Yesterday, over 150 participants took part in our “Higher Returns Through Diversification” webcast. Scott Langmack, the featured speaker, discussed his personal investment strategy in Lending Club Notes that, according to Scott, has allowed him to average an annualized return of 12.5% on his aggregate portfolio since 2008.
During the presentation and Q&A session, Scott shared his research, investment insights, and his “4 Keys to Maximizing Returns.”
If you missed the webinar, check out the replay here >>.
Enjoy!
Lending Club Notes are offered by a prospectus filed with the SEC.
The views and plans expressed by Mr. Langmack are his own and are not endorsed or adopted by Lending Club.
Returns are based upon a variety of factors including, amount invested, diversification, FICO score and other factors that could affect returns. Your returns may vary. You should review the risks and uncertainties described in the prospectus related to your possible investment in the notes.
Veteran Lending Club investor Scott Langmack will explain how proper diversification leads to higher and more stable returns. Mr. Langmack’s portfolios have realized 12.6% net annualized returns since 2008.
Higher Returns through Diversification with Scott Langmack >> Register Now
Free WebCast and Online Discussion
Thursday, October 29th, 2009
4:00 pm PDT (7:00 pm EDT)
Scott along with Patrick Gannon, Lending Club’s SVP of Investor Services, will field your questions after the presentation. Scott Langmack is currently CEO of Blue Chip Expert and author of PeerLendingWealth.com.
While you may have heard that Lending Club notes average 9.66% net annualized returns, you may not know that over a third of our investors have average returns between 12%-18%! Join Scott Langmack this Thursday to find out how he has beaten the average.
Lending Club notes are offered by prospectus filed with the SEC.
See you there,
Sam
Last week, Patrick Gannon, SVP Investor Services, and I had the great pleasure of unveiling Lending Club’s new Statistics page. During the presentation we covered topics such as returns by loan grade, returns by amount invested, and defaults by loan type. After the presentation we opened the floor to questions.
If you missed the webinar check out the replay here >>.
Lending Club’s new statistics page let’s you slice and dice data like never before. You can analyze returns by credit grade, loan amount and purpose across various time periods. For all you datum fans – you can download historical data on declined loans, loans in funding, as well as issued loans. Lending Club notes are offered by prospectus filed with the SEC.
Cheers to data!
Sam
Yesterday John Donovan, Lending Club's COO, and Jack Cohen, Lending
Club's SVP Legal and Collections, shared insights on our credit and
collections processes and policies.
For those of you new to Lending Club this webinar has great
information on who our borrowers are. For LC veterans, the
presentation does a deep dive into our industry leading collections
process. This is a must see webinar for anyone interested in
investing in creditworthy borrowers.
After the 25 minute presentation there is a hard hitting Q&A.
View this must-see event here.
Many happy returns,
Sam
Green initiatives are often promoted as paying for themselves, leading to widespread acceptance. Why wouldn’t we do things that also have environmental benefits if they have little or no financial cost? When considering such matters, it’s important to use conservative estimates of the true costs.
According to a recent Newsweek article, Are We Underestimating the Cost of Going Green, author Robert J. Samuelson argues that in far too many cases, computer models make assumptions that are much too optimistic. As someone who models complex systems regularly for my day job, I can tell you how quickly the accuracy of a model can diminish when faulty assumptions are made. Even the best of models is only as good as its worst assumption.
I am not suggesting that we should blatantly disregard modeled results. In fact, they are often highly accurate and superior to other estimation methods. I simply try to approach all cases where things seem too good to be true with a moderate amount of skepticism. Would you blindly trust a stock-picking algorithm that promised above-average returns for below-average risk? No, you need to balance modeled results with known laws and rules, such as, it takes more risk to achieve more reward.
As stated previously, there are certainly non-monetary reasons to transition to a greener lifestyle. On a micro scale, you often see monetary benefits as well. A simple change, like transitioning to energy-efficient appliances, really can save you more than the cost of the upgrade over time. On a larger scale, coming to accurate cost conclusions can be more difficult. Green initiatives are also a politically charged topic. Supporters can produce highly favorable models as quickly as denouncers can produce ones with conflicting results. A minor change of assumptions can have a major effect on the results. So take the steps you feel are necessary to achieve a greener lifestyle, but remember that it will probably cost more than the supporters suggest and less than those opposed would have you believe.
Did a green project you implemented cost more or less than you expected?
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