Artificial Market Risk: what it is really?
The word "risk" is inherently associated with uncertainty in general term and "returns" in the investment world. Financial markets presents with different kinds of uncertainties which breed risk;
Â· risk associated with uncertain event horizon, Â· credit risk, Â· capital loss risk, Â· risk associated with derivative investment vehicles and instruments, Â· inflation risk, Â· liquidity risk, Â· macroeconomic risk, Â· currency risk, Â· interest rate risk, Â· asset bubble risk, Â· risk of contagion, Â· technical/operational risk Â· trading/settlement risks and so on.
Literature is abounding on modeling and incorporating market risk and credit risk into numerous measures of financial risks similar to value-at-risk or 'var', ( Jarrow, and Protter, 2005 ). Of prime significance in this aspect is the credit risk since the business of lending, borrowing and leverage is directly correlated to the commercial banks' transaction and transfer of such credit risk (Duffie, 2007 ) given that commercial banks and financial institutions as well, the intermediaries associated to them, are in the business of risk (Santomero, 1997). So there is risk management tools designed to measure, quantify, and manage such risks. However, risks associated with certain kinds of instruments traded exotically in the market now seems to be the general cause of a new kind of market risk generated synthetically, so called 'artificial market risk' which poses as a novel problem for risk managers and investors alike following the recent financial market crises. This particular kind of risk is generated from investment vehicles which derive their notional values from the underlying fluctuating values of assets from which they are derived and hence I call them derived risk. Although such traditional underlying assets like stocks and bonds are relatively more or less risky to trade in, and those which carries normal risks associated with them but the risk becomes diversified when they are used as derivative asset classes. With the notional provision of market liquidity, notional risks associated with such investment vehicles tends to increase manifold on account of complexities associated with designing of those derived assets. This may generally be described as assumed risk from diversification since the theory of portfolio diversification is meant to mitigate and minimize risk by minimizing direct exposure to the market forces and momentum (**Ref). However, these diversified instruments like hedge funds and related vehicles have inherent risk associated to their own dynamics of mechanism and function; that is, how they operate on the market. Hence when we add up the general risk with these artificially created risk, the 'associated summed- up' risk increases as well. This so called 'summed-up associated' or 'associated summed- up' risk is what I call artificial market risk since; this risk is 'artificially' generated. It is to be noted that the most common errors in investment decision making on the stock market is to improperly assume market risk. Complexity associated with design process and innovation of financial products though creates new diversified products uncorrelated to the markets, these are not at all risk free; in a sense, the associated payoff and the probability of loss varies much with such innovations which is layered on the mechanism of leverage - a borrowing method which gives the traders the ability to purchase more assets than their wealth would otherwise permit. Financial crises often gets triggered when investors fail to return these borrowed, leveraged assets resulting in default. This is what makes trading on leverage more risky yet can be much profitable nevertheless there are perilous consequences of the use of disproportionate credit (Thurner, Farmer and Geanakoplos, 2010). The art of optimal leveraging lies in the science of balancing credit required for seeking higher investment returns, and this act of optimal balancing of liquidity/credit provisioning for financing investments lies at the core of risk trading and leverage finance. Optimal leverage has several benefits as noted by Dieter & Philipp (2011). A previous contradicting view was suggested by Thurner, et. al, 2010, which depicts that causes fat tails and clustered volatility where they show with a simple model based on leveraged asset purchases that when funds no not borrow, price fluctuations of the asset are normally distributed. 
Decision-making and attitude toward risk:
Among decisions which investors need to take quite often is whether to hold or dispose of assets, buy or sell or not to trade at all or trade in high risk securitized products. Two factors play some role in this aspect; courage and confidence. Investors show different kinds of attitude towards risk since they may have heterogeneous risk preferences (Nanda, 1998 ). Some seek optimum return from their investment while others seek above average returns. Market returns (loss or gain) are hence correlated with the amount of risks that investors can or cannot assume. Investors often cut short of possible gains due to fear and loss aversion bias (**Ref). As also, investors sometimes take in excessive risk to beat the market trends to seek for above average returns. The last factor did play some definite role in the most recent financial crisis when sophisticated instruments as financial innovations failed to model risk properly and which in turn generated synthetic risk which backfired when these strategies crashed in. This might well account to the phenomenon of 'winning by belief' as too much confidence was granted on these innovative products.
How Artificial Market Risk is generated?
It shall be remembered that investors have heterogeneous beliefs and information about securities' fundamental values and the level of risk aversion varies across investor groups, individuals, institutional investors and cultures. That is to say, risk tolerance and aversion is heterogeneously distributed across the markets. Notable among them are Traders" who themselves create a disproportionate amount of risk[S7 as well risk which is often created from financial anomalies.]
There are not only cross-cultural differences in risk perception but there is significant amount of differences about risk generation across markets. Some more developed markets are more complex owing to the whole host of securities and their structured products (derivatives) which are being traded, and thence, more risky. New classes of structured alternative investments including hedge funds which are aimed for decorrelation from market risk themselves create an entirely different kind of risk. The risk preference for risky financial options is as also different among countries and across cultures. For example, Weber and Hsee (1998), notes that there exists cross-cultural differences in risk preference and risk perception among heterogeneous groups of investors across countries. This point bears some relevance to the theory that individual investors (retail) and institutional investors both, across countries, perceive risk differently and hence, they assume different amounts of leverage or might have differential trading strategies those involving structured products bearing artificial risk and securities instruments bearing normal systemic market risk. But a question may be raised thereof; do structured products of financial innovation really mitigate or exacerbate market risk? Or the risk gets diversified across markets by use of such investment vehicles? The potential tradeoff between trading risk (securitized instruments) and riskless instruments must be brought up in this case so as to delineate benefits and disadvantages of leverage, the social costs involved in structured products and financial derivatives with reference to trading equities alone.
It is important to understand how risk is created and at the same time how risk is traded  in the markets. Risk trading is risky, as the common saying goes by, while different traders may have different perceptions about similar kinds of risk owing to their heterogeneous beliefs about uncertainty and returns (payoff). The so called "specialty finance companies" (Duffie, 2007) which design and sell collateralized lending obligations (CLOs), credit default swaps (CDS), credit derivatives products and other exotic options not only create, design and sell risk, but they transfer risk by channeling these products into innovative pipelines meant for credit risk transfer.** To provision more liquidity in need to transfer or diversify risk, banks disburse these risks via financial intermediaries consisting of hedge funds, institutional investors or "specialty finance companies" So, part of the origin of this so called "artificial risk" is from the banks that transfer credit risk for provision of more liquidity. The other part originates from packaging and redesigning these credit-backed products into more attractive marketable instruments. It is to be noted that with such types of innovation, innovation in risk  is the end product to be traded on the market, i.e., elevated imperceptible risk is produced from underlying assets which may or may not have similar risk. Each unique layers of innovation carries with it a unique nature of risk which is different from the systemic market risk. Consider for example, the Market Neutral and Macro strategies which retain a stable market risk exposure whatever the market conditions are**. In such sense, these become standalone derived products much decorrelated from the general market in which they are traded and so carry unique risks which are artificially modeled. However, in options pricing, the price does not depend on the investor attitude toward risk, it matters how much risk they could assume since the products are often based on risk-neutral valuation methods where the probability of price rise or fall determines the risk-neutral probability of expected return on the underlying asset.
the derivative instruments belong to a broader class of assets called contingent claims, which means that the real claim in the asset depends conditionally on the payoff of the outcome of some uncertain event.([S12 Prasanna Chandra, 2005)] Trading on uncertainty involves prediction and probability since nobody knows for definite what the future would look like, but can categorically assume such based on present scenario and historical events. Modeling risk is hence much about modeling uncertainty. The artificial modeling and assumption of such uncertain situation generates what we may call "risk simulation". This may not relate to the straightforward fundamental valuation of a stock or equity whose future value can be determined by discounted cash flow or other account book parameters whereas there is no fundamental value in options pricing whose price is solely determined by the equilibrium price of the option .
A Simple Model of the Levels of Market Risk: Conventional vs Artificial The market for risky investment:
Financial intermediaries who are in the business of structuring, packaging and selling risk to seek higher market returns generally assume such risk transferred by commercial banks who dispel credit/loans to generate more liquidity  for their businesses. In this way, risk gets shared and transferred. In essence, financial market innovations by itself generate uncertainty associated with such products of risk as there are further risks down the line associated with trading of such risky products of innovation. We may hence define artificial market risk as; "Artificial market risk is a kind of derived risk which originates on the market from structured, layered innovations in securities instruments designed by financial intermediaries in search of market beating returns who not only create, design, sell and manage such risks, but transfer them as well across markets."
"It shall however be remembered that leveraged liquidity is a 'high risk liquidity'. Volatility in return patterns hence is much correlated to the nature of market liquidity which may not only be highly leveraged nevertheless invariably carries high risk. This type of risk and the premium associated with such is generated from uncertain outcome from trading on leveraged liquidity which in a sense is notional. The tentative payoff expected from trading beyond conventional market instruments like equities other than from financial innovations that rely on modeling liquidity to meet investor appetite for market beating returns must invariably originate from securitized products and leverage, both of which are highly impulsive market instruments."
This paper is important.
Prof. Duffie in his paper discusses about credit risk transfer widely, and so this paper is a good source of information.
How diversification lowers risk? Or do they elevate such?
This part original thought.
This statement needs to be altered or changed a bit to avoid paraphrasing.
This paper is worth reading and especially relevant.
There are evidences that noise traders do generate risk.
I reverberate this crucial point that whether "if their benefits outweigh the costs for the society", .
Answer to these queries are relevant to the literature and may be looked in some detail.
Some more explanation for this point required.
Should we call this 'innovation risk' as well? Are innovations always beneficial for the financial marketsâ€”or society? Does the cost of innovations outweigh their benefits? This issue is highly contentious. Is it feasible to discuss this topic in some more detail?
A statement I find useful but should be altered a bit (toward more meaningful one and to avoid paraphrasing).
 Conflicting views are as good as to put in research, since that would likely include many different angles, views etc.
In order to understand artificial risk, one should be able to delineate different levels of market risk categorizations and derive definition from such categorizations. This concept I derive from your comments vide RG forum discussion.
Need review and suggestions.
This is a new concept we may be carried forward in another paper...
This part new idea."