~~~ Calculation of the degrees of freedom= whole date sample - rules and regulations - data consumed by rules and conditions.

The dangerous point for Monte Carlos analysis ~~~ you take a trades from the trading logic as you get them from your back-tests. But, what if this trading logic is only curved fitted and over optimized? The Monte Carlos cannot see this...

My concern is that people are using Monte Carlos as a certainty test. It isn't. It's a probability test.

Given enough complexity, it is always possible to fashion a rule that buys at every market low point and and sells at every market high point. This is a bad idea. Perfect timing on past data can only be the result of a rule that is contaminated with noise. In other words, perfect signals or anything approaching them almost certainly means the rule is, to a disturbing degree, a description of past random behavior (i.e. over-fitted). 

If your trading system is simple enough but has a sound logic with valid rules, it is able to capture some parts of the recurrent predictable patterns but does not adjust itself to the market noise. 

It is often better to use just one or two indicators, or only the price itself... Adding more and more rules will just increase the adaption of your trading system to past market data, but it will not increase its predictive power for real trading. 

Be careful with short data samples regardless of timeframe or trading frequency. If your optimisation windows is short, it is more likely you will miss important data outside of the window. 

If you think that systematic trading is a job for life, please do not overrate the importance of programming skill.  

The more complex the system the more easily it will be over-optimised with too many variables or inputs. If you are not a sophisticated programmer this could be good luck because you will never run the risk of writing codes that are too lengthy. 

Portfolio Optimization and Performance Analysis

This could be a very boring book thanks to the complex formulas throughout the book… At the end… yes, it is. It is a real boring book… Tons of formulas and tons of concepts that I might not need it in the first place, LOL…

In fact, I was forced to read on this book by a friend (Ok, potential customer, LOL). I was asked to refer to this book on how to present my trading ideas in a proper way. Gosh… I am backed to academic for a wrong reason. Hey; I thought my end results more important??? Well, people love to have this type of so called “proper” presentation. In real world, how much proper stuff ended up in profitable manners? Hmm...Food for thoughts today…

Having said that… I found myself lost when I am trying to rate this book. This could be a very good book or very bad book depends on a reader’s intention in exploring this book. As mentioned above, I was forced to read this book in the first place. As such, I could not find anything great inside this book. So, allow me to skip in rating this book. I think I am not the appropriate person to judge it. The only thing I know about this book is… this is a real boring book!!! LOL… 

Fixed Odds Sports Betting

A betting book... A kind of book that I usually would avoid… After all, I am already in the biggest casino (and a worldwide casino too) that runs almost 24 hours each day. As such, I do not think I need to understand and explore further into more gambling stuff. But, this book is slightly different. It is a book about sports betting. To be precise, it is a book about football (my favorite) betting. As such, it attracted me at first glance…

End up; well, another disappointing book. There is not a lot of information on finding the edge in football betting. This book deals with various staking plans and show how each one performs over the long term. On its own, I believe it would not make you a successful gambler. So, for those looking high and low for the edge in football betting (including myself), this book is a real disappointment. Perhaps… the fact is: “Overround” imposed by each bookmaker did enough to diminish all the possible probabilities that contributed to certain edge. As such, there are simply zero chances in gaining the best possible edge!

Rating wise, I am so disappointed that I am only giving 2/10 for this book. The overall information given in the book is sufficient to understand the fixed odds of sports betting. However, since my intention is more on the above-mentioned, this book does not serve its purpose. As usual, this book was shifted out immediately after I finish the whole book. Ding, ding, ding… next, LOL!

The Poker Face Of Wall Street

I love Aaron Brown's "Red Blooded Risk" so much... In fact, this is why I am back to one of his old book ~~  "The Poker Face of Wall Street"...

First of all, I must admit… I understand finance, but I have no prior knowledge of poker. As such, I began this book by downloading a poker game to play through and get familiar with it. So, when I thought I had gained enough knowledge (at least some basic rules) on poker, I moved on to this book. End up… confusions follows by confusions was the whole experiences in exploring this book.

Ok… I admit I am with the author when he said that market investing is as good as poker gambling. Examples of risk denials (fantastic examples too) were given in the book to validate the said opinion… But, I thought the author pointed out a lot of theories without supporting evidences. (Perhaps it was due to my ignorance?) At the end, this book although entertaining; but I get frustrated most of the time as it seems not easy to understand the highly technical arguments.

Rating wise… I could not hide my disappointment... and as such, I am rating it at 4/10. “Red Blooded Risk” is so fantastic and maybe that is the reason why I have a lot of expectations in this book. Overall, I would say the author started an interesting topic. However, I just do not know how to digest it. Final word: It deserved some attention (I really believe so…); but, it also needs some brilliant brain to unlock the gems inside this book… 

Red Blooded Risk (The Secret History of Wall Street)

"Applied probability" is something I love to dig always... In fact, books like "The Black Swan" and "The Signal and The Noise" remain my all time favourite. Now, we got this book from Aaron Brown... another "applied probability" stuff with a very special name: "Red-Blooded Risk" taker... Hmm... Something interesting....

Aaron Brown started by define the differences between risk and danger(opportunity)... "Risks are two sided, you can win or you can lose. Dangers and opportunities are one sided...Dangers and opportunities are often not measurable. Risk however are measurable... Dangers and opportunities often come from nature. Risks always refer to human interactions and their level must be under our control..." From there, the author managed to classify 4 different groups of risk takers:
1. Coward - Treats risks as dangers.
2. Thrill seeker - Treats risks as opportunities.
3. Cold-blooded - Treats both dangers and opportunities as risks.
4. Red-blooded - Excited by challenges, but not to the point of being blinded to dangers and opportunities.

Overall, this book presents plenty of ideas on how to be a practical risk-taker. In fact, it is more than investing and financial stuff. To me, it is more like a guide towards risks in life. The whole book combines the real experiences from the author along with the historical episodes that happened in real life. After all, the author is famous as Quant's Quant. Hence, he is absolutely the right person to comment on it.

The best part is... this book contains series of "secret history of Wall Street" along with the diminishing function of money. (Paper money will fade to insignificant economic importance, to be replaced by derivative-like arrangements.) In fact, this is the first book that defended speculators, derivatives and the financial market as a whole. Read this:

Everyone is greedy and finance would be a strange career choice for someone without and above average interest in money. The sin is to be interested only in money.

Finance is just another business, or to be evaluated by how much it improves things for customers, what resources it consumes and the quality of jobs and quantity of profits it creates. It has no mystical value like "making the economy more efficient" and a person who makes that his justification for a huge paycheck is likely looking for an excuse, not a reason. 

Value investor provide liquidity because they buy when others sell and sell when others buy. They are the one kind of speculator polite people like to talk about. They give the markets rationality and liquidity.

Momentum investors give the market volatility. They are behind bubbles and crashes, and they suck liquidity out of the market. But, without them you have no market, or at best a quiet market that adds little economy value.

One silly thing you read about futures markets is that they are zero-sum. But, a bank is also zero-sum. Every dollar in interest paid to depositors is paid by borrowers. Yet banks add tremendously to economic growth. Money itself is zero-sum. It represents an asset to its owner and an equal liability to everyone else. In the case of futures markets, and derivatives in general, since each user has a different numeraire, each one can count a net profit in economic value. Insisting the markets are zero-sum is a symptom of not understanding numeraires.

An even sillier charge is that futures markets are a casino where speculators create risk that spills over and harms the real economy. Of course they are casinos where speculators create risk. If speculators went away or stopped creating risk, the markets would collapse, and they would take their vast economic value with them.

Relatively, compares to the other applied probability stuff (ex. The Black Swan), I thought this book is a more entertaining read. However, I cannot deny on its prolixity and disorganised structure on his articles. In fact, some chapter titles tend to be misleading as the contents may not focus 100% on the title itself. Perhaps, this is due to the author's style of tracing to the origin of the origin. End up, readers might felt a bit of mess and find it hard to concentrate.

As a summary, this is one of another great work on applied probability. If "The Black Swan" and "The Signal & The Noise" deserved 9/10, this book at least scored evenly at 9/10 too. Like I mentioned above, it is the prolixity that bring certain damages to a supposed great book. Other than that, I thought this is a book that benefited me so much. Thumbs up for the author to come up with such a nice writing!

Finally, I picked up some of the nice quotes that I personally love it so much. Well; again, perhaps more prolixity than ever; but catch the point, as it represents some splendid wisdom....

A frequentist might test hypotheses at the 5 percent level... What if the 95 percent she's right about are trivial things we knew anyway and the 5 percent she's wrong about are crucial?

If you take an optimal amount of risk- not more and not less- you can be certain of exponentially growing success... Taking less risk than is optimal is not safer; it just locks in a worse outcome... Taking more risk than is optimal often leads to complete disaster. ~~~ John Kelly

The forms of money that stimulate the economy are those that equate constraints and goals of important risk-taking activities. At the moment, financial derivatives are the most important form of money used in advanced economies.

Mutation is almost always bad for the individual, but the optimal amount is good for the population.

To take advantage of evolution you need to add some randomness to your learning and experiences. ... The more you read, the less certainty you find. The people with the most narrow and rigid views have generally read the least.

You cannot understand the economy without understanding the markets, and you cannot understand the markets without trying to beat them. 

Kelly showed that beyond a certain point, more risk only increases the probability of bad outcomes. Moreover, taking less than optimal risk actually guarantees doing worse in the long run; it only appears to be a safer course.

The reason the portfolio of all seven commodities did so much better than the individual assets when we invested 100 percent of our money is not that diversification lowers risk and lower risk is good; it's that it just happened to produce a portfolio with near the optimal amount of risk.

More and more transactions are mediated by direct good exchange, automated clearing by Internet bidding or matching, and goods delivered by status rather than equal value by transaction... Paper money will not disappear or lose its value, any more than gold lost its value when paper money arrived. But, paper money already lost its place as an economic driver.

You could fight a war for any stupid reason you liked (in fact, in most wars one or both sides claimed to be fighting for peace), except one: you couldn't fight a war against taxes.

Socially, you can be a loner. You're not interested in other people's opinions, since those are what made the market inefficient in the first place.

If you cut losers faster and let profits run longer, you'll have a lower accuracy ratio but a higher performance ratio. Attempting to increase the accuracy ratio by sacrificing performance ratio seldom works. Therefore, the usual advice is to target a specific performance ratio, adjusting your trading if necessary to get to that target, but only to monitor the accuracy ratio. When accuracy ratio is high, bet bigger, when it's low, bet smaller.

Organisations depend on complex information flows. Unless there is constant, rigorous testing of that information, its quality will be very poor. That lack of quality will be obscured by...the poor quality of the data. The poor quality will be further obscured by systems and people that force the data to be consistent.

Bad data leads to inefficiency and uncontrollable risks. Even if it didn't, given the vast sums spent on processing data, it's worth spending a little effort to make it good.

They say if you work in kitchen you'll never eat at a restaurant. Well, I never worked in a restaurant kitchen, but I'll never believe a number unless it's something I can validate.

Success requires innovation, and innovation implies frequent failure. Failure isn't the problem. Slow and expensive failure is. Fail often, fail fast, and fail cheap is the formula for success.

The Signal and the Noise: Why So Many Predictions Fail — but Some Don't

This is a similar book to the Swan... The author Nate Silver is well-known in predicting and forecasting. If the swan talks  about how important it is to accept the unpredictable extraordinary stuff, Nate Silver will present to us tons of noises and "unknown unknown" that can hurt us in long run. As mentioned by the author: "If our appreciation of uncertainty improves, our predictions can get better too."

My first glance on chapters presented in this book did enough to attract me in the first place. Chapter one is about the catastrophic failure of prediction. Here we are presented with the idea of rating agencies who helped in repackaging the CDOs. As mentioned in the book, it is not about stupidity. End up, these peoples simply do not want the music to stop. One of the very nice quotes in this chapter is: The major difference between a thing that might go wrong and a thing that cannot possibly go wrong is that when a thing that cannot possibly go wrong goes wrong it usually turns out to be impossible to get at or repair. How true... especially when we are dealing with something "out of sample" ...

Chapter two kick off with a very good question: Are you smarter than a television pundit? The author is well-known for his projections in political affair. As such, this chapter capitalize on the author's strength. Chapter 3 is my favorite chapter. It is about winning and losing via baseball game. Those who love "Moneyball" (I love it so much!)will surely love this chapter... One surprise discovery is that the author did consult a Malaysia company while serving for KPMG. Hmm.. the world is really flat! LOL...

Chapter 4 is about weather forecasting and chapter 5 is about earthquake forecasting. Honestly, the said two chapters really blew me away. Ok, I admit that I have zero knowledge in both industries. As such, the evolution of both industries is like an amazing journey to me. After all, both industries are full of numerous uncertainties. Hence, professionals in these industries need to convert such uncertainties into risks. In another words, they are changing something immeasurable into something measurable; even though the measurable does not imply all time accuracy. The best part is... both industries although similar in certain way, the final outcome is very contradict.

By going through weather and earthquake, the author finally turned his attention to economic forecasting in chapter 6. Ok, we all know how bad an economic indicator can be. Well, noises basically do not run far regardless of weather, earthquake or economics. It is the same old stories except it happens ineffectively in a supposed effective capitalism system.

Similar cases happen in chapter 7 when the author presented tons of role models that suppposed to help us in forecasting. Yet, the said models fail once again when noises are obviously much more than the actual facts.  In fact, "noises" in the universe are mostly covered from Chapter 1- 7. All 7 chapters provide tons of approximations where some served us well and some failed us completely. Chapter 8 and the remaining chapters deal with methodoloy on how to filter noises and make them better. At least, a little bit at a time, LOL.

Chapter 8 started with an amazing story by Bob Voulgaris where he utilizes facts and try to distant himself from noises. At the end, his forecasting is so much successful. This is follow by the Bayesian Reasoning model (What a model in applied Statistic!!!) and the amazing human brains that defeated programmed chess players (computer). In chapter 10, we have poker games, one of the most important stuff in forecasting. Chapter 11 is another favorite of mine where chartists are being question once again, LOL. The last two chapters focus on the climate of health and the famous terrorist attack.

Finally.... it comes to the end and I must admit that it is very tough to finish a book with more than 500 pages. Fortunately, this is a book with topics that I like. Otherwise, it is very hard to digest some of the "unknown unknown" stuff, LOL. Overall, this is an excellent book to explore especially when we are presented with millions and zillions of noises, thanks to the advancement in information technology these days. However, I think it will be much better if the thickness can be reduce, LOL. Having said that, I am rating this book at 9/10. After some pollution in the last read, thank god that Nate Silver did not disappoint me at all. Thumbs up!

Lastly, listed below are quotes that I personally like it so much:

1. In statistics, the name given to the act of mistaking noise for a signal is overfitting.

2. You are most likely to overfit a model when the data is limited and noisy and when your understanding of the fundamental relationships is poor.

3. Successful gamblers - and successful forecasters of any kind - do not think of the future in terms of no-lose bets, unimpeachable theories, and infinitely precise measurements.

4. This is why our predictions may be more prone to failure in the era of Big Data. Most of the data is just noise, as most of the universe is filled with empty space.

5. Purely statistical approaches toward forecasting are ineffective at best when there is not a sufficient sample of data to work with.

6. If you do detect a pattern, particularly an obvious-seeming one, the odds are that other investors will have found it as well, and the signal will begin to cancel out or even reverse itself.

7. The answer as to why bubbles form, is that it's in everybody's interest to keep markets going up!

8. The winner's curse ~~~ Although of some of the students's bids are too low and some are about right, it's the student who most overestimates the value, who is obligated to pay for them. The worst forecaster takes the "prize".

9. He went to Harvard and has been doing it for 25 years. How can he not be smart enough to beat the market? The answer is: Because there are nine million of him and they all have the same computers that are collocated in the NYSE.

10. Bayes's theorem holds that we will converge toward the better approach. Bayes's theorem predicts that the Bayesians will win.

11. Amateur players, when presented with a chess problem, often frustrated themselves by looking for the perfect move, rendering themselves incapable of making any move at all.

12. Chess masters, by contrast are looking for a "good" move - and certainly if at all possible the best move in a given position -  but they are more forecasting how the move might favorably dispose their position than trying to enumerate every possibility.

13. In economic forecasting, the data is very poor and the theory is weak. Hence, the more complex you make the model the worse the forecast gets.

14. The more complex you make the model the worse the forecast gets is equivalent to saying "Never add too much salt to the recipe."

15. The more often you are willing to test your ideas, the sooner you can begin to avoid these problems and learn from your mistakes.

My Life As A Quant

This is a special biography... a biography between the field of physics and finance. In fact, it is a book that divided equally between physics and finance since the author began his career as a physicist and came to finance relatively late in his life... As mentioned by the author: "Character and chance counted at least as much as talent. Luck, combined with the capacity to persevere played an overwhelmed role." How true for a person who transformed himself from a theoretical physicist to becomes an employee of Goldman Sacs and Salomon Brothers in his late careers..

To be honest, I do not really enjoy this book for few reasons. First of all, I have to admit that I am not familiar with physics stuff. As such, it is torturing to read through the first part of the author's memoir. Basically, the first part is mostly about the life of a physicist. There is zero finance related issue. Secondly, I am rather disappointed with the brief explanation in quantitative finance. Perhaps, my expectations were too high. I thought the author will reveal tons of quantitative finance stuff. In fact, the subtitle "Reflections on physics and finance" really confuse me in the first place. If I treat this book purely as "My Life As A Quant", then perhaps my expectations could be lower. End of the day, I think the title itself is kind of misleading too.. After all, the author becomes a quant in his late career. As such, I do not see this as a perfect memoir for a quant. In fact, it is more on the transformation rather than a real quant's adventures.

To be frank, just before the second part coming in, I almost gave up this book umpteen times. Fortunately, my perseverance helps to move myself into the second part. Yes, that is the moment when the author decided to venture into the world of investment. Ok, the second part is more entertaining. At least, I fully understand what he wanted to express, LOL. In fact, the second half of the biography is all about the blending of physics and finance. Of course, the amazing stories were full of human emotions too.

Finally, I am not discounting the author's contribution to readers around the world. From this book, readers can peep in the inner workings of a major investment bank. The quant although did not appear in the whole book, but readers can see through the process on how a quant plays his role in new products as well as investment strategies. However, I cannot deny the facts that I hate reading something that I do not understand. In fact, I do not think I will purchase any physic books for the rest of my life, LOL. Having said that, I really find it hard to rate this book highly... Ok.. since I hate first half of the book while I kind of enjoying the second half, I am going to rate this book at half of 10. Fair enough, right? LOL... 

Nerds On Wall Street

I love IT stuff and of course... I love investment stuff too. Since "Algo" is the combination of what I love... this book attracted me so much at first glance...

As mentioned on the cover, it is all about Math, machines and wires markets... I think for those who are keen on the said subject, this book serves as a very good introduction on how maths and machines become part and parcel of wired market these days. However, for those who are not really keen; they might find it boring. I thought the writing is quite rigid(stiff?LOL) for certain chapter. After all, the author needs to explain the chronology in wired markets from day one. Besides, this book is actually a collection of articles written for technology magazines from the mid-80s to the mid-90s. As such, there are certain items which we may not know since those were the days where computer was still an expensive luxury stuff.

Then, we have some irrelevant stuff in the final few chapters. (In my humble opinions...) Even the author mentioned that he did not planned for that in the first place. Well, it was the sub-prime stuff. But, I honestly do not see any correlation with our topic here. Perhaps a little bit, but not necessary at all. End of the day, the author's view in regards to the said issue seems misleading too...

Ok, some bad stuff... What about the good stuff? Well... to be honest, a lot! In my humble opinion, this is a book that was arranged neatly in a way that tells the whole stories thoroughly. (Bear in mind that this is a collection of articles) End of the day; like I said above, it is a good start for those who are keen on Algo. In fact, I thought it is good refreshment for those who are familiar with Algo stuff. Hence, overall, despite some weaknesses, it is one of the very best investment book(articles?) in the market.

I personally love chapter 6 on the topic of "Stupid Data Miner Tricks". It serves as a good reminder for those who thought they can be a good miner. A few phrases are good enough to prove my point. "Whatever raw materials you choose, fooling yourself remains an occupational hazard in quantitative investing. The market has only one past, and constantly revisiting it until you find that magic formula for untold wealth will eventually produce something that looks great, in the past." Further to this... "When doing data mining, it is important to be very careful of what you ask for, because you will get it." Then, it is followed by "A computer lets you make more mistakes faster than any invention in human history- with the possible exceptions of handguns and tequila." Finally, we got this very nice quote: "The easy access to data and tools to mine it gives new meaning to the admonition about lies, damn lies and statistics. The old adage caveat emptor, buyer beware, is still excellent advice. If it seems too good to be true, it is."

It was then followed by a very details description on manipulating via Chapter 11. Check out list of messages as below (a remarkable stuff published in year 2000 by someone named Tel212):
Message boards guidelines, used by shorters that short sell stocks:
1. Be anonymous, of course.
2. Use 10% fact and 90% suggestion... Facts give credibility, while suggestion does the "sell".
3. Let others "help" you learn about the stock thereby developing rapport and support base.
4. Use multiple handles, but develop a unique style for each.
5. Use multiple ISPs.
6. Start each new handle slowly to build acceptance.
7. Occasionally, use two handles to "discuss" an issue.
8. Do not show all your cards at once when slamming a stock. It's a war- it's ok to lose a battle as long as you save enough ammo to win a war.
9. Know your enemies - they will end up being your best weapons.
10. Only slam until the tide starts to turn. Let doubt carry the stock back with the tide.
11. Maintain an appearance of being open minded but slant in either direction is acceptable.
12. Don't appear meek. No one follows the meek.
13. Strike just as your opponent starts to gather momentum but not before or you lose your sting.
14. Don't worry if people beg you for a slammer. The doubt will remain and that's what you are after.
15. If pegged, put up a brief fight, then let them feel they've won. This puts their guard down within a few days and your other handles can take over from there.
16. When slamming a stock, the intent is to minimize its rise, not to create an instant plunge.
17. To slam a stock requires you only to kill the dream not the company.
18. Use questions to invoke critical thinking and use statements to reinforce. 
19. You can be liberal in your questions but be specific and precise in your statements.
20. Don't lie, but bend the truth.
21. When slamming, encourage research beyond calling the company. You know people are far too lazy and it's only doubt you are after, not confirmation.
22. When slamming, discourage people from taking the company's word- encourage them to seek outside proof. If the company's history is bad, point them there.
23. When slamming, refer to missed deadlines and weak financials.
24. When slamming, if the price rises, blame it on a temporary mass reaction to a press release rather than real interest in the stock. Point out low volume and emphasize the selling.
25. Pretend to share the same concerns by learning what they want to hear.
26. And above all else, be unpredictable.
Such "pump and dump" strategies sound frightening... The only thing I can comment: the author (the anonymous?) seems revealing too much through this "frightening" posting! LOL.

Final thoughts... Out of 10, I am going to rate it at 7. Overall, this is a very good book to explore. Although there are some weaknesses from my very own perspective, it is confirmed not a polluted stuff, LOL.

Despite some nice quotes above, I preserve few as below to serve as a soft reminder to myself. Enjoy it...

A computer does not substitute for judgement any more than a pencil substitutes for literacy. But writing without a pencil is no particular advantage. 

Life would be so much easier if we only had the source code. - Hacker Proverb

To err is human. To really screw up, you need a computer.

If you give someone a program, you will frustrate them for a day; if you teach them how to program, you will frustrate them for a lifetime.

Be careful what you ask for - you might get it.

In the real world, potential alpha is reduced, and sometimes eliminated by transaction costs. Trading is the implementation of investment ideas, and poor implementation can negate the potential value of any idea.

The Black Swan

I have this habit... whenever I feel I had been polluted by tons of investment books, I know I need to reread two books... namely, "Fooled By Randomness" or "The Black Swan". This time around, I choose to go for the extraordinary swan. Reason? Well; I always thought Nassim Nicholas Taleb produced a better book in "Fooled By Randomness". To me, both books are equally good. However, relatively... I still think the first book beats easily the second book. As such, I am always looking forward to challenge my very own "black swan", LOL. Furthermore, I think I had enough with his first book. Meanwhile, this is only my second read on the swan.

So, after another round of scratching head on the swan; do I still insist that first book is better? Honestly... YES, LOL! Ok, the swan was still too prolixity to me. End of the day, I still think there are a better way to express the swan. After all, I think some readers may not want to dig that further into the swan... especially when "Fooled By Randomness" had showed its randomness with simple yet understandably wordings...

Well, please do not get me wrong... I actually love this book. After a second read, I still think this book deserved a rating of 9/10. The only point being deducted was due to its complexity (which I think can be avoided) when compares with the first book. Every reread on this book serves as a good reminder as well as some refreshment to my career. After all, I deal with black swan now and then...

Here we are with some of the quotes that I found useful... Obviously, there is a lot of differences compares to last read. Maybe I had improved... or maybe, I had accepted that I am actually one of the extraordinary black swans too... LOL.

"One death is a tragedy, a million is a statistic." Statistic stay silent in us.

Readers would not pay $26.95 for a story of failure, even if you convinced them that it had more useful tricks than a story of success.

It is why we do not see Black Swan: We worry about those that had happened, not those that may happen but did not.

The more detailed knowledge one gets of empirical reality the more one will see the noise and mistake it for actual information... listening to the news on radio every hour is far worse than reading a weekly magazine, because the longer interval allows information to be filtered a bit.

These "experts" were lopsided: on the occasions when they were right, they attributed it to their own depth of understanding and expertise; when wrong, it was either the situation that was to blame, since it was unusual, or, worse, they did not recognize that they were wrong. 

We attribute our successes to our skills, and our failures to our external events outside our control, namely to randomness... this causes us to think that we are better than others at whatever we do for a living.

Perhaps the wise one is the one who knows that he cannot see things far away.

So, why on earth do we plan? Some people do it for monetary gains, others because it's their job. But, we also do it without such intentions - spontaneously.

We have a natural tendency to listen to the expert, even in fields where there may be no experts.

We are made to follow leaders who can gather peoples together because the advantages of being in a group trump the disadvantages of being alone. It has been more profitable for us to bind together in the wrong direction than to be alone in the right one. 

We grossly overestimate the length of the effect of misfortune on our lives... More likely, you will adapt to anything, as you probably did after past misfortunes. 

Our problem is not just that we do not know the future, we do not know much of the past either.

Avoid the big subjects that may hurt your future: be fooled in small matters, not in the large. Do not listen to economic forecasters or to predictors in social science (they are mere entertainers), but do make your own forecast for the picnic.

American culture encourages the process of failure... America's specialty is to take these small risks for the rest of the world. Once established, an idea is later "perfected" over there.

People are often ashamed of losses, so they engage in strategies that produce very little volatility but contain the risk of large loss... People hate volatility, thus engage in strategies exposed to blowups.

If you know that you are vulnerable to predictions errors because of the black swan, then your strategy is to be as hyper-conservative and hyper-aggressive as you can be instead of being mildly aggressive or conservative. 

If venture capital firms are profitable, it is not because of the stories they have in their heads, but because they are exposed to unplanned rare events.

You have high risk on one side and no risk on the other... the average will be medium risk but constitutes a positive exposure to the black swan. 

Invest in preparedness, not in prediction.

Trading may have princess, but nobody stays as a king.

The people you meet on the way up, you will meet again on the way down.

We are quick to forget that just being alive is an extraordinary piece of good luck... So, stop sweating the small stuff... Remember that you are a Black Swan.