Portfolio Risk Management

First published 23 Aug 2026 · Last verified 29 Aug 2026

In the summer of 2078 B.S. (2021), a taxi driver in Kathmandu told his passenger, a retired schoolteacher, that he had turned his savings from two years of driving into shares of three hydropower companies and two finance companies. NEPSE was near its all-time high of 3,198.60 points. Everyone was making money. The teacher, impressed, put her retirement gratuity into the same five stocks the following week. Within a year, NEPSE had fallen by more than 40 percent from that peak, grinding down toward the 1,800s through 2022 as Nepal Rastra Bank tightened lending, margin calls forced liquidation, and remittance-driven liquidity dried up. The taxi driver's hydropower shares and the teacher's finance shares fell together, on the same days, for the same reasons. Neither had built a portfolio. Both had built a single bet wearing five different name tags.

This is the problem this chapter exists to solve. Chapter 60 taught you how to build a well-diversified equity sleeve — enough stocks, spread across enough sectors, none of them too large a slice of the pie. That is necessary. It is not sufficient. A portfolio can look diversified on a spreadsheet — ten stocks, five sectors — and still behave like one giant undiversified bet, because Nepali sectors do not always move independently. Banks, finance companies, and even many "diversified" conglomerates in Nepal share the same fuel: interest rates set by Nepal Rastra Bank (NRB), remittance inflows, and the general mood of margin-lending investors. When that fuel changes, correlated stocks fall together, hard, regardless of how many tickers you own.

Portfolio risk management is the discipline of stepping back from individual stocks and asking a different question: what happens to my entire wealth, all at once, in a bad scenario? This chapter gives you the vocabulary, the simple tools, and the practical limits to answer that question — before the market answers it for you.

Lesson 61.1 — What "Portfolio Risk" Means Beyond a Single Stock

Think of a farmer who plants three fields instead of one, to protect against the risk that any single field fails. That works well if the fields face different threats: one is near a river and might flood, one is on a hillside and might face drought, one is shaded and might face blight. But if all three fields sit on the same floodplain, side by side, then "three fields" gives no real protection. A single monsoon flood destroys all three on the same day. The farmer diversified in name — three separate fields — but not in substance, because the fields shared the same risk: the river.

Nepali retail portfolios often make exactly this mistake. An investor buys Nabil Bank, Global IME Bank, Nepal Investment Mega Bank, and Prabhu Bank — four different companies, four different tickers, four different management teams. On paper, that looks like diversification. In practice, all four are commercial banks, all four are regulated by the same NRB directives, all four borrow and lend using the same interest-rate environment, and all four are sensitive to the same credit cycle. When NRB tightens monetary policy, all four typically feel it together. The "four fields" sit on the same floodplain.

Portfolio-level risk has three components that individual stock analysis does not capture on its own:

Volatility is how much your portfolio's value swings up and down over time, regardless of direction. A portfolio that moves between minus 3 percent and plus 3 percent in a typical month is more volatile than one that moves between minus 1 percent and plus 1 percent, even if both end up flat over a year. Volatility matters because large swings are stressful, and stress causes investors to sell at the worst possible moments — near the bottom of a fall, in panic, locking in a loss that a calmer investor would have ridden out.

Drawdown is the fall from a portfolio's highest recorded value to its lowest subsequent value, before it recovers. If your portfolio was worth Rs 10,00,000 at its peak and later fell to Rs 6,50,000 before turning around, your maximum drawdown was 35 percent. Drawdown is the risk measure that matters most to real people, because it is the number you actually feel — the gap between what your wealth used to be and what it is now.

Correlation and concentration risk is the risk that your holdings are not truly independent of each other — that they will rise and fall together because they share a common driver (an interest rate, a sector, a single family of promoters, or general market sentiment). This is the "same floodplain" problem, and in NEPSE it is unusually severe, as Lesson 61.3 will show in detail.

None of this means diversification is worthless — Chapter 60's sector spread across banking, hydropower, insurance, hotels, manufacturing, and microfinance is real protection, because those sectors genuinely do respond to different forces some of the time. But it means diversification must be checked, not assumed. The rest of this chapter gives you the tools to check it.

Lesson 61.2 — Measuring Drawdown and Volatility Without a Finance Degree

You do not need a Bloomberg terminal or a statistics course to track portfolio risk. You need a notebook, a calculator, and a habit.

Tracking maximum drawdown, the simple way. Every month, write down your total portfolio value — the sum of every holding at current market price, in NPR. Keep a running record of the single highest value your portfolio has ever reached. Every time your current value is below that peak, calculate the percentage gap:

Drawdown (%) = (Peak Value − Current Value) ÷ Peak Value × 100

Why does this matter more than daily price-watching? Because drawdown captures the lived experience of loss in a way that a single day's percentage move does not. A portfolio that falls 2 percent in one bad session is not alarming. A portfolio that has quietly bled from a peak of Rs 12,00,000 down to Rs 8,00,000 over eight months — a 33 percent drawdown — is a portfolio in genuine trouble, even though no single day felt dramatic. Drawdown adds up what daily moves hide.

Understanding standard deviation informally. Standard deviation is a technical term for a simple idea: how spread out your returns typically are around their average. You do not need to compute it precisely to use it. Think of it as your portfolio's "typical wobble." If your portfolio's monthly returns over the past two years have mostly ranged between minus 4 percent and plus 4 percent, with the average around 1 percent, your typical wobble is roughly plus-or-minus 4 to 5 percentage points. A portfolio with a wide typical wobble is a "jumpy" portfolio; a portfolio with a narrow wobble is a "calm" one. A retail investor's version of measuring this is simply: write down your monthly percentage return for two years, look at the highest and lowest months, and ask whether that range feels tolerable if it repeated going forward. If a minus-15-percent month would cause you to panic-sell, your portfolio's wobble is too large for your temperament, regardless of what the long-run average return might be.

A rule of thumb for Nepali retail investors. NEPSE, as a market, has historically been considerably more volatile than Nepal government savings bonds or fixed deposits, and it has also shown sharper swings than many regional emerging-market peers, in part because of NEPSE's relatively thin daily turnover, heavy retail participation, and sensitivity to margin-lending cycles. A useful mental anchor: expect NEPSE-linked equity portfolios to move by double-digit percentages within any given twelve-month window, in either direction, as a matter of routine — not as an emergency. What separates a manageable year from a genuine crisis is not whether volatility occurred, but how deep the drawdown went and how long it lasted.

Lesson 61.3 — Correlation and Concentration Risk on NEPSE

Correlation measures whether two things move together. If two stocks almost always rise and fall on the same days, in the same direction, they are highly correlated. If one tends to rise while the other falls, or their movements seem unrelated, they are lowly correlated (or even negatively correlated). Diversification only reduces risk to the extent that your holdings are not highly correlated with each other.

Picture a bus queue during a sudden downpour in Kathmandu. If everyone in the queue is standing under one shared shelter, the rain affects them all identically — they all stay dry together, or the wind shifts and they all get wet together. Their outcomes are correlated because they share one shelter. Now picture the same number of people spread across five separate shelters at different bus stops. Some stay dry, some get wet, depending on which shelter's roof leaks and which direction the wind blows at each stop. Their outcomes are less correlated because they no longer share a single point of exposure. A NEPSE portfolio needs "separate shelters" — holdings exposed to genuinely different economic forces — not just separate company names under one shared roof.

Why NEPSE correlation is unusually high. Several structural features of the Nepali market push correlation upward, especially within the financial sector:

First, banks, development banks, finance companies, and microfinance institutions are all regulated by the same institution — Nepal Rastra Bank — and all respond to the same policy levers: the policy rate, the cash reserve ratio, and directives on lending limits or capital adequacy. When NRB tightens, nearly the entire BFI (banks and financial institutions) universe feels pressure on the same day.

Second, a very large share of NEPSE's daily turnover flows through margin lending — investors borrowing against their existing shares to buy more shares. When margin calls hit during a downturn, brokers and investors sell whatever is most liquid, which is usually banking and finance shares, pushing those prices down together in a self-reinforcing spiral, independent of each company's individual fundamentals.

Third, general market sentiment in Nepal — driven by remittance trends, monsoon and agricultural output, tourist arrivals, and political stability — tends to lift or depress the entire index at once, because retail investors, who dominate NEPSE trading volume, often trade the "market mood" rather than individual company analysis.

A practical correlation check without formulas. You do not need to calculate a correlation coefficient. Ask three questions about every pair of holdings in your portfolio:

Do they answer to the same regulator with the same policy tools (for example, two banks, or a bank and a finance company)? Do they depend on the same underlying economic input (for example, two hydropower companies both depend on monsoon rainfall and the same power purchase agreement structure with the Nepal Electricity Authority)? Do they tend to move on the same days when you check prices, rising and falling together? If the answer to two or more of these is yes for a given pair, treat them as one combined position for risk purposes, not two separate ones.

The practical takeaway from Chapter 60's sector limits becomes sharper here: a cap of, say, 30 percent in "financials" broadly defined is not just a diversification nicety — it is a direct defence against the single largest correlated-risk cluster on the entire exchange. Hydropower, for its part, carries its own correlated cluster risk (monsoon dependency, NEA tariff and transmission bottlenecks, and interest-rate sensitivity on construction-phase debt), so a portfolio overloaded with hydropower counters faces a parallel — though different — concentration problem.

Lesson 61.4 — Stress-Testing Your Portfolio Against Realistic NEPSE Scenarios

Stress-testing means asking, in a calm moment, "if a specific bad scenario happened, what would happen to my portfolio?" — and doing the arithmetic before the scenario arrives, not during it. It is the financial equivalent of a monsoon flood drill: nobody performs a flood drill while the water is already rising. You do it in the dry season, so that when the rains come, you already know where to go.

Below are four realistic stress scenarios for a Nepali equity portfolio, each grounded in patterns NEPSE has actually shown.

Scenario 1: Sector-wide correction in banking and finance. NRB issues a directive tightening the loan-to-value ratio for margin lending, or raises the cash reserve ratio, prompting a broad sell-off concentrated in BFI counters. Based on the pattern seen through 2021–2022, a severe version of this scenario has historically produced declines of 30 to 45 percent in the finance and microfinance sub-indices, with banking proper falling somewhat less, in the 20 to 30 percent range, over a period of several months to a year.

Scenario 2: NRB monetary policy tightening cycle. NRB raises its policy rate and reduces overall system liquidity to control inflation or defend foreign exchange reserves. This raises borrowing costs across the economy, compresses bank net interest margins in the near term even as loan growth slows, and reduces the attractiveness of margin-funded equity purchases, causing a broad, gradual NEPSE decline rather than a single sharp crash — typically unfolding over two to four quarters, in the 15 to 25 percent range for the headline index.

Scenario 3: Liquidity crunch. Remittance inflows soften, banks face deposit pressure, and interbank lending rates spike. Trading volumes on NEPSE fall sharply as investors and margin lenders pull back simultaneously. In this scenario, the damage is not just a price decline but a widening of the practical bid-ask gap: even investors who want to sell struggle to find buyers at reasonable prices, worsening realised losses for anyone forced to exit. Headline index declines in past liquidity-driven episodes have ranged from 10 to 20 percent, but the effective cost to an investor needing to raise cash quickly can be considerably higher, because thin markets force selling at unfavorable prices.

Scenario 4: Circuit-breaker cascade event. As covered in Chapter 58, NEPSE employs circuit breakers that pause trading when the index moves beyond preset thresholds in a single session. In a genuine panic — a rapid confidence shock, a major default, or a geopolitical or macro surprise — the market can hit a negative circuit breaker, reopen, fall further, hit a second breaker, and in the most extreme cases trigger a third breaker that halts trading for the day entirely. Nepali markets have experienced sessions where consecutive negative circuit breakers closed the market early with the index down several percentage points in a matter of hours, and turnover collapsing as sellers vastly outnumbered buyers. The risk in this scenario is not just the single-day loss; it is that you cannot exit even if you want to, because trading is paused, and the next session can gap down further before you get a chance to act.

The table below works through these four scenarios against a hypothetical Rs 10,00,000 equity portfolio built the way Chapter 60 describes: 40 percent banking and finance, 25 percent hydropower, 15 percent insurance, 10 percent hotels and manufacturing, 10 percent microfinance and other.

How to actually run this exercise on your own portfolio. List your current holdings and their rupee weights. For each scenario, estimate a plausible decline for each sector based on the ranges above (heavier for BFI-concentrated scenarios, lighter for scenarios that hit the broad market evenly). Multiply each holding's weight by its scenario-specific estimated decline, sum the results, and you have a rough portfolio-level stress estimate. Do this once a year, or whenever you make a significant change to your holdings. The output is not a forecast — it is a gut check: if a plausible scenario would push your portfolio down by an amount that would force you to sell at the worst time (to cover an emergency, meet a loan payment, or simply because you could not tolerate it emotionally), your portfolio is too aggressively positioned for your actual life circumstances, regardless of its expected long-run return.

Lesson 61.5 — Rebalancing: When and How to Reset Your Portfolio

Rebalancing is the practice of periodically adjusting your holdings back toward your originally intended weights, after market moves have pushed them off target. Think of it like re-leveling a set of shop scales that has drifted out of balance — not because you did anything wrong, but simply because different items on each side gained or lost weight at different rates over time.

Here is the mechanic in plain terms. Suppose Chapter 59 and 60 led you to a target of 40 percent banking and finance, 25 percent hydropower, 15 percent insurance, and 20 percent everything else. A year later, hydropower has rallied hard and now represents 35 percent of your portfolio, while banking and finance has lagged and fallen to 32 percent. Your portfolio has drifted from your intended risk profile without you making a single active decision — the market did it for you. Rebalancing means selling some of the outperforming hydropower position and adding to the underperforming banking position, to bring both back toward their original targets.

When to rebalance. Two common approaches, both reasonable for a Nepali retail investor:

Calendar-based rebalancing means reviewing your portfolio weights on a fixed schedule — once or twice a year is typical for a long-term investor — regardless of how far things have drifted. This is simple and prevents both over-trading and neglect.

Threshold-based rebalancing means acting only when a holding or sector drifts beyond a pre-set tolerance band — for example, if any single sector moves more than 5 to 7 percentage points away from its target weight. This is more responsive to actual market moves but requires you to check your weights periodically to know when a threshold has been crossed.

A sensible combination for most retail investors: check your weights every six months, and rebalance only if drift exceeds your threshold band. This avoids constant fiddling while still catching the meaningful drifts that matter.

Tax and transaction cost considerations. Part VII covered Nepal's capital gains tax regime for listed securities — a lower rate for long-term holdings (generally those held more than 365 days) and a higher rate for short-term holdings, along with brokerage commission and SEBON/CDSC fees on every transaction. Rebalancing is not free, and this must factor into how aggressively you do it.

Three practical rules follow from this:

First, before rebalancing, check whether a position is close to crossing the long-term holding threshold. If a stock is 340 days into being held and would qualify for the lower long-term capital gains rate in three weeks, it is usually worth waiting those three weeks before trimming it, unless the drift is severe enough to pose an immediate risk concern.

Second, use new contributions to rebalance where possible, before selling existing winners. If you are still adding fresh savings to your portfolio, direct new purchases toward your underweight sectors rather than your overweight ones. This achieves the same rebalancing effect without triggering any capital gains tax at all, because you are not selling anything.

Third, do not rebalance on a hair-trigger. A sector drifting from 25 percent to 28 percent is normal market noise, not a risk emergency. Reserve actual selling-based rebalancing for drifts that genuinely change your risk profile — typically moves of 5 percentage points or more away from target — so that the tax and transaction costs of rebalancing are justified by a real reduction in concentration risk.

Lesson 61.6 — Setting Practical Portfolio Risk Limits

Everything in this chapter builds toward one output: a written, specific set of limits that you set for yourself before you need them, so that in a moment of market stress you are executing a plan rather than improvising a reaction. This is the retail investor's equivalent of an institutional risk policy — simpler, but the same underlying idea.

Maximum single-position size. Chapter 60 introduced position limits at the individual stock level; restate it here as a hard portfolio-risk rule: no single stock should exceed roughly 10 to 15 percent of your total equity portfolio at cost, and ideally you act to trim it back toward target if market appreciation pushes it meaningfully above that, say past 18 to 20 percent, even if you like the company. A position that grows large enough on its own can undo the benefit of everything else you hold, simply through its own bad day.

Maximum sector exposure. Given the correlation dynamics detailed in Lesson 61.3, a firm cap on combined banking, finance, and microfinance exposure — commonly recommended in the 30 to 35 percent range of total equity holdings — protects you against the single largest correlated-risk cluster on NEPSE. A parallel, somewhat looser cap on hydropower exposure (given its own correlated monsoon and interest-rate sensitivities) is also reasonable, often in the 25 to 30 percent range.

Maximum drawdown tolerance triggering review. Set a specific number in advance — for example, "if my portfolio's drawdown from its peak exceeds 20 percent, I will conduct a full portfolio review within two weeks." This does not mean automatically selling at 20 percent down. It means treating that threshold as a forcing function: a scheduled moment to reassess whether your original assumptions (sector weights, position sizes, time horizon, emergency fund adequacy from Chapter 59) still hold, rather than drifting passively through an extended decline without ever stepping back to think.

Putting the limits together. A complete, practical risk-limit policy for a Nepali retail equity portfolio might read like this, written once and kept somewhere you will actually see it again: no single stock above 15 percent of the equity sleeve at cost; combined banking, finance, and microfinance exposure capped at 35 percent; combined hydropower exposure capped at 30 percent; portfolio rebalanced when any sector drifts more than 5 percentage points from target, checked semi-annually; and a full strategy review triggered automatically at a 20 percent portfolio drawdown from peak value.

None of these numbers are laws of physics. A younger investor with a longer horizon and steady employment income (Chapter 59's capacity-for-risk framework) can reasonably tolerate wider bands than someone nearing retirement. But the discipline of having explicit, written numbers — decided in a calm moment, not during a circuit-breaker cascade — is what turns "I hope my portfolio is fine" into an actual, defensible risk management practice.