36-500-100: Much Big Data about Hedge Funding

Stock market data diagram
Stock Market Data

By Vinit Kaushik,


I put aside “The Fear Index ,” a novel by Robert Harris. What percolated is an extreme self-learning software automaton called VIXAL could cause extreme hedge-fund returns from a world-wide web of opportunities while also becoming uncontainable. That puts a demand and a responsibility on us for any thing or being we create, whether it uses big data or otherwise.

Just in case you are wondering what a software automaton is, think of it as a recipe programmed into a computer. When that recipe is for growing funds, e.g., in the stock market by putting automatic buy and sell orders, some refer to it as algorithmic trading or systematic trading.

Now for this conversation, let’s look at ourselves and what’s around through a lens of integrity, harmony, and power. Rolling back to 2008, one can observe gaps in wealth management, both at an individual and institutional level. Gaps versus what, one might ask. Again for this conversation, consider wealth growing at 36% CAGR (Compound Annual Growth Rate). Powerful, sure. Risky, yes, but let’s say the fees are (also) based on real growth of wealth, say, measured by Net Present Value (NPV). Like fees on profit, but also that in case there’s a real loss, the corresponding (%) fee flows from wealth management to investor. And while profit considers neither time value of money (consider you’d surely have earned something on that fixed deposit you gave up) nor risk premium (consider you had to tolerate a notional loss of 60% on the Net Asset Value to get your final return), NPV considers both when computing the real growth. Now, that sounds little complex, but harmonious. If you cannot align management and customer to a single purpose (of maximizing wealth) in wealth management, where else can you? Ok, so what’s the integrity part? That’s workability. Like keeping promises, except that it’s not a stick to beat up with, but used by leaders to create an empowering context. You do want people to step forward, commit to expanded results, and deliver on those commitments. And you want investors to play their part. That’s what’s good for the economy and raising standard of living. Alright, imagine multiple such funds piped into pensions. Won’t that be good for society?

OK, so let’s say we want to bridge those gaps. By 2017-Feb, which is a quarter after US elections. Let’s pick a fund size that would tip the wealth-management ecosystem into transformation. If you are emerging in India, say, INR Rs.100 crore, which would be about USD $16 million. Let’s say that’s for 500 investors. Of course, depending on how soon the fund starts, it gets more time to grow into that size. That’s a real enough result and calls for leadership and performance. Codename this fund 36-500-100 to remember 36% CAGR, 500 investors, and INR Rs.100cr.

With that intended vital statistic, is there much big data can offer?

[Readers are invited to respond for this article to be continued.]


   The Fear Index:     http://www.barnesandnoble.com/sample/read/9780307957955.

Hedge Funds:     http://en.wikipedia.org/wiki/Hedge_fund.
About the author:

Vinit Kaushik Photo
Vinit Kaushik

Vinit Kaushik is an adviser for Spider OpsNet and and is in the IT industry for more than 25 years. He is an expert in algorithmic trading and his system built using R language is being used by many hedge funds.
Vinit Kaushik is living part of his career through this conversation. As he shares this adventure, he is causing the results expressed here and invites you to co-create them and other such results for raising well being. More at http://in.linkedin.com/pub/vinit-kaushik/22/a7b/1ab.


One thought on “36-500-100: Much Big Data about Hedge Funding”

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