I have tweaked the model once more. As I gain more knowledge the model gets more sophisticated. Note this does not mean I curve fit. There is zero back testing in the model to calibrate parameters. The model changes as I get more sophisticated, and then I simply modify the equation.
What I have noticed since the new update is, the model and SPX agree within two handles of each other. Now, one would think this is great, he has found the holy grail, right? Well, I ask you, even though I think I have a decent (or even nearly perfect) understanding of how the SPX is priced, what good does it do to know that the SPX is perfectly priced to within two handles? As far as I can tell, two handle difference could easily be attributed to noise and it is probably close to impossible for me to take advantage of it.
So this creates the next conundrum. If NFV always says that SPX is essentially priced "correctly" to within two handles, what good is it? Allow me to answer that question with an analogy. My current thinking is that the market is like an organism, with genes that are constantly expressing or repressed at any given time. So say my model has three parameters, price of gold, price of oil, price of GE, and by some machinery, I take those three values and out comes a number. If I used the three parameters like this, SPX = GOLD + OIL + GE, implicit in that equation is that there are weights to each of those parameters, or more explicitly, a*GOLD + b*OIL + c*GE = SPX, in this case a = b = c = 1. So abc is the genome that gives how expressive each parameter is, in this case the genome is 111. If the genome was 101, the equation would become, SPX = 1* GOLD + 0 * OIL + 1*GE, or if the genome is .5.5.8, the equation would become SPX = .5*GOLD + .5*OIL + .8*GE.
Now here is the point. My genes comprising the genome are all 1 at this point. The reason is that so far, having the genes be exactly 1 gives me the price of SPX to within two handles. I am actually hoping that this is false (not too much to ask for since I am 98% sure that as markets change the gene expression will need to change), and then the question becomes one of predicting what the gene expression will be "better" than the market currently expresses (this would then pass subtlety from biology to information theory). The point is that if my equation is right and there is no prediction (gene expression is always 1 and the list of parameters never change), then it is all hopeless, because that would mean that while I found the holy grail, it would mean that I would have no edge in trading it since the market would be nearly 100% efficient from the point of view of my model.
Another possibility is that I am simply too dumb to understand how to make use of what I have now without having to wait for the gene expression that makes up my parameters to change.
"NFV" ~1179.69
At the time of that I wrote that, SPX = 1,179.48. It has been tracking it almost exactly for three days counting, in realtime.
What I have noticed since the new update is, the model and SPX agree within two handles of each other. Now, one would think this is great, he has found the holy grail, right? Well, I ask you, even though I think I have a decent (or even nearly perfect) understanding of how the SPX is priced, what good does it do to know that the SPX is perfectly priced to within two handles? As far as I can tell, two handle difference could easily be attributed to noise and it is probably close to impossible for me to take advantage of it.
So this creates the next conundrum. If NFV always says that SPX is essentially priced "correctly" to within two handles, what good is it? Allow me to answer that question with an analogy. My current thinking is that the market is like an organism, with genes that are constantly expressing or repressed at any given time. So say my model has three parameters, price of gold, price of oil, price of GE, and by some machinery, I take those three values and out comes a number. If I used the three parameters like this, SPX = GOLD + OIL + GE, implicit in that equation is that there are weights to each of those parameters, or more explicitly, a*GOLD + b*OIL + c*GE = SPX, in this case a = b = c = 1. So abc is the genome that gives how expressive each parameter is, in this case the genome is 111. If the genome was 101, the equation would become, SPX = 1* GOLD + 0 * OIL + 1*GE, or if the genome is .5.5.8, the equation would become SPX = .5*GOLD + .5*OIL + .8*GE.
Now here is the point. My genes comprising the genome are all 1 at this point. The reason is that so far, having the genes be exactly 1 gives me the price of SPX to within two handles. I am actually hoping that this is false (not too much to ask for since I am 98% sure that as markets change the gene expression will need to change), and then the question becomes one of predicting what the gene expression will be "better" than the market currently expresses (this would then pass subtlety from biology to information theory). The point is that if my equation is right and there is no prediction (gene expression is always 1 and the list of parameters never change), then it is all hopeless, because that would mean that while I found the holy grail, it would mean that I would have no edge in trading it since the market would be nearly 100% efficient from the point of view of my model.
Another possibility is that I am simply too dumb to understand how to make use of what I have now without having to wait for the gene expression that makes up my parameters to change.
"NFV" ~1179.69
At the time of that I wrote that, SPX = 1,179.48. It has been tracking it almost exactly for three days counting, in realtime.
