stub8535
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personal opinions only. Not qualified to advise on investment products.
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Post by stub8535 on Jul 20, 2017 14:37:02 GMT
The 0 5% promise must be coming by the same transport as money from Switzerland on another platform as its been so long. The 0.5% is already present insofar that Invoice Discount is capped at 0.5%per position (see @bobo comment above relating to spreading out riskier loan types). Also, when clients are Fully Invested, then the Diversification Optimisation System kicks in: this enables clients to be allocated positions relating to the new underlying loan, with 5 existing positions reducing by 20% each to make way. This means a client with a 1% setting; will end up with 5@ 0.8% and 1@ 1% instead of 5@ 1%. This can then continue for each new loan that comes in. Diversification is a key part of what we enable. But stevefindlay you were talking about 0.5% ootion for all loans a long time ago. Has this option been silently made available to investors? After all, one of you selling points is tgat you are invest and leave it to your team.
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justme
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Post by justme on Aug 7, 2017 13:13:42 GMT
I tackled some of the maths on P2P loan diversification recently. To keep it simple the lending model is a loan that returns 10% interest in a single end of year repayment, and has a 5% bad debt rate with no recoveries. When invested in an infinite number of such loans the expected return is +4.5%, but we are concerned with what happens when the investment is spread over a much smaller numbers of equal sized loans. Outcomes with 1 loan: Outcome No defaults One default Probability 95% 5% Return +10% -100% Outcomes with 2 loans: Outcome No defaults One default Two defaults Probability 90.25% 9.5% 0.25% Return +10% -45% -100% Outcomes with 3 loans: Outcome No defaults One default Two defaults Three defaults Probability 85.74% 13.54% 0.71% 0.01% Return +10% -27% -63% -100% This is called a binomial distribution. Inspection of these figures shows that by spreading the investment over a number of loans the probability of a total loss is rapidly reduced, but that the probability of making a more modest loss is increasing. This trend continues until with 10 loans the probability of a small loss is a staggering 40%. As the number of loans is increased further the probability of loss falls and rises in steadily decreasing waves. However it is not until there are more than 98 loans is the probability of loss always less than our original 5%. This shows that modest diversification, whilst hugely reducing the chance of a total loss, has the (perhaps) unexpected effect of increasing the likelihood of making an overall small loss. I suspect that this effect is why many who dabble in P2P lending without adequate diversification come away with a bad experience. Curious phenomenon. I can see how it happens but do not understand it enough to be able to predict what effect it would have as circumstances change - different loan failure rate for example. Granted I could do it long hand but I wondered whether there is any formula to it. I wondered about platforms like ablrate and moneything that have just a few dozens of loans going at any time - there would be no way to diversify into 50s let alone hundreds there.
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IFISAcava
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Post by IFISAcava on Aug 7, 2017 13:47:14 GMT
I tackled some of the maths on P2P loan diversification recently. To keep it simple the lending model is a loan that returns 10% interest in a single end of year repayment, and has a 5% bad debt rate with no recoveries. When invested in an infinite number of such loans the expected return is +4.5%, but we are concerned with what happens when the investment is spread over a much smaller numbers of equal sized loans. Outcomes with 1 loan: Outcome No defaults One default Probability 95% 5% Return +10% -100% Outcomes with 2 loans: Outcome No defaults One default Two defaults Probability 90.25% 9.5% 0.25% Return +10% -45% -100% Outcomes with 3 loans: Outcome No defaults One default Two defaults Three defaults Probability 85.74% 13.54% 0.71% 0.01% Return +10% -27% -63% -100% This is called a binomial distribution. Inspection of these figures shows that by spreading the investment over a number of loans the probability of a total loss is rapidly reduced, but that the probability of making a more modest loss is increasing. This trend continues until with 10 loans the probability of a small loss is a staggering 40%. As the number of loans is increased further the probability of loss falls and rises in steadily decreasing waves. However it is not until there are more than 98 loans is the probability of loss always less than our original 5%. This shows that modest diversification, whilst hugely reducing the chance of a total loss, has the (perhaps) unexpected effect of increasing the likelihood of making an overall small loss. I suspect that this effect is why many who dabble in P2P lending without adequate diversification come away with a bad experience. Curious phenomenon. I can see how it happens but do not understand it enough to be able to predict what effect it would have as circumstances change - different loan failure rate for example. Granted I could do it long hand but I wondered whether there is any formula to it. I wondered about platforms like ablrate and moneything that have just a few dozens of loans going at any time - there would be no way to diversify into 50s let alone hundreds there. but the maths will also work across the whole of your P2P, i.e. platform independent. doesn't really matter if one platform make a loss if overall you make up for it elsewhere. also, surely it will also depend on loan size - that model assume equal, whereas in some platforms one has a large minimum (e.g. BridgeCrowd) and others very low. The message I take is that one needs at least 100 times diversification of your single largest investment (i.e no one investment is more than 1% of the total) - and the more you have above that (or the more the amounts are broken into smaller chunks than 1%) the closer you will likely be to the expected average returns. Of course, the expected average returns will then vary by what you are diversified into, but that is another topic...
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angrysaveruk
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Say No To T.D.S
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Post by angrysaveruk on Aug 7, 2017 16:31:15 GMT
I tackled some of the maths on P2P loan diversification recently. To keep it simple the lending model is a loan that returns 10% interest in a single end of year repayment, and has a 5% bad debt rate with no recoveries. When invested in an infinite number of such loans the expected return is +4.5%, but we are concerned with what happens when the investment is spread over a much smaller numbers of equal sized loans. Outcomes with 1 loan: Outcome No defaults One default Probability 95% 5% Return +10% -100% Outcomes with 2 loans: Outcome No defaults One default Two defaults Probability 90.25% 9.5% 0.25% Return +10% -45% -100% Outcomes with 3 loans: Outcome No defaults One default Two defaults Three defaults Probability 85.74% 13.54% 0.71% 0.01% Return +10% -27% -63% -100% This is called a binomial distribution. Inspection of these figures shows that by spreading the investment over a number of loans the probability of a total loss is rapidly reduced, but that the probability of making a more modest loss is increasing. This trend continues until with 10 loans the probability of a small loss is a staggering 40%. As the number of loans is increased further the probability of loss falls and rises in steadily decreasing waves. However it is not until there are more than 98 loans is the probability of loss always less than our original 5%. This shows that modest diversification, whilst hugely reducing the chance of a total loss, has the (perhaps) unexpected effect of increasing the likelihood of making an overall small loss. I suspect that this effect is why many who dabble in P2P lending without adequate diversification come away with a bad experience. Curious phenomenon. I can see how it happens but do not understand it enough to be able to predict what effect it would have as circumstances change - different loan failure rate for example. Granted I could do it long hand but I wondered whether there is any formula to it. I wondered about platforms like ablrate and moneything that have just a few dozens of loans going at any time - there would be no way to diversify into 50s let alone hundreds there. What is going on here can be explained with a simple example. Firstly you should note that the risk is going down in terms of the probability of making an extreme loss of 100%. This has a 5% chance with one investment but only 0.01% chance with 3 investments. What is increasing is the probability of making any type of loss. Think about rolling a 20 sided dice once (you wont have seen one of these unless you played D&D as a kid like me but they do exist  ). If it is a one you lose. if you roll the dice once you have a low 5% chance of making 1 loss. If you roll the dice 100 times you are very likely to make a loss atleast once. Roll it a million times you will certainly have some losses but what becomes increasingly important is you profit or gain on 19 times out of 20, and if you win enough that will start to eat up all the losses.
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macq
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Post by macq on Aug 7, 2017 17:07:36 GMT
is the probability of diversification (and i do believe in it as my mind says it makes sense even if i can't prove it) not down to good old fate or Murphy's law?
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mary
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Post by mary on Aug 7, 2017 18:14:14 GMT
Curious phenomenon. I can see how it happens but do not understand it enough to be able to predict what effect it would have as circumstances change - different loan failure rate for example. Granted I could do it long hand but I wondered whether there is any formula to it. I wondered about platforms like ablrate and moneything that have just a few dozens of loans going at any time - there would be no way to diversify into 50s let alone hundreds there. but the maths will also work across the whole of your P2P, i.e. platform independent. doesn't really matter if one platform make a loss if overall you make up for it elsewhere. also, surely it will also depend on loan size - that model assume equal, whereas in some platforms one has a large minimum (e.g. BridgeCrowd) and others very low. The message I take is that one needs at least 100 times diversification of your single largest investment (i.e no one investment is more than 1% of the total) - and the more you have above that (or the more the amounts are broken into smaller chunks than 1%) the closer you will likely be to the expected average returns. Of course, the expected average returns will then vary by what you are diversified into, but that is another topic... The maths is obviously correct, however I need to balance against my time available to track each loan and stay on top of issues/problems that may crop up. Therefore I find that 20-25 loans consumes my time, and, excluding hands-off platforms that I do use to add to diversification, try to have a maximum of 5% in each loan, although I often go higher in the early stages and use the SM to reduce exposure over time as new, good quality, loans become available. Unless P2P is your full time job, I don't think it's possible to track 50-100 loans with sufficient diligence.
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easylender
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Post by easylender on Aug 8, 2017 12:10:48 GMT
is the probability of diversification (and i do believe in it as my mind says it makes sense even if i can't prove it) not down to good old fate or Murphy's law? Murphy's law certainly comes into it, but there is so much more, such as the Binomial Distribution as described above.
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easylender
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Post by easylender on Aug 8, 2017 12:24:49 GMT
but the maths will also work across the whole of your P2P, i.e. platform independent. doesn't really matter if one platform make a loss if overall you make up for it elsewhere. also, surely it will also depend on loan size - that model assume equal, whereas in some platforms one has a large minimum (e.g. BridgeCrowd) and others very low. The message I take is that one needs at least 100 times diversification of your single largest investment (i.e no one investment is more than 1% of the total) - and the more you have above that (or the more the amounts are broken into smaller chunks than 1%) the closer you will likely be to the expected average returns. Of course, the expected average returns will then vary by what you are diversified into, but that is another topic... The maths is obviously correct, however I need to balance against my time available to track each loan and stay on top of issues/problems that may crop up. Therefore I find that 20-25 loans consumes my time, and, excluding hands-off platforms that I do use to add to diversification, try to have a maximum of 5% in each loan, although I often go higher in the early stages and use the SM to reduce exposure over time as new, good quality, loans become available. Unless P2P is your full time job, I don't think it's possible to track 50-100 loans with sufficient diligence. The maths example above which resulted in a recommendation to diversify into at least 100 loans was based on a return after fees of 10% and a bad debt rate of 5%. This is quite close to new loans available on Zopa plus which currently show me an expected return of 10.1% and an expected bad debt rate of 4%. In contrast there are other platforms offering secured loans with expected returns of 12% and bad debt rates of 2%. In this case it's only necessary to diversify into 25 loans to keep the chance of making a loss below 2%.
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pikestaff
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Post by pikestaff on Aug 8, 2017 13:02:42 GMT
...there are other platforms offering secured loans with expected returns of 12% and bad debt rates of 2%... I assume you are looking at property lending. In a bad year the losses will be a large multiple of that, and they will all come at once. I would expect long-term returns net of losses to be 7% at best.
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marka
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Post by marka on Aug 8, 2017 14:11:36 GMT
True, but do you want a single default to wipe out a year's gain? I want to be able to stand at least two defaults in any year without an overall loss.
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Post by dudave on Aug 8, 2017 16:12:02 GMT
I tend not to enter a platform if i do not see the potential to diversify my portfolio to at least 40 loans, i did made an exception with Ablerate though, currently with only 20 loans in my portfolio. i do have several platforms with more than 100 loans but i personally believe it's not really necessary, for me 100 is the magic number.
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am
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Post by am on Aug 8, 2017 17:00:09 GMT
I have mixed feelings about diversification. It was probably what I saw as the highest priority when I set out, but after a few months it became apparent that unlike stocks and shares, you can to some extent pick losers and winners in P2P, especially the losers. I'm not advocating ignoring it, but if you have the opportunity/time/interest to, I'd still say it's worth a critical look at the proposals and/or this forum. This will happen naturally anyway, as when you hit your first bad eggs, it's human nature to want to find out what went wrong and whether it was foreseeable. I have about 70-80 loans going currently aside from the 'blind' platforms - I'd love to take on more and diversify further, but not at the cost of taking on loans I perceive to be more risk then their offered rate. So, newbiealert , I would wager that many (possibly most?) people who have been using P2P for a couple of years or more find that quality rather than quantity counts and are less focused that you might expect on driving the pure number of loans upwards and upwards. I'm sure some would disagree though. However, early on, I think you're wise to make that a starting point to lessen the blows of any early possible mistakes. If you prefer not to have to put the time/effort to building all of this up at this stage, then there are plenty of P2P sites that offer auto-diversification - e.g. Zopa, Assetz, Ratesetter, Bondmason, Growth Street. All have their own pros and cons of course, very well documented in their respective threads You can pick winners in stocks and shares as well. There is an argument for concentrated stock portfolios - there's less benefit to picking a 10-bagger if it's only 0.5% of your portfolio. With stocks and shares one 10-bagger outweighs 5 wipeouts. This isn't the case for P2P, where there's an upwards cap on returns, but you can still lose the lot. Because of this I think (depending on your appetite for risk) diversifying away abnormal returns is more important for P2P. I've got a few hundred loans going across several platforms (I managed to reach 200 at FC after several years), as well as autodiversification via P2P Global, RS, GEIA (AC) and GBBA (AC). which I think is a small number compared to some people. I try to restrict myself to "quality" loans, for reasons relating to comfort and investment ethics, but the diversification is there is case I get it wrong, and a loan turns out to be a disaster. (I traded out of some of the bad loans at Lendy for cash flow management reasons, but if I had foreseen the problems I wouldn't have been in them in the first place.) As the purpose of diversification is to suppress abnormal returns, and as loans are not wholly independent, I think that you should be looking at diversifying across several axes (borrower, platform, asset class, possibly even duration). Investing in the ITs adds discount risk; investing in non-sterling loans add exchange rate risks. You have to make a decision whether the extra diversification outweighs the idiosyncratic risks. Possibly we might agree - don't take on any old dross just to increase diversity, but try to keep a moderately diverse portfolio of decent assets.
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macq
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Post by macq on Aug 8, 2017 18:41:42 GMT
Not sure what it proves except may be quality as well as diversification counts but talking of Stocks & Shares and using investment funds as an example the holdings in 3 top funds is
Fundsmith - 30 stocks
F & C it - 477 stocks
Vanguard dev world - 1945 stocks
which may mean fund managers can't make their minds up about diversification either
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Post by dudave on Aug 8, 2017 19:12:18 GMT
Not sure what it proves except may be quality as well as diversification counts but talking of Stocks & Shares and using investment funds as an example the holdings in 3 top funds is Fundsmith - 30 stocks F & C it - 477 stocks Vanguard dev world - 1945 stocks which may mean fund managers can't make their minds up about diversification either Diversification in stocks works a bit differently , too much diversification has been proven to give you results that are pretty close to what the market actually does, which is about 9% a year in average (that is if you invest for many years of course). many investors believe that anything above 40 stocks in your portfolio will reduce the risks significantly, but the results are not likely to be spectacular and you won't be able to beat the market by much if at all.
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macq
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Post by macq on Aug 8, 2017 21:33:57 GMT
Not sure what it proves except may be quality as well as diversification counts but talking of Stocks & Shares and using investment funds as an example the holdings in 3 top funds is Fundsmith - 30 stocks F & C it - 477 stocks Vanguard dev world - 1945 stocks which may mean fund managers can't make their minds up about diversification either Diversification in stocks works a bit differently , too much diversification has been proven to give you results that are pretty close to what the market actually does, which is about 9% a year in average (that is if you invest for many years of course). many investors believe that anything above 40 stocks in your portfolio will reduce the risks significantly, but the results are not likely to be spectacular and you won't be able to beat the market by much if at all. Would agree diversification in stocks works differently but was trying to point out how fund managers perceive risk and how they tackle it(and most managers are happy to track the average of the market first & then look to beat it)and many investors are happy with average in a belief that there is less risk.Sites such as Citywire & Morningstar will even say in some of their reviews that something like Scottish Mortgage is higher risk due to having only 30 odd stocks with big swings in price at times but which has paid off if you got your timing right verses say Witan IT with its 500 stocks which has still risen 120% over 5 years and would be called lower risk May be in the investment world a better comparison would be private equity trusts that are investing in small start ups etc that hold many holdings due to spreading the risk of smaller companies or micro cap funds that hold over 200-300 stocks and in my mind compare to SME loans.While it may not be possible to run your p2p in the same way i still think more spread is better.One way may be is not to look at each platform separately so if there is only 1 loan on say Abundance but it is only 1% or 2% of your p2p pot you can still do it rather then saying i want a minimum of 20 or 30 etc per platform,assuming people want that sort of spread
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). If it is a one you lose. if you roll the dice once you have a low 5% chance of making 1 loss. If you roll the dice 100 times you are very likely to make a loss atleast once. Roll it a million times you will certainly have some losses but what becomes increasingly important is you profit or gain on 19 times out of 20, and if you win enough that will start to eat up all the losses.
