fairy_smile
Members
-
Joined
-
Last visited
Reputation Activity
-
fairy_smile reacted to siniri in The Official Stock Market Boardfairy_smile, I made that mistake with POWR -- it was at a record low, so I bought 1k. And then I bought another k. And it never rose. And I rode it all the way down. And years later, it's still not risen. Had I caught it on one of the earlier times when it had come down and then rebounded, I'd have been fine. But it's risky. I had the NP to spare and nothing I was burning to spend them on, but I haven't been willing to risk that kind of loss again. Consider it a gamble -- like spinning the Wheel of Extravagance or betting on Food Club without calculating arbitrage. To give you an idea of how much it can burn, here's my bottom line:
Totals: 683,500 16,648,500 12,714,500 -23.63%
And here's how much those POWR losses contribute to that overall loss:
I'm a little embarrassed to share that, but if it can spare someone else the loss, it's worth the embarrassment. If you're going to gamble on the market like this, have some rules to minimize your losses:
1) Only use money you don't mind losing*
2) Have a bottom sellpoint so if you caught it on a plummet, you can minimize your loss (*so the amount you're willing to lose should be the amount you spend minus this sellpoint, plus a buffer depending on how often you check on stocks).
3) Have a top sellpoint (to cash in while you can, so you don't go past the next crest and lose all your winnings) -- this can be either a flat NP value, or you can have a rule (e.g., I sometimes use a rule that once it loses 10% from its peak, I sell all I have left, so that I catch it near the peak -- sometimes it jumps back up beyond that peak, so I lose out on additional profit, but that's rarer than if I had a 5% rule. Of course, by not having a 5% rule, I sell at a slightly lower price when there are no extra peaks -- but since stocks do fluctuate, I found 5% to not be very good at capturing the "true" peak. You could probably pick a better % sell rule based on Neodaq data; mine was empirically derived.)