Should Worldwide Stock Markets Stop Electronic Trading Using Algorithms?

We’ve entered the age of the Algorithm, which is the age when computer programs run and make decisions that affect our lives. These Algorithms have already become quite good at beating most experts at games such as chess, poker and checkers, but there are others that can also beat the common investor in stocks. Currently we’re witnessing the Darwinian battle of the remaining Algorithms in the trading of stocks. These successful Algorithms have made a great deal of money for their investors, so there is a reluctance to abandon them, but we are in unique and unprecedented times that require us to think about the higher order effects on the overall equilibrium and stability of the global markets.

Many successful Hedge funds have used stock trading algorithms to make billions of dollars. Now that many investors have learned that the way to make a small fortune in the stock markets is to start with a larger one, these trading algorithms are left and pitted against one another. However, there are flaws with regulators allowing these scenarios to be played out. One flaw is that the overly successful algorithms will extract billions of dollars in wealth out of the markets. Any market strategy that wins repeatedly will eventually ruin the markets for everyone else. This has to be recognized by the market regulators and eventually corrected in order to maintain orderly markets.

Previously, some market rules and regulations may have functioned as brakes on the rapid electronic trading using these algorithms. Unintended consequences that may have made algorithmic trading more difficult may have resulted from the suspension of these rules such as the uptick rule. These have to be carefully considered by market regulators as necessary brakes on these powerful funds.

An interesting evolutionary perspective from these epic Darwinian struggles suggests that it isn’t necessarily for the best to eliminate all competition in evolving systems. Of course this raises many questions, such as: “What is the best?” and “What is the purpose of evolving systems?”, that can’t be answered here in terse and nonphilosophical words. Even the purpose of competition, itself, becomes a philosophical conundrum in this context, so I should stop here.

Credit Default Swaps and the Financial Crisis

A couple months ago, most of us never heard about credit default swaps (CDS), but now we learn that they may be at the heart of the financial crisis. This is primarily because many banks and financial institutions have credit default swaps on their books and no one knows how to value them or how much these financial institutions may owe.

According to Wikipedia (http://en.wikipedia.org/wiki/Credit_default_swap):

A credit default swap (CDS) is a swap contract in which a buyer makes a series of payments to a seller, and in exchange receives the right to a payoff if a credit instrument goes into default or on the occurrence of a specified credit event, for example bankruptcy or restructuring. The associated instrument does not need to be associated with the buyer or the seller of this contract.

Estimates of the credit default swap market has grown to the tens of trillions, (yes, that’s trillions), of dollars. It is now estimated to be larger than the world’s GDP. This has caused many institutions to hoard cash and not lend to others for fear that many have these “toxic debts” on their books.

Why don’t we make credit default swaps illegal? They will always remain as a source of doubt about financial institutions. Those who’ve engaged in these unregulated practices will just have to eat their loses, which they appear to be doing now. Just look at the recent auction of Lehman Brother’s credit default swaps, which yielded about 8 cents on the dollar. Wouldn’t we be better off legislating them all away and starting again from zero?

The Market Mess

Having been glued to the set last week watching the financial crises, I can’t help but wonder if we have finally come to the end of this problem... Perhaps we need to stop the whole mortgage derivative business and go back to the more simple time of mortgage lending...

The Structure and Function of G Protein-Coupled Receptors

For those who may wish to understand my and my collaborator's work on the structure and function of G protein-coupled receptors, I’ve provided the following links to the papers that are most important for understanding this work. I like to bunch them into groups of three. First are:


Weber's Law Modeled by the Mathematical Description of a Beam Balance, Mathematical Biosciences 122: 89-94 (1994)

Method for determining drug compositions to prevent desensitization of cellular receptors, US Patent # 5,597,699 (1997)

Activation of G Protein-Coupled Receptors Entails Cysteine Modulation of Agonist Binding, J. Molecular Structure (Theochem), 430/1-3: 57-71 (1998)

The next three papers are:

Compositions to enhance the safety and efficacy of bio-pharmaceutical drugs. US Patent# 6,593,094 (2003)

Optimal Agonist/Antagonist Combinations Maintain Receptor Response by Preventing Rapid Beta-1 adrenergic Receptor Desensitization Intl. J. Pharmacol., 1(2): 122-131, (2005)

Molecular dynamics of a biophysical model for beta-2-adrenergic and G protein-coupled receptor activation Journal of Molecular Graphics and Modelling 25: 396-409 (2006)

The Calcium Gate Hypothesis of Cancer

In 1978 I was finishing my Masters in Public Health at the University of Michigan School of Public Health. I had fallen under the spell of Dr. Bruce Chin who was enthusiastically studying the mechanisms of carcinogenesis. I took his advanced class in understanding the cellular mechanisms of cancer three times. During this time, I also developed my ideas that there must be a crucial switch that turns this cancerous process on and off and that the most likely candidate for this switch was an as yet unknown calcium gate that could be controlled by phosphorylation and dephosphorylation. This gate would be analogous to the then known cardiac gate controlled by phospholamban, which was discovered by Dr. Madeleine Kirchberger at the Mount Sinai School of Medicine in New York. I wrote this hypothesis into a paper that I submitted to the Journal of Theoretical Biology, but it wasn’t accepted for publication.

Ironically I came to New York in 1979 and later found myself working in Dr. Kirchberger’s lab on a project to isolate and purify phospholamban, but phopholamban is a membrane bound protein that was more difficult to purify than we initially thought and since I couldn’t reproduce my initial results, I had to drop this project and start a new project for a Ph.D. thesis. However, I very much admired the rigorous research integrity and intensity of Dr. Kirchberger’s lab and I learned a great deal about phospholamban and calcium signaling in the heart. I was still convinced that there must be a connection between the uncontrolled cell division in cancer cells and the control of the calcium gate in normal cells. I discussed this idea with many scientists because I wanted to find someone who was working in this area, but it still needed much more development to become a mainstream idea.

Years passed and I periodically scanned the literature to see if there had been more thought about the calcium gate hypothesis and cancer. The cancer field seemed to take off in the direction of a balance between kinase and phosphatase control of the cell’s metabolic machinery. This seemed to be promising since I had thought that the calcium gate would be controlled by the kinase and phosphatase molecules. The calcium field seemed to have its own direction and developed into an important field of research focusing on the myriad number of enzymes and kinases controlled by calcium signals. However, there didn’t appear to be a direct connection made between a particular kinase/phosphatase pair that were crucial in controlling a start/stop point in cell division.

This has now begun to change and suggests a redox sensitive switch -see:

http://www.ncbi.nlm.nih.gov/pubmed/18377233?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum

http://www.ncbi.nlm.nih.gov/pubmed/17168752?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DiscoveryPanel.Pubmed_Discovery_RA&linkpos=5&log$=relatedarticles&logdbfrom=pubmed

http://www.ncbi.nlm.nih.gov/pubmed/18544350?ordinalpos=2&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum

http://www.ncbi.nlm.nih.gov/pubmed/18372105?ordinalpos=20&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum

http://www.ncbi.nlm.nih.gov/pubmed/18671159?ordinalpos=11&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum

http://www.ncbi.nlm.nih.gov/pubmed/18466777?ordinalpos=10&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum


Is it just coincidence that oncogenes and calcium control genes are near each other? The following list contains searches for oncogenes that happen to appear near to calcium control genes (clicking on the links give GOOGLE searches for the oncogene and the calcium gene and cancer):


27
Hs
ABL2
v-abl Abelson murine leukemia viral
oncogene homolog 2 (arg, Abelson-related
gene)
1q24-q25


777
Hs
CACNA1E
calcium channel, voltage-dependent,
alpha 1E subunit
1q25-q31

http://www.google.com/search?hl=en&lr=&suggon=0&safe=off&as_qdr=all&q=%221q24-q25%22+1q25-q31&as_q=cancer&btnG=Search%C2%A0within%C2%A0results



208
Hs
AKT2
v-akt murine thymoma viral oncogene
homolog 2
19q13.1-q13.2

773
Hs
CACNA1A
calcium channel, voltage-dependent,P/Q type, alpha 1A subunit
19p13.1-p13.2


51476
Hs
CABP3
calcium binding protein 3
19q13.33

http://www.google.com/search?hl=en&lr=&suggon=0&safe=off&as_qdr=all&q=%2219q13.1-q13.2+%22+19q13.33&as_q=cancer&btnG=Search%C2%A0within%C2%A0results



867
Hs
CBL
Cas-Br-M (murine) ecotropic retroviral
transforming sequence
11q23.3

57010
Hs
CABP4
calcium binding protein 4
11



781
Hs
CACNA2D1
calcium channel, voltage-dependent,
alpha 2/delta subunit 1
7q21-q22
673
Hs
BRAF
v-raf murine sarcoma viral oncogene
homolog B1
7q34

674
HsBRAFP
v-raf murine sarcoma viral oncogene
homolog B1 pseudogene
7q34

http://www.google.com/search?hl=en&lr=&suggon=0&safe=off&as_qdr=all&q=%227q34+%22+7q21-q22&as_q=cancer&btnG=Search%C2%A0within%C2%A0results


12298
Mm
Cacnb4
calcium channel beta 4 subunit
2 33.9 cM
12170
Mm
Bmyc
brain expressed myelocytomatosis
oncogene
2


782
Hs
CACNB1
calcium channel, voltage-dependent,
beta 1 subunit
17q21-q22
1398
Hs
CRK
v-crk avian sarcoma virus CT10 oncogene
homolog
17p13.3



54245
Rn
Crk
v-crk avian sarcoma virus CT10 oncogene
homolog
10
783
Hs
CACNB2calcium channel, voltage-dependent,
beta 2 subunit
10p12

12296
Mm
Cacnb2
calcium channel beta 2 subunit
2 14.5 cM

12298
Mm
Cacnb4
calcium channel beta 4 subunit
2 33.9 cM

12170
Mm
Bmyc
brain expressed myelocytomatosis
oncogene
2



773
Hs
CACNA1A
calcium channel, voltage-dependent,
P/Q type, alpha 1A subunit
19p13.1-p13.2

1398
Hs
CRK
v-crk avian sarcoma virus CT10 oncogene
homolog
17p13.3

http://www.google.com/search?hl=en&lr=&suggon=0&safe=off&as_qdr=all&q=%2217p13.3+%22+19p13.1-p13.2&as_q=cancer&btnG=Search%C2%A0within%C2%A0results



775
HsCACNA1C
calcium channel, voltage-dependent, L
type, alpha 1C subunit
12p13.3
1398
Hs
CRK
v-crk avian sarcoma virus CT10 oncogene
homolog
17p13.3

http://www.google.com/search?hl=en&lr=&suggon=0&safe=off&as_qdr=all&q=%2217p13.3+%22+12p13.3&as_q=cancer&btnG=Search%C2%A0within%C2%A0results

778
Hs
CACNA1F
calcium channel, voltage-dependent,
alpha 1F subunit
Xp11.23
867
Hs
CBL
Cas-Br-M (murine) ecotropic retroviral
transforming sequence
11q23.3

http://www.google.com/search?hl=en&lr=&suggon=0&safe=off&as_qdr=all&q=%2211q23.3%22+Xp11.23&as_q=cancer&btnG=Search%C2%A0within%C2%A0results



8911
Hs
CACNA1I
calcium channel, voltage-dependent,
alpha 1I subunit
22q13.1

1399
Hs
CRKL
v-crk avian sarcoma virus CT10 oncogene
homolog-like
22q11.21

http://www.google.com/search?hl=en&lr=&suggon=0&safe=off&as_qdr=all&q=%2222q11.21%22+22q13.1&as_q=cancer&btnG=Search%C2%A0within%C2%A0results


782
Hs
CACNB1
calcium channel, voltage-dependent,
beta 1 subunit
17q21-q22

1398
Hs
CRK
v-crk avian sarcoma virus CT10 oncogene
homolog
17p13.3

http://www.google.com/search?hl=en&lr=&suggon=0&safe=off&as_qdr=all&q=%2217p13.3%22+17q21-q22&as_q=cancer&btnG=Search%C2%A0within%C2%A0results


12295
Mm
Cacnb1
calcium channel beta 1 subunit
11 58.0 cM
12928
Mm
Crko
avian sarcoma virus CT10 (v-crk)
oncogene homolog
11 44.15 cM

http://www.google.com/search?hl=en&lr=&suggon=0&safe=off&as_qdr=all&q=%2211+44.15+cM%22+11+58.0+cM&as_q=cancer&btnG=Search%C2%A0within%C2%A0results


1436
Hs
CSF1R
colony stimulating factor 1 receptor,
formerly McDonough feline sarcoma viral
(v-fms) oncogene homolog
5q33-q35
Links309
Hs
ANXA6
annexin A6
5q32-q34



776
Hs
CACNA1D
calcium channel, voltage-dependent, L
type, alpha 1D subunit
3p14.3

1894
Hs
ECT2
epithelial cell transforming sequence 2
oncogene
3q26.1-q26.2

http://www.google.com/search?hl=en&lr=&suggon=0&safe=off&as_qdr=all&q=%223q26.1-q26.2%22+3p14.3&as_q=cancer&btnG=Search%C2%A0within%C2%A0results

12291
Mm
Cacna1g
calcium channel, voltage-dependent, T
type, alpha 1G subunit
11
13649
Mm
Egfr
epidermal growth factor receptor
11 9.0 cM


12295
Mm
Cacnb1
calcium channel beta 1 subunit
11 58.0 cM

13649Mm
Egfr
epidermal growth factor receptor
11 9.0 cM



24329
Rn
Egfr
Epidermal growth factor receptor, formerly
avian erythroblastic leukemia viral (v-erbB)
oncogene homolog (Erbb1)
14

12289
Mm
Cacna1d
calcium channel, voltage-dependent, L
type, alpha 1D subunit
14 8.0 cM

54234
Rn
Cacna1e
calcium channel, voltage-dependent, L
type, alpha 1E subunit



2002
Hs
ELK1
ELK1, member of ETS oncogene family
Xp11.2

778
Hs
CACNA1F
calcium channel, voltage-dependent,
alpha 1F subunit
Xp11.23

http://www.google.com/search?hl=en&lr=&suggon=0&safe=off&as_qdr=all&q=Xp11.2+Xp11.23&as_q=cancer&btnG=Search%C2%A0within%C2%A0results

A Creative Financial Fix to the Mortgage Crises?

Rick Santelli of CNBC (see - http://www.cnbc.com/id/15837966/) suggested that we create an opportunity for young home buyers to purchase foreclosed properties. There are pluses and minuses to such deals, but the underlying theme is that we need to create a way out of the mortgage crises. An interesting point that Rick made is that we (investors and financial institutions) must “bite the bullet” and step up to invest in new mortgage backed instruments. As a small investor, I agree that investors should invest some of their money to promote the greater good. However, this is sometimes difficult to see and reconcile with the capitalist creed to make money...

How to turn the mortgage crises around so that we have a win-win scenario? Perhaps there could be a way to interest REITs in the housing market if the offer was too good to ignore? Fannie and Freddie are sitting on large amounts of federal aid that are becoming more difficult for home buyers to access. If existing or new REITs could access these funds to buy, rent and sell homes, then perhaps we could create a creative way forward out of the current mortgage crises.

Active and Inactive Receptor States

When we write the set of brackets around a chemical species to represent a chemical concentration, it really represents a sum of probable chemical species that are grouped together. This is especially important when we consider the potential states of large protein molecules such as cellular receptors. In pharmacologic theory, we often characterize the active or inactive states of the receptor as initial quantities such as [R] and [R*]. This is convenient for mathematically manipulating these receptor states in order to derive information about how they behave in the presence of stimulating or inhibiting molecules such as agonists or antagonists, but conveys little about the underlying molecular species connected with these active and inactive states.

Even using specific and detailed molecular dynamic simulations, the meaning behind the [R] and [R*] receptor states becomes less clear when we explicitly model these states. Since there are a vast multitude of possible conformations, it becomes increasingly difficult to separate out those conformations that belong to the active or inactive receptor states. Ironically, this has brought us full circle to consider what [R] and [R*] represent as specific molecular species. The closer we are to understanding the details of these states from crystallographic structures, the further we are from understanding the molecular species that make up the active and inactive states.

Anyone who has truly studied pharmacologic theory and molecular modeling knows that we often wind up with this essential conundrum. Some have chosen particular molecular motions or interactions such as the breaking of a salt bridge or the twist or turn of a helix to describe what they think is the active receptor state. These descriptions may contain accurate descriptions of the active receptor state, but the fact that receptors exist in a sea of thermal noise and that activating drugs or ligands bind to their target receptors with only a 3-4 kcal/mol maximum energy difference and display different active molecular conformations suggest that we need a clearer on and off molecular switch for receptor activation.

These are not impossible physical constraints to accommodate in a biophysical molecular model for receptor activation (see - http://www.bio-balance.com/JMGM_article.pdf and http://www.bio-balance.com/GPCR_Activation.pdf ), but because receptors are complex molecular structures that exist in multiple domains, the teasing apart of the essential molecular signal is very difficult from both an experimental and theoretical perspective. This is particularly true if the biophysical models fail to accommodate major experimental findings such as the redox sensitivity of receptor systems or the reduction in desensitization by combining an antagonist with an agonist. A comprehensive molecular model for receptor activation should contain these findings.