St. Lawrence Neighborhood in Toronto

St. Lawrence Neighborhood in Toronto

St. Lawrence Market: In 1803, Lieutenant Governor Peter Hunter established a public marketplace in what today is downtown Toronto, where farmers from nearby townships sold produce and livestocks to residents of the town of York (now Toronto). A wooden building was constructed in 1820 and replaced in 1831 by a brick building, which was also used for city council meetings. The market expanded south of Front Street in 1844 with the construction of the Market House and City Hall. It was enlarged again in 1851 when the St. Lawrence Hall and Market was built north of Front Street. The market was an important source of revenue and the City of Toronto rebuilt the north and south market buildings in 1899. The resulting complex, including the present-day south market, was designed by John. W. Siddall and completed in 1904. The market remains an important part of Ontario’s commercial history.(Ontario Heritage Foundation, an agency of the Government of Ontario).

Marché St. Lawrence: En 1803, le lieutenant-gouverneur Peter Hunter créa ici un marché public où les fermiers des cantons avoisinants vendaient leurs produits et bétail aux résidents de la ville de York (Toronto). Un bâtiment en bois érigé en 1820 fut remplacé, en 1831, par un édifice en briques, où avaient aussi lieu les réunions du conseil municipal. La construction de Market House et de l’hôtel de ville, en 1844, entraîna l’expansion du marché au sud de la rue Front. Elle continua au nord de la rue Front avec la construction du St. Lawrence Hall et marché, en 1851. Source importante de revenu, les bâtiments nord et Sud du marché furent reconstruits en 1899 par la ville de Toronto. Terminé en 1904, le complexe, qui inclut le marché Sud actuel, fut conçu par John W. Siddall. Il reste un symbole important de l’histoire commerciale de l’Ontario. (Fondation du patrimoin canadien, un organisme du gouvernement de l’Ontario).

St. Lawrence Hall

A building on Front street and Wellington street corner

St. Lawrence market graffiti

St. Larwrence Hall clock

Credit History: Goodwill Letter to Remove Non Payment

Goodwill Letter to Remove Non Payment from the Credit History

Dear Madam, Sir:

I have enjoyed being Creditcarma customer since XXXXXX I have always been a model customer, but on September XX, 2017 I failed to make one credit payment totaling $XXXXX (XXX dollars and XXX cents). The only reason for the delay was that I wrongly assumed that Creditcarma took the payment automatically, and I do apologize for the situation.

As a result, I fell behind on my payments by about 50 days, but I fully paid the sum due of $XXX (XXX dollars and 96 cents) as soon as I received the Creditcarma alert notification. Based on the amount due you can certainly understand that my finances have not been wrecked, as well as my ability to make timely credit card payments.

At this moment I’m shopping for a mortgage for a new house and I'm afraid this late payment of XXX dollars will keep me from getting the best interest rate.

Bank of Montréal. Photo by Elena

Therefore, I’m kindly requesting a goodwill adjustment since the payments do not reflect my current payment status.

Thank you for your time reading this letter and the consideration you’ve given my situation. I can only assure you that I have not fell behind on my payment in my life before. This is the very first time, and this very important to me.

Once again, I kindly ask you to remove this late payment fee record from my credit history

Thank you.

How Diversification Reduces Risk

How Diversification Reduces Risk

Risk of Portfolio (Standard Deviation of Return)

Total risk – Unsystematic Risk – Systematic Risk. Number of Securities in Portfolio.

Both financial theorists and practitioners agree that investors should be compensated for taking one more risk by a higher expected return. Stock prices must therefore adjust to offer higher returns where more risk is perceived, to ensure that all securities are held by someone. Obviously, risk-averse investors wouldn't buy securities with extra risk without the expectation of extra reward. But not all of the risk of individual securities is relevant in determining the premium for bearing risk. The unsystematic part of the total risk is easily eliminated by adequate diversification. So there is no reason to think that investors will be compensated with a risk premium for bearing unsystematic risk. The only part of total risk that investors will get paid for bearing is systematic risk, the risk that diversification cannot help. Thus, the capital-asset pricing model says that returns (and, therefore, risk premiums) for any stock (or portfolio) will be related to beta, the systematic risk that cannot be diversified away.

The proposition that risk and reward are related is not new. Finance specialists have agreed for years that investors do need to be compensated for taking on more risk. Whait is different about the new investment technology is the definition and measurement of risk. Before the advent of the capital-asset pricing model, it was believed that the return on each security believed that the return from a security varied with the instability of that security's particular performance, that is, with the variability or standard deviation of the returns it produced. The new theory says that the total risk of each individual security is irrelevant. It is only the systematic component of that total instability that is relevant for valuation.

Bank of Nova Scotia. Photo by Elena

While the mathematical proof of this proposition would stun even a Yoda, the logic behind it is fairly simple. Consider a case where there are two groups of securities – Group I and Group II – with 20 securities in each. Suppose that the systematic risk (beta) for each security is 1; that is, each of the securities in the two groups tends to move up and down in tandem with the general market. Now suppose that, because of factors peculiar to the individual securities in Group I, the total risk for each of them is substantially higher than the total risk for each security in Group II. Imagine, for example, that in addition to general market factors the securities in Group I are also particularly susceptible to climatic variations, to changes in exchange rates, and to natural disasters. The specific risk for each of the securities in Group I will therefore be very high. The specific risk for each of the securities in Group II, however, is assumed to be very low, and hence the total risk for each of them will be very low. Schematically, this situation appears as follows:

Group I (20 securities) – Group II (20 securities)

• Systematic risk (beta) = 1 for each security in both cases.
• Specific risk is high for each security is for the Group I and is low for each security in the Group II.
• Total risk is high for each security in the Group I and it is low for each security in the Group II.

Now, according to the old theory, commonly accepted before the advent of the capital-asset pricing model, returns should be higher for a portfolio made up of Group I securities than for a portfolio made up of Group II securities, because each security in Group I has a higher total risk, and risk, as we know, has its reward. The advent of the new investment technology changed that sort of thinking. Under the capital-asset pricing model, returns from both portfolios should be equal. Why?

First, as the number of securities in the portfolio approach 20, the total risk of the portfolio is reduced to its systematic level. All of the unsystematic risk is eliminated. As the number of securities in each portfolio is 20, that means that the unsystematic risk has essentially been washed away: An unexpected weather calamity is balanced bu a favorable exchange rate, and so forth. What remains is only the systematic risk of each stock in the portfolio, which is given by its beta of 1. Hence, a portfolio of Group I securities and a portfolio of Group II securities will perform exactly the same with respect to risk (standard deviation) even though the stocks in Group I display higher total risk than the stocks in Group II.

The old and the new views now meet head on. Under the old system of valuation, Group I securities were regarded as offering a higher return because of their greater risk. The capital-asset pricing model says there is no greater risk in holding Groop O securities if they are in a diversified portfolio. Indeed, if the securities of Group I did offer higher returns, then all rational investors would prefer them over Group II securities and would attempt to rearrange their holdings to capture the higher returns from Group I. But by this very process they would bid up the prices of Group I securities and push down the prices of Group II securities until, with the attain,ment of equilibrium (when investors no longer want to switch from security to security), the portfolio for each group had identical returns, related to the systematic component of their risk (beta) rather than to their total risk (including the unsystematic or specific portions).

Because stocks can be combined in portfolios to eliminate specific risk, only the undiversifiable or systematic risk will command a risk premium. Investors will not get paid for bearing risks that can be diversifed away. This is the basic logic behind the capital-asset pricing model.

In a big fat nutshell, the proof of the capital-asset pricing model (henceforth to be known as CAPM because we economists love to use letter abbreviations) can be stated as follows:

If investors did get an extra return (a risk premium) for bearing unsystematic risk, it would turn out that diversified portfolios made up of stocks with large amounts of unsystematic risk would give large returns than equally risky portfolios of stocks with less unsystematic risk. Investors would snap at the chance to have these higher returns, bidding up the prices of stocks with less unsystematic risk and selling stocks with equivalent bets but lower unsystematic risk. This process would continue until the prospective returns of stocks with the same betas were equalized and no risk premium could be obtained for bearing unsystematic risk. Any other result would be inconsistent with the existence of an efficient market.

The key relationship of the theory can be shown as follows: As the systematic risk (beta) of an individual stock (or portfolio) increases, so does the return an investor can expect. If an investor's portfolio has a beta or zero, as might be the case if all his funds were invested in a bank savings certificate (beta would be zero since the returns from the certificate would not vary at all with swings in the stock market), the investor would receive some modest rate of return, which is generally called the risk-free rate of interest. As the indiviual takes on more risk, however, the return should increase. If the investor holds a portfolio with a beta of 1 (as, for example, holding a share in one of the broad stock-market averages) his return will equal the general return from common stocks. This return has over long periods of time exceeded the risk-free rate of interest, but the investment is a risky one. In certain periods the return is much less than the risk-free rate and involves taking substantial losses. This, as we have said, is precisely what is meant by risk.

Risk and Return According to the Capital-Asset Pricing Model

Those who remember their high school algebra will recall that any straight line can be written as an equation. The equation for the model is Rate of Return = Risk-free Rate + Beta (Return from Market – Risk-free Rate).

Alternately, the equation can be written as an expression for the reisj premium, that is, the rate of return on the portfolio or stock over and above the risk-free rate of interest:

Rate of Return – Risk-free Rate = Beta (Return from Market – Risk-free Rate).

The equation says that the risk premium you get on any stock or portfolio increases directly with the beta value you assume. Some may wonder what relationship beta has to the covariance concept that is so critical in the discussion of portfolio theory. The beta for any security is essentially the same thing as the covariance between that security and the market index as measured on the basis of past experience.

A number of different expected returns are possible simply by adjusting the beta of the portfolio. For example, suppose the investor put half of his money in a savings certificate and half in a share of the market averages. In this case, he would receive a return midway between the risk-free return and the return from the market and his portfolio would have an average beta of 0.5 (in general, the beta of a portfolio is simply the weighted average of the betas of its component parts). The CAPM then asserts very simply that to get a higher average long-run rate of return you should just increase the beta of your portfolio. An investor can get a portfolio with a beta larger than 1 either by buying high-beta stocks or by purchasing a portfolio with average volatility of margin. There was an actual fund proposed by a West Coast bank that would have allowed an investor to buy S&P average on margin, thus increasing both his risk and potential reward. Of course, in times of rapidly declining stock prices, such a fund would have enabled an investor to lose his shirt in a hurry. This may explain why the fund found few customers in the 1870s.

Just as stocks had their fads, so beta came into high fashion by the early 1970s. The Institutional Investor, the glossy prestige magazine that spent most of its pages chronicling the accomplishments of professional money managers, put its imprimatur on the movement in 1971 by featuring on its cover the letters BETA on top of a temple and including as its lead story “The Beta Cult!” The New Way to Measure Risk!” The magazine noted that money men whose mathematics hardly went beyond long division were now “tossing betas around with the abandon of Ph.D.s in statistical theory.” Even the Securities and Exchange Commission gave beta its approval as a risk measure in its Institutional Investors Study Report.

In Wall Street the early beta fans boasted that they could earn higher long-run rates of return simply by buying a few high-beta stocks. Those who thought they were able to tine the market thought they had an even better idea. They would buy high-beta stocks when they thought the market was going up, switching to low-beta ones when they feared the market might decline. To accommodate the enthusiasm for this new investment idea, beta measurement services proliferated among brokers, and it was a symbol of progressiveness for an investment house to provide its own beta estimates. Today, you can obtain beta estimates from brokers such as Merrill Lynch and investment advisory services such as Value Line. The beta boosters on the Street oversold their product with an abandon that would have shocked even the most enthusiastic academic scribblers intent on spreading the beta gospel.

Excerpt from Burton G. Malkiel. A Random Walk Down Wall Street, including a life-cycle guide to personal investing. First edition, 1973, by W.W. Norton and company, Inc.

The Yield Yen

The Yield Yen : A Case History of the Importance of Other Systematic Risk Influences

Is the quant quest for better risk measures an assault on windmills – a useless exercise that succeeds only in enabling academics to continue to play with their computers? No! It has important implications for protecting investors. Take, for example, the yield yen. The yield yen, which attracted a considerable following in the investment community by the 1980s, was the idea that institutional investors should place their funds in a yield-tilted index fund.

The reasoning behind this proposal seemed appealingly plausible. Dividends are generally taxed more highly than capital gains. This was especially true before the Tax Reform Act of 1986. since the market equilibrium is presumably achieved on the basis of after-tax returns, the equilibrium pre-tax returns ought to be higher for stocks that pay high dividends than for securities that produce lower dividends and correspondingly higher capital gains, which, even if fully taxed at regular rates when realized, provide some tax benefits since unrealized capital gains do not bear any tax at all. Hence, the tax-exempt investor should specialize in buying high-dividend-paying stocks. In order to avoid the assumption of any greater risk than is involved in buying the market index, however, this tax-exempt investor is advised to purchase a yield-tilted index fund; that is a very broadly diversified portfolio of high-dividend-paying stocks that mirrors the market index in the sense that it is constructed to have a beta coefficient exactly equal to 1.0.

Even on a priori grounds one might question the logic of the yield-tilted index fund. The validity of the proposal rests on the premise that the major market participants prefer to receive income through capital gains rather than through dividends. But many of the largest investors in the market (such as corporations) actually pay a higher tax on capital gains than on dividend income (For corporate investors, 70 percent of dividend income is currently excluded from taxable income, while capital gains are taxed at normal gains rates). It is far from clear that the most important investors in the stock market prefer to receive income in the form of capital gains. Therefore, the market may not price high-dividend-paying stocks so that they offer especially attractive returns to tax-exempt institutions. But apart from these a priori arguments, the statistical results just reviewed can be interpreted as providing another argument against the yield-tilted index fund.

If the traditional beta calculation does not provide a full description of systematic risk, a yield-tilted index fund may well fail to mirror the market index. Specifically, during periods when inflation and interest rates rise, high-dividend stocks may be particularly vulnerable. Public-utility common stocks are a good example. Although they are known as low-beta stocks, they are likely to have high systematic risk with respect to interest rates and inflation. This is so not only because they are good substitutes for fixed-income securities but also because public utilities are vulnerable to a profits squeeze during periods of rising inflation, as a result of regulatory lags and increased borrowing costs. Hence, the yield-tilted index fund with a beta of 1.0 may not mirror the market index when inflation accelerates.

The actual experience of yield-tilted index funds during the period of their popularity in the early 1980s was far from reassuring. The performance of these funds was significantly worse than that of the market. At other times, high yield stocks have significantly outperformed the market. Of course, we should not reject a model simply because of its failure over any specific short-term period. Nevertheless, we believe that an understanding of the wider aspects of systematic risk, as analyzed here, can potentially help to prevent serious investment errors.

A Summing Up

The stock market appears to be an efficient mechanism that adjusts quite quickly to new information. Neither technical analysis, which analzyes the past price movements of stocks, nor fundamental analysis, which analyzes more basic information about the prospects for individual companies and the economy, seems to yield consistent benefits. It appears that the only way to obtain higher long-run investment returns is to accept greater risks – and those risks can be horrendous, as any investor who has lived through the great bear markets of the late 1960s and 1970s and who suffered through October 1987 can tell you.

Unfortunatley, a perfect risk measure does not exist. Beta, the risk measure from the capital-asset pricing model, looks nice on the surface. It is a simple, easy-to-understand measure of market sensitivity, and differences in long-run rates of return form portfolios are clearly related to that single risk factor.

Unfortunately, beta also has its warts. The actual relationship between beta and rate of return does not correspond to the relationship predicted in theory. Moreover, the relationship is undependable in the short run and has even failed to work in periods as long as a decade, such as the 1980s. Finally, beta is not stable from period to period, and it is sensitive to the particular market proxy against which it is measured.

No single measure is likely to capture adequately the variety pf systematic risk influences on individual stocks and portfolios. The actual relationship between beta and rate of return does not correspond to the relationship predicted in theory. Moreover, the relationship is undependable in the short run and has even failed to work in periods as long as a decade, such as the 1980s. Finally, beta is not stable from period to period, and it is sensitive to the particular market proxy against which it is measured.

I have argued here that no single measure is likely to capture adequately the variety of systematic risk influences on individual stocks and portfolios. Returns are sensitive to general market swings, to changes in interest and inflation rates, to changes in national income, and, undoubtedly, to other economic factors such as exchange rates. And if the best single risk estimate were to be chosen, the traditional beta measure would not be the only possibility. The mystical perfect risk measure is still beyond our grasp.

To the great relief of assistant professors who must publish or perish, there is still much debate within the academic community on risk measurement, and much more empirical testing needs to be done. Undoubtedly, there will yet be many improvements in the techniques of risk analysis, and the quantitative analysis of risk measurement is far from dead. Our guess is that future risk measures will be even more sophisticated – not less so. Nevertheless, we must be careful not to accept beta or any other measure as an easy way to assess risk and to predict future returns with any certainty. You should know about the best of the modern techniques of the new investment technology – they can be useful aids. But there is never going to be a handsome genie who will appear and solve all our investment problems. And even if he did, we would probably foul it up – as did the little lady in the following favorite story of Robert Kirby of Capital Guardian Trust:

She was sitting in her rocking chair on the porch of the retirement home when a little genie appeared and said, ”I’ve decided to grand you three wishes.”

The little old lady answered, “Buzz off, you little twerp, I’ve seen all the wise guys I need to in my life.”

The genie answered, “Look, I’m not kidding. This is for real. Just try me.”

She ahrugged and said, “Okay, turn my rocking chair into solid gold.”

When, in a puff of smoke, he did it, her interest picked up noticeably. She said, “Turn me into a beautiful young maiden.”

Again, in a puff of smoke, he did it. Finally, she said, “Okay, for my third wish turn my cat into a handsome young prince.”

In an instant, there stood the young prince, who then turned to her and asked, “Now aren’t you sorry you had me fixed?”

Intact Insurance. Photo: Elena

The Rise of the Office Romance

The Rise of the Office Romance

Old rules about dating co-workers are giving way to new realities

Ask a couple of our times where they were when Cupid’s arrow struck and chances are they’ll say the office. We’ve become very work-centered, so the reality is that the workplace is now one of our primary meeting places.

Long workdays that leave little time or energy for the social circuit and the increasing presence of women in formerly male-dominated spheres have made the office a viable, even attractive, alternative to cruising the club scene or scanning the personal ads. People in the same line of work can be sure they have at least one major interest in common. And co-workers who date each other avoid fear of the unknown (as Lisa Mainiero, a professor of management at Fairfield University, pointed out in her book Office Romance: Love, Power and Sex in the Workplace.

“With the difficulties involved in meeting people of kindred spirit, and the rampant fear of sexually transmitted diseases, we are more comfortable establishing relationships with those whom we already know well”, she writes.

It also helps that companies are updating their attitudes toward office lovebirds. The fraternization policies that pervades corporate culture in the past almost always required one member of a soon-to-be-married office couple to leave the company.

“The woman usually ended up looking elsewhere for work,” Mainiero says. “In the past decade, corporations have realized that those policies were somewhat neanderthal.”

In fact, a recent Fortune magazine survey of 200 corporate chief executives found that 70 percent of them believe office romance is “none of the company’s business.” And the Society for Human Resource Management reports that in a survey of its members, who are personal managers in industries from construction to finance, nearly 72 percent don’t think employers should be allowed to require a member of a co-working couple to resign if they marry.

You spend too much time listening to what people say. That’s your trouble. (J.R. Tolkien)

Though companies’ approaches to office romance are changing, a slight generation gap is still noticeable in the opinions of their employees. According to Gallup polls, working men and women under 40 are more likely than their older counterparts to say they would consider dating a co-worker.

No surprise there. The younger workforce has a totally different attitude about work anyway. For example, they’re not motivated as much by power and money and success. They tend to look more for a balance between work and family.

Office romances can be wonderful, but they require careful planning and maintenance. Mainiero says the most successful relationships she has come across in her research involve people who work in different departments, have different business contacts, and follow different career paths.

The same tendency among couples: as long as people aren’t working together too closely, there doesn’t seem to be any negative impact on their relationship. One executive actually saw increased productivity when two employees became romantically involved – they spent more time at the office because they weren’t always rushing off to see each other.

Though the office may be a good place to meet a potential mate, the pick-up tactics tolerated at a singles bar are unacceptable at the water cooler. Companies are responding to the increasing awareness of sexual harassment by creating strict policies to deal with the issue. But sexual harassment guidelines shouldn’t be extended to outlaw consensual office romances.

Polices will fail that forbid all relationships. When people find each other attractive, they will act on that. And people who work together can have very satisfying relationships.

Sexual harassment policies have made people a little more cautious, but they are not putting a lid on the number of officer romances. Though people sometimes try to lump them together, the two issues are separate. Trying to control one is not necessarily going to prevent the other.

The benefits of an office relationship can extend even beyond the couple involved. Mainiero’s observations of couples in the workplace have convinced her that their influence can motivate other employees, minimize personality conflicts, and increase communication among departments.

Attraction and romance at work bring out the best in all of us, she writes, as long as it is handled properly by the couple.

In the Company of a Colleague

Some important do’s and don’ts of an office love affaire

Office romantics who want to keep their careers and their love lives out of the circular file should heed to advice to Lisa Mainiero, the author of Office Romance : Love, Power and Sex in the Workplace.

Don’t fall in love with your boss. While peer relationships can be manageable in the workplace, research shows very clearly that hierarchical romance brings up concerns about favoritism, exploitation, and low morale among employees. The lower-level person struggles (usually without success) to live down the stigma of sleeping his or her way to the top, while the higher-level person’s business judgment suddenly looks questionable. People can end up committing career suicide.

Be clear about your intentions, but don’t force the issue. If you sense that your interest in a co-worker is not reciprocated, back off immediately. The office is not the place to be persistent. At the first indication that the other person is not interested, drop your pursuit because if you don’t, it can be considered harassment.

Be professional at all times. Don’t have lunch with your lover every day, hang out in his or her office, or hold hands in the hallway. When you’re at work, act as you would around any other colleague. Most co-working couples with successful relationships lead separate lives at work as much as possible. Some married couples drive in separately, for example, or use different last names. There should be clear boundaries between work and after-hours relationships.

Keep up the professionalism when it’s over. Though breaking up is hard to do, couples who successfully maintain their work relationship after the romance has died have an easier time. It’s a good idea to set up a kind of “psychic contract” at the beginning of the relationship, outlining ground rules for making the office a romance-fee zone and talking about the best way to handle a possible breakup