Financial Risk for Beginners by William T

Financial Risk for Beginners by William T
Financial Risk for Beginners by William T. Park A Presentation to Retired Executives and Professionals (REAP) April 20, 2017 See speaker’s notes for explanations

Introduction Why understand financial risk? What is financial risk?
What causes financial risk? What can you do about financial risk?

Why Understand Financial Risk?
Risk can cost you money An investment’s risk can change!! Some risks can be reduced or even avoided

Risk means unpredictability
What is financial risk? Risk means unpredictability of a increase or decrease of some quantity (price, return, dividend…) by the end of some time period. Most people only care about the chance of a decrease (“loss,” “downside risk”) They ignore chance of an increase (“gain,” “upside potential”) Professionals think about both

What is financial risk? Kinds of Risk
Long-term risk Short-term events with long-term effects (9-11) Changes that persist (the Internet, climate) Short-term risk Trading errors, computer outages Weather Instability (bubbles and crashes)

What is financial risk? Kinds of Risk
Unsystematic risk Affects a portion of the entire market One sector or even one stock Can reduce it by diversification Systematic (“market”) risk Affects all stocks / bonds / options / futures Difficult to reduce it by diversification Can reduce it by hedging

Waterproof Soap Co. Consumer staples sector Paid dividend for 10 years
Price not trending up or down Not much variation in price lately Low risk Price Current price: $100 $100 $0 Time 2016 2017 WS ?

Describing Risk With a Price Probability Distribution
2 x Volatility Low risk $97 $98 $99 $100 $101 $102 $103 Probabilitydensity … $0 … Possible price … $100.50 $99.50 2/3 Waterproof Soap Co. Fri., June 30, 2017 Tail 1/6 * Risk is experessed by a probability distribution (red line) over possible prices at the end of the prediction interval. * Distribution is computed from historical price data * Distribution is a log-normal distribution, not a normal (Bell curve) distrib. * A normal distribution would say negative prices are possible. * Log-normal distributions say prices are only zero or positive * Height of red line over a price shows how likely it will be the final price. * Most likely final price is $100 because the Waterproof stock has a flat trend * Shade the area under the curve equal to 2/3 of the area under the curve, centered on the most likely price. * Half the width of the shaded area is called “the volatility of the stock price.” * Volatility is also the “standard deviation” of the price history * Volatility is usually stated as a percentage of the initial price. * Professionals only need the volatility and most likely price to make most decisions * The computer can give the probability that the final stock price will be in any range, as the area under the red line over that range. * Riskier stocks have larger volatility, the red curve is stretched left and right. $97 $98 $99 $100 $101 $102 $103 High risk Probability density 2 x Volatility … … Possible price 2/3 Tail 1/6 $0

What causes financial risk?
Flash trading Front running Dark pools Order flow payments Tax & interest rates Insider trading Pump-and-dump Short-and-distort Influential investors Emergent behavior Value traders & technical traders Competition Mergers and acquisitions Dishonest management The market process itself Time * See Investopedia for definitions... * The process by which a stock market establishes the price of a stock is a source of variation in the stock price (a source of risk). * Time increases risk because more of the events in the list can occur over a longer time period.

What causes financial risk?
Time and volatility increase risk 3Q 4Q $2 $101 $100 $99 $98 $97 $102 $103 $104 FY 1Q $1 2Q * Time increases risk by increasing volatility as a prediction is made farther into the future * Example: Assume that - A stock is trading at $100 at the beginning of the fiscal year (FY) - The stock has a volatility of 1% -- $1 over the first quarter (1Q) based on the stock’s past price history -- The volatility is constant (1% over each quarter) * Volatilty over longer periods increases as the square root of the length of the period - Twice as much ( 2% or $2) over 4 quarters as over one quarter - Three times larger (3% or $3) over 9 quarters - Four time larger (4% or $4) over 16 quarters

Types of Orders Market Order (“at the market”) Limit Order
Fast execution No control over price, exchange decides Limit Order Exchange decides when executed, if ever Can specify worst price you will accept Can cancel at any time GTC, GTD, AON, FOK, OCO, IF/THEN... * When you place a limit order, you can specify over a hundred different kinds of conditions on how the exchange is to handle it. For example: GTC -- Good Till Canceled (otherwise it’s canceled at close of market) GTD -- Good Till Date AON -- All Or None (Fill the order completely if at all) FOK -- Fill Or Kill (Cancel if not filled immediately) OCO -- One Cancels the Other (Two limit orders, first filled cancels the other) IF/THEN -- Complicated conditions specified in a computer-like language Allowed conditions depend on the broker and stock exchange..

Types of Orders Market: “Buy/sell 200 shares of XYZ at the market.”
Limit: “Place a good-till-cancelled limit order to buy/sell 200 shares of XYZ at $100 (or better).”

Overview of a Stock Exchange
Worst Price $ XYZ stock order book Limit orders to buy Limit orders to sell Total number of shares at each price * An exchange maintains an “order book” that records the currently active limit orders (waiting to be filled). * The order book used to be a real book with paper pages. * Now the book is data in the exchange’s computers * Only NYSE still has people (“specialists.”) maintaining an order book - Their book is now an electronic wireless tablet - Specialists handle about 15% of daily volume - Each specialist handles only a few stocks (8 to 15) - Specialists usually handle only the least active stocks. * Limit orders in the book are sorted by: - the stock to be bought or sold - the price specified in the order - the time of arrival at the market’s computers * The book also records - The number of shares (”volume”) in each order - Which broker placed the order (usually not shown to the public) - Any conditions on the order (GTC, FOK, etc.) - Limit, stop, and other special orders awaiting activation Order of arrival

Worst Price $ XYZ stock order book Limit orders to buy Limit orders to sell Bid Ask Spread * Exchange computers (and specialists on the NYSE) try to maintain: - Liquidity: - Fast fills for market orders - Minimum waits for limit orders to be filled - Priority for large-volume limit orders - An orderly market: - Maintains a small bid-ask spread - Acts as buyer or seller of last resort during periods of instability through - “Market Maker” brokers - Specialists (NYSE only) - “Circuit breakers” -- stop trading automatically on instability * Exchanges report to the public, brokers, and the SEC - Level I real-time information (usually free) - Bid and ask prices on each stock - Stock, time, price, and volume (number of shares) of each trade - Open, high, low, and closing prices of each stock - Level II real-time information (an expensive service) - Contents of the order book, except for identities of traders Order of arrival

Worst Price $ XYZ stock order book Limit orders to buy Limit orders to sell Market orders Bid Ask Spread Trades · · · * Market orders arrive at the exchange in approximately the order in which they were placed by brokers - Multiple communication lines between brokers’ offices and an exchange - Orders take longer to reach exchange from brokers farther away. - So, the sequence in which orders arrive is partly random * Exchanges are required to give market orders the best available price - A “matching engine” program in exchange computers decides how to fill market orders as they arrive - Market buy orders are matched with limit order(s) to sell at the lowest price - Market sell orders are matched with limit order(s) to buy at the highest price - Some exchanges try to match market orders with other market orders - At the same price as the price of the preceding trade - As long as approximately equal numbers of market buy and sell orders arrive. - If market buy and sell orders are unbalanced, they are matched with limit orders Order of arrival

Continuous Double Auction
$102 $98 $97 $96 $100 Communication Lines Stock Exchange Order book for XYZ stock Price “Market” orders Buy order Sell order Investors Brokers $103 ... $101 $99 Limit Orders “Bids” to buy Offers to sell (“Asks”) Current Ask Current Bid XYZ Spread: $2 *All stock exchanges conduct a “continuous double auction.” - Continuous - Runs continuously while the market is open (9:30 AM to 4:00 PM) - Double auction - A market order to SELL arrives and starts an auction - Limit orders to BUY try to win the auction with the HIGHEST price - Like an ordinary auction - A market order to BUY arrives and starts an auction - Limit orders to SELL try to win the auction with the LOWEST price - Like construction companies bidding on a construction contract by trying to submit the lowest priced bid (called the lowest priced “ask” on the exchange) * The next market order (1) to arrive at the exchange’s computers will be to BUY one round lot of XYZ stock at the current “market price.”. * The smallest difference between prices in this example is $1 (the “tick” size) * On any real stock exchange, the tick is only 1 cent * Orders to buy or sell can be for any number of shares. For simplicity, we assume all orders are for a volume of 1 round lot (100 shares)

Communication Lines Price Investors Brokers $99 $101 $102 $98 $97 $96 $100 $103 Matched orders Limit Orders “Bids” to buy Offers to sell (“Asks”) Current Ask Current Bid ...XYZ 1 101 XYZ Spread: $2 Order book for XYZ stock “Market” orders Buy order Sell order * Market order (1) reaches the exchange’s computers * They activate the “matching engine” program - It matches the market order (1) to BUY 1 round lot XYZ stock at the “market price” with a limit order to sell 1 round lot at $101 ( the current “ask”) - That determines the “market price’ at which the market order is filled - So, the market order buys its stock at the lowest price it has to pay.. * Exchange computers report the trade to the public - To the brokers of each order - “Your order - for 1 round lot - was filled completely - at $101 - at 10:28: EST (accurate to 1 microsecond !!) - To the “consolidated tape” (stock ticker display services) - “XYZ ” - I.e., “1 round lot of XYZ traded at $101” - To the exchange’s journal for use by the Securities and Exchange Commission to verify quality of service and analyze any crashes or bubbles.

Communication Lines Price Investors Brokers $99 $101 $102 $98 $97 $96 $100 $103 Limit Orders “Bids” to buy Offers to sell (“Asks”) Current Ask Current Bid ...XYZ 1 101 XYZ Spread: $2 Order book for XYZ stock “Market” orders Buy order Sell order * The matching engine removes the market order (1) and the limit order(s) that were filled completely in the trade. * It updates the bid and ask prices for the stock - They haven’t changed as a result of this trade - The bid and ask can change because - Limit orders get filled by market orders and removed - A large market order may be filled from multiple limit orders - Orders may be only partly filled, depending on demand and supply, market liquidity, and conditions placed on limit orders - Limit orders get canceled (quite often) automatically or manually - New limit orders get placed (quite often) * It reports the current bid and ask to the public through financial information services

Price Limit Orders $99 $101 $102 $98 $97 $96 $103 Matched market orders Communication Lines Investors Brokers $100 “Bids” to buy Offers to sell (“Asks”) Current Ask Current Bid ...XYZ 1 101…XYZ 1 99 XYZ Spread: $2 Order book for XYZ stock “Market” orders Buy order Sell order * The next market order (2) to arrive at the exchange’s computers is another order to SELL one round lot of XYZ “at the market.” * The matching engine fills the market order from the longest-waiting limit order to buy that has the highest “worst price’ ($99) * So, the market order sells its stock for the highest price it can get. * The exchange reports the trade to the brokers, ticker tape services, and information services

$99 $101 $102 $97 $96 $103 Communication Lines Price Investors Brokers $100 Limit Orders Current Ask Current Bid $98 “Bids” to buy Offers to sell (“Asks”) ...XYZ 1 101…XYZ 1 99 XYZ Spread: $3 Order book for XYZ stock “Market” orders Buy order Sell order * The matching engine removes the market order (2) and limit order from the order book. * It updates the bid and ask prices and reports them - This time the bid price has changed - When it removed the limit order to buy at $99 there were no more limit orders to buy at that price (the limit order was the last one in the $99 queue). - So the bid dropped to $98 (the price of the now-highest-priced bid).

$99 $101 $102 $98 $97 $96 $103 Matched market orders Communication Lines Price Investors Brokers Current Ask Current Bid $100 Limit Orders “Bids” to buy Offers to sell (“Asks”) Spread: $3 ...XYZ 1 101…XYZ XYZ 1 98 Order book for XYZ stock “Market” orders Buy order Sell order * The next market order (3) to arrive at the exchange’s computers is an order to SELL one round lot of XYZ at the market. * The matching engine fills the market order with the longest-waiting limit order to buy whose “worst price it will pay” is highest ($99) * So, the market order sells its stock at the highest price it can get from any limit order to sell.. * The exchange reports the trade and updates the bid and ask.

$99 $101 $102 $98 $97 $96 $103 Communication Lines Price Investors Brokers Current Ask Current Bid $100 Limit Orders “Bids” to buy Offers to sell (“Asks”) Spread: $3 ...XYZ 1 101…XYZ XYZ 1 98 Order book for XYZ stock “Market” orders Buy order Sell order * On a real stock exchange, the tick size is one cent, so on most trades prices would change by pennies instead of dollars * The ticker tape shows that XYZ stock dropped in price * You might think this indicates a problem at XYZ Inc. * The reason the price dropped is simply that a market buy order happened to arrive BEFORE the sell orders. * If the market buy order happened to arrive AFTER the sell orders, XYZ stock would have gone UP in the same time, and the ticker tape would show ...XYZ 1 99…XYZ …XYZ * The order in which market and limit orders arrive at the exchange is RANDOM, depending on when brokers submit them and when they arrive. * That randomness causes short-term unpredictability (risk) proportional to the bid-ask spread -- it is ”random noise in the price signal.” * Exchanges therefore try to keep spreads small -- to a few pennies * Therefore don’t overreact to price changes over short time periods * Try to find out if the price changes are random or the beginning of a trend up or down.

What can you do about risk?
Evaluate it Like taking a pen knife to a gunfight Minimize it without sacrificing returns Avoid downside risk But less risky investments return less Accept downside risk If you are not risk-averse psychologically

Reduce it without sacrificing returns “Buy portfolio insurance” (options) Use options to limit downside risk -- BUT: Difficult math to find a “fair” option price Experts disagree on the math Guesswork is unavoidable (e.g. future interest rates) Complex strategies (combinations of options and stock) High trading fees, losses can be UNBOUNDED If you’re a beginner, your broker won’t even take your order to trade an option because the risks are too great

Reduce it without sacrificing returns Combine uncorrelated investments (“beta hedging,” “diversification”) Diversify across... Market sectors (utilities, high-tech, pharma, hospitality…) Size (“small cap,” “mid cap,” “large cap”) Countries (developed, developing) Debt risk (treasuries, munis, corporate bonds, junk) Funds and exchange-traded funds (ETFs) Roll the dice! Leveraged investments (Beta > 1 or < -1)

Avoid it but still make money Antifragility to Black Swans, (Nicholas Taleb) Predict bubbles and crashes Dragon Kings (Didier Sornette) The Prediction Company (Doyne Farmer) Renaissance Technologies (Jim Simons) Portfolio optimization (Modern Portfolio Theory) Efficient frontier (Harry Markowitz) Sharpe ratio (William Sharpe)

Modern Portfolio Theory Economist Harry Markowitz, Nobel Laureate
High Return * How can we pick the best investments? * Modern Portfolio Theory provides two answers - Prof. Harry Markowitz’ “Efficient Portfolios” - Prof. William Sharpe’s “Sharpe Ratio” * Efficient Portfolios - Select a set of investments (stocks, bonds, options, futures, porfolios...) - Estimate the risk and rate of return for each investment over your investment horizon interval - Plot them in a cluster on a chart showing return versus risk - If two investments have equal risk, the one with higher return is better - If two investments have equal returns, the one with lower risk is better Low T- bills None Low Risk High

High Return Buy Sell * Efficient Portfolios - The best investments will lie along the boundary of the cluster in the direction of high return and low risk (the green stars) Low T- bill None Low Risk High

High Efficient frontier Return Buy Sell * Efficient Portfolios - Draw a line connecting the green stars - Markowitz calls this line the “efficient frontier” - The green stars on the efficient frontier are the “efficient investments.” * To decide what to invest in - Pick one of the efficient investment whose return is closest to the return you need, or, - Pick the efficient investment that has the most risk you are willing to accept, - allocate your funds across two adjacent efficient investments to get an “artificial investment” that has risk and return along the line between them Low T- bill None Low Risk High

Modern Portfolio Theory Professor William Sharpe, Nobel Laureate
High ? Return Buy Sell * Efficient Portfolios * Prof. Sharpe of Stanford U. showed how you can allocate your funds to construct a portfolio that has a higher return and a lower risk than points along the efficient frontier, * The artificial portfolio will lie in the blank area beyond the efficient frontier * If Treasury bills are not included in the investments, add it to the chart * Draw the steepest line from the T-bill that passes through one of the efficient portfolios. * The slope of the line is the “Sharpe ratio,” Low T- bill None Low Risk High

Modern Portfolio Theory Professor William Sharpe, Nobel Laureate
High $ Return Buy Sell * To construct a portfolio whose risk and return lie anywhere along the line, Sharpe said: - Put all your funds into the efficient portfolio on the line - Borrow money at the risk-free rate (the rate of return on a T-bill) - Put the money you borrowed into the efficient portfolio on the line. - The portfolio of the loan plus the long position in the efficient investment has a risk and return that lie along the line in the region beyond the efficient frontier (big green star) - Borrowing more puts the artificial portfolio farther along the line. * If you can’t borrow at that rate, an alternative is to sell T-bills short and pay your broker the T-bill interest rate on the short position. - A brokerage may restrict shorting of Treasury securities. - Margin requirements will limit the size of the short position * The risk and return values will only be estimates based on historical performance, which is no indication of future performance * Markowits and Sharpe make assumptions that may not hold -- e.g., that the risk and return of the various investments are uncorrelated. Low T- bill None Low Risk High

Beta Hedging Try to buy two stocks whose prices are not correlated (don’t always move in the same direction) Difficult to see how correlated two stocks are from the usual stock charts (price vs time) Computer can calculate and plot correlations 3,000 stocks means 4.5 million pairs to compare Published beta values may help find good pairs

Time Series Hide Correlation
Ford Price $ Time GM Price $ Time Do GM & Chrysler prices tend to move up and down together?

Correlation Plot Price $ Ford $ Price GM Time

Ford & GM prices tend to move up and down together.
Correlation Plot Price $ Ford Positive correlation(R > 0) $ Price * When stocks tend to move up and down together, the correlation plot will be a cluster of points that lie along a line with a positive slope (up and to the right). * The angle of the line indicates whether one stock varies more than the other. * The width of the cluster to either side of the line indicates how much the two stocks follow each other up and down. Narrower means more. . * Ford and GM followed each other closely, as expected for two companies in the same sector (automotive) who sell similar products to customers in the same country.. GM Time Ford & GM prices tend to move up and down together.

High Negative Correlation
Acme Snowshoes Sun Tan Lotions, Inc. Time $ Price Price $ Negative correlation (R < 0) * It’s difficult to find two stocks that move in opposite directions. * When they do, the correlation plot lies along a line sloping down to the right . * In this ficticious example the products of Sun Tan Lotion and Snowshoes are likely to sell well at different times of the year, so we would expect revenues and profits to peak in different seasons of the year. * Those results would tend to drive their stock prices up and down in opposite directions. Sun Tan & Acme prices tend to move in opposite directions.

Real Correlation Examples
Yahoo website is a good place to get data Free charts Free price histories suitable for spreadsheets 1786 days of Ford, GM, P&G, & Unilever (7 years of trading) Ford vs GM (automotive sector) P&G vs Unilever (consumer staples sector) P&G vs Ford (cross-sector) P&G vs GM (cross-sector)

Ford vs GM (Automotive Sector)
* Strong (narrow cluster) positive correlation due to similarities of product and market. * On average, Ford went up 37 cents when GM went up $1 * A portfolio shorting 3 shares of Ford for each long GM share would have had low volatility, low risk, and a stable, predictable price. * Portfolio return would hve been GM dividends minus 3 times Ford dividends. * If that return was negative (a loss), then instead shorting 1 GM share for each 3 long Ford would have had a positive return with low risk. * The greater the difference in the stocks’ dividends/share ratios, the better the portfolio return would have been. * BUT: Past performance is no indication of future performance.

P&G vs Unilever (Consumer Staples Sector)

Consumer Staples Sector
P&G vs Ford Consumer Staples Sector Automotive Sector

Consumer Staples Sector
P&G vs GM Consumer Staples Sector Automotive Sector

WARNING !! Correlations are not constant! Climate can change
Cooler summers -- worse for Sun Tan Lotions Warmer winters -- worse for Acme Snowshoes Customer demographics can vary More beachgoers -- better for Sun Tan Lotions More northerners -- better for Acme Snowshoes Gains in one stock may no longer balance losses on the other, so portfolio risk increases

Advanced Topics The Central Limit Theorem and the Black-Scholes formula in options trading Portfolio Optimization (Sharpe) Black swans, Antifragility (Nicolas Taleb) Black dragons (Didier Sornette) High-frequency trading (Michael Lewis) Log-periodic price distributions Levy-stable distributions Fractal geometry * Look these topics up on Wikipedia, Gooogle, or Bing * If they seem interesting, there are lots of books, articles, and tutorials about them for further study.

References Best: The Physics of Wall Street by James Owen Weatherall
A Random Walk Down Wall Street by Burton G. Malkiel Flash Boys by Michael Lewis Chaos Monkeys by Antonio García Martínez * All of these books are easy to read and, entertaing. None have any mathematics. * Weatherall’s book covers more topics thatn any of the others, and deeper, too. * Malkiel’s is aclassic. In print since 1973, it keeps getting up dated and reprinted. The last edition came out in 2015. * Flash Boys is about the computer revolution in the financial industry. It tells how fast computers, high-speed communications, and “algorithmic trading” sllow the big brokerages, commercial banks, funds, and insurance companies to make you pay more and get less for your stocks. *Chaos Monkeys is about the world of high-technology startups in Silicon Valley. It shows you how the sausage gets made, and how some of the sausages get to be worth billions of dollars.

References Nicholas Nassim Taleb
Black Swans Fooled by Randomness Antifragile Why Stock Markets Crash by Didier Sornette The Fractal Geometry of Nature by Benoit Mandelbrot * A” black swan” is a rare but extreme event. In the stock market, they are bubbles and crashes. Taleb says predicting Black Swans is impractical, and all you can do is preparefor them. “Antifragile” is the opposite of “fragile.” In extreme situations an antifragile system doesn’t just survive, it does better. * A “Dragon King” is also a rare but extreme event, but Sornette claims to have found a way to predict them, and has predicted several crashes and ends of bubbles. He is Chair of Entrepreneurial Risks at the Electrotechnische Hochscule in Zurich. * Mandlebrot showed that stock market price histories trace out fractal pattern ( the same patterns of variation occur at any scale of magnification).

References The Investopedia Guide to Wall Speak by Jack Guinan, ed.
Best definitions at Note the button at the bottom of the web page: “Download to Spreadsheet” You’ll get a file “GM.csv” containing “comma-separated values.” Your spreadsheet program (Excel, Numbers) can open that file * If you find an unfamiliar financial term, you can find a clear definition and explanation of it in either the Investopedia book or on its free website. * Yahoo is a great source of detailed price histories for stocks. You can download daily open, close, high, and low prices, plus volume (number of shares traded) for any stock, fund, or exchange traded fund (ETF).

“Past performance is no indication of future performance.”
--Every financial advisor Be Careful Out There !!

Financial Risk for Beginners by William T

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