There are those who want to know why and there are those who want the biggest piece of the pie. As far as fundamentals, by the time you get information, those like Buffet and Clintons have had it a week and are well positioned but if you ever get information before them, you will end up going to jail as "they" don't want anyone else in their club. Plays in techie better than most except for Drug companies going nuts as they released a new Happy drug that will be taken off the market 3 years later and it tanks cause it grows hair on women's boobs like you need chainsaw to take off, but then drug co says Hey we can grow hair on a cue ball so stock goes back up till taken off the market again cause it grows hair on your feet and you start grunting and look like Sasquatch. They then take hair sample to a techy firm which goes through the roof. Ya just got to know on the chart where the weak hands are going to be screwed over and when the most mental pain will happen, you feed them stocks or futures for them to get out while you are only now getting it.
For fundamentals, read "One Up On Wall Street" by Peter Lynch. Legendary manager of the Fidelity Magellan mutual fund. Its 30 years old, and still applies. Any second hand bookstore will have one for a few bucks. It was a huge best-seller. Easy, entertaining read. http://www.simonandschuster.com/books/One-Up-On-Wall-Street/Peter-Lynch/9780743200400 I bought CMG out of the gate because of this book in the $40's. Unlike Lynch though... I took a quick profit in the $60's. Dumb. Good book, worth the trip to the second hand bookstore.
I have one because I started from Fx. But not everyone needs to have an opinion. And those with opinions aren't better off than those w/o. As Handle said ... There's no need of knowing it all for being a trader. Usually you know something because it's a potential solution for a problem. What's your problems ? You're into programing. Must make sense for you. You want real solutions to real problem. You don't want education. Who do you want to impress ? Your ego ? Friends ? Or PnL ? Your PnL doesn't care about your useless know it all. It's specific things that solve specific problems.
Do you want to be a trader, or an investor? Big difference. My best trading systems over the years have had absolutely nothing to do with fundamentals, either micro or macro.
Is there money to be made in the gray area between trading and investing, or is that the "twilight zone" that no one wants to go? I appreciate your perspective.
IMHO, a trader is better off developing an edge from a technical perspective, because that's a personal edge developed outside the public sphere, where fundamental information lives and is available to anyone for the price of a browser. If I was advising anyone looking at learning to trade, I would pass along advice that I received many years ago, and which I should have followed at the time. And that advice is to focus on one or two instruments, live with them through thick and thin - or tick and trin - and find an edge. Regarding the OP, my advice would be to put his time and effort into a good backtesting/trading platform - work it for 10,000 hours until his fingers are bloody - and keep Peter Lynch on his bookshelf for his leisure time. But that's just my 2 cents.
Watch Limitless 2011 movie...that's kind of a good movie in regards to opening your mind/learning and trading; , Be resourceful, and open-minded...and very patient. -- and hopefully then, you will see some glimmer of light at the end of the tunnel. Alot of new people in this trading world are very impatient, and expect to get things handed to them...you will get things handed to you, but most likely it will be fool's gold.
If no one wants to get through this zone, Then there must be Gold still in plenty there. Assuming this spurious area ain't a fantasy land.
Information about "fundamentals" in investing encompasses a vast field of topics and aspects. It is evolving and "ongoing" and isn't available from just one or a few sources. I have collected 30 years worth of text and quotes from articles, books, internet, etc. Here is some from the past 10 years: "Improving your portfolio results versus conventional means presented in the mainstream literature doesn't require specialized knowledge. You just need the right tools and mindset. The difficultly is finding the right tools in the midst of the (forecasting power for next month’s market returns), which becomes stronger at longer horizons of one to five years, as theR-squared of the forecasting regression rises with forecasting horizon ........ Optimal Portfolios For The Long Run. Blanchett. Phau Historically, stocks in the United States haven’t been very risky over long holding periods. Campbelland Viceira (2003) argue that empirical evidence shows that stock returns are not independent and identically distributed over time (they tend to mean revert), which implies that long-run stock returns may be predictable and that long-run investors should overweight equities The authors find that the annualized standard deviation of stocks is actually lower than annually reinvested T-bills after fewer than 30 years.Dolvin, Templeton, and Rieber (2010) find that a 100% stockportfolio dominated other strategies for a retiree with a 40-year time horizon over historical rolling periods in the United States. The most convincing explanation for time diversification (and the mean reverting equity prices that cause time diversification) is perhaps sentiment-driven investor valuation (Barberis, Shleifer and Vishny,1998). Investors require a larger risk premium during recessions and are more risk tolerant duringan expansion. This creates short-run volatility through regular swings in prices, but these prices evenout over the long-run as valuations move toward their long-run average. Time diversification relies on these regular but irrational swings in values that follow business cycles. ( An ideal recommendationwould be to) temper historical findings with the reality of future uncertainty, although the empirical evidence supports an increasing allocation to equities with longer time horizons. Ned Davis rules 1. look at objective indicators. Remove the emotions ( emotional reasoning ) from the investing process, they focus on data instead of reacting to events; 2. Discipline: The data drives decision making with pre-established rules. External factors do not influence them; 3. Flexibility: The best investors are open-minded to new ideas, or revisiting previous thoughts; 4. Risk adverse: Not always obvious to investors, it is a crucial part of successful investing Employ the scientific method. this approach is also in sharp contrast to the many money managers today who are more concerned with what others are doing and piling on than in doing the work themselves. Our industry has way too many alleged experts who aren’t nearly as expert as they think. On the negative side, we have people who simply don’t know what they’re doing, people who know less than they think, and people who know a lot but aren’t able to discern what is important about it. On the positive side, we have those who get help when they need it (which should be all of us at various times) and all too few real experts. The key skill is knowing when and how we need help. I hope these signposts provide a decent starting point for trying to get there. Usability is more important than capability ( the more bells and whistles on a product ( capability ) confuses people; people like / will choose simplicity over complexity and regret it after purchasing the more complex model ) Schwartz if we believe something to be true, we quite naturally assume that those who disagree have some sort of problem. Our beliefs are deemed merely to reflect the objective facts because we think they are true. The problem is even more acute when the “answer” is counter-intuitive, and good investing is often wildly counter-intuitive (it’s really hard to sell when we’re euphoric or buy when we’re terrified, for example) (the S&P has averaged 11.82 percent return annually from 1926 through the end of 2012 and 9.78 over 40 years ) Top Ten Ways to Deal with Behavioral Biases Seawright "Semmelweis effect" is a metaphor for the reflex-like tendency to reject new evidence or new knowledge because it contradicts established norms, beliefs or paradigms. Strong economic intuition. Can you make a strong, evidence-based story beforehand that would justify the proposed effect? An intellectually honest source. Are the parties behind the back-test credible? Do they have any motivation to data-snoop or lie? Simple and transparent methodology. Complex models often underperform simple, robust ones in out-of-sample tests. Sample size. Academics usually expect at least several decades of data in a sample, at least when considering back-tested equity strategies. The highest-quality back-tests are conducted using big, high-quality data sets. Effect size and statistical significance. Many analysts look for high returns and high statistical significance in order to determine whether they should accept the validity of a proposition. While statistical and economic significance are necessary, they themselves are often weak predictors of a study's validity. Anyone can produce statistically significant results by data-snooping or even outright fabrication. Transaction costs. As quant-fund manager Ted Aronson gently pointed out to me, a strategy's costs are just as important as its gross returns. There are plenty of back-tested strategies that "work" in illiquid markets that wouldn't survive after all frictional costs are taken into account. And even then you're not done. You want several high-quality studies from skeptical, independent researchers that broadly find similar results before you conclude something is likely "true." These are high hurdles, yes, but necessary if you want decent odds of striking nuggets of truth rather than fool's gold. (1) Dickson, Joel M., Padmawar, Sachin, & Hammer, Sarah. "Joined at the Hip: ETF and Index Development." Vanguard research, 2012. (2) Ioannidis, John P. A. "Why Most Published Research Findings Are False." PLoS Medicine, 2005. (3) Buffett, Warren E. "The Superinvestors of Graham and Doddsville." Hermes, 1984. (4) McLean, R. David, & Pontiff, Jeffrey. "Does Academic Research Destroy Stock Return Predictability?" Working paper, 2013. Empirical research concerning successful long term investment results indicates that under-performing the S&P 500 25% - 40% of the time is not uncommon for successful investment managers. In fact, it appears to be normal. (More on this later.) Investors who understand this are more likely to stick with a perfectly valid long-term investment strategy in the inevitable and, we believe, normal, under performing periods. It is all too human, in the field of investing, to extrapolate recent results, which have no statistical significance, rather than emphasizing long-run odds and empirical data. Your own psychology and ability to handle the emotional ups and downs of investing are likely to be important determinants of your long-run investment success. “Unfortunately, there is no way to distinguish between a poor 3-year stretch for a manager who will do well over 15 years, from a poor 3-year stretch for a manager who will continue to do poorly. Nor is there any reason to believe that a manager who does well from the outset cannot continue to do well, and consistently The biggest mistake that is taught in corporate finance/investments is the way that we measure risk (always measured by a standard deviation of 1 year returns; it is applied that to any time period). When we have a mean reverting stochastic process applied to equities over a long time frame, it is not a random walk - the risk goes way down (vs. the 1 year returns short term - which IS a random walk) Siegel ( Random walk hypothesis states that a series of daily / monthly or annual rates of return in the market are uncorrelated much like the sequential outcomes of a coin flip ( data may be "convincing" but not conclusive ). There is increasing evidence of mean reversion in prices over periods of a about 2 - 4 years ( Stewart myers and Miller " Frontiers of Finance - 1990 Batterymarch of Fellowship Papers). Stock market price returns approximate a geometric random process. They don’t just climb in a steady curve, and close each day at a new high GestaltU To become a truly great investor and outperform the market on a consistent basis you must (1) develop a strategy that gives you a repeatable edge over the markets, (2) have an understanding of financial market history, (3) have a true passion for the craft to put in the time and effort required and (4) develop enough emotional intelligence to control and take advantage of the many behavioral biases of market participants. Even then it takes a considerable amount of luck. Wealth of Common Sense Taleb / Farnam Street "The accepted beliefs about how events played out may change in light of new information and then the new accepted beliefs may change over time as well. History is useful for the thrill of knowing the past, and for the narrative (indeed), provided it remains a harmless narrative. One should learn under severe caution. History is certainly not a place to theorize or derive general knowledge, nor is it meant to help in the future, without some caution. We can get negative confirmation from history, which is invaluable, but we get plenty of illusions of knowledge along with it when people are looking into the rear view mirror of the past, they can take facts and like a string of pearls draw lines of causal relationships that facilitate their argument while ignoring disconfirming facts that detract from their central argument or point of view" "There are many more deep intellectuals in the business today plus, the explosion of information on the Internet, creates an illusion that there is an explanation for everything. Hence, the thinking goes, your primary task is to find that explanation. Younger generation are hampered by the need to understand (and rationalize) why something should go up or down. By the time that it becomes self-evident, the move is over. There is no training — classroom or otherwise — that can prepare for trading the last third of a move, whether it’s the end of a bull market or the end of a bear market. There’s typically no logic to it; irrationality reigns supreme, and no class can teach what to do during that brief, volatile reign. The only way to learn how to trade during that last, exquisite third of a move is to do it, or, more precisely, live it. Fundamentals might be good for the first third or first 50 or 60 percent of a move, but the last third of a great bull market is typically a blow-off, whereas the mania runs wild and prices go parabolic. The concept of paying one-hundred-and-something times earnings for any company for me is just anathema. Having said that, at the end of the day, your job is to buy what goes up and to sell what goes down so really who gives a damn about PE’s?" Paul Tudor Jones .... "A sample size is the number of units studied. The larger the sample size, the more units we study , and the more accurate our results become . Our minds create plausible stories from limited data sets. When making decisions based on intution / subjective interpretation, when we're proven wrong and change our minds, we can't recall very well what led us to wrong conclusions to begin with ( as intuition / subj int. operate from system 1 unconscious emotional state. We have no idea why things went the way that they did ( hindsight bias ). And if we "got it right" last time, we'll probably get it right this time ( illusion of skill, winning streaks / overconfidence ). We have evolved to recognize patterns, yet in the stock market, we recognize patterns where none exist ( "patternicity").confirmation bias = the selective interpretation of information to match a preconcieved belief or narrative. You're biased towars confirming what you've already decided, rather than taking the more useful approach of assigning equal weight to all available information. An environment that is sufficiently regular to be predictable. Learn these regularities through prolonged practice or empirical research. We must protect ourselves against the investment industry's never ending flow of groundless information by ignoring it. They get paid despite not knowing; their clients suffer the consequences of their not knowing. We're not naturally good at tuning out noise. The conventional investment process is grounded in "getting it right". The financial media know how to make a convincing case using BELIEVABLE EXPERTS AND compelling evidence. The latter is often couched in terms of some market measurement being at what the media claim to be some historically significant level. You're left to believe that an important conclusion should be drawn from this "anecdotal" information, but you'll have to draw it for yourself ( and will you really take definitive action in asset allocation with it ? ). Most plans include no mechanism for signalling for lows to be bought or highs to be sold. The stock market's 66% uptrend vs. 33% downtrend statistical advantage is informed by Federal reserve policy, the uptrend in corporate profitability, techical innovation ... that is, the stock market is not a 50/50 coin toss proposition. The plan reacts to what did happen rather than trying to predict what might happen. Putting volatility to work. Automate an important part of your financial life to help you get back to living. This strategy is a variation of value averaging, we simply provide our stock fund with whatever profit the market failed to provide ina quarter, and we replenish the bond fund with excess profits delivered by the market in other quarters pg 46 We ran into 19 quarterly cash shortages when the buy signal called for more shares than our bond fund could afford ( 2K bond fund 8K stock to start ) 1 = less than $100, 5 = between $100 and $300, 5 = between $300 and $800 and 8 = more than $1000 Q308 to Q109 needed $3K, $6.5K, and $3.9K . All 19 needed $30.7K such shortfalls occasionally happen when we are dealing with the stock market because we can't know what it's going to do. If we knew enough to achieve the perfect balance, we'd know enough to time the market in the first place and wouldn't need this plan. Nobody can do that, which means we're occasionally going to have to manage cash shortages. As long as you can fund them, they're great opportunities." Jason Kelly "In other words, there are value stocks and value traps… A value stock is a beaten-down company that’s cheap compared to its earnings, its competitors and/or some other relevant benchmark that’s poised for a turnaround. Conversely, a value trap is a beaten-down company that’s cheap compared to its earnings, its competitors and/or some other relevant benchmark that’s poised to never quite turn around. We spend way more time using applications on our mobile devices than we do surfing the internet – more than six times as much per month, in fact, based on recent analysis by Business Insider." Wall st. daily CAPE, the popular cyclically adjusted P/E ratio, for the S&P 500 has signaled an "overvalued" market in all but nine months in the last 22 years. Financial metrics can make lots of sense in theory but be flawed in practice. ?? "Usually beta is a comparison relative to the S&P 500 (but could be some other index) and covers a certain amount of history. Your source of data should specify how they compute beta. The sign of the beta (positive or negative number) indicates direction relative to the index (positive being the same direction, gaining when the index gains, losing when the index loses; negative being opposite the index). With that in mind, generally a beta of "1" indicates that over the period represented by the beta, historically the stock would move in the same direction (because beta is positive) and about the same amount as the index. A positive beta greater than one would indicate that the stock moved more than the index, while a positive beta less than one would indicate it moved less than the index. A negative beta means the stock moved opposite to the index but the magnitude is still determined as it is for a positive beta. As for expectations, in general we expect the future to be like the past, and this holds true except when it doesn't. Some low volatility companies experience periods of high volatility and some some high experience low. And sometimes those periods can last for a long time, until eventually the beta comes to represent the new reality for the company." Robert Carver with Michael Covel Risk is about unknowns - Predictable / Unpredictable risks. Market returns / the model fall within a normal distribution and they have a particular standard deviation. In order to predict something, you need to have some kind of model / some way of deciding what's going to happen. You need the mathematical functions and then you need to feed into them some estimates of what you think should be in those mathematical functions. Then you need to determine what a normal distribution of market returns and what is the particular standard deviation variance and particular correlation. The more complicated that your notion of what the predictable risk is, the less and less that you think about unpredicatable risk / black swans. Many discretionary traders may be overestimating their ability ( very few are “rare” geniuses ) and could do with some self examination in whether they are doing better than just using a simple system Formalize into an algorithm and get the same results every time ( repeatable ). “Read the charts” phase = initial phase that traders / investors may go through as analytic information presented by CNBC and financial media is superficial and discretionary. Most people don’t have a good judgement / development of talent of what is good evidence and bad evidence of what adds value. Are you using the same process that you were using X years ago ? Are you ascribing your performance to skill vs. luck ( skill in reading charts ) ? HFT represents ( weird ) non linear patterns Avoid the temptation to change the system’s parameters “Ideas” first vs. “data” first trading system development - “Data” first is what most people imagine that you do first as a systematic trader and is becoming increasingly common perception as things like machine learning and neural networks big data are all very fashionable at the moment. People assume that you get price data and drop it into some sort of giant optimizing machine that will come up with a trading rule that will give you a profitable account curve. Yet the data correlations may not make any sense as it might be using random, non linear data variables ( buy on Tuesday, if the Dow is up 1% ) Jim Simmons has been using these very strange data based trading rules successfully for a long time, it doesn’t meanthat it will work for everybody. The alternative is where you use “ideas” first, which may be economic or behavioral / trend following data based and then build the rule around the idea. Data first seems to work better over shorter time frames and idea first lends itself towards working better over longer time frames. Idea first gives an underlying understanding of why it may be working. .................... Mohamed El-Erian the junction in our economy is a political implementation issue . If an investor ends up making a mistake ( in facing times of approaching uncertainty with historical measures indicating market overvaluation / subpar forward market returns ) can they afford to make the mistake. The conventional wisdom is that diversification will bail you out, When there is an enormous amount of intervention by central banks, it changes the correlation between different asset classes. Don't be afraid to hold cash. You need the "resilience" to be able to continue operating if our political system doesn't step up to it's reponsibility, and will be able to purchase assets at very depressed prices and agility to respond to the better equilibrium . David Stein Investing information is overwhelming. It's a relief to give up focusing on individual securities / short term price movements as it frees up time from having to follow alot of "security" specific information. Different asset classes ( sectors universes ) have different return drivers ( growth in the economy, income, real estate fundamentals. etc ). Develop reasonable return objectives over a long term period have realistic expectation. Less worried about the day to day volatitlity and more worried about the extreme losses / maximum drawdown typically based on history. What is the worst thing worst case scenario that had happened in the past. Arnott uses term, "third pillar" assets ( assets outside of traditional stocks and bonds ) What drives stock returns? Starting conditions, dividend yield, expected / estimated earnings growth ( influenced over the long term by economic growth or contraction ), valuations ( when valuations are high then we lower our expectations ) There is occasional “repricing” of assets We evaluate long term return expections, not for the pupose of anticipating short term price movements, but rather for assessing comparative valuation levels across a panolaply of global markets engaging when they are most at odds with market perception - R. Arnott Use a process that works. Incrementally adjust my allocation based on certain variables and market conditions. Rely on objective measures. Instead of trying to follow all of the data and all of the information, limit it to certain criteria that has proven successful to invest or adjust asset allocation. A market index that approximates the U.S. stock market is the Russell 3000 Index. The S&P 500 Index in turn is a subset of the overall U.S. stock market. The S&P 500 is comprised of the largest 500 U.S. stocks weighted by the total market value of each company’s outstanding share. Factors and Smart Beta An active manager’s style can be described as the factors that drive its performance such as value, growth, momentum, low volatility etc. A value manager for example invests in stocks that are cheap relative to the market. At times these factors earn excess returns above what one could earn investing in the overall market. The market itself is the sum of what all investors own. In other words, the average investor owns the market. The market is the most diversified portfolio an investor can own. An investor or manager that owns a portfolio that differs from the market is no longer average. They are willing to suffer through bad times such as underperformance or losses in order to outperform the market and earn an excess return. The excess return from investing in certain market factors such as value is compensation for suffering through these bad times. These excess returns are sometimes called risk premiums. Some risk premiums are persistent in that when the factors that generate those risk premiums are held in a portfolio for a long enough period of time the investor will eventually outperform the market. These persistent factors are called smart beta. Growth and Value Investing Other factors such as growth investing do not earn a persistent risk premium. An investor who maintains a long-term exposure to stocks with higher growth rates in terms of sales or earnings will eventually underperform the market. Why? Because growth stocks tend to be more expensive than value stocks. Growth stocks are often highly recognizable names such as Apple and Google, and they are found in sectors of the economy experiencing rapid, exciting changes like technology and healthcare. Growth investors often assume the good times will continue indefinitely so they are willing to pay more to own the stocks of high growth companies. Invariably, the rapid growth slows, the investors are disappointed and the stocks underperform the market. Meanwhile, investors often believe the bad times experienced by struggling companies or sectors will continue indefinitely and so the stocks become cheap relative to the market and to growth stocks. Invariably, the bad times end and the cheap stocks get re-priced upward, earning the value investor excess returns relative to growth stocks and the overall market. As an investor you can choose to be average and own the market and earn the market return. Or if you are willing to suffer through bad times, you can outperform the market by holding a portfolio with smart beta factors that differ from what the average investor owns The purpose of the financial markets are to preserve wealth ( from inflation ). What builds wealth is having an income stream that is generated in the real economy either from a business or profession and then living below our means so that we can save large portion of those profits and then preserve them by investing in public and private markets. Most people don’t have an informational / competitive edge in the markets and they don’t necessarily need one. They just need to understand the math and emotion of investing: understanding the mechanics of what drives asset class returns . How bond returns are primarily driven by current interest rates. How stock returns are driven by dividend yields and corporate profit growth. How real estate returns are driven by rents. In other words, the math of investing n other words, the math of investing involves understanding how a particular security or asset class generates cash flow. Business owners and buyers do the same thing as they assess how a business generates cash flow. The emotion of investing is about understanding how investors are valuing investment cash flows. When investors place a high value on investment cash flows, bidding up security prices, then subsequent returns will be lower. When investors are fearful and place a low value on an investment’s expected cash flow, then subsequent returns will be higher. Another aspect of investing is controlling our own emotions. We need to look at the investment math and investors’ emotional state—what I call investment conditions—and then make investment decisions without getting caught up in the hype and fear that drives other investors into a frenzy or panic. Value …. Seth Klarman Value investors need to be both patient and arrogant, humble, opportunistic, and have an understanding of risk ( of taking risk and avoiding risk ( avoiding market risk, interest rate risk, inadequate diversification, country risk ) . Waiting for opportunities. Being early and right look exactly the same .. we need to be patient for the value Investing is an arrogant act ( they know more than the seller, they have some sort of competitive “edge” or “advantage” ) Look for unsophisticated forced selling. A combination of quantitative (model) variables that takes advantage of periods unsophisticated forced selling / forced undervaluation It is difficult for managers to hold cash, because you might not get paid very much to hold that cash ( but it gives you the opportunity. Risks that are to be avoided: Market risk Interest rate risk Inadequate diversification Country risk ( political, socio economic, currency, debt instability/ credit risk ) Credit risk Company specific risk What is your potential loss ? What’s the worst case scenario ? Maximum potential loss ? Difficult to quantify how much risk to take / to assess risk . There could have been things that may have happened that didn’t happen that you were completely unaware (of). It’s relatively easy to know what to do at market extremes, Often times investing is somewhere inbetween. In order to invest in a nation’s stock market, one has to believe / have an assumption that economic growth will continue. And economic growth is based on a growing workforce, worker productivity ( producing goods and services, and access to reasonably priced resources used to produce those goods and services. Buy and Hold investors are willing to ride out the inevitable up and downtrends in these markets with the belief in these assumptions. Rana Foroohar from “American Capitalism’s Great Crisis” The U.S. system of market capitalism itself is broken From the creation of a unified national bond and banking system in the U.S. in the late 1790s to the early 1970s, finance took individual and corporate savings and funneled them into productive enterprises, creating new jobs, new wealth and, ultimately, economic growth. Of course, there were plenty of blips along the way (most memorably the speculation leading up to the Great Depression, which was later curbed by regulation). But for the most part, finance—which today includes everything from banks and hedge funds to mutual funds, insurance firms, trading houses and such—essentially served business. It was a vital organ but not, for the most part, the central one. Over the past few decades, finance has turned away from this traditional role. Academic research shows that only a fraction of all the money washing around the financial markets these days actually makes it to Main Street businesses. “The intermediation of household savings for productive investment in the business sector—the textbook description of the financial sector—constitutes only a minor share of the business of banking today,” around 15% of capital coming from financial institutions today is used to fund business investments, whereas it would have been the majority of what banks did earlier in the 20th century. “Across all advanced economies, and the United States and the U.K. in particular, the role of the capital markets and the banking sector in funding new investment is decreasing.” Most of the money in the system is being used for lending against existing assets such as housing, stocks and bonds. Being willing to give up something today, for the payoff later. A deep reconsideration of time and how we perceive it. We must change dimensions from the immediate to the intermediate. From the A-temporal to the intertemporal. It requires resolute, forward looking orientation away from what is happening now. What can be seen to what is to come; what cannot be seen. Depth of field = our ability to sharply perceive a long span of forward moments. Let’s think of time as intertemporal comprised of a series of coordinated now moments each providing for the next, one after another like beads on a string. We need to maintain balance between the now and the long term. Sometimes we pay a price for long term gains and do have to be patient. We always have to keep all of the different temporal aspects in mind. In order to understand what is driving markets and not get caught up in bubbles; behavioral traps. Americans are apt to be unduly interested in discovering what average opinion believes average opinion to be. And this weakness finds it’s nemesis in the stock market. It is rare, one is told, for an American to invest as many Englishmen do; for income. And he will not readily purchase an investment except for capital appreciation- he is in the above sense, a speculator. Speculators may do no harm as long as a bubble lead to a steady stream of enterprise creation. But the position is serious when enterprise becomes the bubble on a whirlpool of speculation. When the capital development of a country becomes the byproduct of the activities of the “casino”, the job is likely to be done(?) ( the tail wagging the dog ). When demand for securities starts to impact mainstreeet, then it becomes a problem. In the 2008 financial crisis, the demand for collaterelized debt obligations and other mortgaged backed securities contributed to the housing crisis ( leverage vs. natural supply and demand ). One of the first bubbles created out of mortgage backed bonds was in the the early 1920s – early 1930’s used “skyscraper” bonds which an average person could participate. ........ The path to achieving investment success is to study long-term results and find a strategy or group of strategies that make sense. Remember to consider risk (the standard deviation of return, more on that later) and choose a level that is acceptable. Then stay on that path. To succeed, let history guide you. Successful investors look at history. They understand and react to the present in terms of the past. Yesterday and tomorrow, as well as today, make up their now. Successful investing, however, runs contrary to human nature. We make the simple complex, follow the crowd, we allow our love of a story about some stock inflame our emotions and dictate decisions, buying and selling based on tips and hunches, and approach each investment decision on a case-by-case basis, with no underlying consistency or strategy. Models beat the human forecasters because they reliably and consistently apply the same criteria time after time. In almost every instance, it is the total reliability of application of the model that accounts for its superior performance. Models never vary. They are always consistent. They are never moody, never fight with their spouse, are never hung over from a night on the town, and never get bored. They don’t favor vivid, interesting stories over reams of statistical data. They never take anything personally. They don’t have egos. They’re not out to prove anything. If they were people, they’d be the death of any party. People, on the other hand, are far more interesting. It’s far more natural to react emotionally or personalize the problem than is to dispassionately review broad statistical occurrences – and so much more fun! It’s much more natural for us to look at the limited set of our personal experiences and then generalize from this small sample to create a rule of thumb heuristic. We are a bundle of inconsistencies, and although making us interesting, it plays havoc with our ability to successfully invest our money Generally, predictions are made in two ways. Most common is for a person to run through a variety of possible outcomes in his or her head, essentially relying on personal knowledge, experience, and common sense to reach a decision. This is known as a clinical or intuitive approach, and it is how most traditional active money managers make choices. The other way to reach a decision is the actuarial or quantitative approach. Here, the forecaster makes no subjective judgments, nor does she rely on a rule of thumb heuristic. Rather, only empirical relationships between the data and the desired outcome are used to reach conclusions. This method relies solely on proven relationships using larger samples of data, in which the data are systematically weighed and integrated. "Good financial planning decisions extend well beyond where and how you invest. Two major research efforts have attempted to quantify how good financial decision making can enhance one’s lifetime standard of living.The research identifies how good decision making can enhance sustainable lifetime income on a risk-adjusted basis In the field of finance, the term “alpha” identifies how a fund manager can combine securities into a portfolio that provides excess returns to investors above the appropriate related benchmark index for those investments on a risk-adjusted basis. In simple terms, achieving alpha means earning more money than expected. This generally is achieved through either timing market trends correctly or picking winning individual securities. If a fund manager charges a fee of 1% of assets under management, but then produces alpha of 2%, the fund owner enjoys an overall net gain of 1%. After fees, they’ve earned 1% more than they would have had they invested directly in the benchmark index. “ The Value of Financial Advice” Pfau Rob Arnott on "Fundamental Index" Mean reversion is the most powerful force at work in the capital markets; it is the largest inefficiency in capital markets. Why is it a sustained inefficiency ? Because it means buying what it most feared and loathed and selling what is most beloved and extravagantly expensive. Why will active managers always underperform the market? The market is cap weighted. The index funds are cap weighted. Take the index funds out, and you left with more or less the same portfolio; that’s what active managers collectively own. Since they collectively own the market, you’re going to get market returns minus fees and trading costs. Since the costs no negligible, active managers can’t win collectively. It doesn’t mean that active managers with skill can’t win individually, but they have to have someone on the other side of the trade. The fundamental index is based on the same assumption as active management; that prices deviate from intrinsic value, that the price = intrinsic fair value + - error term and because the, market is constantly hunting for that intrinsic value that error term is mean reverting. If that error term is mean reverting , than you can anchor on anything other than market cap, then you will be contra trading against the market’s more extreme bets and you’ll be turning the noise / the pricing error into alpha. It doesn’t win in every year; you have times when the market has errors in price that diverge further ( tech bubble ) 6 year out of 10, the contra trading adds value. What can you anchor on ? Well you can anchor on equal weighting or the dart board. Because your weighting is independent of price, you’re not going to be anchoring on overweighting the overvalued and underweighted the undervalued as cap weighting assuredly does. Or if you bought a liquid, low turnover portfolio, you could anchor on the size of the business and that’s what fundamental index does. It goes against human nature to buy an investment/fund that has fallen. It is driven by deeply ingrained behavioral biases one of the most notable of which is we all want more of which has given us pleasure, joy, and profit and less of what has whatever has given us pain and losses ( on the African plain, we ran away from the lion ( losses ) yet may have outside profits by running towards it ) . In the actuarial profession, you’re required to use history in shaping your equity expectations The mean reversion will bring it back to historic norms Growth (in earnings) will come from entrepreneurial capitalism the creation of new enterprises, not from the growth of existing enterprises. Over the last 100 years, real GDP growth has averaged 3% per annum, from the vantage point of the shareholder and existing assets, existing companies has seen real growth average 1.3% per annum. A booming economy has to have a vibrant entrepreneurial engine to it, has to have new enterprise creation @ 2% per annum. There will be no multiple expansion or contraction over the next 10 years. If there is a mean reversion in CAPE from 25 to 17 over the next 10 years, it will cost about 4% per annum compounded. What if the market sustains CAPE 25 for the next 10 years and valuations are “reasonable” no multiple expansion or contraction and we split the difference with CAPE 17 then it is still -2% a year. CAPE for emerging markets says that they are poised to give superior returns. And at a time when people hate and dread EM’s … Why? Because they’ve inflicted pain and losses on investors. Valuation matters and it will always encourage us to buy what’s unloved, out of favor, feared and loathed. The investing community, in general, has a home country bias that’s profound. Most investors have a domestic centric portfolio. An average norm for U.S. managers have about 85 domestic equity favor. Most investment professionals use discounted cash flow (DCF) analysis to estimate a stock’s inherent worth,3 and so to judge whether it is mispriced.But DCF analysis, P/E multiples, and other theoretically sound valuation measures cannot tell us how much more misvalued the market will get nor can they explain the wild swings we’ve experienced in the two equity market cycles in the last 15 years.4 As Figure 1 illustrates, the stock market seems to go too far in both directions—up and down—and the amplitude of these movements cannot be satisfactorily explained within the cool analytical framework of the standard model. Empirical research has established that sooner or later stock prices revert toward their long-term averages. There is also strong evidence that the value premium is mean reverting (Hsu, 2014). If the market rises or falls to an extreme level despite a natural tendency to self-correct, then countervailing forces must be at work. The stock market’s turning points, as well as the valuation peaks and troughs of individual stocks, increasingly appear to be driven more by mass psychology than by sober professional judgment based on disciplined valuation techniques. In fact, the active investor’s conundrum is such a challenge that many investors have chosen passive investing—simply removing timing decisions from their purview. But there is strong evidence that the popularity of passive investing tied to prominent cap-weighted indices is actually associated with higher return correlations among stocks and, therefore, higher systematic equity market risk At this juncture, we must acknowledge that financial theory does not provide clear and timely trading signals. Calling the turns is hard because we don’t have a mechanics of mean reversion. Our best theories—including behavioral finance, neuroeconomics, experimental economics, and evolutionary psychology—do not enable us to foresee the sudden exogenous shock that will trigger a reversal, or to sense when a gradual change in investors’ attitudes will reach the tipping point. Not even the most skilled and experienced asset allocators can pinpoint in advance the onset of a reversal. Most of us are well advised not to attempt market timing. The soundest plan is to choose a strategy that suits our investment objectives and risk tolerance—potentially including a disciplined smart beta strategy that systematically rebalances over time—and to stick with that choice for the long term. ....... What amazes me is (, among a lot of those folks,) there’s not even an understanding of the difference between an arithmetic expected return and a geometric one. A geometric one is what you actually get to earn and consume. But people model portfolio optimization and Monte Carlo’s with arithmetic returns. And so they’re embedding in expected returns that are typically arithmetic, not understand the geometric flow. You don’t know anything in this business. You can only attach confidence levels to them. And I think to be a good investor, you’ve got to start thinking that way. It’s not black or white. Everything is grey. There’s an expected outcome. There’s a variance around that expected outcome. And with that comes essentially confidence levels. And so I’ll give you an example. There were many times in history that a value premium or value tilt would have under-performed a growth tilt or the market for five or 10 years, or more. So it didn’t mean that it stopped working, it turns out. And so a lot of these things, empirical research, where you have evidence that supports a claim, really takes time to play out. So I think as time goes by, you have to evaluate all of the past empirical research, and look at it, and you have to make a judgment call. And then you’ve got to ask yourself about confidence levels, right? So I believe in the market factor going forward more than I believe in the value factor, the momentum factor. But I believe in the value factor, the momentum factor going forward, more than I believe in the persistence of an individual manager’s alpha. And I can tell you that the prevalence of true alpha that’s statistically significant is very, very, very thin across all asset classes. And without these tools and methods, I’d say, “Good luck.” I’ll take it a step further and say the challenge there is that what you think is outperformance may just be factor risk. And that even if you even if you observe outperformance after solving for factor risk, then you have to ask yourself, “Is it likely random, or is it likely statistically significant and therefore true?” And almost nobody does it.When you find a manager who has raw, pure skill, regardless of expenses they charge, that interests me. And then the question is, “Can we get it so that the skill survives the fees?” But it’s a critical question, because a lot of managers will just perform well, even risk-adjusted, randomly. And you have to solve for whether what you were observing is likely true skill or randomness. Pete Mladina In the financial markets, it’s really complex to understand whether someone actually was doing the right thing or the wrong thing, which means in the end all you can really rely on is at some level trust in whoever you’re working with, and that’s a good thing in the sense that you wanna build trust, you know, so you can do the right thing and help people out. Also the problem with that is once you have someone’s trust, because it’s so hard to ascertain whether you’re basically full of shit or not, you know, in theory you could use it for a nefarious means, and that’s kinda why integrity is kind of a big deal in financial markets. “Empirical asset pricing research can sometimes get monotonous because you end up circling back relentlessly to the same conclusions, value works, momentum works, and yet markets are remarkably efficient. But sometimes research uncovers absolutely stunning and counterintuitive results, and that is where things get truly exciting. This is why anyone whose in the industry knows that you’re always waiting this trade off between, “I got to run a business and I want to maintain my assets base,” but at the same time you also want to actually generate performance for your clients. The problem is sometimes those two objectives are in conflict, because if I’m a large asset manager, you know, I don’t really have huge incentives to knock it, you know, knock the cover off the ball. Because if I out preform by a lot, whatever, I got my same assets, if I under perform by a little, no one’s gonna fire me because it’s kind of sticky. But if I get destroyed by the market in the year, I’m like done. Everyone is gonna rip their assets out. So what do people do? They cause an index. But then you start doing it ( investment in the market ) and then you I start asking, “Well, why do things work?” Because does it work just because stuff is cheap? No! Investing is all about essentially front running other people’s expectations. Because the only reason value investing works is because those cheap stocks, eventually someone else in the marketplace down the road says, “Oh, wow, this is not a total dire situation. It’s not as bad as we thought.” They reevaluate expectations and then you make a spread there. That’s why value works (I recommend everyone probably get started there because it’s a common sense approach that a lot of times will keep you out of trouble from doing crazy things like day trading or what have you ) . And the core psychology is it’s basically an overreaction to crappy news. People throw the baby out the bath water on average and then what happens is expectations down the road change, they get reevaluated, you make money. Wes Grey Systematic firms combine three key pillars: data, technology and people. Historical data related to financial instruments is critical to discovering and refining hypotheses. State of the art technology is essential if one is to extract meaningful information from decades and decades of such data - no serious statistical analysis can take place without serious computing. Although the third pillar is sometimes emphasised less than the first two(1) people are just as crucial as the first two pillars. High powered computing and reams of data are worth little without the skill and expertise to extract meaningful information from data. Misunderstanding the difference between information and data is a common mistake. Data is not information: once data has been processed, aggregated, visualized and transformed it becomes information. Data and information must be distinguished: if the processing, aggregation, transformation or visualization processes are flawed then the resultant information is incorrect. Any successful investment firm requires exceptional people in every area of its business, from operations and finance to research and software development. The best systematic firms hire teams of PhD scientists or quantitative researchers to analyse data.(4) Computing skills aside, scientific training is essential to extract information from data but an abundance of computing power and software makes it easy to do statistical analysis badly. The subtleties involved in analysing data correctly are so important, that much of the intellectual property of a systematic firm centers on the creation of clean and bias-free research pipelines.(5) Let's make this concrete through an example. Consider the general problem of building a portfolio of systematic strategies. Ultimately we want to discover stable relationships which have predicted financial markets and, most importantly, stable relationships which are likely to persist into the future.(6) But there are many nuances before we even attempt to build statistical models. In fact there are many more than we could ever hope to cover here Classical model of decision making employs a well-structured judgment process based on the maximization of value, a painstaking and all-inclusive search for all information, and an in-depth analysis of alternatives Well informed systematic decisions which are in their own self interest and the decision maker is acting in a world of complete certainty. ??? Suggested reading material : Read books and articles by : Larry Swedroe, Howard Marks (( Oaktree capital ) & quarterly letters), Jim O'Shaughnessy , Michael J. Mauboussin, Rob Arnott, Clifford Asness