Category Archives: trading

Tradervue launches today!

Well, it’s been a while in the making, but today I’m very excited to announce the launch of Tradervue, a web application for active traders!

When I left my full-time position at NewsGator about a year and a half ago, I started actively trading equities intraday. Yep, one of those day traders. I was thinking “I’m an engineer, how hard can this be?” Ha! Turns out it was harder than I thought.

I spent some time searching for a trading methodology that worked for me, and one that specifically worked for my personality. I like instant gratification – I often use overnight shipping when I order things, I hate that my TV takes 10 seconds or so to warm up, and I like trading during the day where I’m not subject to the whims of the market overnight when I can’t do much about it.

I eventually settled into a rhythm, with the help of many smart traders I met online, where I was trading actively moving stocks that had some catalyst for moving that day (earnings announcement, fresh news, etc.), and I would watch the order flow and do my thing. I worked pretty hard at it – I was at the screens an hour before the market opened, would trade most of the day, and then a few hours of prep work at night for the next day.

I also kept a trading journal in Pages (a word processor), where I would write down why I was making certain trades, how I was feeling about it at the time (confident, anxious, etc.), and I’d paste in order execution data and charts from my trading platform at the end of the day. I’d review this journal at the end of the week, and try to learn from my successful and not-so-successful trades. All in all, this was one of the best tools I had for understanding my trading.

But I hated keeping it.

I didn’t mind writing in it – why I was taking a trade, what was making me nervous about it, etc. That part was easy, and pseudo-creative work. What I hated was having to paste in my execution data, and pasting charts into it from my trading platform. It ended up being about an hour of busy-work at the end of every trading day. Once I even caught myself not taking a quick trade because I didn’t want to add even more work to my after-close routine. Obviously not good; my very best tool for improving my trading was becoming so onerous it was discouraging me from trading.

On the advice of many experienced traders, I also made a list of trading goals for the year. For 2011, two of my non-P&L-related trading goals were a) continue keeping my trading journal, because I was learning a lot from doing it, and b) come up with a way to objectively analyze my data to understand strengths and weaknesses that might not be obvious. For the second item, my hope was to find a product that would just work for me; I looked around for a while, but never found anything that “clicked.”

So with these two things in the back of my mind, I set to work to build something, just for myself, to address them. Find a way to write in my journal, but have the busy work be automated. Find a way to load all of my trading data, and show me views of it I haven’t seen before. Show me what’s working. And show me what’s not.

As I was building this, somehow I got distracted and decided to refocus a bit, and build a web application that could do this for everyone. And so was born Tradervue.

As Tradervue was taking shape, in the back of my mind I was thinking about the trading community I had learned a lot from, and the traders that actively share their ideas online on Twitter, StockTwits, and their blogs. What I have rarely seen is traders sharing actual trades. I don’t mean the sensitive data like how many shares were traded, or how much money was made – that’s not important. Rather, things like where did you enter this trade? How did you get in when it popped through the price level you were watching, but then dropped 0.50 before moving higher? When did you start to sell? Questions like that. Execution is everything – and so perhaps show people how you executed.

As I thought more about this, I noted that Tradervue had all of the data necessary to share trades. The challenge was more a matter of figuring out specifically what information should be excluded and kept private, and then make it easy to share the more educational parts. Shouldn’t it just be a click or two to share a trade with the community, complete with charts and commentary? I thought so.

So I built the sharing into Tradervue. And combined with the trading journal capabilities (with generated charts) and the analysis it can do, allowing you to drill down as far as you want, I think it’s a pretty cool product.

There were beta users whose average session length was measured in hours, with no more than a few minutes idle during that period. It was quite amazing, and exciting; I’m even more excited to see where it goes from here.

So, happy birthday to Tradervue – today is its day!

Implied Volatility

As many of you know, I’ve been spending much of my time lately trading stocks and options. It’s been quite an adventure – I went from being a buy-and-holder starting in the mid-90′s, to a day trader who thinks of a long-term position as something I hold over lunch. :-)

The longer-term positions I do hold are usually option positions. Over the last year or so, I’ve been learning the ins and outs of option trading; the greeks, the vix, implied volatility, all of that. I remember one of the first articles I read about the greeks – all I could think was, how am I supposed to remember all this? But as time goes on, things all started becoming more clear.

Except, of course, for this concept of implied volatility.

Now, just like everybody else, I read that there’s this thing called the Black-Scholes model for option pricing, and you plug in a bunch of stuff and out comes the price of the option. Most of what goes into that calculation (or one of the other options pricing models) are facts – the current stock price, time to expiration, etc. But part of what goes into that is this notion of expected, or implied, volatility.

Hmm. At first glance one would assume this implied volatility has something to do with the historical volatility. While that’s partially true in most cases, it’s not a good assumption.

augen1.jpgAnd then finally, out of the blue, it all clicked. I was reading The Volatility Edge in Options Trading by Jeff Augen, which is a fantastic (but definitely non-beginner) book which discusses some statistical approaches to option trading. And somewhere in this book, it all suddenly became clear.

At a given moment in time, where all other things are equal (so all other variables are fixed), the price of an option is related to its implied volatility (IV). If IV goes up, the price goes up.  Ok, great. Didn’t need a long blog post for that.

But you can also think of it the other way. If price goes up, IV goes up. And make no mistake – fancy equations aside, options are priced based on supply and demand.

IV isn’t something magical that’s calculated by “them”, and foisted on the rest of us. Rather, one can think of it as a way to express how much premium exists in an option. If an option is trading on the offer, you’ll see IV higher than if it’s trading on the bid, because the transaction price is higher.  If you buy enough of them to drive up the price, that will manifest as a higher IV.  And in the last few hours of option trading on expiration Friday, when there’s technically still a day to expiration (equity options technically expire on Saturday), you’ll see the IV drop to nearly zero in order for the option price to drop to its intrinsic value.

I’m sure many will argue, and most won’t care…but this was really the last piece of the way options are priced to “click” for me. So I wanted to write it down, in the hopes of helping someone else get through it all a little more easily.