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Your question could also apply to a company whose shares have been suspended.
My understanding is that in situations like these you still need to 'acquire' the stock at some stage, even if the company's stock is no longer traded on a market.
When a company goes belly up or is suspended, you will always be able to find people happy enough to sell you their shares - after all, they're worth virtually nothing anyway. This I believe is the way you 'deliver' the shares back to the broker who permitted you to short the stock in the first place.
So ... tell all. Who are you thinking of shorting Choccy?
My understanding is that in situations like these you still need to 'acquire' the stock at some stage, even if the company's stock is no longer traded on a market.
When a company goes belly up or is suspended, you will always be able to find people happy enough to sell you their shares - after all, they're worth virtually nothing anyway. This I believe is the way you 'deliver' the shares back to the broker who permitted you to short the stock in the first place.
So ... tell all. Who are you thinking of shorting Choccy?
Chocolate
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Thanks for the reponse. The question was purely theoretical. I use spreadbetting firm finspreads, so maximum gain is (price of share) * (bet size per point), so winnings on shorts are obviously limited. (Aside: this means that odds are better for going long than going short because a stock is more likely to go 50% up than 50% down for example, in theory at least)
I was thinking of stocks such as Scotia Holdings, whose cancer drug was refused by the FDA and the stock subsequently plummeted and has since disappeared. I had bought some stock on the fall, but quickly got out when I found that its market value was about the same as its debt. I am sure there are lots of technology stocks out there which are in the same position. If someone does not take them over, they are running out of money within months. I'm sure QXL is in this position, its price about a hundredth of what it used to be. Of course, EBAY may be generous.
An irritating fact about spread-betting etc is this. If you lose 50% of your money, you then need to double your money in order to get back where you started. This doesn't seem fair in a way. I guess the answer is to deal less agressively.
I think I've deviated from the post subject, but hey!
I was thinking of stocks such as Scotia Holdings, whose cancer drug was refused by the FDA and the stock subsequently plummeted and has since disappeared. I had bought some stock on the fall, but quickly got out when I found that its market value was about the same as its debt. I am sure there are lots of technology stocks out there which are in the same position. If someone does not take them over, they are running out of money within months. I'm sure QXL is in this position, its price about a hundredth of what it used to be. Of course, EBAY may be generous.
An irritating fact about spread-betting etc is this. If you lose 50% of your money, you then need to double your money in order to get back where you started. This doesn't seem fair in a way. I guess the answer is to deal less agressively.
I think I've deviated from the post subject, but hey!
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Hill Farmer
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Chocolate, why do think the odds are higher in favour of a stock going up by 50% than down by 50%?
Chocolate
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That is a good point. If you consider movement of a stock as some kind of random walk, both seem equally likely. I guess my counter-argument would be as follows:
Suppose a stock is equally likely to lose 50% as gain 50%. Let T(1) be time zero. Write down the stock price at time T(1). Let T(2) be the first time when the price of the stock has halved or doubled. Write down the new price. When the stock next doubles or halves from this new price, call it time T(3) etc. By time T
, the stock will have halved about n/2 times and doubled about n/2 times. Its price will be approximately:
((0.50)^(n/2)) x ((1.50)^(n/2))
And here's the crunch:
0.50 * 1.50 = 0.75.
So its average price at time T is (0.75 ^ (n/2)) times its original price, so on our original assumption, the company would most certainly go broke.
This is why I was complaining in my original thread that the same argument applies to me and implies that I am almost certainly going to lose all my money. But that's not fair. Surely something's wrong in the above argument. And I think I have resolved my own paradox.
Yes, I am almost certainly going to lose all my money in the long time because of the above.
BUT if you go through the above argument more carefully and work out the _AVERAGE_ price at time T we find that it is actually the same as the original price. (Use binomial co-efficients to work out probabilities; sorry for technicalities)
Basically, I am almost certainly going to go broke, but I have only a finite amount to lose and an infinite amount to gain, so I may be broke with probability 99%, but with prob. 1% I have 100 times as much money.
SO, how to avoid going broke!?
(I've been betting on small amounts and lost 90% of what I had two weeks ago having doubled my money in the two weeks before that.)
Sorry for the rant.
Suppose a stock is equally likely to lose 50% as gain 50%. Let T(1) be time zero. Write down the stock price at time T(1). Let T(2) be the first time when the price of the stock has halved or doubled. Write down the new price. When the stock next doubles or halves from this new price, call it time T(3) etc. By time T
, the stock will have halved about n/2 times and doubled about n/2 times. Its price will be approximately:((0.50)^(n/2)) x ((1.50)^(n/2))
And here's the crunch:
0.50 * 1.50 = 0.75.
So its average price at time T
is (0.75 ^ (n/2)) times its original price, so on our original assumption, the company would most certainly go broke.This is why I was complaining in my original thread that the same argument applies to me and implies that I am almost certainly going to lose all my money. But that's not fair. Surely something's wrong in the above argument. And I think I have resolved my own paradox.
Yes, I am almost certainly going to lose all my money in the long time because of the above.
BUT if you go through the above argument more carefully and work out the _AVERAGE_ price at time T
we find that it is actually the same as the original price. (Use binomial co-efficients to work out probabilities; sorry for technicalities)Basically, I am almost certainly going to go broke, but I have only a finite amount to lose and an infinite amount to gain, so I may be broke with probability 99%, but with prob. 1% I have 100 times as much money.
SO, how to avoid going broke!?
(I've been betting on small amounts and lost 90% of what I had two weeks ago having doubled my money in the two weeks before that.)
Sorry for the rant.
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Chocolate
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I've been thinking about this a bit further and realised something.
So far in trading, I have have rarely used stops, simply because if a stop is filled, it stops you out at a really bad price, quite likely the low of the day or something. My philosophy in the past has generally been: place a trade and if at all possible, try to exit that trade at a profit. Of course, this means that I lose lots of money with a small probability and little with a large probability.
Now, as is probably well known among members, most pros tend to admit that most of their trades are losing ones, but their winners are big and their losers small. They must have discovered this rule of thumb through their experience, but there is no other way. I you want to make money, you must rely on size of winners and NOT quantity. If not, then your chances of success are much less. WHY?
Because of basically what I was saying in my previous posts. If you win 50% one day and lose it the next, you end up with less than you started with. Let me give an example with figures. Suppose you start with £100:
FINAL AMOUNT
WIN 50% WIN 50% £225
WIN 50% LOSE 50% £ 75
LOSE 50% WIN 50% £ 75
LOSE 50% LOSE 50% £ 25
If your decisions are totally random, ten the probability of a WIN or a LOSS are equal, so all the above are equally likely. Taking their average, we find you would end up with £100 on average as expected.
But notice something. If we keep on trading like this, our average will still be £100, but we are almost certainly going to end up with les than we started. In only one of the above scenarios do we have more than our original £100. Thus the 'fluky' scenarios pull up the average.
Must go now. Post the rest later. But you see what I am getting at.
So far in trading, I have have rarely used stops, simply because if a stop is filled, it stops you out at a really bad price, quite likely the low of the day or something. My philosophy in the past has generally been: place a trade and if at all possible, try to exit that trade at a profit. Of course, this means that I lose lots of money with a small probability and little with a large probability.
Now, as is probably well known among members, most pros tend to admit that most of their trades are losing ones, but their winners are big and their losers small. They must have discovered this rule of thumb through their experience, but there is no other way. I you want to make money, you must rely on size of winners and NOT quantity. If not, then your chances of success are much less. WHY?
Because of basically what I was saying in my previous posts. If you win 50% one day and lose it the next, you end up with less than you started with. Let me give an example with figures. Suppose you start with £100:
FINAL AMOUNT
WIN 50% WIN 50% £225
WIN 50% LOSE 50% £ 75
LOSE 50% WIN 50% £ 75
LOSE 50% LOSE 50% £ 25
If your decisions are totally random, ten the probability of a WIN or a LOSS are equal, so all the above are equally likely. Taking their average, we find you would end up with £100 on average as expected.
But notice something. If we keep on trading like this, our average will still be £100, but we are almost certainly going to end up with les than we started. In only one of the above scenarios do we have more than our original £100. Thus the 'fluky' scenarios pull up the average.
Must go now. Post the rest later. But you see what I am getting at.
Chocolate
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Conclusion from Above:
If I trade by the rule: set limit 50% above, stop 50% below, and assuming my decisions to buy or sell to be random, in a long sequence of trades, I will on average lose on much as I gain. BUT the suprising fact is that if you come back to me at some later time, then the chances of me having more than I started with are very small. On average I will hve had an equal number of WINs and LOSSes and WIN + LOSS is an overall loss. My average is pushed up by the small probability event that WINs far outnumber LOSSes.
Now, suppose my decisions are not random. If they are a bit better han random, I still lose out. My decision making has to be MUCH MUCH better than random in order for the above strategy to work. So how to improve it?
Increasing the percentage stop is going to make things even worse. Suppose we put the stop at 10%, keep limit at 50%. It turns out that if price movement is random, the stop will be hit four times out of five and the limit one time out of five:
(0.9 ^ 4)(1.5) = 0.885...
This is better than the 0.75 from last time. Reducing stop gives further improvement. There are two reasons why we cannot let stop be too small:
1) Commissions, spreads and the like
2) Fuzziness of Data
The first is clear. The second needs more explanation. In currency markets and even in share markets, prices jump around quite a lot due to MM's messing around, volatility and the like. It is important not to get stopped out due to fuzziness in the data, so that data is more like a random walk.
CONCLUSION: Set stop large compared to fuzziness, spread size / commission, but small compared to gain which we hope for.
Of course everyone knows this already. This is just to prove that it is a FACT. There is no other way.
If I trade by the rule: set limit 50% above, stop 50% below, and assuming my decisions to buy or sell to be random, in a long sequence of trades, I will on average lose on much as I gain. BUT the suprising fact is that if you come back to me at some later time, then the chances of me having more than I started with are very small. On average I will hve had an equal number of WINs and LOSSes and WIN + LOSS is an overall loss. My average is pushed up by the small probability event that WINs far outnumber LOSSes.
Now, suppose my decisions are not random. If they are a bit better han random, I still lose out. My decision making has to be MUCH MUCH better than random in order for the above strategy to work. So how to improve it?
Increasing the percentage stop is going to make things even worse. Suppose we put the stop at 10%, keep limit at 50%. It turns out that if price movement is random, the stop will be hit four times out of five and the limit one time out of five:
(0.9 ^ 4)(1.5) = 0.885...
This is better than the 0.75 from last time. Reducing stop gives further improvement. There are two reasons why we cannot let stop be too small:
1) Commissions, spreads and the like
2) Fuzziness of Data
The first is clear. The second needs more explanation. In currency markets and even in share markets, prices jump around quite a lot due to MM's messing around, volatility and the like. It is important not to get stopped out due to fuzziness in the data, so that data is more like a random walk.
CONCLUSION: Set stop large compared to fuzziness, spread size / commission, but small compared to gain which we hope for.
Of course everyone knows this already. This is just to prove that it is a FACT. There is no other way.
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