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We have developed a novel risk management measure called the concentration risk indicator (CRI). The CRI has been created to address drawbacks with prevailing methodologies and to supplement existing methods. Modified and adapted from the Herfindahl-Hirschman (HH) index, the CRI can give a single numeric score that can be helpful to evaluate the extent of risks that arise from holding concentrated portfolios. We discuss how the CRI can become an indicator of financial stability at any desired aggregation unit: regional, national or international level. We show how the CRI can be easily applied to insurance risk and to any product portfolio mix. The CRI is particularly applicable to the current facet of the decentralized terrain, wherein the majority of the wealth is restricted to a small number of tokens. We calculate and report the CRI -- along with other risk metrics -- for individual assets and portfolios of crypto assets using a daily data sample from January 01, 2019 until August 10, 2022. The CRI is an example of developing metrics that can useful for sending concise yet powerful messages to the relevant audience. This tactic -- which can be described as marketing the benefits of any product or service by using concepts from multiple disciplines -- of creating new metrics goes further beyond the use of metrics to evaluate marketing efficacy. The simplicity of our metric -- and the intuitive explanations we have provided for the CRI -- makes it straightforward to properly articulate a strong -- clear and positive -- signal as part of marketing campaigns. The development -- and implementation -- of new risk management metrics will have greater impact when a wider rigorous risk management process has been established. We discuss several topics related to bringing about more improved risk management across all types of institutions and assets., Comment: arXiv admin note: text overlap with arXiv:2302.06348

We engineer blockchain based risk managed portfolios by creating three funds with distinct risk and return profiles: 1) Alpha - high risk portfolio; 2) Beta - mimics the wider market; and 3) Gamma - represents the risk free rate adjusted to beat inflation. Each of the sub-funds (Alpha, Beta and Gamma) provides risk parity because the weight of each asset in the corresponding portfolio is set to be inversely proportional to the risk derived from investing in that asset. This can be equivalently stated as equal risk contributions from each asset towards the overall portfolio risk. We provide detailed mechanics of combining assets - including mathematical formulations - to obtain better risk managed portfolios. The descriptions are intended to show how a risk parity based efficient frontier portfolio management engine - that caters to different risk appetites of investors by letting each individual investor select their preferred risk-return combination - can be created seamlessly on blockchain. Any Investor - using decentralized ledger technology - can select their desired level of risk, or return, and allocate their wealth accordingly among the sub funds, which balance one another under different market conditions. This evolution of the risk parity principle - resulting in a mechanism that is geared to do well under all market cycles - brings more robust performance and can be termed as conceptual parity. We have given several numerical examples that illustrate the various scenarios that arise when combining Alpha, Beta and Gamma to obtain Parity. The final investment frontier is now possible - a modification to the efficient frontier, thus becoming more than a mere theoretical construct - on blockchain since anyone from anywhere can participate at anytime to obtain wealth appreciation based on their financial goals.

We have designed an innovative portfolio rebalancing mechanism termed the Cascading Waterfall Round Robin Mechanism. This algorithmic approach recommends an ideal size and number of trades for each asset during the periodic rebalancing process, factoring in the gas fee and slippage. The essence of the model we have created gives indications regarding whether trades should be made on individual assets depending on the uncertainty in the micro - asset level characteristics - and macro - aggregate market factors - environments. In the hyper-volatile crypto market, our approach to daily rebalancing will benefit from volatility. Price movements will cause our algorithm to buy assets that drop in prices and sell as they soar. In fact, the buying and selling happen only when certain boundaries are crossed in order to weed out any market noise and ensure sound trade execution. We have provided several numerical examples to illustrate the steps - including the calculation of several intermediate variables - of our rebalancing mechanism. The Algorithm we have developed can be easily applied outside blockchain to investment funds across all asset classes at any trading frequency and rebalancing duration. Shakespeare As A Crypto Trader: To Trade Or Not To Trade, that is the Question, Whether an Optimizer can Yield the Answer, Against the Spikes and Crashes of Markets Gone Wild, To Quench One's Thirst before Liquidity Runs Dry, Or Wait till the Tide of Momentum turns Mild.

We develop several innovations to bring the best practices of traditional investment funds to the blockchain landscape. Specifically, we illustrate how: 1) fund prices can be updated regularly like mutual funds; 2) performance fees can be charged like hedge funds; 3) mutually hedged blockchain investment funds can operate with investor protection schemes, such as high water marks; and 4) measures to offset trading related slippage costs when redemptions happen. Using our concepts - and blockchain technology - traditional funds can calculate performance fees in a simplified manner and alleviate several operational issues. Blockchain can solve many problems for traditional finance, while tried and tested wealth management techniques can benefit decentralization, speeding its adoption. We provide detailed steps - including mathematical formulations and instructive pointers - to implement these ideas and discuss how our designs overcome several blockchain bottlenecks, making smart contracts smarter. We provide numerical illustrations of several scenarios related to our mechanisms.

The primary innovation we pioneer -- focused on blockchain information security -- is called the Safe-House. The Safe-House is badly needed since there are many ongoing hacks and security concerns in the DeFi space right now. The Safe-House is a piece of engineering sophistication that utilizes existing blockchain principles to bring about greater security when customer assets are moved around. The Safe-House logic is easily implemented as smart contracts on any decentralized system. The amount of funds at risk from both internal and external parties -- and hence the maximum one time loss -- is guaranteed to stay within the specified limits based on cryptographic fundamentals. To improve the safety of the Safe-House even further, we adapt the one time password (OPT) concept to operate using blockchain technology. Well suited to blockchain cryptographic nuances, our secondary advancement can be termed the one time next time password (OTNTP) mechanism. The OTNTP is designed to complement the Safe-House making it even more safe. We provide a detailed threat assessment model -- discussing the risks faced by DeFi protocols and the specific risks that apply to blockchain fund management -- and give technical arguments regarding how these threats can be overcome in a robust manner. We discuss how the Safe-House can participate with other external yield generation protocols in a secure way. We provide reasons for why the Safe-House increases safety without sacrificing the efficiency of operation. We start with a high level intuitive description of the landscape, the corresponding problems and our solutions. We then supplement this overview with detailed discussions including the corresponding mathematical formulations and pointers for technological implementation. This approach ensures that the article is accessible to a broad audience.

We consider the problem of being a cross-chain wealth management platform with deposits, redemptions and investment assets across multiple networks. We discuss the need for blockchain bridges to facilitates fund flows across platforms. We point out several issues with existing bridges. We develop an algorithm - tailored to overcome current constraints - that dynamically changes the utilization of bridge capacities and hence the amounts to be transferred across networks. We illustrate several scenarios using numerical simulations.

We discuss numerous justifications for why crypto-currencies would be highly conducive for the smooth functioning of today's society. We provide several comparisons between cryptocurrencies issued by blockchain projects, crypto, and conventional government issued currencies, cash or fiat. We summarize seven fundamental innovations that would be required for participants to have greater confidence in decentralized finance (DeFi) and to obtain wealth appreciation coupled with better risk management. The conceptual ideas we discuss outline an approach to: 1) Strengthened Security Blueprint; 2) Rebalancing and Trade Execution Suited for Blockchain Nuances 3) Volatility and Variance Adjusted Weight Calculation 4) Accommodating Investor Preferences and Risk Parity Construction; 5) Profit Sharing and Investor Protection; 6) Concentration Risk Indicator and Performance Metrics; 7) Multi-chain expansion and Select Strategic Initiatives including the notion of a Decentralized Autonomous Organization (DAO). Incorporating these concepts into several projects would also facilitate the growth of the overall blockchain eco-system so that this technology can, have wider mainstream adoption and, fulfill its potential in transforming all aspects of human interactions.

We provide a justification for why, and when, endogeneity will not cause bias in the interpretation of the coefficients in a regression model. This technique can be a viable alternative to, or even used alongside, the instrumental variable method. We show that when performing any comparative study, it is possible to measure the true change in the coefficients under a broad set of conditions. Our results hold, as long as the product of the covariance structure between the explanatory variables and the covariance between the error term and the explanatory variables are equal, within the same system at different time periods or across multiple systems at the same point in time., Comment: Statistica Sinica, 32 (2022), 645-651

We consider in detail an investment strategy, titled "The Bounce Basket", designed for someone to express a bullish view on the market by allowing them to take long positions on securities that would benefit the most from a rally in the markets. We demonstrate the use of quantitative metrics and large amounts of historical data towards decision making goals. This investment concept combines macroeconomic views with characteristics of individual securities to beat the market returns. The central idea of this theme is to identity securities from a regional perspective that are heavily shorted and yet are fundamentally sound with at least a minimum buy rating from a consensus of stock analysts covering the securities. We discuss the components of creating such a strategy including the mechanics of constructing the portfolio. Using simulations, in which securities lending data is modeled as geometric brownian motions, we provide a few flavors of creating a ranking of securities to identity the ones that are heavily shorted. An investment strategy of this kind will be ideal in market scenarios when a downturn happens due to unexpected extreme events and the markets are anticipated to bounce back thereafter. This situation is especially applicable to incidents being observed, and relevant proceedings, during the Coronavirus pandemic in 2020-2021. This strategy is one particular way to overcome a potential behavioral bias related to investing, which we term the "rebound effect"., Comment: arXiv admin note: substantial text overlap with arXiv:1910.02144

We discuss preliminary results from two experiments and put forth the notion that the development of sensory systems might be more geared towards discerning differences rather than for spotting similarities. We present the possibility that the necessity to spot differences might have evolved to ensure the survival of the organism, which suggests numerous other experiments to assess the response of participants to various stimuli. We consider our present state of affairs, wherein the need is to thrive and not merely survive, which requires us to spot similarities around us. We provide some suggestions on how this attribute can be developed, which includes mathematical education. We conclude with an alternate measure for intelligence, termed the Involvement Quotient (also, IQ), which gauges the level of involvement of the sense organs to whatever is happening around the individual., Comment: World Futures

We discuss the objectives of automation equipped with non-trivial decision making, or creating artificial intelligence, in the financial markets and provide a possible alternative. Intelligence might be an unintended consequence of curiosity left to roam free, best exemplified by a frolicking infant. For this unintentional yet welcome aftereffect to set in a foundational list of guiding principles needs to be present. A consideration of these requirements allows us to propose a test of intelligence for trading programs, on the lines of the Turing Test, long the benchmark for intelligent machines. We discuss the application of this methodology to the dilemma in finance, which is whether, when and how much to Buy, Sell or Hold., Comment: arXiv admin note: substantial text overlap with arXiv:1907.04659, arXiv:1703.08812

We take a closer look at the life and legacy of Micheal Milken. We discuss why Michael Milken, also know as the Junk Bond King, was not just any other King or run-of-the-mill Junk Dealer, but "The Junk Dealer". We find parallels between the three parts to any magic act and what Micheal Milken did, showing that his accomplishments were nothing short of a miracle. His compensation at that time captures to a certain extent the magnitude of the changes he brought about, the eco-system he created for businesses to flourish, the impact he had on the wider economy and also on the future growth and development of American Industry. We emphasize two of his contributions to the financial industry that have grown in importance over the years. One was the impetus given to the Private Equity industry and the use of LBOs. The second was the realization that thorough research was the key to success, financial and otherwise. Perhaps an unintended consequence of the growth in junk bonds and tailored financing was the growth of Silicon valley and technology powerhouses in the California bay area. Investors witnessed that there was a possibility for significant returns and that financial success could be had due to the risk mitigation that Milken demonstrated by investing in portfolios of so called high risk and low profile companies. We point out the current trend in many regions of the world, which is the birth of financial and technology firms and we suggest that finding innovative ways of financing could be the key to the sustained growth of these eco-systems.

This paper acts as a collection of various trading strategies and useful pieces of market information that might help to implement such strategies. This list is meant to be comprehensive (though by no means exhaustive) and hence we only provide pointers and give further sources to explore each strategy further. To set the stage for this exploration, we consider the factors that determine good and bad trades, the notions of market efficiency, the real prospect amidst the seemingly high expectations of homogeneous expectations from human beings and the catch-22 connotations that arise while comprehending the true meaning of rational investing. We can broadly classify trading ideas and client market color material into Delta-One and Derivative strategies since this acts as a natural categorization that depends on the expertise of the various trading desks that will implement these strategies. For each strategy, we will have a core idea and we will present different flavors of this central theme to demonstrate that we can easily cater to the varying risk appetites, regional preferences, asset management styles, investment philosophies, liability constraints, investment horizons, notional trading size, trading frequency and other preferences of different market participants., Comment: The concepts in this present paper have circulated previously under the title, "Trading Strategies and Market Color: The Benefits of Friendship with Quantitative Analysts and Financial Engineers". This present article is the first part of the two parts into which the original manuscript has been split into. arXiv admin note: text overlap with arXiv:1603.06047

We formulate one methodology to put a value or price on knowledge using well accepted techniques from finance. We provide justifications for these finance principles based on the limitations of the physical world we live in. We start with the intuition for our method to value knowledge and then formalize this idea with a series of axioms and models. To the best of our knowledge this is the first recorded attempt to put a numerical value on knowledge. The implications of this valuation exercise, which places a high premium on any piece of knowledge, are to ensure that participants in any knowledge system are better trained to notice the knowledge available from any source. Just because someone does not see a connection does not mean that there is no connection. We need to try harder and be more open to acknowledging the smallest piece of new knowledge that might have been brought to light by anyone from anywhere about anything.

We discuss the objectives of any endeavor in creating artificial intelligence, AI, and provide a possible alternative. Intelligence might be an unintended consequence of curiosity left to roam free, best exemplified by a frolicking infant. This suggests that our attempts at AI could have been misguided. What we actually need to strive for can be termed artificial curiosity, AC, and intelligence happens as a consequence of those efforts. For this unintentional yet welcome aftereffect to set in a foundational list of guiding principles needs to be present. We start with the intuition for this line of reasoning and formalize it with a series of definitions, assumptions, ingredients, models and iterative improvements that will be necessary to make the incubation of intelligence a reality. Our discussion provides conceptual modifications to the Turing Test and to Searle's Chinese room argument. We discuss the future implications for society as AI becomes an integral part of life. We provide a road-map for creating intelligence with the technical parts relegated to the appendix so that the article is accessible to a wide audience. The central techniques in our formal approach to creating intelligence draw upon tools and concepts widely used in physics, cognitive science, psychology, evolutionary biology, statistics, linguistics, communication systems, pattern recognition, marketing, economics, finance, information science and computational theory highlighting that solutions for creating artificial intelligence have to transcend the artificial barriers between various fields and be highly multi-disciplinary.

We discuss a possible solution to an unintended consequence of having grades, certificates, rankings and other diversions in the act of transferring knowledge; and zoom in specifically to the topic of having grades, on a curve. We conduct a thought experiment, taking a chapter (and some more?) from the financial markets, (where we trade pollution and what not?), to create a marketplace, where we can trade our grade, similar in structure to the interest rate swap. We connect this to broader problems that are creeping up, unintentionally, due to artificial labels we are attaching, to ourselves. The policy and philosophical implications of our arguments are to suggest that all trophies that we collect (including certificates, grades, medals etc.) should be viewed as personal equity or private equity (borrowing another widely used term in finance) and we should not use them to determine the outcomes in any selection criteria except have a cutoff point: either for jobs, higher studies, or, financial scholarships, other than for entertainment or spectator sports. We suggest alternate methods for grading and performance assessment and put forth tests for teaching and learning similar to the Turing Test for intelligence.

We develop extensions to auction theory results that are useful in real life scenarios. 1. Since valuations are generally positive we first develop approximations using the log-normal distribution. This would be useful for many finance related auction settings since asset prices are usually non-negative. 2. We formulate a positive symmetric discrete distribution, which is likely to be followed by the total number of auction participants, and incorporate this into auction theory results. 3. We develop extensions when the valuations of the bidders are interdependent and incorporate all the results developed into a final combined realistic setting. 4. Our methods can be a practical tool for bidders and auction sellers to maximize their profits. The models developed here could be potentially useful for inventory estimation and for wholesale procurement of financial instruments and also non-financial commodities. All the propositions are new results and they refer to existing results which are stated as Lemmas., Comment: arXiv admin note: substantial text overlap with arXiv:1603.00987

Market Microstructure is the investigation of the process and protocols that govern the exchange of assets with the objective of reducing frictions that can impede the transfer. In financial markets, where there is an abundance of recorded information, this translates to the study of the dynamic relationships between observed variables, such as price, volume and spread, and hidden constituents, such as transaction costs and volatility, that hold sway over the efficient functioning of the system. "My dear, here we must process as much data as we can, just to stay in business. And if you wish to make a profit you must process at least twice as much data." - Red Queen to Alice in Hedge-Fund-Land. In this age of (Too Much) Information, it is imperative to uncover nuggets of knowledge (signal) from buckets of nonsense (noise). To aid in this effort to extract meaning from chaos and to gain a better understanding of the relationships between financial variables, we summarize the application of the theoretical results from (Kashyap 2016b) to microstructure studies. The central concept rests on a novel methodology based on the marriage between the Bhattacharyya distance, a measure of similarity across distributions, and the Johnson Lindenstrauss Lemma, a technique for dimension reduction, providing us with a simple yet powerful tool that allows comparisons between data-sets representing any two distributions. We provide an empirical illustration using prices, volumes and volatilities across seven countries and three different continents. The degree to which different markets or sub groups of securities have different measures of their corresponding distributions tells us the extent to which they are different. This can aid investors looking for diversification or looking for more of the same thing., Comment: arXiv admin note: substantial text overlap with arXiv:1603.09060

Models to price long term loans in the securities lending business are developed. These longer horizon deals can be viewed as contracts with optionality embedded in them. This insight leads to the usage of established methods from derivatives theory to price such contracts. Numerical simulations are used to demonstrate the practical applicability of these models. The techniques advanced here can lead to greater synergies between the management of derivative and delta-one trading desks, perhaps even being able to combine certain aspects of the day to day operations of these seemingly disparate entities. These models are part of one of the least explored, yet profit laden, areas of modern investment management. A heuristic is developed to mitigate any loss of information, which might set in when parameters are estimated first and then the valuations are performed, by directly calculating valuations using the historical time series. This approach to valuations can lead to reduced models errors, robust estimation systems, greater financial stability and economic strength. An illustration is provided regarding how the methodologies developed here could be useful for inventory management, emissions trading and insurance risk mitigation. All these techniques could have applications for dealing with other financial instruments, non-financial commodities and many forms of uncertainty.

The equity risk premium puzzle is that the return on equities has far exceeded the average return on short-term risk-free debt and cannot be explained by conventional representative-agent consumption based equilibrium models. We review a few attempts done over the years to explain this anomaly: 1. Inclusion of highly unlikely events with low probability (Ugly state along with Good and Bad), or market crashes / Black Swans. 2. Slow moving habit, or time-varying subsistence level, added to the basic power utility function. 3. A separation of the inter-temporal elasticity of substitution and risk aversion, combined with long run risks which captures time varying economic uncertainty. We explore whether a fusion of the above approaches supplemented with better methods to handle the below reservations would provide a more realistic and yet tractable framework to tackle the various conundrums in the social sciences: 1. Unlimited ability of individuals to invest as compared to their ability to consume. 2. Lack of an objective measuring stick of value 3. Unintended consequences due to the dynamic nature of social systems 4. Relaxation of the transversality condition to avoid the formation of asset price bubbles 5. How durable is durable? Accounting for durable goods since nothing lasts forever The world we live in produces fascinating phenomenon despite (or perhaps, due to) being a hotchpotch of varying doses of the above elements. The rationale for a unified theory is that beauty can emerge from chaos since the best test for a stew is its taste. Many long standing puzzles seem to have been resolved using different techniques. The various explanations need to stand the test of time before acceptance; but then unexpected outcomes set in and new puzzles emerge. As real analysis and limits tell us: We are getting Closer and Closer; Yet it seems we are still Far Far Away...

We develop a novel methodology based on the marriage between the Bhattacharyya distance, a measure of similarity across distributions of random variables, and the Johnson-Lindenstrauss Lemma, a technique for dimension reduction. The resulting technique is a simple yet powerful tool that allows comparisons between data-sets representing any two distributions. The degree to which different entities, (markets, universities, hospitals, cities, groups of securities, etc.), have different distance measures of their corresponding distributions tells us the extent to which they are different, aiding participants looking for diversification or looking for more of the same thing. We demonstrate a relationship between covariance and distance measures based on a generic extension of Stein's Lemma. We consider an asset pricing application and then briefly discuss how this methodology lends itself to numerous market-structure studies and even applications outside the realm of finance / social sciences by illustrating a biological application. We provide numerical illustrations using security prices, volumes and volatilities of both these variables from six different countries.

We will look at the entire cycle of the investment process relating to all aspects of, formulating an investment hypothesis, constructing a portfolio based on that, executing the trades to implement it, on-going risk management, periodically measuring the performance of the portfolio, and rebalancing the portfolio either due to an increase in the risk parameters or due to a deviation from the intended asset allocation. We provide several illustrative analogies that are meant to intuitively explain the pleasures and the pitfalls that can arise while managing a portfolio. If we consider the entire investment management procedure as being akin to connecting the dots of a circle, then the Circle of Investment can be represented as a dotted circle with many dots falling approximately on the circumference and with no clue about the exact location of the centre or the length of the radius. We represent the investment process as a dotted circle since there is a lot of ambiguity in the various steps involved. The circle also indicates the repetitive nature of many steps that are continuously carried out while investing. This work introduces two new points pertaining to this dotted circle and improves the ability, to understand how far-off this dotted circle is, from a more well-defined circle and, to create a well-formed circle. The two innovations we introduce are: 1. The first, relating to the limitations that apply to any finding in the social sciences, would be the additional point we introduce that lies near the centre of the circle. We title this as, 'The Uncertainty Principle of the Social Sciences'. 2. The second, relating to establishing confidence levels in a systematic manner for each view we associate with a security or group of securities as required by the Black-Litterman framework, would be the new point we present near the circumference of the circle., Comment: Expanded into a book "The Circle of Investment", Available at http://www.amazon.com

We look at a collection of conjectures with the unifying message that smaller social systems, tend to be less complex and can be aligned better, towards fulfilling their intended objectives. We touch upon a framework, referred to as the four pronged approach that can aid the analysis of social systems. The four prongs are: 1. The Uncertainty Principle of the Social Sciences 2. The Objectives of a Social System or the Responsibilities of the Players 3. The Need for Smaller Organizations 4. Redirecting Unintended Outcomes Smaller organizations mitigating the disruptive effects of corruption is discussed and also the need for organizations, whose objective is to foster the development of other smaller organizations. We consider a way of life, which is about respect for knowledge and a desire to seek it. Knowledge can help eradicate ignorance, but the accumulation of knowledge can lead to overconfidence. Hence it becomes important to instill an attitude that does not knowledge too seriously, along with the thirst for knowledge. All of this is important to create an environment that is conducive for smaller organizations and can be viewed as a natural extension of studies that fall under the wider category of understanding factors and policies aimed at increasing the welfare or well-being to society., Comment: arXiv admin note: substantial text overlap with arXiv:1603.00991

A four-pronged approach to dealing with Social Science Phenomenon is outlined. This methodology is applied to Financial Services, Economic Growth and Well-Being. The four prongs are like the four directions for an army general looking for victory. Just like the four directions, we need to be aware that there is a degree of interconnectedness in the below four prongs. -Uncertainty Principle of the Social Sciences -Responsibilities of Fiscal Janitors -Need for Smaller Organizations -Redirecting Growth that Generates Garbage The importance of gaining a more profound comprehension of welfare and delineating its components into those that result from an increase in goods and services, and hence can be attributed to economic growth, and into those that are not related to economic growth but lead to a better quality of life, is highlighted. The reasoning being that economic growth alone is an inadequate indicator of well-being. Hand in hand with a better understanding of the characteristics of welfare, comes the need to consider the metrics we currently have that gauge economic growth and supplement those with measures that capture well-being more holistically., Comment: Contains Supplementary Material (Research Questions, Methodology and Data Sources) in the Appendix

We develop a fundamentally different stochastic dynamic programming model of trading costs. Built on a strong theoretical foundation, our model provides insights to market participants by splitting the overall move of the security price during the duration of an order into the Market Impact (price move caused by their actions) and Market Timing (price move caused by everyone else) components. We derive formulations of this model under different laws of motion of the security prices, starting with a simple benchmark scenario and extending this to include multiple sources of uncertainty, liquidity constraints due to volume curve shifts and relating trading costs to the spread. We develop a numerical framework that can be used to obtain optimal executions under any law of motion of prices and demonstrate the tremendous practical applicability of our theoretical methodology including the powerful numerical techniques to implement them. Our decomposition of trading costs into Market Impact and Market Timing allows us to deduce the zero sum game nature of trading costs. It holds numerous lessons for dealing with complex systems, wherein reducing the complexity by splitting the many sources of uncertainty can lead to better insights in the decision process.

We derive valuations of a portfolio of financial instruments from a securities lending perspective, under different assumptions, and show a weighting scheme that converges to the true valuation. We illustrate conditions under which our alternative weighting scheme converges faster to the true valuation when compared to the minimum variance weighting. This weighting scheme is applicable in any situation where multiple forecasts are made and we need a methodology to combine them. Our valuations can be useful either to derive a bidding strategy for an exclusive auction or to design an appropriate auction mechanism, depending on which side of the fence a participant sits (whether the interest is to procure the rights to use a portfolio for making stock loans such as for a lending desk, or, to obtain additional revenue from a portfolio such as from the point of view of a long only asset management firm). Lastly, we run simulations to establish numerical examples for the set of valuations and for various bidding strategies corresponding to different auction settings., Comment: Incomplete Early Draft - Soliciting suggestions, omissions and other feedback

We utilize a fundamentally different model of trading costs to look at the effect of the opening of the Hong Kong Shanghai Connect that links the stock exchanges in the two cities, arguably the biggest event in international business and finance since Christopher Columbus set sail for India. We design a novel methodology that compensates for the lack of data on trading costs in China. We estimate trading costs across similar positions on the dual listed set of securities in Hong Kong and China, hoping to provide useful pieces of information to help scale 'The Great Wall of Chinese Securities Trading Costs'. We then compare actual and estimated trading costs on a sample of real orders across the Hong Kong securities in the dual listed pair to establish the accuracy of our measurements. The primary question we seek to address is 'Which market would be better to trade to gain exposure to the same (or similar) set of securities or sectors?' We find that trading costs on Shanghai, which might have been lower than Hong Kong, might have become higher leading up to the Connect. What remains to be seen is whether this increase in trading costs is a temporary equilibrium due to the frenzy to gain exposure to Chinese securities or whether this phenomenon will persist once the two markets start becoming more and more tightly coupled. It would be interesting to see if this pioneering policy will lead to securities exchanges across the globe linking up one another, creating a trade anything, anywhere and anytime marketplace. Looking beyond mere trading costs, such studies can be used to gather some evidence on what effect the mode of governance and other aspects of life in one country have on another country, once they start joining up their financial markets., Comment: arXiv admin note: text overlap with arXiv:1603.00984, arXiv:1602.00839

We look at the effect of the tick size changes on the TOPIX 100 index names made by the Tokyo Stock Exchange on Jan-14-2014 and Jul-22-2104. The intended consequence of the change is price improvement and shorter time to execution. We look at security level metrics that include the spread, trading volume, number of trades and the size of trades to establish whether this goal is accomplished. An unintended effect might be the reduction in execution sizes, which would then mean that institutions with large orders would have greater difficulty in sourcing liquidity. We look at a sample of real orders to see if the execution costs have gone up across the orders since the implementation of this change. We study the mechanisms that affect how securities are traded on an exchange, before delving into the specifics of the TSE tick size events. Some of the topics we explore are: The Venue Menu and How to Increase Revenue; To Automate or Not to Automate; Microstructure under the Microscope; The Price of Connections to High (and Faraway) Places; Speed Thrills but Kills; Pick a Size for the Perfect Tick; TSE Tick Size Experiments, Then and Now; Sergey Bubka and the Regulators; Bird`s Eye View; Deep Dive; Possibilities for a Deeper Dive; Does Tick Size Matter? Tick Size Does Matter!, Comment: This version has a mathematical proof to show conditions under which endogeneity is resolved when doing a regression. The idea is consider the changes in the coefficients before and after an event. This theoretical proof is illustrated using the data from our event study

We can overcome uncertainty with uncertainty. Using randomness in our choices and in what we control, and hence in the decision making process, could potentially offset the uncertainty inherent in the environment and yield better outcomes. The example we develop in greater detail is the news-vendor inventory management problem with demand uncertainty. We briefly discuss areas, where such an approach might be helpful, with the common prescription, "Don't Simply Optimize, Also Randomize; perhaps best described by the term - Randoptimization". 1. News-vendor Inventory Management 2. School Admissions 3. Journal Submissions 4. Job Candidate Selection 5. Stock Picking 6. Monetary Policy This methodology is suitable for the social sciences since the primary source of uncertainty are the members of the system themselves and presently, no methods are known to fully determine the outcomes in such an environment, which perhaps would require being able to read the minds of everyone involved and to anticipate their actions continuously. Admittedly, we are not qualified to recommend whether such an approach is conducive for the natural sciences, unless perhaps, bounds can be established on the levels of uncertainty in a system and it is shown conclusively that a better understanding of the system and hence improved decision making will not alter the outcomes.

The author seeks to develop a model to alter the bid-offer spread, currently quoted by market makers, that varies with the market and trading conditions. The dynamic nature of financial markets and trading, as with the rest of social sciences, where changes can be observed and decisions can be made by participants to influence the system, means that this model has to be adaptive and include a feedback loop that alters the bid-offer adjustment based on the modifications observed in the market and trading conditions, without a significant time delay. The factors used to adjust the spread are price volatility, which is publicly observable, and trade count and volume, which are generally known only to the market maker, in various instruments over different historical durations in time. The contributions of each factor to the bid-offer adjustment are computed separately and then consolidated to produce a very adaptive bid-offer quotation. The author uses the currency markets to build the sample model because they are extremely liquid and trading in them is not as transparent as other financial instruments, such as equities. Simulating the number of trades and the average size of trades from a lognormal distribution, the parameters of the lognormal distributions are chosen such that the total volume in a certain interval matches the volume publicly mentioned by currency trading firms. This methodology can easily be extended to other financial instruments and possibly to any product with the ability to make electronic price quotations, or can even be used to periodically perform manual price updates on products that are traded non-electronically.