how does one make a 280% loss? the highest you can make is 100%. unless ur short selling or using borrowed funds

You can make even 1000% loss. Loss is the opposite of profit.

Hi. I believe you can agree that its the share that has slid 1000% but the shareholder has not wiped out 100% of initial investment

Hahaha. Kujiconsole. What if you bought 6 and sold at 66 your gain is?

Your calculation is flawed.

Wazuan accountants, analysts tafadhali saidieni

Haha hehe This maths needs a primary school kid not an accountant. @Obiero uliyowekeza not ulichowekeza kama wilbroda haha. @newfarer Rudi usome hesabu ya profit and loss iko class 4/5 hapo. when the share gets to zero...that is 100% loss no more. You can't losse what you didn't have. Losses do not go beyond 100% save for cases mentioned up there earlier. Profits can be even into millions of %. You can gain many much as you can.

Ok i have seen the argument.
Sale Price - purchase price over purchase price.makosa imefanyika aka nimekubali makosa

Usually everything has to be the difference between the buying price and selling price divided by the buying pricettimes one hundred.iIn this case of buying at 6 shillings and selling at 66 shillings then it's

66 ( selling price)- 6 (buying price) = 60 profit .
then (60/6) X 100 = 1000% profit .

everything has to be divided over the original buying price .
In the first case you bought at 66 and sold at 6 then it's
Selling price - buying price = gain or loss
6 - 66= loss of 60 shillings

now to ccalculate the percentage loss
(Profit or gain)/buying price X 100= percentage of gain or loss
In this case

(60/66) X 100= 90 % loss .

NB in shares anything of loss above 100% loss isn't practical( in this case 280%) . simple because you buy something at shillings 100
then
50% loss is 50/100X 100
equals to selling price of 50

80% loss of same is 80/100X100= 80 shillings loss which equals to selling price of 100-80= 20 shillings

100% loss of same is 100/100X100=100 shilling equals to selling price 100-100 = selling price of 0 shillings yaani you have given it free to a buyer

now 280% loss means the sale of the shares has to be 280/100x100 = loss of 280 shillings hence the selling price is 100-280= selling price of - 180 and Iv never seen shares trade at that figure . ni kama ni mboga unauza it means you pay a buyer 180 shillings to buy your mboga instead of the other way round

Saa ingine accounting is doing what the client want to hear. See the unfair treatment of loss and the hype on profit.
They are calling it a 1000% slide in share price halafu on the other side they hype it as 1000% profit when we move from 6 to 66 and 66 to 6. That was my argument.
But Anyway ni sawa tu that's what investors want to hear. Ndio nikakubali yaishe.

You announce profits on roof tops but whisper losses

@ obiero, KQ can be a good case study for behavioural finance scientists especially as regards to
• The stock volatility.
Relate KQ price movement to the company fundamentals. In a rational world, prices change only when news arrives. Since Robert Shiller's early work was published in 1981 -economists have realized that aggregate stock prices appear to move much more than can be justified by changes in intrinsic value (as measured by, say, the present value of future dividends). Shiller's work generated long and complex controversy, his conclusion is generally thought to be correct: Stock and bond prices are more volatile than advocates of rational efficient market theory would predict

• The predictability of the stock price. (Copy, paste)
In an efficient market, future returns cannot be predicted on the basis of existing information. Thirty years ago, financial economists thought this most basic assumption of the efficient market hypothesis was true (Fama 1970). Now, everyone agrees that stock prices are at least partly predictable (see, for example, Fama 1991) on the basis of past returns, such measures of value as price-to-earnings or price-to-book ratios, company announcements of earnings, dividend changes, and share repurchases and seasoned equity offerings. Although considerable controversy remains about whether the observed predictability is best explained by mispricing or risk, no one has been able to specify an observable, as opposed to theoretical or metaphysical, risk measure that can explain the existing data pattern (see, for example, Lakonishok, Shleifer, and Vishny 1994). Further-more, the charge that these studies are the inevitable result of data mining is belied by the fact that the authors have covered every important corporate announcement that a company can make. Academics have not selectively studied a few obscure situations and published only those results. Rather, it seems closer to the truth to say that virtually every possible trigger produces apparent excess returns. What should one conclude from these and other empirical facts? On one side of the coin is my own conclusion: In many important ways, real financial markets do not resemble the ones we would imagine if we only read finance textbooks. On the other side of the coin is the compelling evidence that markets are efficient: the performance of active fund managers. Many studies have documented the underperformance of mutual fund managers and pension fund managers relative to passive investment strategies (see, for example, Malkiel1 995).Furthermore, although there are always some good performers, good performance this year fails to predict good performance the following year, on average (see, for example, Carhart 1997). These cold facts should be kept firmly in mind when evaluating market efficiency. Regardless of the results of academic studies reporting apparently successful trading rules, real-world portfolio managers apparently have no easy time beating the market. This brief discussion of some of the empirical literature should leave the reader with a mixed impression. Market behavior often diverges from what we would expect in a rational efficient market, but these anomalies do not create such large profit opportunities that active fund managers as a group earn abnormal returns. No inherent contra-diction exists in this combination of facts, although economists have often been confused on this point. A drunk walking through a field can create a random walk, despite the fact that no one would call his choice of direction rational. Still, if asset prices depended on the path the drunk adopted, it would be a good idea to study how drunks navigate.

It's called thinking out of the box. Its questioning simple things which begets bigger things. Ref Isaac Newton Apple. When the apple hit his nyeri area the pain made him think hard.. Science has proved beyond doubt that small heads think faster than bigger ones ask swenani