MongoDB: Handling TMI – Too Much Information

MongoDB: Handling TMI - Too Much Information

Written by Summary

Investing in Equities is an information exploration and organization.

There’s no difficulty in finding information about interesting and promising stocks – thousands of them.

Fortunately, several of the thousands exist to help whip info from all into more orderly evaluation COMPARISONS with one another. And Mongo is a leader in arranging that.

Pgiam/iStock via Getty Images Investment Thesis

Any intelligent stock investment is a bet about what the future holds. It requires a forecast of that future.

The further out in time we probe, the greater is the risk we may turn out to be in error. Time so spent is extremely costly because it cannot be replaced. “Conservative” long-term errors once apparent may become defeaters of major-objective goals.

The truly protective investment strategies are repeatable evaluative shorter-term ones. They can be identified more readily as failing and replaced by pursuits with better odds for desired achievements.

But they take more effort and information inputs, including realistic price target forecasts.

For most investors those inputs and forecasts are better obtained from market professionals making them day by day without biases likely to be counter to the investor’s objectives.

We obtain those inputs from direct work-experience knowledge of how market-makers must work to provide trading liquidity for major institutions in their management of multi-billion-$ portfolios.

We use MongoDB, Inc. (NASDAQ: MDB ) here as an illustration in the pursuit of knowledgeable shorter-term investment guidance in selecting wealth-building stocks.

Company Description

“ MongoDB, Inc. provides general purpose database platform worldwide. The company offers MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premise, or in a hybrid environment; MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB. It also provides professional services, such as consulting and training. The company was formerly known as 10gen, Inc. and changed its name to MongoDB, Inc. in August 2013. MongoDB, Inc. was incorporated in 2007 and is headquartered in New York, New York.”

Source: Yahoo Finance Yahoo Finance The above are “street” analyst estimates “guided” by corporate officials designated as investor interfaces. While it should seem that corporate and investor objectives are parallel, there often are times when they are not. Investor judgment error-incurring times, particularly in regard to shares’ likely coming market prices.

Long-standing stock market mechanics intensified by advances in information technology require 21 st -century equity transactions to be either highly-automated small volume/value trades with/among individual investors or big value/volume trades among “institutional” investors managing Billion-$+ portfolios.

The automated individual small trades are present on a fairly consistent basis, while the larger institutional trades tend to be irregular in their timing and urgency. Knowledge of impending big trades tend to move prices in anticipation, reducing their effectiveness for the trade initiator, so they seek quick, private accomplishment. That is aided by “Market-Maker” [MM] firms like GS, MS and a dozen or so others.

The MMs seek to balance buyer and seller share volumes by, where necessary (usually 90+% of the time) acting as buyers or short sellers of borrowed shares. Their risks thus taken are hedged by “insurance” deals in open public markets for derivative securities.

The costs and structures of the hedges define the price expectations of knowledgeable participants in those markets, often “prop” trade desks of MM firms and other institutions acting for their own accounts.Here In Figure 1 is what the daily ranges of expected prices have been over the past 6 months for MDB: Please do not jump to conclusions about what these pictures show Figure 1 is NOT a conventional backward-in-time-looking “technical price chart.” Instead, it is a recent history of daily forward-looking price range forecasts made by well-informed, experienced market professionals. Figure 1 (used with permission) The vertical lines of Figure 1 span the range of price implied to be likely by the actions of Market-Makers [MMs] as they hedge the firm’s capital required to be put at risk. Their commitments are needed to balance buyers and sellers when “filling” client block trade orders from big-money-fund portfolio managers.The implications of these actions have been known to sometimes vary significantly from forecast statements made by the “research” departments of the same firms.The vertical forecast lines are split into upside and downside prospects by the heavy-dot end-of-day market quote for the issue on the day of the forecast. A measure of the imbalance between up and down implications is the Range Index [RI], which tells what percent […]

source MongoDB: Handling TMI – Too Much Information

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